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.

Iterative Frequency Domain Decision Feedback Equalization and Decoding for Underwater Acoustic Communications

NASA Astrophysics Data System (ADS)

Zhao, Liang; Ge, Jian-Hua

2012-12-01

Single-carrier (SC) transmission with frequency-domain equalization (FDE) is today recognized as an attractive alternative to orthogonal frequency-division multiplexing (OFDM) for communication application with the inter-symbol interference (ISI) caused by multi-path propagation, especially in shallow water channel. In this paper, we investigate an iterative receiver based on minimum mean square error (MMSE) decision feedback equalizer (DFE) with symbol rate and fractional rate samplings in the frequency domain (FD) and serially concatenated trellis coded modulation (SCTCM) decoder. Based on sound speed profiles (SSP) measured in the lake and finite-element ray tracking (Bellhop) method, the shallow water channel is constructed to evaluate the performance of the proposed iterative receiver. Performance results show that the proposed iterative receiver can significantly improve the performance and obtain better data transmission than FD linear and adaptive decision feedback equalizers, especially in adopting fractional rate sampling.

An adaptive approach to invasive plant management on U.S. Fish and Wildlife Service-owned native prairies in the Prairie Pothole Region: decision support under uncertainity

USGS Publications Warehouse

Gannon, Jill J.; Moore, Clinton T.; Shaffer, Terry L.; Flanders-Wanner, Bridgette

2011-01-01

Much of the native prairie managed by the U.S. Fish and Wildlife Service (Service) in the Prairie Pothole Region (PPR) is extensively invaded by the introduced cool-season grasses smooth brome (Bromus inermis) and Kentucky bluegrass (Poa pratensis). The central challenge to managers is selecting appropriate management actions in the face of biological and environmental uncertainties. We describe the technical components of a USGS management project, and explain how the components integrate and inform each other, how data feedback from individual cooperators serves to reduce uncertainty across the whole region, and how a successful adaptive management project is coordinated and maintained on a large scale. In partnership with the Service, the U.S. Geological Survey is developing an adaptive decision support framework to assist managers in selecting management actions under uncertainty and maximizing learning from management outcomes. The framework is built around practical constraints faced by refuge managers and includes identification of the management objective and strategies, analysis of uncertainty and construction of competing decision models, monitoring, and mechanisms for model feedback and decision selection. Nineteen Service field stations, spanning four states of the PPR, are participating in the project. They share a common management objective, available management strategies, and biological uncertainties. While the scope is broad, the project interfaces with individual land managers who provide refuge-specific information and receive updated decision guidance that incorporates understanding gained from the collective experience of all cooperators.

Ventromedial prefrontal and anterior cingulate cortex adopt choice and default reference frames during sequential multialternative choice

PubMed Central

Boorman, Erie D; Rushworth, Matthew F; Behrens, Tim E

2013-01-01

Although damage to medial frontal cortex causes profound decision-making impairments, it has been difficult to pinpoint the relative contributions of key anatomical subdivisions. Here we use fMRI to examine the contributions of human ventromedial prefrontal cortex (vmPFC) and dorsal anterior cingulate cortex (dACC) during sequential choices between multiple alternatives – two key features of choices made in ecological settings. By carefully constructing options whose current value at any given decision was dissociable from their longer-term value, we were able to examine choices in current and long-term frames of reference. We present evidence showing that activity at choice and feedback in vmPFC and dACC was tied to the current choice and the best long-term option, respectively. vmPFC, mid-cingulate, and PCC encoded the relative value between the chosen and next-best option at each sequential decision, whereas dACC encoded the relative value of adapting choices from the option with the highest value in the longer-term. Furthermore, at feedback we identify temporally dissociable effects that predict repetition of the current choice and adaptation away from the long-term best option in vmPFC and dACC, respectively. These functional dissociations at choice and feedback suggest that sequential choices are subject to competing cortical mechanisms. PMID:23392656

What is coded into memory in the absence of outcome feedback?

PubMed

Henriksson, Maria P; Elwin, Ebba; Juslin, Peter

2010-01-01

Although people often have to learn from environments with scarce and highly selective outcome feedback, the question of how nonfeedback trials are represented in memory and affect later performance has received little attention in models of learning and decision making. In this article, the authors use the generalized context model (Nosofsky, 1986) as a vehicle to test contrasting hypotheses about the coding of nonfeedback trials. Data across 3 experiments with selective decision-contingent and selective outcome-contingent feedback provide support for the hypothesis of constructivist coding (Elwin, Juslin, Olsson, & Enkvist, 2007), according to which the outcomes on nonfeedback trials are coded with the most likely outcome, as inferred by the individual. The relation to sampling-based approaches to judgment, and the adaptive significance of constructivist coding, are discussed. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

The Sustained Influence of an Error on Future Decision-Making.

PubMed

Schiffler, Björn C; Bengtsson, Sara L; Lundqvist, Daniel

2017-01-01

Post-error slowing (PES) is consistently observed in decision-making tasks after negative feedback. Yet, findings are inconclusive as to whether PES supports performance accuracy. We addressed the role of PES by employing drift diffusion modeling which enabled us to investigate latent processes of reaction times and accuracy on a large-scale dataset (>5,800 participants) of a visual search experiment with emotional face stimuli. In our experiment, post-error trials were characterized by both adaptive and non-adaptive decision processes. An adaptive increase in participants' response threshold was sustained over several trials post-error. Contrarily, an initial decrease in evidence accumulation rate, followed by an increase on the subsequent trials, indicates a momentary distraction of task-relevant attention and resulted in an initial accuracy drop. Higher values of decision threshold and evidence accumulation on the post-error trial were associated with higher accuracy on subsequent trials which further gives credence to these parameters' role in post-error adaptation. Finally, the evidence accumulation rate post-error decreased when the error trial presented angry faces, a finding suggesting that the post-error decision can be influenced by the error context. In conclusion, we demonstrate that error-related response adaptations are multi-component processes that change dynamically over several trials post-error.

Entropy-functional-based online adaptive decision fusion framework with application to wildfire detection in video.

PubMed

Gunay, Osman; Toreyin, Behçet Ugur; Kose, Kivanc; Cetin, A Enis

2012-05-01

In this paper, an entropy-functional-based online adaptive decision fusion (EADF) framework is developed for image analysis and computer vision applications. In this framework, it is assumed that the compound algorithm consists of several subalgorithms, each of which yields its own decision as a real number centered around zero, representing the confidence level of that particular subalgorithm. Decision values are linearly combined with weights that are updated online according to an active fusion method based on performing entropic projections onto convex sets describing subalgorithms. It is assumed that there is an oracle, who is usually a human operator, providing feedback to the decision fusion method. A video-based wildfire detection system was developed to evaluate the performance of the decision fusion algorithm. In this case, image data arrive sequentially, and the oracle is the security guard of the forest lookout tower, verifying the decision of the combined algorithm. The simulation results are presented.

Introduction of new technologies and decision making processes: a framework to adapt a Local Health Technology Decision Support Program for other local settings.

PubMed

Poulin, Paule; Austen, Lea; Scott, Catherine M; Poulin, Michelle; Gall, Nadine; Seidel, Judy; Lafrenière, René

2013-01-01

Introducing new health technologies, including medical devices, into a local setting in a safe, effective, and transparent manner is a complex process, involving many disciplines and players within an organization. Decision making should be systematic, consistent, and transparent. It should involve translating and integrating scientific evidence, such as health technology assessment (HTA) reports, with context-sensitive evidence to develop recommendations on whether and under what conditions a new technology will be introduced. However, the development of a program to support such decision making can require considerable time and resources. An alternative is to adapt a preexisting program to the new setting. We describe a framework for adapting the Local HTA Decision Support Program, originally developed by the Department of Surgery and Surgical Services (Calgary, AB, Canada), for use by other departments. The framework consists of six steps: 1) development of a program review and adaptation manual, 2) education and readiness assessment of interested departments, 3) evaluation of the program by individual departments, 4) joint evaluation via retreats, 5) synthesis of feedback and program revision, and 6) evaluation of the adaptation process. Nine departments revised the Local HTA Decision Support Program and expressed strong satisfaction with the adaptation process. Key elements for success were identified. Adaptation of a preexisting program may reduce duplication of effort, save resources, raise the health care providers' awareness of HTA, and foster constructive stakeholder engagement, which enhances the legitimacy of evidence-informed recommendations for introducing new health technologies. We encourage others to use this framework for program adaptation and to report their experiences.

Neural correlates of uncertain decision making: ERP evidence from the Iowa Gambling Task

PubMed Central

Cui, Ji-fang; Chen, Ying-he; Wang, Ya; Shum, David H. K.; Chan, Raymond C. K.

2013-01-01

In our daily life, it is very common to make decisions in uncertain situations. The Iowa Gambling Task (IGT) has been widely used in laboratory studies because of its good simulation of uncertainty in real life activities. The present study aimed to examine the neural correlates of uncertain decision making with the IGT. Twenty-six university students completed this study. An adapted IGT was administered to them, and the EEG data were recorded. The adapted IGT we used allowed us to analyze the choice evaluation, response selection, and feedback evaluation stages of uncertain decision making within the same paradigm. In the choice evaluation stage, the advantageous decks evoked larger P3 amplitude in the left hemisphere, while the disadvantageous decks evoked larger P3 in the right hemisphere. In the response selection stage, the response of “pass” (the card was not turned over; the participants neither won nor lost money) evoked larger negativity preceding the response compared to that of “play” (the card was turned over; the participant either won or lost money). In the feedback evaluation stage, feedback-related negativity (FRN) was only sensitive to the valence (win/loss) but not the magnitude (large/small) of the outcome, and P3 was sensitive to both the valence and the magnitude of the outcome. These results were consistent with the notion that a positive somatic state was represented in the left hemisphere and a negative somatic state was represented in the right hemisphere. There were also anticipatory ERP effects that guided the participants' responses and provided evidence for the somatic marker hypothesis with more precise timing. PMID:24298248

Nonlinear dynamics of team performance and adaptability in emergency response.

PubMed

Guastello, Stephen J

2010-04-01

The impact of team size and performance feedback on adaptation levels and performance of emergency response (ER) teams was examined to introduce a metric for quantifying adaptation levels based on nonlinear dynamical systems (NDS) theory. NDS principles appear in reports surrounding Hurricane Katrina, earthquakes, floods, a disease epidemic, and the Southeast Asian tsunami. They are also intrinsic to coordination within teams, adaptation levels, and performance in dynamic decision processes. Performance was measured in a dynamic decision task in which ER teams of different sizes worked against an attacker who was trying to destroy a city (total N = 225 undergraduates). The complexity of teams' and attackers' adaptation strategies and the role of the opponents' performance were assessed by nonlinear regression analysis. An optimal group size for team performance was identified. Teams were more readily influenced by the attackers' performance than vice versa. The adaptive capabilities of attackers and teams were impaired by their opponents in some conditions. ER teams should be large enough to contribute a critical mass of ideas but not so large that coordination would be compromised. ER teams used self-organized strategies that could have been more adaptive, whereas attackers used chaotic strategies. The model and results are applicable to ER processes or training maneuvers involving dynamic decisions but could be limited to nonhierarchical groups.

Using complexity science and negotiation theory to resolve boundary-crossing water issues

NASA Astrophysics Data System (ADS)

Islam, Shafiqul; Susskind, Lawrence

2018-07-01

Many water governance and management issues are complex. The complexity of these issues is related to crossing of multiple boundaries: political, social and jurisdictional, as well as physical, ecological and biogeochemical. Resolution of these issues usually requires interactions of many parties with conflicting values and interests operating across multiple boundaries and scales to make decisions. The interdependence and feedback among interacting variables, processes, actors and institutions are hard to model and difficult to forecast. Thus, decision-making related to complex water problems needs be contingent and adaptive. This paper draws on a number of ideas from complexity science and negotiation theory that may make it easier to cope with the complexities and difficulties of managing boundary crossing water disputes. It begins with the Water Diplomacy Framework that was developed and tested over the past several years. Then, it uses three key ideas from complexity science (interdependence and interconnectedness; uncertainty and feedback; emergence and adaptation) and three from negotiation theory (stakeholder identification and engagement; joint fact finding; and value creation through option generation) to show how application of these ideas can help enhance effectiveness of water management.

Risk assessment and adaptive runoff utilization in water resource system considering the complex relationship among water supply, electricity generation and environment

NASA Astrophysics Data System (ADS)

Zhou, J.; Zeng, X.; Mo, L.; Chen, L.; Jiang, Z.; Feng, Z.; Yuan, L.; He, Z.

2017-12-01

Generally, the adaptive utilization and regulation of runoff in the source region of China's southwest rivers is classified as a typical multi-objective collaborative optimization problem. There are grim competitions and incidence relation in the subsystems of water supply, electricity generation and environment, which leads to a series of complex problems represented by hydrological process variation, blocked electricity output and water environment risk. Mathematically, the difficulties of multi-objective collaborative optimization focus on the description of reciprocal relationships and the establishment of evolving model of adaptive systems. Thus, based on the theory of complex systems science, this project tries to carry out the research from the following aspects: the changing trend of coupled water resource, the covariant factor and driving mechanism, the dynamic evolution law of mutual feedback dynamic process in the supply-generation-environment coupled system, the environmental response and influence mechanism of coupled mutual feedback water resource system, the relationship between leading risk factor and multiple risk based on evolutionary stability and dynamic balance, the transfer mechanism of multiple risk response with the variation of the leading risk factor, the multidimensional coupled feedback system of multiple risk assessment index system and optimized decision theory. Based on the above-mentioned research results, the dynamic method balancing the efficiency of multiple objectives in the coupled feedback system and optimized regulation model of water resources is proposed, and the adaptive scheduling mode considering the internal characteristics and external response of coupled mutual feedback system of water resource is established. In this way, the project can make a contribution to the optimal scheduling theory and methodology of water resource management under uncertainty in the source region of Southwest River.

Can conservation contracts co-exist with change? Payment for ecosystem services in the context of adaptive decision-making and sustainability.

PubMed

Hayes, Tanya; Murtinho, Felipe; Cárdenas Camacho, Luis Mario; Crespo, Patricio; McHugh, Sarah; Salmerón, David

2015-01-01

This paper considers the ability of payment for ecosystem services (PES) programs to operate in the context of dynamic and complex social-ecological systems. Drawing on the experiences of two different PES programs in Latin America, we examine how PES institutions fit with the tenets of adaptive decision-making for sustainable resource management. We identify how the program goals and the connection to the market influence the incentive structure, information gathering, learning and feedback processes, and the structure of decision-making rights, specifically the ability to make and modify resource-use rules. Although limited in their generalizability, findings from the two case studies suggest a tension between the contractual model of PES and adaptive decision-making in natural resource systems. PES programs are not inherently decentralized, flexible management tools, as PES contracts tend to restrict decision-making rights and offer minimal flexibility mechanisms to change resource-use practices over the duration of the contract period. Furthermore, PES design and flexibility is heavily dependent on the goals and mission of the buyer and the respective market. If PES is to facilitate sustainable resource management, greater attention is needed to assess how the institutional design of the PES contracts influence the motivation and capacity of participants and program officers alike to adaptively manage the respective resource systems.

Can Conservation Contracts Co-exist with Change? Payment for Ecosystem Services in the Context of Adaptive Decision-Making and Sustainability

NASA Astrophysics Data System (ADS)

Hayes, Tanya; Murtinho, Felipe; Cárdenas Camacho, Luis Mario; Crespo, Patricio; McHugh, Sarah; Salmerón, David

2015-01-01

This paper considers the ability of payment for ecosystem services (PES) programs to operate in the context of dynamic and complex social-ecological systems. Drawing on the experiences of two different PES programs in Latin America, we examine how PES institutions fit with the tenets of adaptive decision-making for sustainable resource management. We identify how the program goals and the connection to the market influence the incentive structure, information gathering, learning and feedback processes, and the structure of decision-making rights, specifically the ability to make and modify resource-use rules. Although limited in their generalizability, findings from the two case studies suggest a tension between the contractual model of PES and adaptive decision-making in natural resource systems. PES programs are not inherently decentralized, flexible management tools, as PES contracts tend to restrict decision-making rights and offer minimal flexibility mechanisms to change resource-use practices over the duration of the contract period. Furthermore, PES design and flexibility is heavily dependent on the goals and mission of the buyer and the respective market. If PES is to facilitate sustainable resource management, greater attention is needed to assess how the institutional design of the PES contracts influence the motivation and capacity of participants and program officers alike to adaptively manage the respective resource systems.

The Role of Item Feedback in Self-Adapted Testing.

ERIC Educational Resources Information Center

Roos, Linda L.; And Others

1997-01-01

The importance of item feedback in self-adapted testing was studied by comparing feedback and no feedback conditions for computerized adaptive tests and self-adapted tests taken by 363 college students. Results indicate that item feedback is not necessary to realize score differences between self-adapted and computerized adaptive testing. (SLD)

Catechol-O-methyltransferase (COMT) genotype affects cognitive control during total sleep deprivation.

PubMed

Satterfield, Brieann C; Hinson, John M; Whitney, Paul; Schmidt, Michelle A; Wisor, Jonathan P; Van Dongen, Hans P A

2018-02-01

Adaptive decision making is profoundly impaired by total sleep deprivation (TSD). This suggests that TSD impacts fronto-striatal pathways involved in cognitive control, where dopamine is a key neuromodulator. In the prefrontal cortex (PFC), dopamine is catabolized by the enzyme catechol-O-methyltransferase (COMT). A functional polymorphism (Val158Met) influences COMT's enzymatic activity, resulting in markedly different levels of prefrontal dopamine. We investigated the effect of this polymorphism on adaptive decision making during TSD. Sixty-six healthy young adults participated in one of two in-laboratory studies. After a baseline day, subjects were randomized to either a TSD group (n = 32) with 38 h or 62 h of extended wakefulness or a well-rested control group (n = 34) with 10 h nighttime sleep opportunities. Subjects performed a go/no-go reversal learning (GNGr) task at well-rested baseline and again during TSD or equivalent control. During the task, subjects were required to learn stimulus-response relationships from accuracy feedback. The stimulus-response relationships were reversed halfway through the task, which required subjects to learn the new stimulus-response relationships from accuracy feedback. Performance on the GNGr task was quantified by discriminability (d') between go and no-go stimuli before and after the stimulus-response reversal. GNGr performance did not differ between COMT genotypes when subjects were well-rested. However, TSD exposed a significant vulnerability to adaptive decision making impairment in subjects with the Val allele. Our results indicate that sleep deprivation degrades cognitive control through a fronto-striatal, dopaminergic mechanism. Copyright © 2017 Elsevier Ltd. All rights reserved.

Performance improvement of optical wireless communication through fog with a decision feedback equalizer.

PubMed

Aharonovich, Marius; Arnon, Shlomi

2005-08-01

Optical wireless communication (OWC) systems use the atmosphere as a propagation medium. However, a common problem is that from time to time moderate cloud and fog emerge between the receiver and the transmitter. These adverse weather conditions impose temporal broadening and power loss on the optical signal, which reduces the digital signal-to-noise ratio (DSNR), produces significant intersymbol interference (ISI), and degrades the communication system's bit error rate (BER) and throughput. We propose and investigate the use of a combined adaptive bandwidth mechanism and decision feedback equalizer (DFE) to mitigate these atmospheric multipath effects. Based on theoretical analysis and simulations of DSNR penalties, BER, and optimum system bandwidths, we show that a DFE improves the outdoor OWC system immunity to ISI in foggy weather while maintaining high throughput and desired low BER.

When 'solutions of yesterday become problems of today': crisis-ridden decision making in a complex adaptive system (CAS)--the Additional Duty Hours Allowance in Ghana.

PubMed

Agyepong, Irene Akua; Kodua, Augustina; Adjei, Sam; Adam, Taghreed

2012-10-01

Implementation of policies (decisions) in the health sector is sometimes defeated by the system's response to the policy itself. This can lead to counter-intuitive, unanticipated, or more modest effects than expected by those who designed the policy. The health sector fits the characteristics of complex adaptive systems (CAS) and complexity is at the heart of this phenomenon. Anticipating both positive and negative effects of policy decisions, understanding the interests, power and interaction between multiple actors; and planning for the delayed and distal impact of policy decisions are essential for effective decision making in CAS. Failure to appreciate these elements often leads to a series of reductionist approach interventions or 'fixes'. This in turn can initiate a series of negative feedback loops that further complicates the situation over time. In this paper we use a case study of the Additional Duty Hours Allowance (ADHA) policy in Ghana to illustrate these points. Using causal loop diagrams, we unpack the intended and unintended effects of the policy and how these effects evolved over time. The overall goal is to advance our understanding of decision making in complex adaptive systems; and through this process identify some essential elements in formulating, updating and implementing health policy that can help to improve attainment of desired outcomes and minimize negative unintended effects.

Decision making in recurrent neuronal circuits.

PubMed

Wang, Xiao-Jing

2008-10-23

Decision making has recently emerged as a central theme in neurophysiological studies of cognition, and experimental and computational work has led to the proposal of a cortical circuit mechanism of elemental decision computations. This mechanism depends on slow recurrent synaptic excitation balanced by fast feedback inhibition, which not only instantiates attractor states for forming categorical choices but also long transients for gradually accumulating evidence in favor of or against alternative options. Such a circuit endowed with reward-dependent synaptic plasticity is able to produce adaptive choice behavior. While decision threshold is a core concept for reaction time tasks, it can be dissociated from a general decision rule. Moreover, perceptual decisions and value-based economic choices are described within a unified framework in which probabilistic choices result from irregular neuronal activity as well as iterative interactions of a decision maker with an uncertain environment or other unpredictable decision makers in a social group.

A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making.

PubMed

Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

2017-01-01

Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from behavioral, psychobiological and neurophysiological data may help to optimize future applications of this model such that it can be transferred to other domains of comparable dynamic decision tasks.

A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making

PubMed Central

Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

2017-01-01

Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from behavioral, psychobiological and neurophysiological data may help to optimize future applications of this model such that it can be transferred to other domains of comparable dynamic decision tasks. PMID:28824512

Cooperative drought adaptation: Integrating infrastructure development, conservation, and water transfers into adaptive policy pathways

NASA Astrophysics Data System (ADS)

Zeff, Harrison B.; Herman, Jonathan D.; Reed, Patrick M.; Characklis, Gregory W.

2016-09-01

A considerable fraction of urban water supply capacity serves primarily as a hedge against drought. Water utilities can reduce their dependence on firm capacity and forestall the development of new supplies using short-term drought management actions, such as conservation and transfers. Nevertheless, new supplies will often be needed, especially as demands rise due to population growth and economic development. Planning decisions regarding when and how to integrate new supply projects are fundamentally shaped by the way in which short-term adaptive drought management strategies are employed. To date, the challenges posed by long-term infrastructure sequencing and adaptive short-term drought management are treated independently, neglecting important feedbacks between planning and management actions. This work contributes a risk-based framework that uses continuously updating risk-of-failure (ROF) triggers to capture the feedbacks between short-term drought management actions (e.g., conservation and water transfers) and the selection and sequencing of a set of regional supply infrastructure options over the long term. Probabilistic regional water supply pathways are discovered for four water utilities in the "Research Triangle" region of North Carolina. Furthermore, this study distinguishes the status-quo planning path of independent action (encompassing utility-specific conservation and new supply infrastructure only) from two cooperative formulations: "weak" cooperation, which combines utility-specific conservation and infrastructure development with regional transfers, and "strong" cooperation, which also includes jointly developed regional infrastructure to support transfers. Results suggest that strong cooperation aids utilities in meeting their individual objectives at substantially lower costs and with less overall development. These benefits demonstrate how an adaptive, rule-based decision framework can coordinate integrated solutions that would not be identified using more traditional optimization methods.

Feedback control methods for drug dosage optimisation. Concepts, classification and clinical application.

PubMed

Vozeh, S; Steimer, J L

1985-01-01

The concept of feedback control methods for drug dosage optimisation is described from the viewpoint of control theory. The control system consists of 5 parts: (a) patient (the controlled process); (b) response (the measured feedback); (c) model (the mathematical description of the process); (d) adaptor (to update the parameters); and (e) controller (to determine optimum dosing strategy). In addition to the conventional distinction between open-loop and closed-loop control systems, a classification is proposed for dosage optimisation techniques which distinguishes between tight-loop and loose-loop methods depending on whether physician's interaction is absent or included as part of the control step. Unlike engineering problems where the process can usually be controlled by fully automated devices, therapeutic situations often require that the physician be included in the decision-making process to determine the 'optimal' dosing strategy. Tight-loop and loose-loop methods can be further divided into adaptive and non-adaptive, depending on the presence of the adaptor. The main application areas of tight-loop feedback control methods are general anaesthesia, control of blood pressure, and insulin delivery devices. Loose-loop feedback methods have been used for oral anticoagulation and in therapeutic drug monitoring. The methodology, advantages and limitations of the different approaches are reviewed. A general feature common to all application areas could be observed: to perform well under routine clinical conditions, which are characterised by large interpatient variability and sometimes also intrapatient changes, control systems should be adaptive. Apart from application in routine drug treatment, feedback control methods represent an important research tool. They can be applied for the investigation of pathophysiological and pharmacodynamic processes. A most promising application is the evaluation of the relationship between an intermediate response (e.g. drug level), which is often used as feedback for dosage adjustment, and the final therapeutic goal.

Error Argumentation Enhance Adaptability in Adults With Low Motor Ability.

PubMed

Lee, Chi-Mei; Bo, Jin

2016-01-01

The authors focused on young adults with varying degrees of motor difficulties and examined their adaptability in a visuomotor adaptation task where the visual feedback of participants' movement error was presented with either 1:1 ratio (i.e., regular feedback schedule) or 1:2 ratio (i.e., enhanced feedback schedule). Within-subject design was used with two feedback schedules counter-balanced and separated for 10 days. Results revealed that participants with greater motor difficulties showed less adaptability than those with normal motor abilities in the regular feedback schedule; however, all participants demonstrated similar level of adaptability in the enhanced feedback schedule. The results suggest that error argumentation enhances adaptability in adults with low motor ability.

Sure I'm Sure: Prefrontal Oscillations Support Metacognitive Monitoring of Decision Making.

PubMed

Wokke, Martijn E; Cleeremans, Axel; Ridderinkhof, K Richard

2017-01-25

Successful decision making critically involves metacognitive processes such as monitoring and control of our decision process. Metacognition enables agents to modify ongoing behavior adaptively and determine what to do next in situations in which external feedback is not (immediately) available. Despite the importance of metacognition for many aspects of life, little is known about how our metacognitive system operates or about what kind of information is used for metacognitive (second-order) judgments. In particular, it remains an open question whether metacognitive judgments are based on the same information as first-order decisions. Here, we investigated the relationship between metacognitive performance and first-order task performance by recording EEG signals while participants were asked to make a "diagnosis" after seeing a sample of fictitious patient data (a complex pattern of colored moving dots of different sizes). To assess metacognitive performance, participants provided an estimate about the quality of their diagnosis on each trial. Results demonstrate that the information that contributes to first-order decisions differs from the information that supports metacognitive judgments. Further, time-frequency analyses of EEG signals reveal that metacognitive performance is associated specifically with prefrontal theta-band activity. Together, our findings are consistent with a hierarchical model of metacognition and suggest a crucial role for prefrontal oscillations in metacognitive performance. Monitoring and control of our decision process (metacognition) is a crucial aspect of adaptive decision making. Crucially, metacognitive skills enable us to adjust ongoing behavior and determine future decision making when immediate feedback is not available. In the present study, we constructed a "diagnosis task" that allowed us to assess in what way first-order task performance and metacognition are related to each other. Results demonstrate that the contribution of sensory evidence (size, color, and motion direction) differs between first- and second-order decision making. Further, our results indicate that metacognitive performance specifically is orchestrated by means of prefrontal theta oscillations. Together, our findings suggest a hierarchical model of metacognition. Copyright © 2017 the authors 0270-6474/17/370781-09$15.00/0.

Effect of feedback mode and task difficulty on quality of timing decisions in a zero-sum game.

PubMed

Tikuisis, Peter; Vartanian, Oshin; Mandel, David R

2014-09-01

The objective was to investigate the interaction between the mode of performance outcome feedback and task difficulty on timing decisions (i.e., when to act). Feedback is widely acknowledged to affect task performance. However, the extent to which feedback display mode and its impact on timing decisions is moderated by task difficulty remains largely unknown. Participants repeatedly engaged a zero-sum game involving silent duels with a computerized opponent and were given visual performance feedback after each engagement. They were sequentially tested on three different levels of task difficulty (low, intermediate, and high) in counterbalanced order. Half received relatively simple "inside view" binary outcome feedback, and the other half received complex "outside view" hit rate probability feedback. The key dependent variables were response time (i.e., time taken to make a decision) and survival outcome. When task difficulty was low to moderate, participants were more likely to learn and perform better from hit rate probability feedback than binary outcome feedback. However, better performance with hit rate feedback exacted a higher cognitive cost manifested by higher decision response time. The beneficial effect of hit rate probability feedback on timing decisions is partially moderated by task difficulty. Performance feedback mode should be judiciously chosen in relation to task difficulty for optimal performance in tasks involving timing decisions.

Recent advances in applying decision science to managing national forests

USGS Publications Warehouse

Marcot, Bruce G.; Thompson, Matthew P.; Runge, Michael C.; Thompson, Frank R.; McNulty, Steven; Cleaves, David; Tomosy, Monica; Fisher, Larry A.; Andrew, Bliss

2012-01-01

Management of federal public forests to meet sustainability goals and multiple use regulations is an immense challenge. To succeed, we suggest use of formal decision science procedures and tools in the context of structured decision making (SDM). SDM entails four stages: problem structuring (framing the problem and defining objectives and evaluation criteria), problem analysis (defining alternatives, evaluating likely consequences, identifying key uncertainties, and analyzing tradeoffs), decision point (identifying the preferred alternative), and implementation and monitoring the preferred alternative with adaptive management feedbacks. We list a wide array of models, techniques, and tools available for each stage, and provide three case studies of their selected use in National Forest land management and project plans. Successful use of SDM involves participation by decision-makers, analysts, scientists, and stakeholders. We suggest specific areas for training and instituting SDM to foster transparency, rigor, clarity, and inclusiveness in formal decision processes regarding management of national forests.

Polya's bees: A model of decentralized decision-making.

PubMed

Golman, Russell; Hagmann, David; Miller, John H

2015-09-01

How do social systems make decisions with no single individual in control? We observe that a variety of natural systems, including colonies of ants and bees and perhaps even neurons in the human brain, make decentralized decisions using common processes involving information search with positive feedback and consensus choice through quorum sensing. We model this process with an urn scheme that runs until hitting a threshold, and we characterize an inherent tradeoff between the speed and the accuracy of a decision. The proposed common mechanism provides a robust and effective means by which a decentralized system can navigate the speed-accuracy tradeoff and make reasonably good, quick decisions in a variety of environments. Additionally, consensus choice exhibits systemic risk aversion even while individuals are idiosyncratically risk-neutral. This too is adaptive. The model illustrates how natural systems make decentralized decisions, illuminating a mechanism that engineers of social and artificial systems could imitate.

Polya’s bees: A model of decentralized decision-making

PubMed Central

Golman, Russell; Hagmann, David; Miller, John H.

2015-01-01

How do social systems make decisions with no single individual in control? We observe that a variety of natural systems, including colonies of ants and bees and perhaps even neurons in the human brain, make decentralized decisions using common processes involving information search with positive feedback and consensus choice through quorum sensing. We model this process with an urn scheme that runs until hitting a threshold, and we characterize an inherent tradeoff between the speed and the accuracy of a decision. The proposed common mechanism provides a robust and effective means by which a decentralized system can navigate the speed-accuracy tradeoff and make reasonably good, quick decisions in a variety of environments. Additionally, consensus choice exhibits systemic risk aversion even while individuals are idiosyncratically risk-neutral. This too is adaptive. The model illustrates how natural systems make decentralized decisions, illuminating a mechanism that engineers of social and artificial systems could imitate. PMID:26601255

Reward abundance interferes with error-based learning in a visuomotor adaptation task

PubMed Central

Oostwoud Wijdenes, Leonie; Rigterink, Tessa; Overvliet, Krista E.; Smeets, Joeren B. J.

2018-01-01

The brain rapidly adapts reaching movements to changing circumstances by using visual feedback about errors. Providing reward in addition to error feedback facilitates the adaptation but the underlying mechanism is unknown. Here, we investigate whether the proportion of trials rewarded (the ‘reward abundance’) influences how much participants adapt to their errors. We used a 3D multi-target pointing task in which reward alone is insufficient for motor adaptation. Participants (N = 423) performed the pointing task with feedback based on a shifted hand-position. On a proportion of trials we gave them rewarding feedback that their hand hit the target. Half of the participants only received this reward feedback. The other half also received feedback about endpoint errors. In different groups, we varied the proportion of trials that was rewarded. As expected, participants who received feedback about their errors did adapt, but participants who only received reward-feedback did not. Critically, participants who received abundant rewards adapted less to their errors than participants who received less reward. Thus, reward abundance negatively influences how much participants learn from their errors. Probably participants used a mechanism that relied more on the reward feedback when the reward was abundant. Because participants could not adapt to the reward, this interfered with adaptation to errors. PMID:29513681

An Adapting Auditory-motor Feedback Loop Can Contribute to Generating Vocal Repetition

PubMed Central

Brainard, Michael S.; Jin, Dezhe Z.

2015-01-01

Consecutive repetition of actions is common in behavioral sequences. Although integration of sensory feedback with internal motor programs is important for sequence generation, if and how feedback contributes to repetitive actions is poorly understood. Here we study how auditory feedback contributes to generating repetitive syllable sequences in songbirds. We propose that auditory signals provide positive feedback to ongoing motor commands, but this influence decays as feedback weakens from response adaptation during syllable repetitions. Computational models show that this mechanism explains repeat distributions observed in Bengalese finch song. We experimentally confirmed two predictions of this mechanism in Bengalese finches: removal of auditory feedback by deafening reduces syllable repetitions; and neural responses to auditory playback of repeated syllable sequences gradually adapt in sensory-motor nucleus HVC. Together, our results implicate a positive auditory-feedback loop with adaptation in generating repetitive vocalizations, and suggest sensory adaptation is important for feedback control of motor sequences. PMID:26448054

Cognitive Adaptability: The Role of Metacognition and Feedback in Entrepreneural Decision Policies

DTIC Science & Technology

2005-01-01

their environments in such a way as to facilitate effective and dynamic cognitive functioning. In this dissertation, I present three complementary studies ...the study of metacognition (Jost, Kruglanski, and Nelson, 1998; Mischel, 1998; Schwarz, 1998b). This research has three goals, specifically to...environments in such a way as to facilitate effective and dynamic cognitive functioning. In this dissertation, I present three complementary studies that

An adaptive molecular timer in p53-meidated cell fate decision

NASA Astrophysics Data System (ADS)

Zhang, Xiao-Peng; Wang, Ping; Liu, Feng; Wang, Wei

The tumor suppressor p53 decides cellular outcomes in the DNA damage response. It is intriguing to explore the link between p53 dynamics and cell fates. We developed a theoretical model of p53 signaling network to clarify the mechanism of cell fate decision mediated by its dynamics. We found that the interplay between p53-Mdm2 negative feedback loop and p53-PTEN-Mdm2 positive feedback loop shapes p53 dynamics. Depending on the intensity of DNA damage, p53 shows three modes of dynamics: persistent pulses, two-phase dynamics with pulses followed by sustained high levels and straightforward high levels. Especially, p53 shows two-phase dynamics upon moderated damage and the required number of p53 pulses before apoptosis induction decreases with increasing DNA damage. Our results suggested there exists an adaptive molecular timer that determines whether and when the apoptosis switch should be triggered. We clarified the mechanism behind the switching of p53 dynamical modes by bifurcation analysis. Moreover, we reproduced the experimental results that drug additions alter p53 pulses to sustained p53 activation and leads to senescence. Our work may advance the understanding the significance of p53 dynamics in tumor suppression. This work was supported by National Natural Science Foundation of China (Nos. 11175084, 11204126 and 31361163003).

Evolving the US Climate Resilience Toolkit to Support a Climate-Smart Nation

NASA Astrophysics Data System (ADS)

Tilmes, C.; Niepold, F., III; Fox, J. F.; Herring, D.; Dahlman, L. E.; Hall, N.; Gardiner, N.

2015-12-01

Communities, businesses, resource managers, and decision-makers at all levels of government need information to understand and ameliorate climate-related risks. Likewise, climate information can expose latent opportunities. Moving from climate science to social and economic decisions raises complex questions about how to communicate the causes and impacts of climate variability and change; how to characterize and quantify vulnerabilities, risks, and opportunities faced by communities and businesses; and how to make and implement "win-win" adaptation plans at local, regional, and national scales. A broad coalition of federal agencies launched the U.S. Climate Resilience Toolkit (toolkit.climate.gov) in November 2014 to help our nation build resilience to climate-related extreme events. The site's primary audience is planners and decision makers in business, resource management, and government (at all levels) who seek science-based climate information and tools to help them in their near- and long-term planning. The Executive Office of the President assembled a task force of dozens of subject experts from across the 13 agencies of the U.S. Global Change Research Program to guide the site's development. The site's ongoing evolution is driven by feedback from the target audience. For example, based on feedback, climate projections will soon play a more prominent role in the site's "Climate Explorer" tool and case studies. The site's five-step adaptation planning process is being improved to better facilitate people getting started and to provide clear benchmarks for evaluating progress along the way. In this session, we will share lessons learned from a series of user engagements around the nation and evidence that the Toolkit couples climate information with actionable decision-making processes in ways that are helping Americans build resilience to climate-related stressors.

Modelling human decision-making in coupled human and natural systems

NASA Astrophysics Data System (ADS)

Feola, G.

2012-12-01

A solid understanding of human decision-making is essential to analyze the complexity of coupled human and natural systems (CHANS) and inform policies to promote resilience in the face of environmental change. Human decisions drive and/or mediate the interactions and feedbacks, and contribute to the heterogeneity and non-linearity that characterize CHANS. However, human decision-making is usually over-simplistically modeled, whereby human agents are represented deterministically either as dumb or clairvoyant decision-makers. Decision-making models fall short in the integration of both environmental and human behavioral drivers, and concerning the latter, tend to focus on only one category, e.g. economic, cultural, or psychological. Furthermore, these models render a linear decision-making process and therefore fail to account for the recursive co-evolutionary dynamics in CHANS. As a result, these models constitute only a weak basis for policy-making. There is therefore scope and an urgent need for better approaches to human decision-making, to produce the knowledge that can inform vulnerability reduction policies in the face of environmental change. This presentation synthesizes the current state-of-the-art of modelling human decision-making in CHANS, with particular reference to agricultural systems, and delineates how the above mentioned shortcomings can be overcome. Through examples from research on pesticide use and adaptation to climate change, both based on the integrative agent-centered framework (Feola and Binder, 2010), the approach for an improved understanding of human agents in CHANS are illustrated. This entails: integrative approach, focus on behavioral dynamics more than states, feedbacks between individual and system levels, and openness to heterogeneity.

Randomised prior feedback modulates neural signals of outcome monitoring.

PubMed

Mushtaq, Faisal; Wilkie, Richard M; Mon-Williams, Mark A; Schaefer, Alexandre

2016-01-15

Substantial evidence indicates that decision outcomes are typically evaluated relative to expectations learned from relatively long sequences of previous outcomes. This mechanism is thought to play a key role in general learning and adaptation processes but relatively little is known about the determinants of outcome evaluation when the capacity to learn from series of prior events is difficult or impossible. To investigate this issue, we examined how the feedback-related negativity (FRN) is modulated by information briefly presented before outcome evaluation. The FRN is a brain potential time-locked to the delivery of decision feedback and it is widely thought to be sensitive to prior expectations. We conducted a multi-trial gambling task in which outcomes at each trial were fully randomised to minimise the capacity to learn from long sequences of prior outcomes. Event-related potentials for outcomes (Win/Loss) in the current trial (Outcomet) were separated according to the type of outcomes that occurred in the preceding two trials (Outcomet-1 and Outcomet-2). We found that FRN voltage was more positive during the processing of win feedback when it was preceded by wins at Outcomet-1 compared to win feedback preceded by losses at Outcomet-1. However, no influence of preceding outcomes was found on FRN activity relative to the processing of loss feedback. We also found no effects of Outcomet-2 on FRN amplitude relative to current feedback. Additional analyses indicated that this effect was largest for trials in which participants selected a decision different to the gamble chosen in the previous trial. These findings are inconsistent with models that solely relate the FRN to prediction error computation. Instead, our results suggest that if stable predictions about future events are weak or non-existent, then outcome processing can be determined by affective systems. More specifically, our results indicate that the FRN is likely to reflect the activity of positive affective systems in these contexts. Importantly, our findings indicate that a multifactorial explanation of the nature of the FRN is necessary and such an account must incorporate affective and motivational factors in outcome processing. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Randomised prior feedback modulates neural signals of outcome monitoring

PubMed Central

Mushtaq, Faisal; Wilkie, Richard M.; Mon-Williams, Mark A.; Schaefer, Alexandre

2016-01-01

Substantial evidence indicates that decision outcomes are typically evaluated relative to expectations learned from relatively long sequences of previous outcomes. This mechanism is thought to play a key role in general learning and adaptation processes but relatively little is known about the determinants of outcome evaluation when the capacity to learn from series of prior events is difficult or impossible. To investigate this issue, we examined how the feedback-related negativity (FRN) is modulated by information briefly presented before outcome evaluation. The FRN is a brain potential time-locked to the delivery of decision feedback and it is widely thought to be sensitive to prior expectations. We conducted a multi-trial gambling task in which outcomes at each trial were fully randomised to minimise the capacity to learn from long sequences of prior outcomes. Event-related potentials for outcomes (Win/Loss) in the current trial (Outcomet) were separated according to the type of outcomes that occurred in the preceding two trials (Outcomet-1 and Outcomet-2). We found that FRN voltage was more positive during the processing of win feedback when it was preceded by wins at Outcomet-1 compared to win feedback preceded by losses at Outcomet-1. However, no influence of preceding outcomes was found on FRN activity relative to the processing of loss feedback. We also found no effects of Outcomet-2 on FRN amplitude relative to current feedback. Additional analyses indicated that this effect was largest for trials in which participants selected a decision different to the gamble chosen in the previous trial. These findings are inconsistent with models that solely relate the FRN to prediction error computation. Instead, our results suggest that if stable predictions about future events are weak or non-existent, then outcome processing can be determined by affective systems. More specifically, our results indicate that the FRN is likely to reflect the activity of positive affective systems in these contexts. Importantly, our findings indicate that a multifactorial explanation of the nature of the FRN is necessary and such an account must incorporate affective and motivational factors in outcome processing. PMID:26497268

Social closeness and feedback modulate susceptibility to the framing effect

PubMed Central

Sip, Kamila E.; Smith, David V.; Porcelli, Anthony J.; Kar, Kohitij; Delgado, Mauricio R.

2014-01-01

Although, we often seek social feedback from others to help us make decisions, little is known about how social feedback affects decisions under risk, particularly from a close peer. We conducted two experiments using an established framing task to probe how decision making is modulated by social feedback valence (positive, negative) and the level of closeness with feedback provider (friend, confederate). Participants faced mathematically equivalent decisions framed as either an opportunity to keep (gain frame) or lose (loss frame) part of an initial endowment. Periodically, participants were provided with positive (e.g., “Nice!”) or negative (e.g., “Lame!”) feedback about their choices. Such feedback was provided by either a confederate (Experiment 1), or a gender-matched close friend (Experiment 2). As expected, the framing effect was observed in both experiments. Critically, an individual’s susceptibility to the framing effect was modulated by the valence of the social feedback, but only when the feedback provider was a close friend. This effect was reflected in the activation patterns of ventromedial prefrontal cortex and posterior cingulate cortex, regions involved in complex decision making. Taken together, these results highlight social closeness as an important factor in understanding the impact of social feedback on neural mechanisms of decision making. PMID:25074501

Observer-Based Adaptive Neural Network Control for Nonlinear Systems in Nonstrict-Feedback Form.

PubMed

Chen, Bing; Zhang, Huaguang; Lin, Chong

2016-01-01

This paper focuses on the problem of adaptive neural network (NN) control for a class of nonlinear nonstrict-feedback systems via output feedback. A novel adaptive NN backstepping output-feedback control approach is first proposed for nonlinear nonstrict-feedback systems. The monotonicity of system bounding functions and the structure character of radial basis function (RBF) NNs are used to overcome the difficulties that arise from nonstrict-feedback structure. A state observer is constructed to estimate the immeasurable state variables. By combining adaptive backstepping technique with approximation capability of radial basis function NNs, an output-feedback adaptive NN controller is designed through backstepping approach. It is shown that the proposed controller guarantees semiglobal boundedness of all the signals in the closed-loop systems. Two examples are used to illustrate the effectiveness of the proposed approach.

Integrating the Interagency in the Armed Forces of the Philippines Approach to Counterinsurgency

DTIC Science & Technology

2010-03-23

Figure 5 (McCormick’s Diamond Basilan Model ) ................................. 25 v Preface The resurgence of the Abu Sayyaf Group in Basilan, the...address~d by the AFP are the Communist Party of the Philippines/New People’s Army (CPP/NPA), the _ seces~ionist Moro Islamic Uberation Front (MU,F...discussion, holistic thinking, 8 model making, intuitive decision-making, continuous assessment thru feedback, structured learning thru adaptation

Control Automation in Undersea Search and Manipulation

NASA Technical Reports Server (NTRS)

Weltman, Gershon; Freedy, Amos

1974-01-01

Automatic decision making and control mechanisms of the type termed "adaptive" or "intelligent" offer unique advantages for exploration and manipulation of the undersea environment, particularly at great depths. Because they are able to carry out human-like functions autonomously, such mechanisms can aid and extend the capabilities of the human operator. This paper reviews past and present work in the areas of adaptive control and robotics with the purpose of establishing logical guidelines for the application of automatic techniques underwater. Experimental research data are used to illustrate the importance of information feedback, personnel training, and methods of control allocation in the interaction between operator and intelligent machine.

Empirical Analysis of EEG and ERPs for Psychophysiological Adaptive Task Allocation

NASA Technical Reports Server (NTRS)

Prinzel, Lawrence J., III; Pope, Alan T.; Freeman, Frederick G.; Scerbo, Mark W.; Mikulka, Peter J.

2001-01-01

The present study was designed to test the efficacy of using Electroencephalogram (EEG) and Event-Related Potentials (ERPs) for making task allocation decisions. Thirty-six participants were randomly assigned to an experimental, yoked, or control group condition. Under the experimental condition, a tracking task was switched between task modes based upon the participant's EEG. The results showed that the use of adaptive aiding improved performance and lowered subjective workload under negative feedback as predicted. Additionally, participants in the adaptive group had significantly lower RMSE and NASA-TLX ratings than participants in either the yoked or control group conditions. Furthermore, the amplitudes of the N1 and P3 ERP components were significantly larger under the experimental group condition than under either the yoked or control group conditions. These results are discussed in terms of the implications for adaptive automation design.

An incremental database access method for autonomous interoperable databases

NASA Technical Reports Server (NTRS)

Roussopoulos, Nicholas; Sellis, Timos

1994-01-01

We investigated a number of design and performance issues of interoperable database management systems (DBMS's). The major results of our investigation were obtained in the areas of client-server database architectures for heterogeneous DBMS's, incremental computation models, buffer management techniques, and query optimization. We finished a prototype of an advanced client-server workstation-based DBMS which allows access to multiple heterogeneous commercial DBMS's. Experiments and simulations were then run to compare its performance with the standard client-server architectures. The focus of this research was on adaptive optimization methods of heterogeneous database systems. Adaptive buffer management accounts for the random and object-oriented access methods for which no known characterization of the access patterns exists. Adaptive query optimization means that value distributions and selectives, which play the most significant role in query plan evaluation, are continuously refined to reflect the actual values as opposed to static ones that are computed off-line. Query feedback is a concept that was first introduced to the literature by our group. We employed query feedback for both adaptive buffer management and for computing value distributions and selectivities. For adaptive buffer management, we use the page faults of prior executions to achieve more 'informed' management decisions. For the estimation of the distributions of the selectivities, we use curve-fitting techniques, such as least squares and splines, for regressing on these values.

Effect of visuomotor-map uncertainty on visuomotor adaptation.

PubMed

Saijo, Naoki; Gomi, Hiroaki

2012-03-01

Vision and proprioception contribute to generating hand movement. If a conflict between the visual and proprioceptive feedback of hand position is given, reaching movement is disturbed initially but recovers after training. Although previous studies have predominantly investigated the adaptive change in the motor output, it is unclear whether the contributions of visual and proprioceptive feedback controls to the reaching movement are modified by visuomotor adaptation. To investigate this, we focused on the change in proprioceptive feedback control associated with visuomotor adaptation. After the adaptation to gradually introduce visuomotor rotation, the hand reached the shifted position of the visual target to move the cursor to the visual target correctly. When the cursor feedback was occasionally eliminated (probe trial), the end point of the hand movement was biased in the visual-target direction, while the movement was initiated in the adapted direction, suggesting the incomplete adaptation of proprioceptive feedback control. Moreover, after the learning of uncertain visuomotor rotation, in which the rotation angle was randomly fluctuated on a trial-by-trial basis, the end-point bias in the probe trial increased, but the initial movement direction was not affected, suggesting a reduction in the adaptation level of proprioceptive feedback control. These results suggest that the change in the relative contribution of visual and proprioceptive feedback controls to the reaching movement in response to the visuomotor-map uncertainty is involved in visuomotor adaptation, whereas feedforward control might adapt in a manner different from that of the feedback control.

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

PubMed

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

2014-08-20

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

Visuomotor adaptability in older adults with mild cognitive decline.

PubMed

Schaffert, Jeffrey; Lee, Chi-Mei; Neill, Rebecca; Bo, Jin

2017-02-01

The current study examined the augmentation of error feedback on visuomotor adaptability in older adults with varying degrees of cognitive decline (assessed by the Montreal Cognitive Assessment; MoCA). Twenty-three participants performed a center-out computerized visuomotor adaptation task when the visual feedback of their hand movement error was presented in a regular (ratio=1:1) or enhanced (ratio=1:2) error feedback schedule. Results showed that older adults with lower scores on the MoCA had less adaptability than those with higher MoCA scores during the regular feedback schedule. However, participants demonstrated similar adaptability during the enhanced feedback schedule, regardless of their cognitive ability. Furthermore, individuals with lower MoCA scores showed larger after-effects in spatial control during the enhanced schedule compared to the regular schedule, whereas individuals with higher MoCA scores displayed the opposite pattern. Additional neuro-cognitive assessments revealed that spatial working memory and processing speed were positively related to motor adaptability during the regular scheduled but negatively related to adaptability during the enhanced schedule. We argue that individuals with mild cognitive decline employed different adaptation strategies when encountering enhanced visual feedback, suggesting older adults with mild cognitive impairment (MCI) may benefit from enhanced visual error feedback during sensorimotor adaptation. Copyright © 2016 Elsevier B.V. All rights reserved.

Critical role for the mediodorsal thalamus in permitting rapid reward-guided updating in stochastic reward environments

PubMed Central

Chakraborty, Subhojit; Kolling, Nils; Walton, Mark E; Mitchell, Anna S

2016-01-01

Adaptive decision-making uses information gained when exploring alternative options to decide whether to update the current choice strategy. Magnocellular mediodorsal thalamus (MDmc) supports adaptive decision-making, but its causal contribution is not well understood. Monkeys with excitotoxic MDmc damage were tested on probabilistic three-choice decision-making tasks. They could learn and track the changing values in object-reward associations, but they were severely impaired at updating choices after reversals in reward contingencies or when there were multiple options associated with reward. These deficits were not caused by perseveration or insensitivity to negative feedback though. Instead, monkeys with MDmc lesions exhibited an inability to use reward to promote choice repetition after switching to an alternative option due to a diminished influence of recent past choices and the last outcome to guide future behavior. Together, these data suggest MDmc allows for the rapid discovery and persistence with rewarding options, particularly in uncertain or changing environments. DOI: http://dx.doi.org/10.7554/eLife.13588.001 PMID:27136677

Conservation in the face of climate change: The roles of alternative models, monitoring, and adaptation in confronting and reducing uncertainty

USGS Publications Warehouse

Conroy, M.J.; Runge, M.C.; Nichols, J.D.; Stodola, K.W.; Cooper, R.J.

2011-01-01

The broad physical and biological principles behind climate change and its potential large scale ecological impacts on biota are fairly well understood, although likely responses of biotic communities at fine spatio-temporal scales are not, limiting the ability of conservation programs to respond effectively to climate change outside the range of human experience. Much of the climate debate has focused on attempts to resolve key uncertainties in a hypothesis-testing framework. However, conservation decisions cannot await resolution of these scientific issues and instead must proceed in the face of uncertainty. We suggest that conservation should precede in an adaptive management framework, in which decisions are guided by predictions under multiple, plausible hypotheses about climate impacts. Under this plan, monitoring is used to evaluate the response of the system to climate drivers, and management actions (perhaps experimental) are used to confront testable predictions with data, in turn providing feedback for future decision making. We illustrate these principles with the problem of mitigating the effects of climate change on terrestrial bird communities in the southern Appalachian Mountains, USA. ?? 2010 Elsevier Ltd.

Adaptive method with intercessory feedback control for an intelligent agent

DOEpatents

Goldsmith, Steven Y.

2004-06-22

An adaptive architecture method with feedback control for an intelligent agent provides for adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. An adaptive architecture method with feedback control for multiple intelligent agents provides for coordinating and adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. Re-programming of the adaptive architecture is through a nexus which coordinates reflexive and deliberator components.

Usability evaluation and adaptation of the e-health Personal Patient Profile-Prostate decision aid for Spanish-speaking Latino men.

PubMed

Berry, Donna L; Halpenny, Barbara; Bosco, Jaclyn L F; Bruyere, John; Sanda, Martin G

2015-07-24

The Personal Patient Profile-Prostate (P3P), a web-based decision aid, was demonstrated to reduce decisional conflict in English-speaking men with localized prostate cancer early after initial diagnosis. The purpose of this study was to explore and enhance usability and cultural appropriateness of a Spanish P3P by Latino men with a diagnosis of prostate cancer. P3P was translated to Spanish and back-translated by three native Spanish-speaking translators working independently. Spanish-speaking Latino men with a diagnosis of localized prostate cancer, who had made treatment decisions in the past 24 months, were recruited from two urban clinical care sites. Individual cognitive interviews were conducted by two bilingual research assistants as each participant used the Spanish P3P. Notes of user behavior, feedback, and answers to direct questions about comprehension, usability and perceived usefulness were analyzed and categorized. Seven participants with a range of education levels identified 25 unique usability issues in navigation, content comprehension and completeness, sociocultural appropriateness, and methodology. Revisions were prioritized to refine the usability and cultural and linguistic appropriateness of the decision aid. Usability issues were discovered that are potential barriers to effective decision support. Successful use of decision aids requires adaptation and testing beyond translation. Our findings led to revisions further refining the usability and linguistic and cultural appropriateness of Spanish P3P.

Proceedings of the NATO IST-128 Workshop: Assessing Mission Impact of Cyberattacks Held in Istanbul, Turkey on 15-17 June 2015

DTIC Science & Technology

2015-12-01

combine satisficing behaviour with learning and adaptation through environmental feedback. This a sequential decision making with one alternative...next action that an opponent will most likely take in a strategic interaction. Also, cognitive models derived from instance- based learning theory (IBL... through instance- based learning . In Y. Li (Ed.), Lecture Notes in Computer Science (Vol. 6818, pp. 281-293). Heidelberg: Springer Berlin. Gonzalez, C

Learning Rate Updating Methods Applied to Adaptive Fuzzy Equalizers for Broadband Power Line Communications

NASA Astrophysics Data System (ADS)

Ribeiro, Moisés V.

2004-12-01

This paper introduces adaptive fuzzy equalizers with variable step size for broadband power line (PL) communications. Based on delta-bar-delta and local Lipschitz estimation updating rules, feedforward, and decision feedback approaches, we propose singleton and nonsingleton fuzzy equalizers with variable step size to cope with the intersymbol interference (ISI) effects of PL channels and the hardness of the impulse noises generated by appliances and nonlinear loads connected to low-voltage power grids. The computed results show that the convergence rates of the proposed equalizers are higher than the ones attained by the traditional adaptive fuzzy equalizers introduced by J. M. Mendel and his students. Additionally, some interesting BER curves reveal that the proposed techniques are efficient for mitigating the above-mentioned impairments.

Using engineering control principles to inform the design of adaptive interventions: a conceptual introduction.

PubMed

Rivera, Daniel E; Pew, Michael D; Collins, Linda M

2007-05-01

The goal of this paper is to describe the role that control engineering principles can play in developing and improving the efficacy of adaptive, time-varying interventions. It is demonstrated that adaptive interventions constitute a form of feedback control system in the context of behavioral health. Consequently, drawing from ideas in control engineering has the potential to significantly inform the analysis, design, and implementation of adaptive interventions, leading to improved adherence, better management of limited resources, a reduction of negative effects, and overall more effective interventions. This article illustrates how to express an adaptive intervention in control engineering terms, and how to use this framework in a computer simulation to investigate the anticipated impact of intervention design choices on efficacy. The potential benefits of operationalizing decision rules based on control engineering principles are particularly significant for adaptive interventions that involve multiple components or address co-morbidities, situations that pose significant challenges to conventional clinical practice.

Using Engineering Control Principles to Inform the Design of Adaptive Interventions: A Conceptual Introduction

PubMed Central

Rivera, Daniel E.; Pew, Michael D.; Collins, Linda M.

2007-01-01

The goal of this paper is to describe the role that control engineering principles can play in developing and improving the efficacy of adaptive, time-varying interventions. It is demonstrated that adaptive interventions constitute a form of feedback control system in the context of behavioral health. Consequently, drawing from ideas in control engineering has the potential to significantly inform the analysis, design, and implementation of adaptive interventions, leading to improved adherence, better management of limited resources, a reduction of negative effects, and overall more effective interventions. This article illustrates how to express an adaptive intervention in control engineering terms, and how to use this framework in a computer simulation to investigate the anticipated impact of intervention design choices on efficacy. The potential benefits of operationalizing decision rules based on control engineering principles are particularly significant for adaptive interventions that involve multiple components or address co-morbidities, situations that pose significant challenges to conventional clinical practice. PMID:17169503

The economics of abrupt climate change.

PubMed

Perrings, Charles

2003-09-15

The US National Research Council defines abrupt climate change as a change of state that is sufficiently rapid and sufficiently widespread in its effects that economies are unprepared or incapable of adapting. This may be too restrictive a definition, but abrupt climate change does have implications for the choice between the main response options: mitigation (which reduces the risks of climate change) and adaptation (which reduces the costs of climate change). The paper argues that by (i) increasing the costs of change and the potential growth of consumption, and (ii) reducing the time to change, abrupt climate change favours mitigation over adaptation. Furthermore, because the implications of change are fundamentally uncertain and potentially very high, it favours a precautionary approach in which mitigation buys time for learning. Adaptation-oriented decision tools, such as scenario planning, are inappropriate in these circumstances. Hence learning implies the use of probabilistic models that include socioeconomic feedbacks.

A Decentralized Compositional Framework for Dependable Decision Process in Self-Managed Cyber Physical Systems

PubMed Central

Hou, Kun-Mean; Zhang, Zhan

2017-01-01

Cyber Physical Systems (CPSs) need to interact with the changeable environment under various interferences. To provide continuous and high quality services, a self-managed CPS should automatically reconstruct itself to adapt to these changes and recover from failures. Such dynamic adaptation behavior introduces systemic challenges for CPS design, advice evaluation and decision process arrangement. In this paper, a formal compositional framework is proposed to systematically improve the dependability of the decision process. To guarantee the consistent observation of event orders for causal reasoning, this work first proposes a relative time-based method to improve the composability and compositionality of the timing property of events. Based on the relative time solution, a formal reference framework is introduced for self-managed CPSs, which includes a compositional FSM-based actor model (subsystems of CPS), actor-based advice and runtime decomposable decisions. To simplify self-management, a self-similar recursive actor interface is proposed for decision (actor) composition. We provide constraints and seven patterns for the composition of reliability and process time requirements. Further, two decentralized decision process strategies are proposed based on our framework, and we compare the reliability with the static strategy and the centralized processing strategy. The simulation results show that the one-order feedback strategy has high reliability, scalability and stability against the complexity of decision and random failure. This paper also shows a way to simplify the evaluation for dynamic system by improving the composability and compositionality of the subsystem. PMID:29120357

A Decentralized Compositional Framework for Dependable Decision Process in Self-Managed Cyber Physical Systems.

PubMed

Zhou, Peng; Zuo, Decheng; Hou, Kun-Mean; Zhang, Zhan

2017-11-09

Cyber Physical Systems (CPSs) need to interact with the changeable environment under various interferences. To provide continuous and high quality services, a self-managed CPS should automatically reconstruct itself to adapt to these changes and recover from failures. Such dynamic adaptation behavior introduces systemic challenges for CPS design, advice evaluation and decision process arrangement. In this paper, a formal compositional framework is proposed to systematically improve the dependability of the decision process. To guarantee the consistent observation of event orders for causal reasoning, this work first proposes a relative time-based method to improve the composability and compositionality of the timing property of events. Based on the relative time solution, a formal reference framework is introduced for self-managed CPSs, which includes a compositional FSM-based actor model (subsystems of CPS), actor-based advice and runtime decomposable decisions. To simplify self-management, a self-similar recursive actor interface is proposed for decision (actor) composition. We provide constraints and seven patterns for the composition of reliability and process time requirements. Further, two decentralized decision process strategies are proposed based on our framework, and we compare the reliability with the static strategy and the centralized processing strategy. The simulation results show that the one-order feedback strategy has high reliability, scalability and stability against the complexity of decision and random failure. This paper also shows a way to simplify the evaluation for dynamic system by improving the composability and compositionality of the subsystem.

Adapting Progress Feedback and Emotional Support to Learner Personality

ERIC Educational Resources Information Center

Dennis, Matt; Masthoff, Judith; Mellish, Chris

2016-01-01

As feedback is an important part of learning and motivation, we investigate how to adapt the feedback of a conversational agent to learner personality (as well as to learner performance, as we expect an interaction effect between personality and performance on feedback). We investigate two aspects of feedback. Firstly, we investigate whether the…

Method and apparatus for adaptive force and position control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1989-01-01

The present invention discloses systematic methods and apparatus for the design of real time controllers. Real-time control employs adaptive force/position by use of feedforward and feedback controllers, with the feedforward controller being the inverse of the linearized model of robot dynamics and containing only proportional-double-derivative terms is disclosed. The feedback controller, of the proportional-integral-derivative type, ensures that manipulator joints follow reference trajectories and the feedback controller achieves robust tracking of step-plus-exponential trajectories, all in real time. The adaptive controller includes adaptive force and position control within a hybrid control architecture. The adaptive controller, for force control, achieves tracking of desired force setpoints, and the adaptive position controller accomplishes tracking of desired position trajectories. Circuits in the adaptive feedback and feedforward controllers are varied by adaptation laws.

The dissociable effects of punishment and reward on motor learning.

PubMed

Galea, Joseph M; Mallia, Elizabeth; Rothwell, John; Diedrichsen, Jörn

2015-04-01

A common assumption regarding error-based motor learning (motor adaptation) in humans is that its underlying mechanism is automatic and insensitive to reward- or punishment-based feedback. Contrary to this hypothesis, we show in a double dissociation that the two have independent effects on the learning and retention components of motor adaptation. Negative feedback, whether graded or binary, accelerated learning. While it was not necessary for the negative feedback to be coupled to monetary loss, it had to be clearly related to the actual performance on the preceding movement. Positive feedback did not speed up learning, but it increased retention of the motor memory when performance feedback was withdrawn. These findings reinforce the view that independent mechanisms underpin learning and retention in motor adaptation, reject the assumption that motor adaptation is independent of motivational feedback, and raise new questions regarding the neural basis of negative and positive motivational feedback in motor learning.

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.

Walking Flexibility after Hemispherectomy: Split-Belt Treadmill Adaptation and Feedback Control

ERIC Educational Resources Information Center

Choi, Julia T.; Vining, Eileen P. G.; Reisman, Darcy S.; Bastian, Amy J.

2009-01-01

Walking flexibility depends on use of feedback or reactive control to respond to unexpected changes in the environment, and the ability to adapt feedforward or predictive control for sustained alterations. Recent work has demonstrated that cerebellar damage impairs feedforward adaptation, but not feedback control, during human split-belt treadmill…

Hold it! The influence of lingering rewards on choice diversification and persistence.

PubMed

Schulze, Christin; van Ravenzwaaij, Don; Newell, Ben R

2017-11-01

Learning to choose adaptively when faced with uncertain and variable outcomes is a central challenge for decision makers. This study examines repeated choice in dynamic probability learning tasks in which outcome probabilities changed either as a function of the choices participants made or independently of those choices. This presence/absence of sequential choice-outcome dependencies was implemented by manipulating a single task aspect between conditions: the retention/withdrawal of reward across individual choice trials. The study addresses how people adapt to these learning environments and to what extent they engage in 2 choice strategies often contrasted as paradigmatic examples of striking violation of versus nominal adherence to rational choice: diversification and persistent probability maximizing, respectively. Results show that decisions approached adaptive choice diversification and persistence when sufficient feedback was provided on the dynamic rules of the probabilistic environments. The findings of divergent behavior in the 2 environments indicate that diversified choices represented a response to the reward retention manipulation rather than to the mere variability of outcome probabilities. Choice in both environments was well accounted for by the generalized matching law, and computational modeling-based strategy analyses indicated that adaptive choice arose mainly from reliance on reinforcement learning strategies. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

An Examination of Students' Adaptation, Aggression, and Apprehension Traits with Their Instructional Feedback Orientations

ERIC Educational Resources Information Center

Malachowski, Colleen C.; Martin, Matthew M.; Vallade, Jessalyn I.

2013-01-01

Feedback orientations refer to students' perceptions of instructional feedback utility, retention, sensitivity, and confidentiality. In this paper, we report three studies that investigated the relationships among feedback orientations and communication traits. Specifically, we examined the associations among communication adaptation traits (Study…

Evaluating Adaptation of a Cancer Clinical Trial Decision Aid for Rural Cancer Patients: A Mixed-Methods Approach.

PubMed

Pathak, Swati; George, Nerissa; Monti, Denise; Robinson, Kathy; Politi, Mary C

2018-06-03

Rural-residing cancer patients often do not participate in clinical trials. Many patients misunderstand cancer clinical trials and their rights as participant. The purpose of this study is to modify a previously developed cancer clinical trials decision aid (DA), incorporating the unique needs of rural populations, and test its impact on knowledge and decision outcomes. The study was conducted in two phases. Phase I recruited 15 rural-residing cancer survivors in a qualitative usability study. Participants navigated the original DA and provided feedback regarding usability and implementation in rural settings. Phase II recruited 31 newly diagnosed rural-residing cancer patients. Patients completed a survey before and after using the revised DA, R-CHOICES. Primary outcomes included decisional conflict, decision self-efficacy, knowledge, communication self-efficacy, and attitudes towards and willingness to consider joining a trial. In phase I, the DA was viewed positively by rural-residing cancer survivors. Participants provided important feedback about factors rural-residing patients consider when thinking about trial participation. In phase II, after using R-CHOICES, participants had higher certainty about their choice (mean post-test = 3.10 vs. pre-test = 2.67; P = 0.025) and higher trial knowledge (mean percentage correct at post-test = 73.58 vs. pre-test = 57.77; P < 0.001). There was no significant change in decision self-efficacy, communication self-efficacy, and attitudes towards or willingness to join trials. The R-CHOICES improved rural-residing patients' knowledge of cancer clinical trials and reduced conflict about making a trial decision. More research is needed on ways to further support decisions about trial participation among this population.

Multiclassifier system with hybrid learning applied to the control of bioprosthetic hand.

PubMed

Kurzynski, Marek; Krysmann, Maciej; Trajdos, Pawel; Wolczowski, Andrzej

2016-02-01

In this paper the problem of recognition of the intended hand movements for the control of bio-prosthetic hand is addressed. The proposed method is based on recognition of electromiographic (EMG) and mechanomiographic (MMG) biosignals using a multiclassifier system (MCS) working in a two-level structure with a dynamic ensemble selection (DES) scheme and original concepts of competence function. Additionally, feedback information coming from bioprosthesis sensors on the correct/incorrect classification is applied to the adjustment of the combining mechanism during MCS operation through adaptive tuning competences of base classifiers depending on their decisions. Three MCS systems operating in decision tree structure and with different tuning algorithms are developed. In the MCS1 system, competence is uniformly allocated to each class belonging to the group indicated by the feedback signal. In the MCS2 system, the modification of competence depends on the node of decision tree at which a correct/incorrect classification is made. In the MCS3 system, the randomized model of classifier and the concept of cross-competence are used in the tuning procedure. Experimental investigations on the real data and computer-simulated procedure of generating feedback signals are performed. In these investigations classification accuracy of the MCS systems developed is compared and furthermore, the MCS systems are evaluated with respect to the effectiveness of the procedure of tuning competence. The results obtained indicate that modification of competence of base classifiers during the working phase essentially improves performance of the MCS system and that this improvement depends on the MCS system and tuning method used. Copyright © 2015 Elsevier Ltd. All rights reserved.

Free-space optics mode-wavelength division multiplexing system using LG modes based on decision feedback equalization

NASA Astrophysics Data System (ADS)

Amphawan, Angela; Ghazi, Alaan; Al-dawoodi, Aras

2017-11-01

A free-space optics mode-wavelength division multiplexing (MWDM) system using Laguerre-Gaussian (LG) modes is designed using decision feedback equalization for controlling mode coupling and combating inter symbol interference so as to increase channel diversity. In this paper, a data rate of 24 Gbps is achieved for a FSO MWDM channel of 2.6 km in length using feedback equalization. Simulation results show significant improvement in eye diagrams and bit-error rates before and after decision feedback equalization.

Adaptive reliance on the most stable sensory predictions enhances perceptual feature extraction of moving stimuli.

PubMed

Kumar, Neeraj; Mutha, Pratik K

2016-03-01

The prediction of the sensory outcomes of action is thought to be useful for distinguishing self- vs. externally generated sensations, correcting movements when sensory feedback is delayed, and learning predictive models for motor behavior. Here, we show that aspects of another fundamental function-perception-are enhanced when they entail the contribution of predicted sensory outcomes and that this enhancement relies on the adaptive use of the most stable predictions available. We combined a motor-learning paradigm that imposes new sensory predictions with a dynamic visual search task to first show that perceptual feature extraction of a moving stimulus is poorer when it is based on sensory feedback that is misaligned with those predictions. This was possible because our novel experimental design allowed us to override the "natural" sensory predictions present when any action is performed and separately examine the influence of these two sources on perceptual feature extraction. We then show that if the new predictions induced via motor learning are unreliable, rather than just relying on sensory information for perceptual judgments, as is conventionally thought, then subjects adaptively transition to using other stable sensory predictions to maintain greater accuracy in their perceptual judgments. Finally, we show that when sensory predictions are not modified at all, these judgments are sharper when subjects combine their natural predictions with sensory feedback. Collectively, our results highlight the crucial contribution of sensory predictions to perception and also suggest that the brain intelligently integrates the most stable predictions available with sensory information to maintain high fidelity in perceptual decisions. Copyright © 2016 the American Physiological Society.

Developmental and Gender Related Differences in Response Switches after Nonrepresentative Negative Feedback

ERIC Educational Resources Information Center

Jansen, Brenda R. J.; van Duijvenvoorde, Anna C. K.; Huizenga, Hilde M.

2014-01-01

In many decision making tasks negative feedback is probabilistic and, as a consequence, may be given when the decision is actually correct. This feedback can be referred to as nonrepresentative negative feedback. In the current study, we investigated developmental and gender related differences in such switching after nonrepresentative negative…

The absence or temporal offset of visual feedback does not influence adaptation to novel movement dynamics.

PubMed

McKenna, Erin; Bray, Laurence C Jayet; Zhou, Weiwei; Joiner, Wilsaan M

2017-10-01

Delays in transmitting and processing sensory information require correctly associating delayed feedback to issued motor commands for accurate error compensation. The flexibility of this alignment between motor signals and feedback has been demonstrated for movement recalibration to visual manipulations, but the alignment dependence for adapting movement dynamics is largely unknown. Here we examined the effect of visual feedback manipulations on force-field adaptation. Three subject groups used a manipulandum while experiencing a lag in the corresponding cursor motion (0, 75, or 150 ms). When the offset was applied at the start of the session (continuous condition), adaptation was not significantly different between groups. However, these similarities may be due to acclimation to the offset before motor adaptation. We tested additional subjects who experienced the same delays concurrent with the introduction of the perturbation (abrupt condition). In this case adaptation was statistically indistinguishable from the continuous condition, indicating that acclimation to feedback delay was not a factor. In addition, end-point errors were not significantly different across the delay or onset conditions, but end-point correction (e.g., deceleration duration) was influenced by the temporal offset. As an additional control, we tested a group of subjects who performed without visual feedback and found comparable movement adaptation results. These results suggest that visual feedback manipulation (absence or temporal misalignment) does not affect adaptation to novel dynamics, independent of both acclimation and perceptual awareness. These findings could have implications for modeling how the motor system adjusts to errors despite concurrent delays in sensory feedback information. NEW & NOTEWORTHY A temporal offset between movement and distorted visual feedback (e.g., visuomotor rotation) influences the subsequent motor recalibration, but the effects of this offset for altered movement dynamics are largely unknown. Here we examined the influence of 1 ) delayed and 2 ) removed visual feedback on the adaptation to novel movement dynamics. These results contribute to understanding of the control strategies that compensate for movement errors when there is a temporal separation between motion state and sensory information. Copyright © 2017 the American Physiological Society.

Social closeness and feedback modulate susceptibility to the framing effect.

PubMed

Sip, Kamila E; Smith, David V; Porcelli, Anthony J; Kar, Kohitij; Delgado, Mauricio R

2015-01-01

Although we often seek social feedback (SFB) from others to help us make decisions, little is known about how SFB affects decisions under risk, particularly from a close peer. We conducted two experiments using an established framing task to probe how decision-making is modulated by SFB valence (positive, negative) and the level of closeness with feedback provider (friend, confederate). Participants faced mathematically equivalent decisions framed as either an opportunity to keep (gain frame) or lose (loss frame) part of an initial endowment. Periodically, participants were provided with positive (e.g., "Nice!") or negative (e.g., "Lame!") feedback about their choices. Such feedback was provided by either a confederate (Experiment 1) or a gender-matched close friend (Experiment 2). As expected, the framing effect was observed in both experiments. Critically, an individual's susceptibility to the framing effect was modulated by the valence of the SFB, but only when the feedback provider was a close friend. This effect was reflected in the activation patterns of ventromedial prefrontal cortex and posterior cingulate cortex, regions involved in complex decision-making. Taken together, these results highlight social closeness as an important factor in understanding the impact of SFB on neural mechanisms of decision-making.

The Dynamics of Coalition Formation on Complex Networks

NASA Astrophysics Data System (ADS)

Auer, S.; Heitzig, J.; Kornek, U.; Schöll, E.; Kurths, J.

2015-08-01

Complex networks describe the structure of many socio-economic systems. However, in studies of decision-making processes the evolution of the underlying social relations are disregarded. In this report, we aim to understand the formation of self-organizing domains of cooperation (“coalitions”) on an acquaintance network. We include both the network’s influence on the formation of coalitions and vice versa how the network adapts to the current coalition structure, thus forming a social feedback loop. We increase complexity from simple opinion adaptation processes studied in earlier research to more complex decision-making determined by costs and benefits, and from bilateral to multilateral cooperation. We show how phase transitions emerge from such coevolutionary dynamics, which can be interpreted as processes of great transformations. If the network adaptation rate is high, the social dynamics prevent the formation of a grand coalition and therefore full cooperation. We find some empirical support for our main results: Our model develops a bimodal coalition size distribution over time similar to those found in social structures. Our detection and distinguishing of phase transitions may be exemplary for other models of socio-economic systems with low agent numbers and therefore strong finite-size effects.

Online participation in climate change adaptation: A case study of agricultural adaptation measures in Northern Italy.

PubMed

Bojovic, Dragana; Bonzanigo, Laura; Giupponi, Carlo; Maziotis, Alexandros

2015-07-01

The new EU strategy on adaptation to climate change suggests flexible and participatory approaches. Face-to-face contact, although it involves time-consuming procedures with a limited audience, has often been considered the most effective participatory approach. In recent years, however, there has been an increase in the visibility of different citizens' initiatives in the online world, which strengthens the possibility of greater citizen agency. This paper investigates whether the Internet can ensure efficient public participation with meaningful engagement in climate change adaptation. In elucidating issues regarding climate change adaptation, we developed an eParticipation framework to explore adaptation capacity of agriculture to climate change in Northern Italy. Farmers were mobilised using a pre-existing online network. First they took part in an online questionnaire for revealing their perceptions of and reactions to the impacts of ongoing changes in agriculture. We used these results to suggest a portfolio of policy measures and to set evaluation criteria. Farmers then evaluated these policy options, using a multi criteria analysis tool with a simple user-friendly interface. Our results showed that eParticipation is efficient: it supports a rapid data collection, while involving high number of participants. Moreover, we demonstrated that the digital divide is decreasingly an obstacle for using online spaces for public engagement. This research does not present eParticipation as a panacea. Rather, eParticipation was implemented with well-established participatory approaches to both validate the results and, consequently, communicate meaningful messages on local agricultural adaptation practices to regional decision-makers. Feedbacks from the regional decision-makers showed their interest in using eParticipation to improve communication with farmers in the future. We expect that, with further Internet proliferation, eParticipation may allow the inclusion of more representative samples, which would contribute to an informed and legitimate decision-making process. Copyright © 2015 Elsevier Ltd. All rights reserved.

Quaternion-based adaptive output feedback attitude control of spacecraft using Chebyshev neural networks.

PubMed

Zou, An-Min; Dev Kumar, Krishna; Hou, Zeng-Guang

2010-09-01

This paper investigates the problem of output feedback attitude control of an uncertain spacecraft. Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe the spacecraft attitude for global representation without singularities. The nonlinear reduced-order observer is used to estimate the derivative of the spacecraft output, and the CNN is introduced to further improve the control performance through approximating the spacecraft attitude motion. The implementation of the basis functions of the CNN used in the proposed controllers depends only on the desired signals, and the smooth robust compensator using the hyperbolic tangent function is employed to counteract the CNN approximation errors and external disturbances. The adaptive NN controller-II can efficiently avoid the over-estimation problem (i.e., the bound of the CNNs output is much larger than that of the approximated unknown function, and hence, the control input may be very large) existing in the adaptive NN controller-I. Both adaptive output feedback controllers using CNN can guarantee that all signals in the resulting closed-loop system are uniformly ultimately bounded. For performance comparisons, the standard adaptive controller using the linear parameterization of spacecraft attitude motion is also developed. Simulation studies are presented to show the advantages of the proposed CNN-based output feedback approach over the standard adaptive output feedback approach.

Learning in an interactive simulation tool against landslide risks: the role of strength and availability of experiential feedback

NASA Astrophysics Data System (ADS)

Chaturvedi, Pratik; Arora, Akshit; Dutt, Varun

2018-06-01

Feedback via simulation tools is likely to help people improve their decision-making against natural disasters. However, little is known on how differing strengths of experiential feedback and feedback's availability in simulation tools influence people's decisions against landslides. We tested the influence of differing strengths of experiential feedback and feedback's availability on people's decisions against landslides in Mandi, Himachal Pradesh, India. Experiential feedback (high or low) and feedback's availability (present or absent) were varied across four between-subject conditions in a tool called the Interactive Landslide Simulation (ILS): high damage with feedback present, high damage with feedback absent, low damage with feedback present, and low damage with feedback absent. In high-damage conditions, the probabilities of damages to life and property due to landslides were 10 times higher than those in the low-damage conditions. In feedback-present conditions, experiential feedback was provided in numeric, text, and graphical formats in ILS. In feedback-absent conditions, the probabilities of damages were described; however, there was no experiential feedback present. Investments were greater in conditions where experiential feedback was present and damages were high compared to conditions where experiential feedback was absent and damages were low. Furthermore, only high-damage feedback produced learning in ILS. Simulation tools like ILS seem appropriate for landslide risk communication and for performing what-if analyses.

Studying citizen science through adaptive management and learning feedbacks as mechanisms for improving conservation.

PubMed

Jordan, Rebecca; Gray, Steven; Sorensen, Amanda; Newman, Greg; Mellor, David; Newman, Greg; Hmelo-Silver, Cindy; LaDeau, Shannon; Biehler, Dawn; Crall, Alycia

2016-06-01

Citizen science has generated a growing interest among scientists and community groups, and citizen science programs have been created specifically for conservation. We examined collaborative science, a highly interactive form of citizen science, which we developed within a theoretically informed framework. In this essay, we focused on 2 aspects of our framework: social learning and adaptive management. Social learning, in contrast to individual-based learning, stresses collaborative and generative insight making and is well-suited for adaptive management. Adaptive-management integrates feedback loops that are informed by what is learned and is guided by iterative decision making. Participants engaged in citizen science are able to add to what they are learning through primary data collection, which can result in the real-time information that is often necessary for conservation. Our work is particularly timely because research publications consistently report a lack of established frameworks and evaluation plans to address the extent of conservation outcomes in citizen science. To illustrate how our framework supports conservation through citizen science, we examined how 2 programs enacted our collaborative science framework. Further, we inspected preliminary conservation outcomes of our case-study programs. These programs, despite their recent implementation, are demonstrating promise with regard to positive conservation outcomes. To date, they are independently earning funds to support research, earning buy-in from local partners to engage in experimentation, and, in the absence of leading scientists, are collecting data to test ideas. We argue that this success is due to citizen scientists being organized around local issues and engaging in iterative, collaborative, and adaptive learning. © 2016 Society for Conservation Biology.

Modeling the Adaptive Role of Negative Signaling in Honey Bee Intraspecific Competition.

PubMed

Johnson, Brian R; Nieh, James C

2010-11-01

Collective decision making in the social insects often proceeds via feedback cycles based on positive signaling. Negative signals have, however, been found in a few contexts in which costs exist for paying attention to no longer useful information. Here we incorporate new research on the specificity and context of the negative stop signal into an agent based model of honey bee foraging to explore the adaptive basis of negative signaling in the dance language. Our work suggests that the stop signal, by acting as a counterbalance to the waggle dance, allows colonies to rapidly shut down attacks on other colonies. This could be a key adaptation, as the costs of attacking a colony strong enough to defend itself are significant. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10905-010-9229-5) contains supplementary material, which is available to authorized users.

Adaptive management of urban watersheds

NASA Astrophysics Data System (ADS)

Garmestani, A.; Shuster, W.; Green, O. O.

2013-12-01

Consent decree settlements for violations of the Clean Water Act (1972) increasingly include provisions for redress of combined sewer overflow activity through hybrid approaches that incorporate the best of both gray (e.g., storage tunnels) and green infrastructure (e.g., rain gardens). Adaptive management is an environmental management strategy that uses an iterative process of decision-making to improve environmental management via system monitoring. A central tenet of adaptive management is that management involves a learning process that can help regulated communities achieve environmental quality objectives. We are using an adaptive management approach to guide a green infrastructure retrofit of a neighborhood in the Slavic Village Development Corporation area (Cleveland, Ohio). We are in the process of gathering hydrologic and ecosystem services data and will use this data as a basis for collaboration with area citizens on a plan to use green infrastructure to contain stormflows. Monitoring data provides researchers with feedback on the impact of green infrastructure implementation and suggest where improvements can be made.

Building Adaptive Capacity with the Delphi Method and Mediated Modeling for Water Quality and Climate Change Adaptation in Lake Champlain Basin

NASA Astrophysics Data System (ADS)

Coleman, S.; Hurley, S.; Koliba, C.; Zia, A.; Exler, S.

2014-12-01

Eutrophication and nutrient pollution of surface waters occur within complex governance, social, hydrologic and biophysical basin contexts. The pervasive and perennial nutrient pollution in Lake Champlain Basin, despite decades of efforts, exemplifies problems found across the world's surface waters. Stakeholders with diverse values, interests, and forms of explicit and tacit knowledge determine water quality impacts through land use, agricultural and water resource decisions. Uncertainty, ambiguity and dynamic feedback further complicate the ability to promote the continual provision of water quality and ecosystem services. Adaptive management of water resources and land use requires mechanisms to allow for learning and integration of new information over time. The transdisciplinary Research on Adaptation to Climate Change (RACC) team is working to build regional adaptive capacity in Lake Champlain Basin while studying and integrating governance, land use, hydrological, and biophysical systems to evaluate implications for adaptive management. The RACC team has engaged stakeholders through mediated modeling workshops, online forums, surveys, focus groups and interviews. In March 2014, CSS2CC.org, an interactive online forum to source and identify adaptive interventions from a group of stakeholders across sectors was launched. The forum, based on the Delphi Method, brings forward the collective wisdom of stakeholders and experts to identify potential interventions and governance designs in response to scientific uncertainty and ambiguity surrounding the effectiveness of any strategy, climate change impacts, and the social and natural systems governing water quality and eutrophication. A Mediated Modeling Workshop followed the forum in May 2014, where participants refined and identified plausible interventions under different governance, policy and resource scenarios. Results from the online forum and workshop can identify emerging consensus across scales and sectors and be simulated in adaptation scenarios within integrated models. Comparing interventions and scenarios to existing and planned policy and governance systems in Lake Champlain Basin allows for new feedback to build adaptive capacity to identify key leverage points in the coupled natural and human system.

Robust high-performance control for robotic manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1989-01-01

A robust control scheme to accomplish accurate trajectory tracking for an integrated system of manipulator-plus-actuators is proposed. The control scheme comprises a feedforward and a feedback controller. The feedforward controller contains any known part of the manipulator dynamics that can be used for online control. The feedback controller consists of adaptive position and velocity feedback gains and an auxiliary signal which is simply generated by a fixed-gain proportional/integral/derivative controller. The feedback controller is updated by very simple adaptation laws which contain both proportional and integral adaptation terms. By introduction of a simple sigma modification to the adaptation laws, robustness is guaranteed in the presence of unmodeled dynamics and disturbances.

Adaptive Fuzzy Control for Nonstrict Feedback Systems With Unmodeled Dynamics and Fuzzy Dead Zone via Output Feedback.

PubMed

Wang, Lijie; Li, Hongyi; Zhou, Qi; Lu, Renquan

2017-09-01

This paper investigates the problem of observer-based adaptive fuzzy control for a category of nonstrict feedback systems subject to both unmodeled dynamics and fuzzy dead zone. Through constructing a fuzzy state observer and introducing a center of gravity method, unmeasurable states are estimated and the fuzzy dead zone is defuzzified, respectively. By employing fuzzy logic systems to identify the unknown functions. And combining small-gain approach with adaptive backstepping control technique, a novel adaptive fuzzy output feedback control strategy is developed, which ensures that all signals involved are semi-globally uniformly bounded. Simulation results are given to demonstrate the effectiveness of the presented method.

Structural learning in feedforward and feedback control.

PubMed

Yousif, Nada; Diedrichsen, Jörn

2012-11-01

For smooth and efficient motor control, the brain needs to make fast corrections during the movement to resist possible perturbations. It also needs to adapt subsequent movements to improve future performance. It is important that both feedback corrections and feedforward adaptation need to be made based on noisy and often ambiguous sensory data. Therefore, the initial response of the motor system, both for online corrections and adaptive responses, is guided by prior assumptions about the likely structure of perturbations. In the context of correcting and adapting movements perturbed by a force field, we asked whether these priors are hard wired or whether they can be modified through repeated exposure to differently shaped force fields. We found that both feedback corrections to unexpected perturbations and feedforward adaptation to a new force field changed, such that they were appropriate to counteract the type of force field that participants had experienced previously. We then investigated whether these changes were driven by a common mechanism or by two separate mechanisms. Participants experienced force fields that were either temporally consistent, causing sustained adaptation, or temporally inconsistent, causing little overall adaptation. We found that the consistent force fields modified both feedback and feedforward responses. In contrast, the inconsistent force field modified the temporal shape of feedback corrections but not of the feedforward adaptive response. These results indicate that responses to force perturbations can be modified in a structural manner and that these modifications are at least partly dissociable for feedback and feedforward control.

Structural learning in feedforward and feedback control

PubMed Central

Diedrichsen, Jörn

2012-01-01

For smooth and efficient motor control, the brain needs to make fast corrections during the movement to resist possible perturbations. It also needs to adapt subsequent movements to improve future performance. It is important that both feedback corrections and feedforward adaptation need to be made based on noisy and often ambiguous sensory data. Therefore, the initial response of the motor system, both for online corrections and adaptive responses, is guided by prior assumptions about the likely structure of perturbations. In the context of correcting and adapting movements perturbed by a force field, we asked whether these priors are hard wired or whether they can be modified through repeated exposure to differently shaped force fields. We found that both feedback corrections to unexpected perturbations and feedforward adaptation to a new force field changed, such that they were appropriate to counteract the type of force field that participants had experienced previously. We then investigated whether these changes were driven by a common mechanism or by two separate mechanisms. Participants experienced force fields that were either temporally consistent, causing sustained adaptation, or temporally inconsistent, causing little overall adaptation. We found that the consistent force fields modified both feedback and feedforward responses. In contrast, the inconsistent force field modified the temporal shape of feedback corrections but not of the feedforward adaptive response. These results indicate that responses to force perturbations can be modified in a structural manner and that these modifications are at least partly dissociable for feedback and feedforward control. PMID:22896725

Integrating modeling, monitoring, and management to reduce critical uncertainties in water resource decision making.

PubMed

Peterson, James T; Freeman, Mary C

2016-12-01

Stream ecosystems provide multiple, valued services to society, including water supply, waste assimilation, recreation, and habitat for diverse and productive biological communities. Managers striving to sustain these services in the face of changing climate, land uses, and water demands need tools to assess the potential effectiveness of alternative management actions, and often, the resulting tradeoffs between competing objectives. Integrating predictive modeling with monitoring data in an adaptive management framework provides a process by which managers can reduce model uncertainties and thus improve the scientific bases for subsequent decisions. We demonstrate an integration of monitoring data with a dynamic, metapopulation model developed to assess effects of streamflow alteration on fish occupancy in a southeastern US stream system. Although not extensive (collected over three years at nine sites), the monitoring data allowed us to assess and update support for alternative population dynamic models using model probabilities and Bayes rule. We then use the updated model weights to estimate the effects of water withdrawal on stream fish communities and demonstrate how feedback in the form of monitoring data can be used to improve water resource decision making. We conclude that investment in more strategic monitoring, guided by a priori model predictions under alternative hypotheses and an adaptive sampling design, could substantially improve the information available to guide decision-making and management for ecosystem services from lotic systems. Published by Elsevier Ltd.

Coastal livelihood transitions under globalization with implications for trans-ecosystem interactions.

PubMed

Kramer, Daniel B; Stevens, Kara; Williams, Nicholas E; Sistla, Seeta A; Roddy, Adam B; Urquhart, Gerald R

2017-01-01

Anthropogenic threats to natural systems can be exacerbated due to connectivity between marine, freshwater, and terrestrial ecosystems, complicating the already daunting task of governance across the land-sea interface. Globalization, including new access to markets, can change social-ecological, land-sea linkages via livelihood responses and adaptations by local people. As a first step in understanding these trans-ecosystem effects, we examined exit and entry decisions of artisanal fishers and smallholder farmers on the rapidly globalizing Caribbean coast of Nicaragua. We found that exit and entry decisions demonstrated clear temporal and spatial patterns and that these decisions differed by livelihood. In addition to household characteristics, livelihood exit and entry decisions were strongly affected by new access to regional and global markets. The natural resource implications of these livelihood decisions are potentially profound as they provide novel linkages and spatially-explicit feedbacks between terrestrial and marine ecosystems. Our findings support the need for more scientific inquiry in understanding trans-ecosystem tradeoffs due to linked-livelihood transitions as well as the need for a trans-ecosystem approach to natural resource management and development policy in rapidly changing coastal regions.

Properties of an adaptive feedback equalization algorithm.

PubMed

Engebretson, A M; French-St George, M

1993-01-01

This paper describes a new approach to feedback equalization for hearing aids. The method involves the use of an adaptive algorithm that estimates and tracks the characteristic of the hearing aid feedback path. The algorithm is described and the results of simulation studies and bench testing are presented.

Cal-Adapt: California's Climate Data Resource and Interactive Toolkit

NASA Astrophysics Data System (ADS)

Thomas, N.; Mukhtyar, S.; Wilhelm, S.; Galey, B.; Lehmer, E.

2016-12-01

Cal-Adapt is a web-based application that provides an interactive toolkit and information clearinghouse to help agencies, communities, local planners, resource managers, and the public understand climate change risks and impacts at the local level. The website offers interactive, visually compelling, and useful data visualization tools that show how climate change might affect California using downscaled continental climate data. Cal-Adapt is supporting California's Fourth Climate Change Assessment through providing access to the wealth of modeled and observed data and adaption-related information produced by California's scientific community. The site has been developed by UC Berkeley's Geospatial Innovation Facility (GIF) in collaboration with the California Energy Commission's (CEC) Research Program. The Cal-Adapt website allows decision makers, scientists and residents of California to turn research results and climate projections into effective adaptation decisions and policies. Since its release to the public in June 2011, Cal-Adapt has been visited by more than 94,000 unique visitors from over 180 countries, all 50 U.S. states, and 689 California localities. We will present several key visualizations that have been employed by Cal-Adapt's users to support their efforts to understand local impacts of climate change, indicate the breadth of data available, and delineate specific use cases. Recently, CEC and GIF have been developing and releasing Cal-Adapt 2.0, which includes updates and enhancements that are increasing its ease of use, information value, visualization tools, and data accessibility. We showcase how Cal-Adapt is evolving in response to feedback from a variety of sources to present finer-resolution downscaled data, and offer an open API that allows other organization to access Cal-Adapt climate data and build domain specific visualization and planning tools. Through a combination of locally relevant information, visualization tools, and access to primary data, Cal-Adapt allows users to investigate how the climate is projected to change in their areas of interest.

Rapid feedback responses correlate with reach adaptation and properties of novel upper limb loads.

PubMed

Cluff, Tyler; Scott, Stephen H

2013-10-02

A hallmark of voluntary motor control is the ability to adjust motor patterns for novel mechanical or visuomotor contexts. Recent work has also highlighted the importance of feedback for voluntary control, leading to the hypothesis that feedback responses should adapt when we learn new motor skills. We tested this prediction with a novel paradigm requiring that human subjects adapt to a viscous elbow load while reaching to three targets. Target 1 required combined shoulder and elbow motion, target 2 required only elbow motion, and target 3 (probe target) required shoulder but no elbow motion. This simple approach controlled muscle activity at the probe target before, during, and after the application of novel elbow loads. Our paradigm allowed us to perturb the elbow during reaching movements to the probe target and identify several key properties of adapted stretch responses. Adapted long-latency responses expressed (de-) adaptation similar to reaching errors observed when we introduced (removed) the elbow load. Moreover, reaching errors during learning correlated with changes in the long-latency response, showing subjects who adapted more to the elbow load displayed greater modulation of their stretch responses. These adapted responses were sensitive to the size and direction of the viscous training load. Our results highlight an important link between the adaptation of feedforward and feedback control and suggest a key part of motor adaptation is to adjust feedback responses to the requirements of novel motor skills.

Cortical potentials evoked by confirming and disconfirming feedback following an auditory discrimination.

NASA Technical Reports Server (NTRS)

Squires, K. C.; Hillyard, S. A.; Lindsay, P. H.

1973-01-01

Vertex potentials elicited by visual feedback signals following an auditory intensity discrimination have been studied with eight subjects. Feedback signals which confirmed the prior sensory decision elicited small P3s, while disconfirming feedback elicited P3s that were larger. On the average, the latency of P3 was also found to increase with increasing disparity between the judgment and the feedback information. These effects were part of an overall dichotomy in wave shape following confirming vs disconfirming feedback. These findings are incorporated in a general model of the role of P3 in perceptual decision making.

Combination of Adaptive Feedback Cancellation and Binaural Adaptive Filtering in Hearing Aids

NASA Astrophysics Data System (ADS)

Lombard, Anthony; Reindl, Klaus; Kellermann, Walter

2009-12-01

We study a system combining adaptive feedback cancellation and adaptive filtering connecting inputs from both ears for signal enhancement in hearing aids. For the first time, such a binaural system is analyzed in terms of system stability, convergence of the algorithms, and possible interaction effects. As major outcomes of this study, a new stability condition adapted to the considered binaural scenario is presented, some already existing and commonly used feedback cancellation performance measures for the unilateral case are adapted to the binaural case, and possible interaction effects between the algorithms are identified. For illustration purposes, a blind source separation algorithm has been chosen as an example for adaptive binaural spatial filtering. Experimental results for binaural hearing aids confirm the theoretical findings and the validity of the new measures.

Performance Feedback Utility in a Small Organization: Effects on Organizational Outcomes and Managerial Decision Processes.

ERIC Educational Resources Information Center

Florin-Thuma, Beth C.; Boudreau, John W.

1987-01-01

Investigated the frequent but previously untested assertion that utility analysis can improve communication and decision making about human resource management programs by examining a performance feedback intervention in a small fast-food store. Results suggest substantial payoffs from performance feedback, though the store's owner-managers had…

Higher incentives can impair performance: neural evidence on reinforcement and rationality

PubMed Central

Achtziger, Anja; Hügelschäfer, Sabine; Steinhauser, Marco

2015-01-01

Standard economic thinking postulates that increased monetary incentives should increase performance. Human decision makers, however, frequently focus on past performance, a form of reinforcement learning occasionally at odds with rational decision making. We used an incentivized belief-updating task from economics to investigate this conflict through measurements of neural correlates of reward processing. We found that higher incentives fail to improve performance when immediate feedback on decision outcomes is provided. Subsequent analysis of the feedback-related negativity, an early event-related potential following feedback, revealed the mechanism behind this paradoxical effect. As incentives increase, the win/lose feedback becomes more prominent, leading to an increased reliance on reinforcement and more errors. This mechanism is relevant for economic decision making and the debate on performance-based payment. PMID:25816816

Improving Passive Time Reversal Underwater Acoustic Communications Using Subarray Processing.

PubMed

He, Chengbing; Jing, Lianyou; Xi, Rui; Li, Qinyuan; Zhang, Qunfei

2017-04-24

Multichannel receivers are usually employed in high-rate underwater acoustic communication to achieve spatial diversity. In the context of multichannel underwater acoustic communications, passive time reversal (TR) combined with a single-channel adaptive decision feedback equalizer (TR-DFE) is a low-complexity solution to achieve both spatial and temporal focusing. In this paper, we present a novel receiver structure to combine passive time reversal with a low-order multichannel adaptive decision feedback equalizer (TR-MC-DFE) to improve the performance of the conventional TR-DFE. First, the proposed method divides the whole received array into several subarrays. Second, we conduct passive time reversal processing in each subarray. Third, the multiple subarray outputs are equalized with a low-order multichannel DFE. We also investigated different channel estimation methods, including least squares (LS), orthogonal matching pursuit (OMP), and improved proportionate normalized least mean squares (IPNLMS). The bit error rate (BER) and output signal-to-noise ratio (SNR) performances of the receiver algorithms are evaluated using simulation and real data collected in a lake experiment. The source-receiver range is 7.4 km, and the data rate with quadrature phase shift keying (QPSK) signal is 8 kbits/s. The uncoded BER of the single input multiple output (SIMO) systems varies between 1 × 10 - 1 and 2 × 10 - 2 for the conventional TR-DFE, and between 1 × 10 - 2 and 1 × 10 - 3 for the proposed TR-MC-DFE when eight hydrophones are utilized. Compared to conventional TR-DFE, the average output SNR of the experimental data is enhanced by 3 dB.

Improving Passive Time Reversal Underwater Acoustic Communications Using Subarray Processing

PubMed Central

He, Chengbing; Jing, Lianyou; Xi, Rui; Li, Qinyuan; Zhang, Qunfei

2017-01-01

Multichannel receivers are usually employed in high-rate underwater acoustic communication to achieve spatial diversity. In the context of multichannel underwater acoustic communications, passive time reversal (TR) combined with a single-channel adaptive decision feedback equalizer (TR-DFE) is a low-complexity solution to achieve both spatial and temporal focusing. In this paper, we present a novel receiver structure to combine passive time reversal with a low-order multichannel adaptive decision feedback equalizer (TR-MC-DFE) to improve the performance of the conventional TR-DFE. First, the proposed method divides the whole received array into several subarrays. Second, we conduct passive time reversal processing in each subarray. Third, the multiple subarray outputs are equalized with a low-order multichannel DFE. We also investigated different channel estimation methods, including least squares (LS), orthogonal matching pursuit (OMP), and improved proportionate normalized least mean squares (IPNLMS). The bit error rate (BER) and output signal-to-noise ratio (SNR) performances of the receiver algorithms are evaluated using simulation and real data collected in a lake experiment. The source-receiver range is 7.4 km, and the data rate with quadrature phase shift keying (QPSK) signal is 8 kbits/s. The uncoded BER of the single input multiple output (SIMO) systems varies between 1×10−1 and 2×10−2 for the conventional TR-DFE, and between 1×10−2 and 1×10−3 for the proposed TR-MC-DFE when eight hydrophones are utilized. Compared to conventional TR-DFE, the average output SNR of the experimental data is enhanced by 3 dB. PMID:28441763

The Effects of Sensor Performance as Modeled by Signal Detection Theory on the Performance of Reinforcement Learning in a Target Acquisition Task

NASA Astrophysics Data System (ADS)

Quirion, Nate

Unmanned Aerial Systems (UASs) today are fulfilling more roles than ever before. There is a general push to have these systems feature more advanced autonomous capabilities in the near future. To achieve autonomous behavior requires some unique approaches to control and decision making. More advanced versions of these approaches are able to adapt their own behavior and examine their past experiences to increase their future mission performance. To achieve adaptive behavior and decision making capabilities this study used Reinforcement Learning algorithms. In this research the effects of sensor performance, as modeled through Signal Detection Theory (SDT), on the ability of RL algorithms to accomplish a target localization task are examined. Three levels of sensor sensitivity are simulated and compared to the results of the same system using a perfect sensor. To accomplish the target localization task, a hierarchical architecture used two distinct agents. A simulated human operator is assumed to be a perfect decision maker, and is used in the system feedback. An evaluation of the system is performed using multiple metrics, including episodic reward curves and the time taken to locate all targets. Statistical analyses are employed to detect significant differences in the comparison of steady-state behavior of different systems.

Auditory-motor adaptation to frequency-altered auditory feedback occurs when participants ignore feedback.

PubMed

Keough, Dwayne; Hawco, Colin; Jones, Jeffery A

2013-03-09

Auditory feedback is important for accurate control of voice fundamental frequency (F(0)). The purpose of this study was to address whether task instructions could influence the compensatory responding and sensorimotor adaptation that has been previously found when participants are presented with a series of frequency-altered feedback (FAF) trials. Trained singers and musically untrained participants (nonsingers) were informed that their auditory feedback would be manipulated in pitch while they sang the target vowel [/α /]. Participants were instructed to either 'compensate' for, or 'ignore' the changes in auditory feedback. Whole utterance auditory feedback manipulations were either gradually presented ('ramp') in -2 cent increments down to -100 cents (1 semitone) or were suddenly ('constant') shifted down by 1 semitone. Results indicated that singers and nonsingers could not suppress their compensatory responses to FAF, nor could they reduce the sensorimotor adaptation observed during both the ramp and constant FAF trials. Compared to previous research, these data suggest that musical training is effective in suppressing compensatory responses only when FAF occurs after vocal onset (500-2500 ms). Moreover, our data suggest that compensation and adaptation are automatic and are influenced little by conscious control.

Auditory-motor adaptation to frequency-altered auditory feedback occurs when participants ignore feedback

PubMed Central

2013-01-01

Background Auditory feedback is important for accurate control of voice fundamental frequency (F0). The purpose of this study was to address whether task instructions could influence the compensatory responding and sensorimotor adaptation that has been previously found when participants are presented with a series of frequency-altered feedback (FAF) trials. Trained singers and musically untrained participants (nonsingers) were informed that their auditory feedback would be manipulated in pitch while they sang the target vowel [/ɑ /]. Participants were instructed to either ‘compensate’ for, or ‘ignore’ the changes in auditory feedback. Whole utterance auditory feedback manipulations were either gradually presented (‘ramp’) in -2 cent increments down to -100 cents (1 semitone) or were suddenly (’constant‘) shifted down by 1 semitone. Results Results indicated that singers and nonsingers could not suppress their compensatory responses to FAF, nor could they reduce the sensorimotor adaptation observed during both the ramp and constant FAF trials. Conclusions Compared to previous research, these data suggest that musical training is effective in suppressing compensatory responses only when FAF occurs after vocal onset (500-2500 ms). Moreover, our data suggest that compensation and adaptation are automatic and are influenced little by conscious control. PMID:23497238

Planning an adaptive management process for biodiversity conservation and resource development in the Camisea River Basin.

PubMed

Dallmeier, Francisco; Alonso, Alfonso; Jones, Murray

2002-05-01

The Smithsonian Institution's Monitoring and Assessment of Biodiversity Program joined Shell Prospecting and Development Peru (SPDP) to protect biodiversity during a natural gas exploration project. Emphasis was on long-term societal and environmental benefits in addition to financial gain for the company. The systematic, cyclical adaptive management process was used to generate feedback for SPDP managers. Adaptive management enables ongoing improvement of management policies and practices based on lessons learned from operational activities. Previous to this study, very little information about the local biodiversity was available. Over a 2-year period, the team conducted biological assessments of six taxonomic groups at five sites located within 600 km2. A broad range of management options such as location, timing and technology were developed from the beginning of the project. They were considered in conjunction with emerging lessons from the biodiversity assessments. Critical decisions included location of a gas plant and the cost of helicopter access versus roads to service the full field development. Both of these decisions were evaluated to ensure that they were economically and environmentally feasible. Project design changes, addressed in the planning stage, were accepted once consensus was achieved. Stakeholders were apprised of the implications of the baseline biodiversity assessments.

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

ERIC Educational Resources Information Center

Reb, Jochen; Connolly, Terry

2009-01-01

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

Decision support for patient care: implementing cybernetics.

PubMed

Ozbolt, Judy; Ozdas, Asli; Waitman, Lemuel R; Smith, Janis B; Brennan, Grace V; Miller, Randolph A

2004-01-01

The application of principles and methods of cybernetics permits clinicians and managers to use feedback about care effectiveness and resource expenditure to improve quality and to control costs. Keys to the process are the specification of therapeutic goals and the creation of an organizational culture that supports the use of feedback to improve care. Daily feedback on the achievement of each patient's therapeutic goals provides tactical decision support, enabling clinicians to adjust care as needed. Monthly or quarterly feedback on aggregated goal achievement for all patients on a clinical pathway provides strategic decision support, enabling clinicians and managers to identify problems with supposed "best practices" and to test hypotheses about solutions. Work is underway at Vanderbilt University Medical Center to implement feedback loops in care and management processes and to evaluate the effects.

What Drives Farmers to Make Top-Down or Bottom-Up Adaptation to Climate Change and Fluctuations? A Comparative Study on 3 Cases of Apple Farming in Japan and South Africa

PubMed Central

Fujisawa, Mariko; Kobayashi, Kazuhiko; Johnston, Peter; New, Mark

2015-01-01

Agriculture is one of the most vulnerable sectors to climate change. Farmers have been exposed to multiple stressors including climate change, and they have managed to adapt to those risks. The adaptation actions undertaken by farmers and their decision making are, however, only poorly understood. By studying adaptation practices undertaken by apple farmers in three regions: Nagano and Kazuno in Japan and Elgin in South Africa, we categorize the adaptation actions into two types: farmer initiated bottom-up adaptation and institution led top-down adaptation. We found that the driver which differentiates the type of adaptation likely adopted was strongly related to the farmers’ characteristics, particularly their dependence on the institutions, e.g. the farmers’ cooperative, in selling their products. The farmers who rely on the farmers’ cooperative for their sales are likely to adopt the institution-led adaptation, whereas the farmers who have established their own sales channels tend to start innovative actions by bottom-up. We further argue that even though the two types have contrasting features, the combinations of the both types of adaptations could lead to more successful adaptation particularly in agriculture. This study also emphasizes that more farm-level studies for various crops and regions are warranted to provide substantial feedbacks to adaptation policy. PMID:25822534

Electrophysiological brain indices of risk behavior modification induced by contingent feedback.

PubMed

Megías, Alberto; Torres, Miguel Angel; Catena, Andrés; Cándido, Antonio; Maldonado, Antonio

2018-02-01

The main aim of this research was to study the effects of response feedback on risk behavior and the neural and cognitive mechanisms involved, as a function of the feedback contingency. Sixty drivers were randomly assigned to one of three feedback groups: contingent, non-contingent and no feedback. The participants' task consisted of braking or not when confronted with a set of risky driving situations, while their electroencephalographic activity was continuously recorded. We observed that contingent feedback, as opposed to non-contingent feedback, promoted changes in the response bias towards safer decisions. This behavioral modification implied a higher demand on cognitive control, reflected in a larger amplitude of the N400 component. Moreover, the contingent feedback, being predictable and entailing more informative value, gave rise to smaller SPN and larger FRN scores when compared with non-contingent feedback. Taken together, these findings provide a new and complex insight into the neurophysiological basis of the influence of feedback contingency on the processing of decision-making under risk. We suggest that response feedback, when contingent upon the risky behavior, appears to improve the functionality of the brain mechanisms involved in decision-making and can be a powerful tool for reducing the tendency to choose risky options in risk-prone individuals. Copyright © 2018 Elsevier B.V. All rights reserved.

Perception of traffic accident risk and decision to drive under light alcohol consumption--a double-blind experimental study.

PubMed

Frick, U; Rehm, J; Knoll, A; Reifinger, M; Hasford, J

2000-01-01

Public traffic safety campaigns in Germany have focussed on the changing risk perception of young drivers. While there is some consensus that perceptions of risk affect driving, less is understood about the relationship and interaction of alcohol consumption and risk perception on the decision to drive. We examined the influence of light alcohol consumption on risk perception and decision to drive, and the interaction of alcohol consumption and cognitive feedback on the handicapping effect of alcohol on risk perception and decision to drive. In a double-blind block-randomized experimental study of 104 young drivers between 19 and 24 years of age, with two experimentally manipulated independent factors of alcohol consumption (three levels: 0% BAC, 0.015% BAC, 0.03% BAC) and feedback (positive or negative), we assessed three dependent variables: perception of traffic accident risk, subjective judgement about driving-relevant cognitive performance, decision to drive a car. Analyses of variance and covariance were used to analyze differences between levels of experimental factors. We found that persons with 0.015 BAC performed better than persons in both other alcohol conditions on the standardized risk perception task. Perceived handicap of driving was significantly more pronounced for negative feedback compared to positive feedback with no influence of the level of alcohol consumption. No significant influence on decision to drive was found of either level of alcohol consumption, feedback or sex. Decision to drive in young drivers could not be influenced by feedback or light consumption. Public health approaches have to find better determining factors.

The Feedback-related Negativity Codes Components of Abstract Inference during Reward-based Decision-making.

PubMed

Reiter, Andrea M F; Koch, Stefan P; Schröger, Erich; Hinrichs, Hermann; Heinze, Hans-Jochen; Deserno, Lorenz; Schlagenhauf, Florian

2016-08-01

Behavioral control is influenced not only by learning from the choices made and the rewards obtained but also by "what might have happened," that is, inference about unchosen options and their fictive outcomes. Substantial progress has been made in understanding the neural signatures of direct learning from choices that are actually made and their associated rewards via reward prediction errors (RPEs). However, electrophysiological correlates of abstract inference in decision-making are less clear. One seminal theory suggests that the so-called feedback-related negativity (FRN), an ERP peaking 200-300 msec after a feedback stimulus at frontocentral sites of the scalp, codes RPEs. Hitherto, the FRN has been predominantly related to a so-called "model-free" RPE: The difference between the observed outcome and what had been expected. Here, by means of computational modeling of choice behavior, we show that individuals employ abstract, "double-update" inference on the task structure by concurrently tracking values of chosen stimuli (associated with observed outcomes) and unchosen stimuli (linked to fictive outcomes). In a parametric analysis, model-free RPEs as well as their modification because of abstract inference were regressed against single-trial FRN amplitudes. We demonstrate that components related to abstract inference uniquely explain variance in the FRN beyond model-free RPEs. These findings advance our understanding of the FRN and its role in behavioral adaptation. This might further the investigation of disturbed abstract inference, as proposed, for example, for psychiatric disorders, and its underlying neural correlates.

Sex-ratio control erodes sexual selection, revealing evolutionary feedback from adaptive plasticity.

PubMed

Fawcett, Tim W; Kuijper, Bram; Weissing, Franz J; Pen, Ido

2011-09-20

Female choice is a powerful selective force, driving the elaboration of conspicuous male ornaments. This process of sexual selection has profound implications for many life-history decisions, including sex allocation. For example, females with attractive partners should produce more sons, because these sons will inherit their father's attractiveness and enjoy high mating success, thereby yielding greater fitness returns than daughters. However, previous research has overlooked the fact that there is a reciprocal feedback from life-history strategies to sexual selection. Here, using a simple mathematical model, we show that if mothers adaptively control offspring sex in relation to their partner's attractiveness, sexual selection is weakened and male ornamentation declines. This weakening occurs because the ability to determine offspring sex reduces the fitness difference between females with attractive and unattractive partners. We use individual-based, evolutionary simulations to show that this result holds under more biologically realistic conditions. Sexual selection and sex allocation thus interact in a dynamic fashion: The evolution of conspicuous male ornaments favors sex-ratio adjustment, but this conditional strategy then undermines the very same process that generated it, eroding sexual selection. We predict that, all else being equal, the most elaborate sexual displays should be seen in species with little or no control over offspring sex. The feedback process we have described points to a more general evolutionary principle, in which a conditional strategy weakens directional selection on another trait by reducing fitness differences.

Integrating an agent-based model into a large-scale hydrological model for evaluating drought management in California

NASA Astrophysics Data System (ADS)

Sheffield, J.; He, X.; Wada, Y.; Burek, P.; Kahil, M.; Wood, E. F.; Oppenheimer, M.

2017-12-01

California has endured record-breaking drought since winter 2011 and will likely experience more severe and persistent drought in the coming decades under changing climate. At the same time, human water management practices can also affect drought frequency and intensity, which underscores the importance of human behaviour in effective drought adaptation and mitigation. Currently, although a few large-scale hydrological and water resources models (e.g., PCR-GLOBWB) consider human water use and management practices (e.g., irrigation, reservoir operation, groundwater pumping), none of them includes the dynamic feedback between local human behaviors/decisions and the natural hydrological system. It is, therefore, vital to integrate social and behavioral dimensions into current hydrological modeling frameworks. This study applies the agent-based modeling (ABM) approach and couples it with a large-scale hydrological model (i.e., Community Water Model, CWatM) in order to have a balanced representation of social, environmental and economic factors and a more realistic representation of the bi-directional interactions and feedbacks in coupled human and natural systems. In this study, we focus on drought management in California and considers two types of agents, which are (groups of) farmers and state management authorities, and assumed that their corresponding objectives are to maximize the net crop profit and to maintain sufficient water supply, respectively. Farmers' behaviors are linked with local agricultural practices such as cropping patterns and deficit irrigation. More precisely, farmers' decisions are incorporated into CWatM across different time scales in terms of daily irrigation amount, seasonal/annual decisions on crop types and irrigated area as well as the long-term investment of irrigation infrastructure. This simulation-based optimization framework is further applied by performing different sets of scenarios to investigate and evaluate the effectiveness of different water management strategies and how policy interventions will facilitate drought adaptation in California.

Self-adaptive relevance feedback based on multilevel image content analysis

NASA Astrophysics Data System (ADS)

Gao, Yongying; Zhang, Yujin; Fu, Yu

2001-01-01

In current content-based image retrieval systems, it is generally accepted that obtaining high-level image features is a key to improve the querying. Among the related techniques, relevance feedback has become a hot research aspect because it combines the information from the user to refine the querying results. In practice, many methods have been proposed to achieve the goal of relevance feedback. In this paper, a new scheme for relevance feedback is proposed. Unlike previous methods for relevance feedback, our scheme provides a self-adaptive operation. First, based on multi- level image content analysis, the relevant images from the user could be automatically analyzed in different levels and the querying could be modified in terms of different analysis results. Secondly, to make it more convenient to the user, the procedure of relevance feedback could be led with memory or without memory. To test the performance of the proposed method, a practical semantic-based image retrieval system has been established, and the querying results gained by our self-adaptive relevance feedback are given.

Self-adaptive relevance feedback based on multilevel image content analysis

NASA Astrophysics Data System (ADS)

Gao, Yongying; Zhang, Yujin; Fu, Yu

2000-12-01

In current content-based image retrieval systems, it is generally accepted that obtaining high-level image features is a key to improve the querying. Among the related techniques, relevance feedback has become a hot research aspect because it combines the information from the user to refine the querying results. In practice, many methods have been proposed to achieve the goal of relevance feedback. In this paper, a new scheme for relevance feedback is proposed. Unlike previous methods for relevance feedback, our scheme provides a self-adaptive operation. First, based on multi- level image content analysis, the relevant images from the user could be automatically analyzed in different levels and the querying could be modified in terms of different analysis results. Secondly, to make it more convenient to the user, the procedure of relevance feedback could be led with memory or without memory. To test the performance of the proposed method, a practical semantic-based image retrieval system has been established, and the querying results gained by our self-adaptive relevance feedback are given.

Sensorimotor adaptation of speech in Parkinson's disease.

PubMed

Mollaei, Fatemeh; Shiller, Douglas M; Gracco, Vincent L

2013-10-01

The basal ganglia are involved in establishing motor plans for a wide range of behaviors. Parkinson's disease (PD) is a manifestation of basal ganglia dysfunction associated with a deficit in sensorimotor integration and difficulty in acquiring new motor sequences, thereby affecting motor learning. Previous studies of sensorimotor integration and sensorimotor adaptation in PD have focused on limb movements using visual and force-field alterations. Here, we report the results from a sensorimotor adaptation experiment investigating the ability of PD patients to make speech motor adjustments to a constant and predictable auditory feedback manipulation. Participants produced speech while their auditory feedback was altered and maintained in a manner consistent with a change in tongue position. The degree of adaptation was associated with the severity of motor symptoms. The patients with PD exhibited adaptation to the induced sensory error; however, the degree of adaptation was reduced compared with healthy, age-matched control participants. The reduced capacity to adapt to a change in auditory feedback is consistent with reduced gain in the sensorimotor system for speech and with previous studies demonstrating limitations in the adaptation of limb movements after changes in visual feedback among patients with PD. © 2013 Movement Disorder Society.

Feedback produces divergence from prospect theory in descriptive choice.

PubMed

Jessup, Ryan K; Bishara, Anthony J; Busemeyer, Jerome R

2008-10-01

A recent study demonstrated that individuals making experience-based choices underweight small probabilities, in contrast to the overweighting observed in a typical descriptive paradigm. We tested whether trial-by-trial feedback in a repeated descriptive paradigm would engender choices more correspondent with experiential or descriptive paradigms. The results of a repeated gambling task indicated that individuals receiving feedback underweighted small probabilities, relative to their no-feedback counterparts. These results implicate feedback as a critical component during the decision-making process, even in the presence of fully specified descriptive information. A model comparison at the individual-subject level suggested that feedback drove individuals' decision weights toward objective probability weighting.

Do Amnesic Patients with Korsakoff's Syndrome Use Feedback when Making Decisions under Risky Conditions? An Experimental Investigation with the Game of Dice Task with and without Feedback

ERIC Educational Resources Information Center

Brand, Matthias; Pawlikowski, Mirko; Labudda, Kirsten; Laier, Christian; von Rothkirch, Nadine; Markowitsch, Hans J.

2009-01-01

We investigated the role of feedback processing in decision making under risk conditions in 50 patients with amnesia in the course of alcoholic Korsakoff's syndrome (KS). Half of the patients were administered the Game of Dice Task (GDT) and the remaining 25 patients were examined with a modified version of the GDT in which no feedback was…

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.

Neural Correlates of Sequence Learning with Stochastic Feedback

ERIC Educational Resources Information Center

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

2011-01-01

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

Students' Perceived Usefulness of Formative Feedback for a Computer-Adaptive Test

ERIC Educational Resources Information Center

Lilley, Mariana; Barker, Trevor

2007-01-01

In this paper we report on research related to the provision of automated feedback based on a computer adaptive test (CAT), used in formative assessment. A cohort of 76 second year university undergraduates took part in a formative assessment with a CAT and were provided with automated feedback on their performance. A sample of students responded…

An Iterative Information-Reduced Quadriphase-Shift-Keyed Carrier Synchronization Scheme Using Decision Feedback for Low Signal-to-Noise Ratio Applications

NASA Technical Reports Server (NTRS)

Simon, M.; Tkacenko, A.

2006-01-01

In a previous publication [1], an iterative closed-loop carrier synchronization scheme for binary phase-shift keyed (BPSK) modulation was proposed that was based on feeding back data decisions to the input of the loop, the purpose being to remove the modulation prior to carrier synchronization as opposed to the more conventional decision-feedback schemes that incorporate such feedback inside the loop. The idea there was that, with sufficient independence between the received data and the decisions on it that are fed back (as would occur in an error-correction coding environment with sufficient decoding delay), a pure tone in the presence of noise would ultimately be produced (after sufficient iteration and low enough error probability) and thus could be tracked without any squaring loss. This article demonstrates that, with some modification, the same idea of iterative information reduction through decision feedback can be applied to quadrature phase-shift keyed (QPSK) modulation, something that was mentioned in the previous publication but never pursued.

How do we trust strangers? The neural correlates of decision making and outcome evaluation of generalized trust

PubMed Central

Wang, Yiwen; Zhang, Zhen; Jing, Yiming; Valadez, Emilio A.

2016-01-01

This study investigates the brain correlates of decision making and outcome evaluation of generalized trust (i.e. trust in unfamiliar social agents)—a core component of social capital which facilitates civic cooperation and economic exchange. We measured 18 (9 male) Chinese participants’ event-related potentials while they played the role of the trustor in a one-shot trust game with unspecified social agents (trustees) allegedly selected from a large representative sample. At the decision-making phase, greater N2 amplitudes were found for trustors’ distrusting decisions compared to trusting decisions, which may reflect greater cognitive control exerted to distrust. Source localization identified the precentral gyrus as one possible neuronal generator of this N2 component. At the outcome evaluation phase, principal components analysis revealed that the so called feedback-related negativity was in fact driven by a reward positivity, which was greater in response to gain feedback compared to loss feedback. This reduced reward positivity following loss feedback may indicate that the absence of reward for trusting decisions was unexpected by the trustor. In addition, we found preliminary evidence suggesting that the decision-making processes may differ between high trustors and low trustors. PMID:27317927

Effects of Visual Feedback Distortion on Gait Adaptation: Comparison of Implicit Visual Distortion Versus Conscious Modulation on Retention of Motor Learning.

PubMed

Kim, Seung-Jae; Ogilvie, Mitchell; Shimabukuro, Nathan; Stewart, Trevor; Shin, Joon-Ho

2015-09-01

Visual feedback can be used during gait rehabilitation to improve the efficacy of training. We presented a paradigm called visual feedback distortion; the visual representation of step length was manipulated during treadmill walking. Our prior work demonstrated that an implicit distortion of visual feedback of step length entails an unintentional adaptive process in the subjects' spatial gait pattern. Here, we investigated whether the implicit visual feedback distortion, versus conscious correction, promotes efficient locomotor adaptation that relates to greater retention of a task. Thirteen healthy subjects were studied under two conditions: (1) we implicitly distorted the visual representation of their gait symmetry over 14 min, and (2) with help of visual feedback, subjects were told to walk on the treadmill with the intent of attaining the gait asymmetry observed during the first implicit trial. After adaptation, the visual feedback was removed while subjects continued walking normally. Over this 6-min period, retention of preserved asymmetric pattern was assessed. We found that there was a greater retention rate during the implicit distortion trial than that of the visually guided conscious modulation trial. This study highlights the important role of implicit learning in the context of gait rehabilitation by demonstrating that training with implicit visual feedback distortion may produce longer lasting effects. This suggests that using visual feedback distortion could improve the effectiveness of treadmill rehabilitation processes by influencing the retention of motor skills.

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

Offset quadrature communications with decision-feedback carrier synchronization

NASA Technical Reports Server (NTRS)

Simon, M. K.; Smith, J. G.

1974-01-01

In order to accommodate a quadrature amplitude-shift-keyed (QASK) signal, Simon and Smith (1974) have modified the decision-feedback loop which tracks a quadrature phase-shift-keyed (QPSK). In the investigation reported approaches are considered to modify the loops in such a way that offset QASK signals can be tracked, giving attention to the special case of an offset QPSK. The development of the stochastic integro-differential equation of operation for a decision-feedback offset QASK loop is discussed along with the probability density function of the phase error process.

Decision feedback loop for tracking a polyphase modulated carrier

NASA Technical Reports Server (NTRS)

Simon, M. K. (Inventor)

1974-01-01

A multiple phase modulated carrier tracking loop for use in a frequency shift keying system is described in which carrier tracking efficiency is improved by making use of the decision signals made on the data phase transmitted in each T-second interval. The decision signal is used to produce a pair of decision-feedback quadrature signals for enhancing the loop's performance in developing a loop phase error signal.

Evaluation of the Display of Cognitive State Feedback to Drive Adaptive Task Sharing

PubMed Central

Dorneich, Michael C.; Passinger, Břetislav; Hamblin, Christopher; Keinrath, Claudia; Vašek, Jiři; Whitlow, Stephen D.; Beekhuyzen, Martijn

2017-01-01

This paper presents an adaptive system intended to address workload imbalances between pilots in future flight decks. Team performance can be maximized when task demands are balanced within crew capabilities and resources. Good communication skills enable teams to adapt to changes in workload, and include the balancing of workload between team members This work addresses human factors priorities in the aviation domain with the goal to develop concepts that balance operator workload, support future operator roles and responsibilities, and support new task requirements, while allowing operators to focus on the most safety critical tasks. A traditional closed-loop adaptive system includes the decision logic to turn automated adaptations on and off. This work takes a novel approach of replacing the decision logic, normally performed by the automation, with human decisions. The Crew Workload Manager (CWLM) was developed to objectively display the workload between pilots and recommend task sharing; it is then the pilots who “close the loop” by deciding how to best mitigate unbalanced workload. The workload was manipulated by the Shared Aviation Task Battery (SAT-B), which was developed to provide opportunities for pilots to mitigate imbalances in workload between crew members. Participants were put in situations of high and low workload (i.e., workload was manipulated as opposed to being measured), the workload was then displayed to pilots, and pilots were allowed to decide how to mitigate the situation. An evaluation was performed that utilized the SAT-B to manipulate workload and create workload imbalances. Overall, the CWLM reduced the time spent in unbalanced workload and improved the crew coordination in task sharing while not negatively impacting concurrent task performance. Balancing workload has the potential to improve crew resource management and task performance over time, and reduce errors and fatigue. Paired with a real-time workload measurement system, the CWLM could help teams manage their own task load distribution. PMID:28400716

Evaluation of the Display of Cognitive State Feedback to Drive Adaptive Task Sharing.

PubMed

Dorneich, Michael C; Passinger, Břetislav; Hamblin, Christopher; Keinrath, Claudia; Vašek, Jiři; Whitlow, Stephen D; Beekhuyzen, Martijn

2017-01-01

This paper presents an adaptive system intended to address workload imbalances between pilots in future flight decks. Team performance can be maximized when task demands are balanced within crew capabilities and resources. Good communication skills enable teams to adapt to changes in workload, and include the balancing of workload between team members This work addresses human factors priorities in the aviation domain with the goal to develop concepts that balance operator workload, support future operator roles and responsibilities, and support new task requirements, while allowing operators to focus on the most safety critical tasks. A traditional closed-loop adaptive system includes the decision logic to turn automated adaptations on and off. This work takes a novel approach of replacing the decision logic, normally performed by the automation, with human decisions. The Crew Workload Manager (CWLM) was developed to objectively display the workload between pilots and recommend task sharing; it is then the pilots who "close the loop" by deciding how to best mitigate unbalanced workload. The workload was manipulated by the Shared Aviation Task Battery (SAT-B), which was developed to provide opportunities for pilots to mitigate imbalances in workload between crew members. Participants were put in situations of high and low workload (i.e., workload was manipulated as opposed to being measured), the workload was then displayed to pilots, and pilots were allowed to decide how to mitigate the situation. An evaluation was performed that utilized the SAT-B to manipulate workload and create workload imbalances. Overall, the CWLM reduced the time spent in unbalanced workload and improved the crew coordination in task sharing while not negatively impacting concurrent task performance. Balancing workload has the potential to improve crew resource management and task performance over time, and reduce errors and fatigue. Paired with a real-time workload measurement system, the CWLM could help teams manage their own task load distribution.

Gray matter volume and rapid decision-making in major depressive disorder.

PubMed

Nakano, Masayuki; Matsuo, Koji; Nakashima, Mami; Matsubara, Toshio; Harada, Kenichiro; Egashira, Kazuteru; Masaki, Hiroaki; Takahashi, Kanji; Watanabe, Yoshifumi

2014-01-03

Reduced motivation and blunted decision-making are key features of major depressive disorder (MDD). Patients with MDD show abnormal decision-making when given negative feedback regarding a reward. The brain mechanisms underpinning this behavior remain unclear. In the present study, we examined the association between rapid decision-making with negative feedback and brain volume in MDD. Thirty-six patients with MDD and 54 age-, sex- and IQ-matched healthy subjects were studied. Subjects performed a rapid decision-making monetary task in which participants could make high- or low-risk choices. We compared between the 2 groups the probability that a high-risk choice followed negative feedback. In addition, we used voxel-based morphometry (VBM) to compare between group differences in gray matter volume, and the correlation between the probability for high-risk choices and brain volume. Compared to the healthy group, the MDD group showed significantly lower probabilities for high-risk choices following negative feedback. VBM analysis revealed that the MDD group had less gray matter volume in the right medial prefrontal cortex and orbitofrontal cortex (OFC) compared to the healthy group. The right OFC volume was negatively correlated with the probability that a high-risk choice followed negative feedback in patients with MDD. We did not observe these trends in healthy subjects. Patients with MDD show reduced motivation for monetary incentives when they were required to make rapid decisions following negative feedback. We observed a correlation between this reduced motivation and gray matter volume in the medial and ventral prefrontal cortex, which suggests that these brain regions are likely involved in the pathophysiology of aberrant decision-making in MDD. © 2013.

Building a Framework in Improving Drought Monitoring and Early Warning Systems in Africa

NASA Astrophysics Data System (ADS)

Tadesse, T.; Wall, N.; Haigh, T.; Shiferaw, A. S.; Beyene, S.; Demisse, G. B.; Zaitchik, B.

2015-12-01

Decision makers need a basic understanding of the prediction models and products of hydro-climatic extremes and their suitability in time and space for strategic resource and development planning to develop mitigation and adaptation strategies. Advances in our ability to assess and predict climate extremes (e.g., droughts and floods) under evolving climate change suggest opportunity to improve management of climatic/hydrologic risk in agriculture and water resources. In the NASA funded project entitled, "Seasonal Prediction of Hydro-Climatic Extremes in the Greater Horn of Africa (GHA) under Evolving Climate Conditions to Support Adaptation Strategies," we are attempting to develop a framework that uses dialogue between managers and scientists on how to enhance the use of models' outputs and prediction products in the GHA as well as improve the delivery of this information in ways that can be easily utilized by managers. This process is expected to help our multidisciplinary research team obtain feedback on the models and forecast products. In addition, engaging decision makers is essential in evaluating the use of drought and flood prediction models and products for decision-making processes in drought and flood management. Through this study, we plan to assess information requirements to implement a robust Early Warning Systems (EWS) by engaging decision makers in the process. This participatory process could also help the existing EWSs in Africa and to develop new local and regional EWSs. In this presentation, we report the progress made in the past two years of the NASA project.

Computerized Dynamic Adaptive Tests with Immediately Individualized Feedback for Primary School Mathematics Learning

ERIC Educational Resources Information Center

Wu, Huey-Min; Kuo, Bor-Chen; Wang, Su-Chen

2017-01-01

In this study, a computerized dynamic assessment test with both immediately individualized feedback and adaptively property was applied to Mathematics learning in primary school. For evaluating the effectiveness of the computerized dynamic adaptive test, the performances of three types of remedial instructions were compared by a pre-test/post-test…

Adaptive neural network decentralized backstepping output-feedback control for nonlinear large-scale systems with time delays.

PubMed

Tong, Shao Cheng; Li, Yong Ming; Zhang, Hua-Guang

2011-07-01

In this paper, two adaptive neural network (NN) decentralized output feedback control approaches are proposed for a class of uncertain nonlinear large-scale systems with immeasurable states and unknown time delays. Using NNs to approximate the unknown nonlinear functions, an NN state observer is designed to estimate the immeasurable states. By combining the adaptive backstepping technique with decentralized control design principle, an adaptive NN decentralized output feedback control approach is developed. In order to overcome the problem of "explosion of complexity" inherent in the proposed control approach, the dynamic surface control (DSC) technique is introduced into the first adaptive NN decentralized control scheme, and a simplified adaptive NN decentralized output feedback DSC approach is developed. It is proved that the two proposed control approaches can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded, and the observer errors and the tracking errors converge to a small neighborhood of the origin. Simulation results are provided to show the effectiveness of the proposed approaches.

Visuomotor adaptation needs a validation of prediction error by feedback error

PubMed Central

Gaveau, Valérie; Prablanc, Claude; Laurent, Damien; Rossetti, Yves; Priot, Anne-Emmanuelle

2014-01-01

The processes underlying short-term plasticity induced by visuomotor adaptation to a shifted visual field are still debated. Two main sources of error can induce motor adaptation: reaching feedback errors, which correspond to visually perceived discrepancies between hand and target positions, and errors between predicted and actual visual reafferences of the moving hand. These two sources of error are closely intertwined and difficult to disentangle, as both the target and the reaching limb are simultaneously visible. Accordingly, the goal of the present study was to clarify the relative contributions of these two types of errors during a pointing task under prism-displaced vision. In “terminal feedback error” condition, viewing of their hand by subjects was allowed only at movement end, simultaneously with viewing of the target. In “movement prediction error” condition, viewing of the hand was limited to movement duration, in the absence of any visual target, and error signals arose solely from comparisons between predicted and actual reafferences of the hand. In order to prevent intentional corrections of errors, a subthreshold, progressive stepwise increase in prism deviation was used, so that subjects remained unaware of the visual deviation applied in both conditions. An adaptive aftereffect was observed in the “terminal feedback error” condition only. As far as subjects remained unaware of the optical deviation and self-assigned pointing errors, prediction error alone was insufficient to induce adaptation. These results indicate a critical role of hand-to-target feedback error signals in visuomotor adaptation; consistent with recent neurophysiological findings, they suggest that a combination of feedback and prediction error signals is necessary for eliciting aftereffects. They also suggest that feedback error updates the prediction of reafferences when a visual perturbation is introduced gradually and cognitive factors are eliminated or strongly attenuated. PMID:25408644

Higher incentives can impair performance: neural evidence on reinforcement and rationality.

PubMed

Achtziger, Anja; Alós-Ferrer, Carlos; Hügelschäfer, Sabine; Steinhauser, Marco

2015-11-01

Standard economic thinking postulates that increased monetary incentives should increase performance. Human decision makers, however, frequently focus on past performance, a form of reinforcement learning occasionally at odds with rational decision making. We used an incentivized belief-updating task from economics to investigate this conflict through measurements of neural correlates of reward processing. We found that higher incentives fail to improve performance when immediate feedback on decision outcomes is provided. Subsequent analysis of the feedback-related negativity, an early event-related potential following feedback, revealed the mechanism behind this paradoxical effect. As incentives increase, the win/lose feedback becomes more prominent, leading to an increased reliance on reinforcement and more errors. This mechanism is relevant for economic decision making and the debate on performance-based payment. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Collective irrationality and positive feedback.

PubMed

Nicolis, Stamatios C; Zabzina, Natalia; Latty, Tanya; Sumpter, David J T

2011-04-26

Recent experiments on ants and slime moulds have assessed the degree to which they make rational decisions when presented with a number of alternative food sources or shelter. Ants and slime moulds are just two examples of a wide range of species and biological processes that use positive feedback mechanisms to reach decisions. Here we use a generic, experimentally validated model of positive feedback between group members to show that the probability of taking the best of options depends crucially on the strength of feedback. We show how the probability of choosing the best option can be maximized by applying an optimal feedback strength. Importantly, this optimal value depends on the number of options, so that when we change the number of options the preference of the group changes, producing apparent "irrationalities". We thus reinterpret the idea that collectives show "rational" or "irrational" preferences as being a necessary consequence of the use of positive feedback. We argue that positive feedback is a heuristic which often produces fast and accurate group decision-making, but is always susceptible to apparent irrationality when studied under particular experimental conditions.

Prism adaptation in virtual and natural contexts: Evidence for a flexible adaptive process.

PubMed

Veilleux, Louis-Nicolas; Proteau, Luc

2015-01-01

Prism exposure when aiming at a visual target in a virtual condition (e.g., when the hand is represented by a video representation) produces no or only small adaptations (after-effects), whereas prism exposure in a natural condition produces large after-effects. Some researchers suggested that this difference may arise from distinct adaptive processes, but other studies suggested a unique process. The present study reconciled these conflicting interpretations. Forty participants were divided into two groups: One group used visual feedback of their hand (natural context), and the other group used computer-generated representational feedback (virtual context). Visual feedback during adaptation was concurrent or terminal. All participants underwent laterally displacing prism perturbation. The results showed that the after-effects were twice as large in the "natural context" than in the "virtual context". No significant differences were observed between the concurrent and terminal feedback conditions. The after-effects generalized to untested targets and workspace. These results suggest that prism adaptation in virtual and natural contexts involves the same process. The smaller after-effects in the virtual context suggest that the depth of adaptation is a function of the degree of convergence between the proprioceptive and visual information that arises from the hand.

Information-reduced Carrier Synchronization of Iterative Decoded BPSK and QPSK using Soft Decision (Extrinsic) Feedback

NASA Technical Reports Server (NTRS)

Simon, Marvin; Valles, Esteban; Jones, Christopher

2008-01-01

This paper addresses the carrier-phase estimation problem under low SNR conditions as are typical of turbo- and LDPC-coded applications. In previous publications by the first author, closed-loop carrier synchronization schemes for error-correction coded BPSK and QPSK modulation were proposed that were based on feeding back hard data decisions at the input of the loop, the purpose being to remove the modulation prior to attempting to track the carrier phase as opposed to the more conventional decision-feedback schemes that incorporate such feedback inside the loop. In this paper, we consider an alternative approach wherein the extrinsic soft information from the iterative decoder of turbo or LDPC codes is instead used as the feedback.

Forgone but not forgotten: the effects of partial and full feedback in "harsh" and "kind" environments.

PubMed

Rakow, Tim; Newell, Ben R; Wright, Louise

2015-12-01

In a perfect world, the choice of any course of action would lead to a satisfactory outcome, and we would obtain feedback about both our chosen course and those we have chosen to forgo. In reality, however, we often face harsh environments in which we can only minimize losses, and we receive impoverished feedback. In these studies, we examined how decision makers dealt with these challenges in a simple task in which we manipulated three features of the decision: The outcomes from the available options were either mostly positive or mostly negative (kind or harsh environment); feedback was either full or partial (outcomes revealed for all options or only for the chosen option); and for the final 20 trials in a sequence, participants either chose on each trial or set an "advance-directive" policy. The propensity to choose the better option was explained by several factors: Full feedback was more beneficial in harsh than in kind environments; policy decisions encouraged better decisions and ameliorated the adverse impact of a harsh environment; and beliefs about the value of strategy diversification predicted switch rates and choice quality. The results suggest a subtle interplay between bottom-up and top-down processes: Although harsh environments encourage poor choices, and some decision makers choose less well than others, this need not imply that the decision maker has failed to identify the better option.

Coastal livelihood transitions under globalization with implications for trans-ecosystem interactions

PubMed Central

Stevens, Kara; Williams, Nicholas E.; Sistla, Seeta A.; Roddy, Adam B.; Urquhart, Gerald R.

2017-01-01

Anthropogenic threats to natural systems can be exacerbated due to connectivity between marine, freshwater, and terrestrial ecosystems, complicating the already daunting task of governance across the land-sea interface. Globalization, including new access to markets, can change social-ecological, land-sea linkages via livelihood responses and adaptations by local people. As a first step in understanding these trans-ecosystem effects, we examined exit and entry decisions of artisanal fishers and smallholder farmers on the rapidly globalizing Caribbean coast of Nicaragua. We found that exit and entry decisions demonstrated clear temporal and spatial patterns and that these decisions differed by livelihood. In addition to household characteristics, livelihood exit and entry decisions were strongly affected by new access to regional and global markets. The natural resource implications of these livelihood decisions are potentially profound as they provide novel linkages and spatially-explicit feedbacks between terrestrial and marine ecosystems. Our findings support the need for more scientific inquiry in understanding trans-ecosystem tradeoffs due to linked-livelihood transitions as well as the need for a trans-ecosystem approach to natural resource management and development policy in rapidly changing coastal regions. PMID:29077748

Feedback and feedforward locomotor adaptations to ankle-foot load in people with incomplete spinal cord injury.

PubMed

Gordon, Keith E; Wu, Ming; Kahn, Jennifer H; Schmit, Brian D

2010-09-01

Humans with spinal cord injury (SCI) modulate locomotor output in response to limb load. Understanding the neural control mechanisms responsible for locomotor adaptation could provide a framework for selecting effective interventions. We quantified feedback and feedforward locomotor adaptations to limb load modulations in people with incomplete SCI. While subjects airstepped (stepping performed with kinematic assistance and 100% bodyweight support), a powered-orthosis created a dorisflexor torque during the "stance phase" of select steps producing highly controlled ankle-load perturbations. When given repetitive, stance phase ankle-load, the increase in hip extension work, 0.27 J/kg above baseline (no ankle-load airstepping), was greater than the response to ankle-load applied during a single step, 0.14 J/kg (P = 0.029). This finding suggests that, at the hip, subjects produced both feedforward and feedback locomotor modulations. We estimate that, at the hip, the locomotor response to repetitive ankle-load was modulated almost equally by ongoing feedback and feedforward adaptations. The majority of subjects also showed after-effects in hip kinetic patterns that lasted 3 min in response to repetitive loading, providing additional evidence of feedforward locomotor adaptations. The magnitude of the after-effect was proportional to the response to repetitive ankle-foot load (R(2) = 0.92). In contrast, increases in soleus EMG amplitude were not different during repetitive and single-step ankle-load exposure, suggesting that ankle locomotor modulations were predominately feedback-based. Although subjects made both feedback and feedforward locomotor adaptations to changes in ankle-load, between-subject variations suggest that walking function may be related to the ability to make feedforward adaptations.

Secondary adaptation of memory-guided saccades

PubMed Central

Srimal, Riju; Curtis, Clayton E.

2011-01-01

Adaptation of saccade gains in response to errors keeps vision and action co-registered in the absence of awareness or effort. Timing is key, as the visual error must be available shortly after the saccade is generated or adaptation does not occur. Here, we tested the hypothesis that when feedback is delayed, learning still occurs, but does so through small secondary corrective saccades. Using a memory-guided saccade task, we gave feedback about the accuracy of saccades that was falsely displaced by a consistent amount, but only after long delays. Despite the delayed feedback, over time subjects improved in accuracy toward the false feedback. They did so not by adjusting their primary saccades, but via directed corrective saccades made before feedback was given. We propose that saccade learning may be driven by different types of feedback teaching signals. One teaching signal relies upon a tight temporal relation with the saccade and contributes to obligatory learning independent of awareness. When this signal is ineffective due to delayed error feedback, a second compensatory teaching signal enables flexible adjustments to the spatial goal of saccades and helps maintain sensorimotor accuracy. PMID:20803135

Full Gradient Solution to Adaptive Hybrid Control

NASA Technical Reports Server (NTRS)

Bean, Jacob; Schiller, Noah H.; Fuller, Chris

2017-01-01

This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.

Full Gradient Solution to Adaptive Hybrid Control

NASA Technical Reports Server (NTRS)

Bean, Jacob; Schiller, Noah H.; Fuller, Chris

2016-01-01

This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered-reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.

Feedback for reinforcement learning based brain-machine interfaces using confidence metrics.

PubMed

Prins, Noeline W; Sanchez, Justin C; Prasad, Abhishek

2017-06-01

For brain-machine interfaces (BMI) to be used in activities of daily living by paralyzed individuals, the BMI should be as autonomous as possible. One of the challenges is how the feedback is extracted and utilized in the BMI. Our long-term goal is to create autonomous BMIs that can utilize an evaluative feedback from the brain to update the decoding algorithm and use it intelligently in order to adapt the decoder. In this study, we show how to extract the necessary evaluative feedback from a biologically realistic (synthetic) source, use both the quantity and the quality of the feedback, and how that feedback information can be incorporated into a reinforcement learning (RL) controller architecture to maximize its performance. Motivated by the perception-action-reward cycle (PARC) in the brain which links reward for cognitive decision making and goal-directed behavior, we used a reward-based RL architecture named Actor-Critic RL as the model. Instead of using an error signal towards building an autonomous BMI, we envision to use a reward signal from the nucleus accumbens (NAcc) which plays a key role in the linking of reward to motor behaviors. To deal with the complexity and non-stationarity of biological reward signals, we used a confidence metric which was used to indicate the degree of feedback accuracy. This confidence was added to the Actor's weight update equation in the RL controller architecture. If the confidence was high (>0.2), the BMI decoder used this feedback to update its parameters. However, when the confidence was low, the BMI decoder ignored the feedback and did not update its parameters. The range between high confidence and low confidence was termed as the 'ambiguous' region. When the feedback was within this region, the BMI decoder updated its weight at a lower rate than when fully confident, which was decided by the confidence. We used two biologically realistic models to generate synthetic data for MI (Izhikevich model) and NAcc (Humphries model) to validate proposed controller architecture. In this work, we show how the overall performance of the BMI was improved by using a threshold close to the decision boundary to reject erroneous feedback. Additionally, we show the stability of the system improved when the feedback was used with a threshold. The result of this study is a step towards making BMIs autonomous. While our method is not fully autonomous, the results demonstrate that extensive training times necessary at the beginning of each BMI session can be significantly decreased. In our approach, decoder training time was only limited to 10 trials in the first BMI session. Subsequent sessions used previous session weights to initialize the decoder. We also present a method where the use of a threshold can be applied to any decoder with a feedback signal that is less than perfect so that erroneous feedback can be avoided and the stability of the system can be increased.

Feedback for reinforcement learning based brain-machine interfaces using confidence metrics

NASA Astrophysics Data System (ADS)

Prins, Noeline W.; Sanchez, Justin C.; Prasad, Abhishek

2017-06-01

Objective. For brain-machine interfaces (BMI) to be used in activities of daily living by paralyzed individuals, the BMI should be as autonomous as possible. One of the challenges is how the feedback is extracted and utilized in the BMI. Our long-term goal is to create autonomous BMIs that can utilize an evaluative feedback from the brain to update the decoding algorithm and use it intelligently in order to adapt the decoder. In this study, we show how to extract the necessary evaluative feedback from a biologically realistic (synthetic) source, use both the quantity and the quality of the feedback, and how that feedback information can be incorporated into a reinforcement learning (RL) controller architecture to maximize its performance. Approach. Motivated by the perception-action-reward cycle (PARC) in the brain which links reward for cognitive decision making and goal-directed behavior, we used a reward-based RL architecture named Actor-Critic RL as the model. Instead of using an error signal towards building an autonomous BMI, we envision to use a reward signal from the nucleus accumbens (NAcc) which plays a key role in the linking of reward to motor behaviors. To deal with the complexity and non-stationarity of biological reward signals, we used a confidence metric which was used to indicate the degree of feedback accuracy. This confidence was added to the Actor’s weight update equation in the RL controller architecture. If the confidence was high (>0.2), the BMI decoder used this feedback to update its parameters. However, when the confidence was low, the BMI decoder ignored the feedback and did not update its parameters. The range between high confidence and low confidence was termed as the ‘ambiguous’ region. When the feedback was within this region, the BMI decoder updated its weight at a lower rate than when fully confident, which was decided by the confidence. We used two biologically realistic models to generate synthetic data for MI (Izhikevich model) and NAcc (Humphries model) to validate proposed controller architecture. Main results. In this work, we show how the overall performance of the BMI was improved by using a threshold close to the decision boundary to reject erroneous feedback. Additionally, we show the stability of the system improved when the feedback was used with a threshold. Significance: The result of this study is a step towards making BMIs autonomous. While our method is not fully autonomous, the results demonstrate that extensive training times necessary at the beginning of each BMI session can be significantly decreased. In our approach, decoder training time was only limited to 10 trials in the first BMI session. Subsequent sessions used previous session weights to initialize the decoder. We also present a method where the use of a threshold can be applied to any decoder with a feedback signal that is less than perfect so that erroneous feedback can be avoided and the stability of the system can be increased.

Affect-Aware Adaptive Tutoring Based on Human-Automation Etiquette Strategies.

PubMed

Yang, Euijung; Dorneich, Michael C

2018-06-01

We investigated adapting the interaction style of intelligent tutoring system (ITS) feedback based on human-automation etiquette strategies. Most ITSs adapt the content difficulty level, adapt the feedback timing, or provide extra content when they detect cognitive or affective decrements. Our previous work demonstrated that changing the interaction style via different feedback etiquette strategies has differential effects on students' motivation, confidence, satisfaction, and performance. The best etiquette strategy was also determined by user frustration. Based on these findings, a rule set was developed that systemically selected the proper etiquette strategy to address one of four learning factors (motivation, confidence, satisfaction, and performance) under two different levels of user frustration. We explored whether etiquette strategy selection based on this rule set (systematic) or random changes in etiquette strategy for a given level of frustration affected the four learning factors. Participants solved mathematics problems under different frustration conditions with feedback that adapted dynamic changes in etiquette strategies either systematically or randomly. The results demonstrated that feedback with etiquette strategies chosen systematically via the rule set could selectively target and improve motivation, confidence, satisfaction, and performance more than changing etiquette strategies randomly. The systematic adaptation was effective no matter the level of frustration for the participant. If computer tutors can vary the interaction style to effectively mitigate negative emotions, then ITS designers would have one more mechanism in which to design affect-aware adaptations that provide the proper responses in situations where human emotions affect the ability to learn.

Adaptive Distributed Environment for Procedure Training (ADEPT)

NASA Technical Reports Server (NTRS)

Domeshek, Eric; Ong, James; Mohammed, John

2013-01-01

ADEPT (Adaptive Distributed Environment for Procedure Training) is designed to provide more effective, flexible, and portable training for NASA systems controllers. When creating a training scenario, an exercise author can specify a representative rationale structure using the graphical user interface, annotating the results with instructional texts where needed. The author's structure may distinguish between essential and optional parts of the rationale, and may also include "red herrings" - hypotheses that are essential to consider, until evidence and reasoning allow them to be ruled out. The system is built from pre-existing components, including Stottler Henke's SimVentive? instructional simulation authoring tool and runtime. To that, a capability was added to author and exploit explicit control decision rationale representations. ADEPT uses SimVentive's Scalable Vector Graphics (SVG)- based interactive graphic display capability as the basis of the tool for quickly noting aspects of decision rationale in graph form. The ADEPT prototype is built in Java, and will run on any computer using Windows, MacOS, or Linux. No special peripheral equipment is required. The software enables a style of student/ tutor interaction focused on the reasoning behind systems control behavior that better mimics proven Socratic human tutoring behaviors for highly cognitive skills. It supports fast, easy, and convenient authoring of such tutoring behaviors, allowing specification of detailed scenario-specific, but content-sensitive, high-quality tutor hints and feedback. The system places relatively light data-entry demands on the student to enable its rationale-centered discussions, and provides a support mechanism for fostering coherence in the student/ tutor dialog by including focusing, sequencing, and utterance tuning mechanisms intended to better fit tutor hints and feedback into the ongoing context.

Behavioral assessment of adaptive feedback equalization in a digital hearing aid.

PubMed

French-St George, M; Wood, D J; Engebretson, A M

1993-01-01

An evaluation was made of the efficacy of a digital feedback equalization algorithm employed by the Central Institute for the Deaf Wearable Adaptive Digital Hearing Aid. Three questions were addressed: 1) Does acoustic feedback limit gain adjustments made by hearing aid users? 2) Does feedback equalization permit users with hearing-impairment to select more gain without feedback? and, 3) If more gain is used when feedback equalization is active, does word identification performance improve? Nine subjects with hearing impairment participated in the study. Results suggest that listeners with hearing impairment are indeed limited by acoustic feedback when listening to soft speech (55 dB A) in quiet. The average listener used an additional 4 dB gain when feedback equalization was active. This additional gain resulted in an average 10 rationalized arcsine units (RAU) improvement in word identification score.

Implementation of an Automated Grading System with an Adaptive Learning Component to Affect Student Feedback and Response Time

ERIC Educational Resources Information Center

Matthews, Kevin; Janicki, Thomas; He, Ling; Patterson, Laurie

2012-01-01

This research focuses on the development and implementation of an adaptive learning and grading system with a goal to increase the effectiveness and quality of feedback to students. By utilizing various concepts from established learning theories, the goal of this research is to improve the quantity, quality, and speed of feedback as it pertains…

Induction of appropriate Th-cell phenotypes: cellular decision-making in heterogeneous environments.

PubMed

van den Ham, H-J; Andeweg, A C; de Boer, R J

2013-11-01

Helper T (Th)-cell differentiation is a key event in the development of the adaptive immune response. By the production of a range of cytokines, Th cells determine the type of immune response that is raised against an invading pathogen. Th cells can adopt many different phenotypes, and Th-cell phenotype decision-making is crucial in mounting effective host responses. This review discusses the different Th-cell phenotypes that have been identified and how Th cells adopt a particular phenotype. The regulation of Th-cell phenotypes has been studied extensively using mathematical models, which have explored the role of regulatory mechanisms such as autocrine cytokine signalling and cross-inhibition between self-activating transcription factors. At the single cell level, Th responses tend to be heterogeneous, but corrections can be made soon after T-cell activation. Although pathogens and the innate immune system provide signals that direct the induction of Th-cell phenotypes, these instructive mechanisms could be easily subverted by pathogens. We discuss that a model of success-driven feedback would select the most appropriate phenotype for clearing a pathogen. Given the heterogeneity in the induction phase of the Th response, such a success-driven feedback loop would allow the selection of effective Th-cell phenotypes while terminating incorrect responses. © 2013 John Wiley & Sons Ltd.

Single-trial EEG-informed fMRI analysis of emotional decision problems in hot executive function.

PubMed

Guo, Qian; Zhou, Tiantong; Li, Wenjie; Dong, Li; Wang, Suhong; Zou, Ling

2017-07-01

Executive function refers to conscious control in psychological process which relates to thinking and action. Emotional decision is a part of hot executive function and contains emotion and logic elements. As a kind of important social adaptation ability, more and more attention has been paid in recent years. Gambling task can be well performed in the study of emotional decision. As fMRI researches focused on gambling task show not completely consistent brain activation regions, this study adopted EEG-fMRI fusion technology to reveal brain neural activity related with feedback stimuli. In this study, an EEG-informed fMRI analysis was applied to process simultaneous EEG-fMRI data. First, relative power-spectrum analysis and K-means clustering method were performed separately to extract EEG-fMRI features. Then, Generalized linear models were structured using fMRI data and using different EEG features as regressors. The results showed that in the win versus loss stimuli, the activated regions almost covered the caudate, the ventral striatum (VS), the orbital frontal cortex (OFC), and the cingulate. Wide activation areas associated with reward and punishment were revealed by the EEG-fMRI integration analysis than the conventional fMRI results, such as the posterior cingulate and the OFC. The VS and the medial prefrontal cortex (mPFC) were found when EEG power features were performed as regressors of GLM compared with results entering the amplitudes of feedback-related negativity (FRN) as regressors. Furthermore, the brain region activation intensity was the strongest when theta-band power was used as a regressor compared with the other two fusion results. The EEG-based fMRI analysis can more accurately depict the whole-brain activation map and analyze emotional decision problems.

Auditory-Perceptual Learning Improves Speech Motor Adaptation in Children

PubMed Central

Shiller, Douglas M.; Rochon, Marie-Lyne

2015-01-01

Auditory feedback plays an important role in children’s speech development by providing the child with information about speech outcomes that is used to learn and fine-tune speech motor plans. The use of auditory feedback in speech motor learning has been extensively studied in adults by examining oral motor responses to manipulations of auditory feedback during speech production. Children are also capable of adapting speech motor patterns to perceived changes in auditory feedback, however it is not known whether their capacity for motor learning is limited by immature auditory-perceptual abilities. Here, the link between speech perceptual ability and the capacity for motor learning was explored in two groups of 5–7-year-old children who underwent a period of auditory perceptual training followed by tests of speech motor adaptation to altered auditory feedback. One group received perceptual training on a speech acoustic property relevant to the motor task while a control group received perceptual training on an irrelevant speech contrast. Learned perceptual improvements led to an enhancement in speech motor adaptation (proportional to the perceptual change) only for the experimental group. The results indicate that children’s ability to perceive relevant speech acoustic properties has a direct influence on their capacity for sensory-based speech motor adaptation. PMID:24842067

Frontal cortex electrophysiology in reward- and punishment-related feedback processing during advice-guided decision making: An interleaved EEG-DC stimulation study.

PubMed

Wischnewski, Miles; Bekkering, Harold; Schutter, Dennis J L G

2018-04-01

During decision making, individuals are prone to rely on external cues such as expert advice when the outcome is not known. However, the electrophysiological correlates associated with outcome uncertainty and the use of expert advice are not completely understood. The feedback-related negativity (FRN), P3a, and P3b are event-related brain potentials (ERPs) linked to dissociable stages of feedback and attentional processing during decision making. Even though these ERPs are influenced by both reward- and punishment-related feedback, it remains unclear how extrinsic information during uncertainty modulates these brain potentials. In this study, the effects of advice cues on decision making were investigated in two separate experiments. In the first experiment, electroencephalography (EEG) was recorded in healthy volunteers during a decision-making task in which the participants received reward or punishment feedback preceded by novice, amateur, or expert advice. The results showed that the P3a component was significantly influenced by the subjective predictive value of an advice cue, whereas the FRN and P3b were unaffected by the advice cues. In the second, sham-controlled experiment, cathodal transcranial direct current stimulation (ctDCS) was administered in conjunction with EEG in order to explore the direct contributions of the frontal cortex to these brain potentials. Results showed no significant change in either advice-following behavior or decision times. However, ctDCS did decrease FRN amplitudes as compared to sham, with no effect on the P3a or P3b. Together, these findings suggest that advice information may act primarily on attention allocation during feedback processing, whereas the electrophysiological correlates of the detection and updating of internal prediction models are not affected.

Psychosocial intervention in at-risk adolescents: using event-related potentials to assess changes in decision making and feedback processing.

PubMed

Pincham, H L; Bryce, D; Fonagy, P; Fearon, R M Pasco

2018-05-25

Decision making and feedback processing are two important cognitive processes that are impacted by social context, particularly during adolescence. The current study examined whether a psychosocial intervention could improve psychological wellbeing in at-risk adolescent boys, thereby improving their decision making and feedback processing skills. Two groups of at-risk adolescents were compared: those who were relatively new to a psychosocial intervention, and those who had engaged over a longer time period. Electroencephalography was recorded while the young people participated in a modified version of the Taylor Aggression Paradigm. The late positive potential (LPP) was measured during the decision phase of the task (where participants selected punishments for their opponents). The feedback-related negativity (FRN) and P3 components were measured during the task's outcome phase (where participants received 'win' or 'lose' feedback). Adolescents who were new to the intervention (the minimal-intervention group) were harsher in their punishment selections than those who had been engaged in the program for much longer. The minimal-intervention group also showed an enhanced LPP during the decision phase of the task, which may be indicative of immature decision making in that group. Analysis of the FRN and P3 amplitudes revealed that the minimal-intervention group was physiologically hypo-sensitive to feedback, compared with the extended-intervention group. Overall, these findings suggest that long-term community-based psychosocial intervention programs are beneficial for at-risk adolescents, and that event-related potentials can be employed as biomarkers of therapeutic change. However, because participants were not randomly allocated to treatment groups, alternative explanations cannot be excluded until further randomized controlled trials are undertaken.

Towards Contextualized Learning Services

NASA Astrophysics Data System (ADS)

Specht, Marcus

Personalization of feedback and instruction has often been considered as a key feature in learning support. The adaptations of the instructional process to the individual and its different aspects have been investigated from different research perspectives as learner modelling, intelligent tutoring systems, adaptive hypermedia, adaptive instruction and others. Already in the 1950s first commercial systems for adaptive instruction for trainings of keyboard skills have been developed utilizing adaptive configuration of feedback based on user performance and interaction footprints (Pask 1964). Around adaptive instruction there is a variety of research issues bringing together interdisciplinary research from computer science, engineering, psychology, psychotherapy, cybernetics, system dynamics, instructional design, and empirical research on technology enhanced learning. When classifying best practices of adaptive instruction different parameters of the instructional process have been identified which are adapted to the learner, as: sequence and size of task difficulty, time of feedback, pace of learning speed, reinforcement plan and others these are often referred to the adaptation target. Furthermore Aptitude Treatment Interaction studies explored the effect of adapting instructional parameters to different characteristics of the learner (Tennyson and Christensen 1988) as task performance, personality characteristics, or cognitive abilities, this is information is referred to as adaptation mean.

An Agent-based Modeling of Water-Food Nexus towards Sustainable Management of Urban Water Resources

NASA Astrophysics Data System (ADS)

Esmaeili, N.; Kanta, L.

2017-12-01

Growing population, urbanization, and climate change have put tremendous stress on water systems in many regions. A shortage in water system not only affects water users of a municipality but also that of food system. About 70% of global water is withdrawn for agriculture; livestock and dairy productions are also dependent on water availability. Although researchers and policy makers have identified and emphasized the water-food (WF) nexus in recent decade, most existing WF models offer strategies to reduce trade-offs and to generate benefits without considering feedback loops and adaptations between those systems. Feedback loops between water and food system can help understand long-term behavioral trends between water users of the integrated WF system which, in turn, can help manage water resources sustainably. An Agent-based modeling approach is applied here to develop a conceptual framework of WF systems. All water users in this system are modeled as agents, who are capable of making decisions and can adapt new behavior based on inputs from other agents in a shared environment through a set of logical and mathematical rules. Residential and commercial/industrial consumers are represented as municipal agents; crop, livestock, and dairy farmers are represented as food agents; and water management officials are represented as policy agent. During the period of water shortage, policy agent will propose/impose various water conservation measures, such as adapting water-efficient technologies, banning outdoor irrigation, implementing supplemental irrigation, using recycled water for livestock/dairy production, among others. Municipal and food agents may adapt conservation strategies and will update their demand accordingly. Emergent properties of the WF nexus will arise through dynamic interactions between various actors of water and food system. This model will be implemented to a case study for resource allocation and future policy development.

Reliable video transmission over fading channels via channel state estimation

NASA Astrophysics Data System (ADS)

Kumwilaisak, Wuttipong; Kim, JongWon; Kuo, C.-C. Jay

2000-04-01

Transmission of continuous media such as video over time- varying wireless communication channels can benefit from the use of adaptation techniques in both source and channel coding. An adaptive feedback-based wireless video transmission scheme is investigated in this research with special emphasis on feedback-based adaptation. To be more specific, an interactive adaptive transmission scheme is developed by letting the receiver estimate the channel state information and send it back to the transmitter. By utilizing the feedback information, the transmitter is capable of adapting the level of protection by changing the flexible RCPC (rate-compatible punctured convolutional) code ratio depending on the instantaneous channel condition. The wireless channel is modeled as a fading channel, where the long-term and short- term fading effects are modeled as the log-normal fading and the Rayleigh flat fading, respectively. Then, its state (mainly the long term fading portion) is tracked and predicted by using an adaptive LMS (least mean squares) algorithm. By utilizing the delayed feedback on the channel condition, the adaptation performance of the proposed scheme is first evaluated in terms of the error probability and the throughput. It is then extended to incorporate variable size packets of ITU-T H.263+ video with the error resilience option. Finally, the end-to-end performance of wireless video transmission is compared against several non-adaptive protection schemes.

Effects of subordinate feedback to the supervisor and participation in decision-making in the prediction of organizational support.

DOT National Transportation Integrated Search

1992-03-01

The present study tested the hypothesis that participation in decision-making (PDM) and perceived effectiveness of subordinate feedback to the supervisor would contribute unique variance in the prediction of perceptions of organizational support. In ...

Performance Feedback Processing Is Positively Biased As Predicted by Attribution Theory.

PubMed

Korn, Christoph W; Rosenblau, Gabriela; Rodriguez Buritica, Julia M; Heekeren, Hauke R

2016-01-01

A considerable literature on attribution theory has shown that healthy individuals exhibit a positivity bias when inferring the causes of evaluative feedback on their performance. They tend to attribute positive feedback internally (e.g., to their own abilities) but negative feedback externally (e.g., to environmental factors). However, all empirical demonstrations of this bias suffer from at least one of the three following drawbacks: First, participants directly judge explicit causes for their performance. Second, participants have to imagine events instead of experiencing them. Third, participants assess their performance only after receiving feedback and thus differences in baseline assessments cannot be excluded. It is therefore unclear whether the classically reported positivity bias generalizes to setups without these drawbacks. Here, we aimed at establishing the relevance of attributions for decision-making by showing an attribution-related positivity bias in a decision-making task. We developed a novel task, which allowed us to test how participants changed their evaluations in response to positive and negative feedback about performance. Specifically, we used videos of actors expressing different facial emotional expressions. Participants were first asked to evaluate the actors' credibility in expressing a particular emotion. After this initial rating, participants performed an emotion recognition task and did--or did not--receive feedback on their veridical performance. Finally, participants re-rated the actors' credibility, which provided a measure of how they changed their evaluations after feedback. Attribution theory predicts that participants change their evaluations of the actors' credibility toward the positive after receiving positive performance feedback and toward the negative after negative performance feedback. Our results were in line with this prediction. A control condition without feedback showed that correct or incorrect performance alone could not explain the observed positivity bias. Furthermore, participants' behavior in our task was linked to the most widely used measure of attribution style. In sum, our findings suggest that positive and negative performance feedback influences the evaluation of task-related stimuli, as predicted by attribution theory. Therefore, our study points to the relevance of attribution theory for feedback processing in decision-making and provides a novel outlook for decision-making biases.

Performance Feedback Processing Is Positively Biased As Predicted by Attribution Theory

PubMed Central

Rodriguez Buritica, Julia M.; Heekeren, Hauke R.

2016-01-01

A considerable literature on attribution theory has shown that healthy individuals exhibit a positivity bias when inferring the causes of evaluative feedback on their performance. They tend to attribute positive feedback internally (e.g., to their own abilities) but negative feedback externally (e.g., to environmental factors). However, all empirical demonstrations of this bias suffer from at least one of the three following drawbacks: First, participants directly judge explicit causes for their performance. Second, participants have to imagine events instead of experiencing them. Third, participants assess their performance only after receiving feedback and thus differences in baseline assessments cannot be excluded. It is therefore unclear whether the classically reported positivity bias generalizes to setups without these drawbacks. Here, we aimed at establishing the relevance of attributions for decision-making by showing an attribution-related positivity bias in a decision-making task. We developed a novel task, which allowed us to test how participants changed their evaluations in response to positive and negative feedback about performance. Specifically, we used videos of actors expressing different facial emotional expressions. Participants were first asked to evaluate the actors’ credibility in expressing a particular emotion. After this initial rating, participants performed an emotion recognition task and did—or did not—receive feedback on their veridical performance. Finally, participants re-rated the actors’ credibility, which provided a measure of how they changed their evaluations after feedback. Attribution theory predicts that participants change their evaluations of the actors’ credibility toward the positive after receiving positive performance feedback and toward the negative after negative performance feedback. Our results were in line with this prediction. A control condition without feedback showed that correct or incorrect performance alone could not explain the observed positivity bias. Furthermore, participants’ behavior in our task was linked to the most widely used measure of attribution style. In sum, our findings suggest that positive and negative performance feedback influences the evaluation of task-related stimuli, as predicted by attribution theory. Therefore, our study points to the relevance of attribution theory for feedback processing in decision-making and provides a novel outlook for decision-making biases. PMID:26849646

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

PubMed

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

2016-12-15

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

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

PubMed Central

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

2016-01-01

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

Output Feedback Adaptive Control of Non-Minimum Phase Systems Using Optimal Control Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan

2018-01-01

This paper describes output feedback adaptive control approaches for non-minimum phase SISO systems with relative degree 1 and non-strictly positive real (SPR) MIMO systems with uniform relative degree 1 using the optimal control modification method. It is well-known that the standard model-reference adaptive control (MRAC) cannot be used to control non-SPR plants to track an ideal SPR reference model. Due to the ideal property of asymptotic tracking, MRAC attempts an unstable pole-zero cancellation which results in unbounded signals for non-minimum phase SISO systems. The optimal control modification can be used to prevent the unstable pole-zero cancellation which results in a stable adaptation of non-minimum phase SISO systems. However, the tracking performance using this approach could suffer if the unstable zero is located far away from the imaginary axis. The tracking performance can be recovered by using an observer-based output feedback adaptive control approach which uses a Luenberger observer design to estimate the state information of the plant. Instead of explicitly specifying an ideal SPR reference model, the reference model is established from the linear quadratic optimal control to account for the non-minimum phase behavior of the plant. With this non-minimum phase reference model, the observer-based output feedback adaptive control can maintain stability as well as tracking performance. However, in the presence of the mismatch between the SPR reference model and the non-minimum phase plant, the standard MRAC results in unbounded signals, whereas a stable adaptation can be achieved with the optimal control modification. An application of output feedback adaptive control for a flexible wing aircraft illustrates the approaches.

Adaptive optimal stochastic state feedback control of resistive wall modes in tokamaks

NASA Astrophysics Data System (ADS)

Sun, Z.; Sen, A. K.; Longman, R. W.

2006-01-01

An adaptive optimal stochastic state feedback control is developed to stabilize the resistive wall mode (RWM) instability in tokamaks. The extended least-square method with exponential forgetting factor and covariance resetting is used to identify (experimentally determine) the time-varying stochastic system model. A Kalman filter is used to estimate the system states. The estimated system states are passed on to an optimal state feedback controller to construct control inputs. The Kalman filter and the optimal state feedback controller are periodically redesigned online based on the identified system model. This adaptive controller can stabilize the time-dependent RWM in a slowly evolving tokamak discharge. This is accomplished within a time delay of roughly four times the inverse of the growth rate for the time-invariant model used.

Adaptive Optimal Stochastic State Feedback Control of Resistive Wall Modes in Tokamaks

NASA Astrophysics Data System (ADS)

Sun, Z.; Sen, A. K.; Longman, R. W.

2007-06-01

An adaptive optimal stochastic state feedback control is developed to stabilize the resistive wall mode (RWM) instability in tokamaks. The extended least square method with exponential forgetting factor and covariance resetting is used to identify the time-varying stochastic system model. A Kalman filter is used to estimate the system states. The estimated system states are passed on to an optimal state feedback controller to construct control inputs. The Kalman filter and the optimal state feedback controller are periodically redesigned online based on the identified system model. This adaptive controller can stabilize the time dependent RWM in a slowly evolving tokamak discharge. This is accomplished within a time delay of roughly four times the inverse of the growth rate for the time-invariant model used.

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.

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

NASA Astrophysics Data System (ADS)

Marom, Yuval; Hayes, Gillian

2001-06-01

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

Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions

PubMed Central

Lawley, Mark A.; Siscovick, David S.; Zhang, Donglan; Pagán, José A.

2016-01-01

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions. PMID:27236380

Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions.

PubMed

Li, Yan; Lawley, Mark A; Siscovick, David S; Zhang, Donglan; Pagán, José A

2016-05-26

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions.

Adaptive feedback synchronization of a unified chaotic system

NASA Astrophysics Data System (ADS)

Lu, Junan; Wu, Xiaoqun; Han, Xiuping; Lü, Jinhu

2004-08-01

This Letter further improves and extends the work of Wang et al. [Phys. Lett. A 312 (2003) 34]. In detailed, the linear feedback synchronization and adaptive feedback synchronization with only one controller for a unified chaotic system are discussed here. It is noticed that this unified system contains the noted Lorenz and Chen systems. Two chaotic synchronization theorems are attained. Also, numerical simulations are given to show the effectiveness of these methods.

Adaptive Sliding Mode Control of Dynamic Systems Using Double Loop Recurrent Neural Network Structure.

PubMed

Fei, Juntao; Lu, Cheng

2018-04-01

In this paper, an adaptive sliding mode control system using a double loop recurrent neural network (DLRNN) structure is proposed for a class of nonlinear dynamic systems. A new three-layer RNN is proposed to approximate unknown dynamics with two different kinds of feedback loops where the firing weights and output signal calculated in the last step are stored and used as the feedback signals in each feedback loop. Since the new structure has combined the advantages of internal feedback NN and external feedback NN, it can acquire the internal state information while the output signal is also captured, thus the new designed DLRNN can achieve better approximation performance compared with the regular NNs without feedback loops or the regular RNNs with a single feedback loop. The new proposed DLRNN structure is employed in an equivalent controller to approximate the unknown nonlinear system dynamics, and the parameters of the DLRNN are updated online by adaptive laws to get favorable approximation performance. To investigate the effectiveness of the proposed controller, the designed adaptive sliding mode controller with the DLRNN is applied to a -axis microelectromechanical system gyroscope to control the vibrating dynamics of the proof mass. Simulation results demonstrate that the proposed methodology can achieve good tracking property, and the comparisons of the approximation performance between radial basis function NN, RNN, and DLRNN show that the DLRNN can accurately estimate the unknown dynamics with a fast speed while the internal states of DLRNN are more stable.

Age-related changes in decision making: comparing informed and noninformed situations.

PubMed

Van Duijvenvoorde, Anna C K; Jansen, Brenda R J; Bredman, Joren C; Huizenga, Hilde M

2012-01-01

Advantageous decision making progressively develops into early adulthood, most specifically in complex and motivationally salient decision situations in which direct feedback on gains and losses is provided (Figner & Weber, 2011). However, the factors that underlie this developmental improvement in decision making are still not well understood. The current study therefore investigates 2 potential factors, long-term memory and working memory, by assigning a large developmental sample (7-29 years of age) to a condition with either high or low demands on long-term and working memory. The first condition featured an age-adapted version of the Iowa Gambling Task (IGT; Bechara, Damasio, Damasio, & Anderson, 1994; i.e., a noninformed situation), whereas the second condition provided an external store where explicit information on gains, losses, and probabilities per choice option was presented (i.e., an informed situation). Consistent with previous developmental IGT studies, children up to age 12 did not learn to prefer advantageous options in the noninformed condition. In contrast, all age groups learned to prefer the advantageous options in the informed conditions, although a slight developmental increase in advantageous decision making remained. These results indicate that lowering dependence on long-term and working memory improves children's advantageous decision making. The results additionally suggest that other factors, like inhibitory control processes, may play an additional role in the development of advantageous decision making.

Modifying Evaluations and Decisions in Risky Situations.

PubMed

Maldonado, Antonio; Serra, Sara; Catena, Andrés; Cándido, Antonio; Megías, Alberto

2016-09-20

The main aim of this research was to investigate the decision making process in risky situations. We studied how different types of feedback on risky driving behaviors modulate risk evaluation and risk-taking. For a set of risky traffic situations, participants had to make evaluative judgments (judge the situation as risky or not) and urgent decisions (brake or not). In Experiment 1, participants received feedback with and without negative emotional content when they made risky behaviors. In Experiment 2 we investigated the independent effects of feedback and negative emotional stimuli. The results showed three important findings: First, urgent decisions were faster [F(1, 92) = 6.76, p = .01] and more cautious [F(1, 92) = 17.16, p < .001] than evaluative judgments. These results suggest that evaluative judgments of risk and actual risk-taking may not always coincide, and that they seem to be controlled by two different processing systems as proposed by dual process theories. Second, feedback made participants' responses even faster [F(1, 111) = 71.53, p < .001], allowing greater risk sensitivity [F(1, 111) = 22.12, p < .001] and skewing towards more cautious responses [F(1, 111) = 14.09, p < .001]. Finally, emotional stimuli had an effect only when they were presented as feedback. The results of this research increase our understanding of the processes involved in risky driving behavior and suggest efficient ways to control risk taking through the use of feedback.

Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework.

PubMed

El-Assady, Mennatallah; Sevastjanova, Rita; Sperrle, Fabian; Keim, Daniel; Collins, Christopher

2018-01-01

Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability. We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. We also report feedback from a two-stage study which shows that our technique results in topic model quality improvements on two independent measures.

Using virtual human technology to provide immediate feedback about participants' use of demographic cues and knowledge of their cue use.

PubMed

Wandner, Laura D; Letzen, Janelle E; Torres, Calia A; Lok, Benjamin; Robinson, Michael E

2014-11-01

Demographic characteristics have been found to influence pain management decisions, but limited focus has been placed on participants' reactions to feedback about their use of sex, race, or age to make these decisions. The present study aimed to examine the effects of providing feedback about the use of demographic cues to participants making pain management decisions. Participants (N = 107) viewed 32 virtual human patients with standardized levels of pain and provided ratings for virtual humans' pain intensity and their treatment decisions. Real-time lens model idiographic analyses determined participants' decision policies based on cues used. Participants were subsequently informed about cue use and completed feedback questions. Frequency analyses were conducted on responses to these questions. Between 7.4 and 89.4% of participants indicated awareness of their use of demographic or pain expression cues. Of those individuals, 26.9 to 55.5% believed this awareness would change their future clinical decisions, and 66.6 to 75.9% endorsed that their attitudes affect their imagined clinical practice. Between 66.6 and 79.1% of participants who used cues reported willingness to complete an online tutorial about pain across demographic groups. This study was novel because it provided participants feedback about their cue use. Most participants who used cues indicated willingness to participate in an online intervention, suggesting this technology's utility for modifying biases. This is the first study to make individuals aware of whether a virtual human's sex, race, or age influences their decision making. Findings suggest that a majority of the individuals who were made aware of their use of demographic cues would be willing to participate in an online intervention. Copyright © 2014 American Pain Society. Published by Elsevier Inc. All rights reserved.

Adaptive and Rational Anticipations in Risk Management Systems and Economy

NASA Astrophysics Data System (ADS)

Dubois, Daniel M.; Holmberg, Stig C.

2010-11-01

The global financial crisis of year 2009 is explained as a result of uncoordinated risk management decisions in business firms and economic organisations. The underlying reason for this can be found in the current financial system. As the financial market has lost much of its direct coupling to the concrete economy it provides misleading information to economic decision makers at all levels. Hence, the financial system has moved from a state of moderate and slow cyclical fluctuations into a state of fast and chaotic ones. Those misleading decisions can further be described, but not explained, by help of adaptive and rational expectations from macroeconomic theory. In this context, AE, the Adaptive Expectations are related to weak passive Exo-anticipation, and RE, the Rational expectations can be related to a strong, active and design oriented anticipation. The shortcomings of conventional cures, which builds on a reactive paradigm, have already been demonstrated in economic literature and are here further underlined by help of Ashby's "Law of Requisite Variety", Weaver's distinction between systems of "Disorganized Complexity" and those of "Organized Complexity", and Klir's "Reconstructability Analysis". Anticipatory decision-making is hence here proposed as a replacement to current expectation based and passive risk management. An anticipatory model of the business cycle is presented for supporting that proposition. The model, which is an extension of the Kaldor-Kalecki model, includes both retardation and anticipation. While cybernetics with the feedback process in control system deals with an explicit goal or purpose given to a system, the anticipatory system discussed here deals with a behaviour for which the future state of the system is built by the system itself, without explicit goal. A system with weak anticipation is based on a predictive model of the system, while a system with strong anticipation builds its own future by itself. Numerical simulations on computer confirm the feasibility of this approach. Hence, functional differential equations with both retardation and anticipation are found to be useful tools for modelling financial systems.

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.

Cross-Layer Adaptive Feedback Scheduling of Wireless Control Systems

PubMed Central

Xia, Feng; Ma, Longhua; Peng, Chen; Sun, Youxian; Dong, Jinxiang

2008-01-01

There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS) scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting cross-layer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An event-driven invocation mechanism for the feedback scheduler is also developed. Simulation results show that the proposed approach is efficient in dealing with channel capacity variations and noise interference, thus providing an enabling technology for control over WLAN. PMID:27879934

Implicit knowledge of visual uncertainty guides decisions with asymmetric outcomes.

PubMed

Whiteley, Louise; Sahani, Maneesh

2008-03-06

Perception is an "inverse problem," in which the state of the world must be inferred from the sensory neural activity that results. However, this inference is both ill-posed (Helmholtz, 1856; Marr, 1982) and corrupted by noise (Green & Swets, 1989), requiring the brain to compute perceptual beliefs under conditions of uncertainty. Here we show that human observers performing a simple visual choice task under an externally imposed loss function approach the optimal strategy, as defined by Bayesian probability and decision theory (Berger, 1985; Cox, 1961). In concert with earlier work, this suggests that observers possess a model of their internal uncertainty and can utilize this model in the neural computations that underlie their behavior (Knill & Pouget, 2004). In our experiment, optimal behavior requires that observers integrate the loss function with an estimate of their internal uncertainty rather than simply requiring that they use a modal estimate of the uncertain stimulus. Crucially, they approach optimal behavior even when denied the opportunity to learn adaptive decision strategies based on immediate feedback. Our data thus support the idea that flexible representations of uncertainty are pre-existing, widespread, and can be propagated to decision-making areas of the brain.

Performance analysis of adaptive equalization for coherent acoustic communications in the time-varying ocean environment.

PubMed

Preisig, James C

2005-07-01

Equations are derived for analyzing the performance of channel estimate based equalizers. The performance is characterized in terms of the mean squared soft decision error (sigma2(s)) of each equalizer. This error is decomposed into two components. These are the minimum achievable error (sigma2(0)) and the excess error (sigma2(e)). The former is the soft decision error that would be realized by the equalizer if the filter coefficient calculation were based upon perfect knowledge of the channel impulse response and statistics of the interfering noise field. The latter is the additional soft decision error that is realized due to errors in the estimates of these channel parameters. These expressions accurately predict the equalizer errors observed in the processing of experimental data by a channel estimate based decision feedback equalizer (DFE) and a passive time-reversal equalizer. Further expressions are presented that allow equalizer performance to be predicted given the scattering function of the acoustic channel. The analysis using these expressions yields insights into the features of surface scattering that most significantly impact equalizer performance in shallow water environments and motivates the implementation of a DFE that is robust with respect to channel estimation errors.

Adaptive Neural Output Feedback Control for Nonstrict-Feedback Stochastic Nonlinear Systems With Unknown Backlash-Like Hysteresis and Unknown Control Directions.

PubMed

Yu, Zhaoxu; Li, Shugang; Yu, Zhaosheng; Li, Fangfei

2018-04-01

This paper investigates the problem of output feedback adaptive stabilization for a class of nonstrict-feedback stochastic nonlinear systems with both unknown backlashlike hysteresis and unknown control directions. A new linear state transformation is applied to the original system, and then, control design for the new system becomes feasible. By combining the neural network's (NN's) parameterization, variable separation technique, and Nussbaum gain function method, an input-driven observer-based adaptive NN control scheme, which involves only one parameter to be updated, is developed for such systems. All closed-loop signals are bounded in probability and the error signals remain semiglobally bounded in the fourth moment (or mean square). Finally, the effectiveness and the applicability of the proposed control design are verified by two simulation examples.

Water demand and supply co-adaptation to mitigate climate change impacts in agricultural water management

NASA Astrophysics Data System (ADS)

Giuliani, Matteo; Mainardi, Matteo; Castelletti, Andrea; Gandolfi, Claudio

2013-04-01

Agriculture is the main land use in the world and represents also the sector characterised by the highest water demand. To meet projected growth in human population and per-capita food demand, agricultural production will have to significantly increase in the next decades. Moreover, water availability is nowadays a limiting factor for agricultural production, and is expected to decrease over the next century due to climate change impacts. To effectively face a changing climate, agricultural systems have therefore to adapt their strategies (e.g., changing crops, shifting sowing and harvesting dates, adopting high efficiency irrigation techniques). Yet, farmer adaptation is only one part of the equation because changes in water supply management strategies, as a response to climate change, might impact on farmers' decisions as well. Despite the strong connections between water demand and supply, being the former dependent on agricultural practices, which are affected by the water available that depends on the water supply strategies designed according to a forecasted demand, an analysis of their reciprocal feedbacks is still missing. Most of the recent studies has indeed considered the two problems separately, either analysing the impact of climate change on farmers' decisions for a given water supply scenario or optimising water supply for different water demand scenarios. In this work, we explicitly connect the two systems (demand and supply) by activating an information loop between farmers and water managers, to integrate the two problems and study the co-evolution and co-adaptation of water demand and water supply systems under climate change. The proposed approach is tested on a real-world case study, namely the Lake Como serving the Muzza-Bassa Lodigiana irrigation district (Italy). In particular, given an expectation of water availability, the farmers are able to solve a yearly planning problem to decide the most profitable crop to plant. Knowing the farmers decisions, the operation of the upstream reservoir (Como Lake) is optimised with respect to the real irrigation demand of the crops. Then, the farmers can re-adapt their decisions according with the new optimal operating strategy, thus activating a loop between the two systems that exchange expected supply and irrigation demand. Results show that the proposed interaction between farmers and water managers is able to enhance the efficiency of water management practices, foster crop production and mitigate climate change impacts.

Adaptive Nonlinear Tracking Control of Kinematically Redundant Robot Manipulators with Sub-Task Extensions

DTIC Science & Technology

2005-01-01

C. Hughes, Spacecraft Attitude Dynamics, New York, NY: Wiley, 1994. [8] H. K. Khalil, “Adaptive Output Feedback Control of Non- linear Systems...Closed-Loop Manipulator Control Using Quaternion Feedback ”, IEEE Trans. Robotics and Automation, Vol. 4, No. 4, pp. 434-440, (1988). [23] E...full-state feedback quaternion based controller de- veloped in [5] and focuses on the design of a general sub-task controller. This sub-task controller

Multiple factors, including non-motor impairments, influence decision making with regard to exercise participation in Parkinson's disease: a qualitative enquiry.

PubMed

O'Brien, Christine; Clemson, Lindy; Canning, Colleen G

2016-01-01

To explore how the meaning of exercise and other factors interact and influence the exercise behaviour of individuals with Parkinson's disease (PD) enrolled in a 6-month minimally supervised exercise program to prevent falls, regardless of whether they completed the prescribed exercise or not. This qualitative study utilised in-depth semi-structured interviews analysed using grounded theory methodology. Four main themes were constructed from the data: adapting to change and loss, the influence of others, making sense of the exercise experience and hope for a more active future. Participation in the PD-specific physiotherapy program involving group exercise provided an opportunity for participants to reframe their identity of their "active" self. Three new influences on exercise participation were identified and explored: non-motor impairments of apathy and fatigue, the belief in a finite energy quota, and the importance of feedback. A model was developed incorporating the themes and influences to explain decision-making for exercise participation in this group. Complex and interacting issues, including non-motor impairments, need to be considered in order to enhance the development and ongoing implementation of effective exercise programmes for people with PD. Exercise participation can assist individuals to reframe their identity as they are faced with losses associated with Parkinson's disease and ageing. Non-motor impairments of apathy and fatigue may influence exercise participation in people with Parkinson's disease. Particular attention needs to be paid to the provision of feedback in exercise programs for people with Parkinson's disease as it important for their decision-making about continuing exercise.

Finite-Time Adaptive Control for a Class of Nonlinear Systems With Nonstrict Feedback Structure.

PubMed

Sun, Yumei; Chen, Bing; Lin, Chong; Wang, Honghong

2017-09-18

This paper focuses on finite-time adaptive neural tracking control for nonlinear systems in nonstrict feedback form. A semiglobal finite-time practical stability criterion is first proposed. Correspondingly, the finite-time adaptive neural control strategy is given by using this criterion. Unlike the existing results on adaptive neural/fuzzy control, the proposed adaptive neural controller guarantees that the tracking error converges to a sufficiently small domain around the origin in finite time, and other closed-loop signals are bounded. At last, two examples are used to test the validity of our results.

Feedback and feedforward adaptation to visuomotor delay during reaching and slicing movements.

PubMed

Botzer, Lior; Karniel, Amir

2013-07-01

It has been suggested that the brain and in particular the cerebellum and motor cortex adapt to represent the environment during reaching movements under various visuomotor perturbations. It is well known that significant delay is present in neural conductance and processing; however, the possible representation of delay and adaptation to delayed visual feedback has been largely overlooked. Here we investigated the control of reaching movements in human subjects during an imposed visuomotor delay in a virtual reality environment. In the first experiment, when visual feedback was unexpectedly delayed, the hand movement overshot the end-point target, indicating a vision-based feedback control. Over the ensuing trials, movements gradually adapted and became accurate. When the delay was removed unexpectedly, movements systematically undershot the target, demonstrating that adaptation occurred within the vision-based feedback control mechanism. In a second experiment designed to broaden our understanding of the underlying mechanisms, we revealed similar after-effects for rhythmic reversal (out-and-back) movements. We present a computational model accounting for these results based on two adapted forward models, each tuned for a specific modality delay (proprioception or vision), and a third feedforward controller. The computational model, along with the experimental results, refutes delay representation in a pure forward vision-based predictor and suggests that adaptation occurred in the forward vision-based predictor, and concurrently in the state-based feedforward controller. Understanding how the brain compensates for conductance and processing delays is essential for understanding certain impairments concerning these neural delays as well as for the development of brain-machine interfaces. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Adaptive Inferential Feedback Partner Training for Depression: A Pilot Study

ERIC Educational Resources Information Center

Dobkin, Roseanne DeFronzo; Allen, Lesley A.; Alloy, Lauren B.; Menza, Matthew; Gara, Michael A.; Panzarella, Catherine

2007-01-01

Adaptive inferential feedback (AIF) partner training is a cognitive technique that teaches the friends and family members of depressed patients to respond to the patients' dysfunctional thoughts in a targeted manner. These dysfunctional attributions, which AIF addresses, are a common residual feature of depression amongst remitted patients, and…

Exploring the bases for a mixed reality stroke rehabilitation system, Part II: design of interactive feedback for upper limb rehabilitation.

PubMed

Lehrer, Nicole; Chen, Yinpeng; Duff, Margaret; L Wolf, Steven; Rikakis, Thanassis

2011-09-08

Few existing interactive rehabilitation systems can effectively communicate multiple aspects of movement performance simultaneously, in a manner that appropriately adapts across various training scenarios. In order to address the need for such systems within stroke rehabilitation training, a unified approach for designing interactive systems for upper limb rehabilitation of stroke survivors has been developed and applied for the implementation of an Adaptive Mixed Reality Rehabilitation (AMRR) System. The AMRR system provides computational evaluation and multimedia feedback for the upper limb rehabilitation of stroke survivors. A participant's movements are tracked by motion capture technology and evaluated by computational means. The resulting data are used to generate interactive media-based feedback that communicates to the participant detailed, intuitive evaluations of his performance. This article describes how the AMRR system's interactive feedback is designed to address specific movement challenges faced by stroke survivors. Multimedia examples are provided to illustrate each feedback component. Supportive data are provided for three participants of varying impairment levels to demonstrate the system's ability to train both targeted and integrated aspects of movement. The AMRR system supports training of multiple movement aspects together or in isolation, within adaptable sequences, through cohesive feedback that is based on formalized compositional design principles. From preliminary analysis of the data, we infer that the system's ability to train multiple foci together or in isolation in adaptable sequences, utilizing appropriately designed feedback, can lead to functional improvement. The evaluation and feedback frameworks established within the AMRR system will be applied to the development of a novel home-based system to provide an engaging yet low-cost extension of training for longer periods of time.

Exploring the bases for a mixed reality stroke rehabilitation system, Part II: Design of Interactive Feedback for upper limb rehabilitation

PubMed Central

2011-01-01

Background Few existing interactive rehabilitation systems can effectively communicate multiple aspects of movement performance simultaneously, in a manner that appropriately adapts across various training scenarios. In order to address the need for such systems within stroke rehabilitation training, a unified approach for designing interactive systems for upper limb rehabilitation of stroke survivors has been developed and applied for the implementation of an Adaptive Mixed Reality Rehabilitation (AMRR) System. Results The AMRR system provides computational evaluation and multimedia feedback for the upper limb rehabilitation of stroke survivors. A participant's movements are tracked by motion capture technology and evaluated by computational means. The resulting data are used to generate interactive media-based feedback that communicates to the participant detailed, intuitive evaluations of his performance. This article describes how the AMRR system's interactive feedback is designed to address specific movement challenges faced by stroke survivors. Multimedia examples are provided to illustrate each feedback component. Supportive data are provided for three participants of varying impairment levels to demonstrate the system's ability to train both targeted and integrated aspects of movement. Conclusions The AMRR system supports training of multiple movement aspects together or in isolation, within adaptable sequences, through cohesive feedback that is based on formalized compositional design principles. From preliminary analysis of the data, we infer that the system's ability to train multiple foci together or in isolation in adaptable sequences, utilizing appropriately designed feedback, can lead to functional improvement. The evaluation and feedback frameworks established within the AMRR system will be applied to the development of a novel home-based system to provide an engaging yet low-cost extension of training for longer periods of time. PMID:21899779

Collective Cellular Decision-Making Gives Developmental Plasticity: A Model of Signaling in Branching Roots

NASA Astrophysics Data System (ADS)

McCleery, W. Tyler; Mohd-Radzman, Nadiatul A.; Grieneisen, Veronica A.

Cells within tissues can be regarded as autonomous entities that respond to their local environment and signaling from neighbors. Cell coordination is particularly important in plants, where root architecture must strategically invest resources for growth to optimize nutrient acquisition. Thus, root cells are constantly adapting to environmental cues and neighbor communication in a non-linear manner. To explain such plasticity, we view the root as a swarm of coupled multi-cellular structures, ''metamers'', rather than as a continuum of identical cells. These metamers are individually programmed to achieve a local objective - developing a lateral root primordia, which aids in local foraging of nutrients. Collectively, such individual attempts may be halted, structuring root architecture as an emergent behavior. Each metamer's decision to branch is coordinated locally and globally through hormone signaling, including processes of controlled diffusion, active polar transport, and dynamic feedback. We present a physical model of the signaling mechanism that coordinates branching decisions in response to the environment. This work was funded by the European Commission 7th Framework Program, Project No. 601062, SWARM-ORGAN.

INITIATE: An Intelligent Adaptive Alert Environment.

PubMed

Jafarpour, Borna; Abidi, Samina Raza; Ahmad, Ahmad Marwan; Abidi, Syed Sibte Raza

2015-01-01

Exposure to a large volume of alerts generated by medical Alert Generating Systems (AGS) such as drug-drug interaction softwares or clinical decision support systems over-whelms users and causes alert fatigue in them. Some of alert fatigue effects are ignoring crucial alerts and longer response times. A common approach to avoid alert fatigue is to devise mechanisms in AGS to stop them from generating alerts that are deemed irrelevant. In this paper, we present a novel framework called INITIATE: an INtellIgent adapTIve AlerT Environment to avoid alert fatigue by managing alerts generated by one or more AGS. We have identified and categories the lifecycle of different alerts and have developed alert management logic as per the alerts' lifecycle. Our framework incorporates an ontology that represents the alert management strategy and an alert management engine that executes this strategy. Our alert management framework offers the following features: (1) Adaptability based on users' feedback; (2) Personalization and aggregation of messages; and (3) Connection to Electronic Medical Records by implementing a HL7 Clinical Document Architecture parser.

Using mobile health technology to deliver decision support for self-monitoring after lung transplantation.

PubMed

Jiang, Yun; Sereika, Susan M; DeVito Dabbs, Annette; Handler, Steven M; Schlenk, Elizabeth A

2016-10-01

Lung transplant recipients (LTR) experience problems recognizing and reporting critical condition changes during their daily health self-monitoring. Pocket PATH(®), a mobile health application, was designed to provide automatic feedback messages to LTR to guide decisions for detecting and reporting critical values of health indicators. To examine the degree to which LTR followed decision support messages to report recorded critical values, and to explore predictors of appropriately following technology decision support by reporting critical values during the first year after transplantation. A cross-sectional correlational study was conducted to analyze existing data from 96 LTR who used the Pocket PATH for daily health self-monitoring. When a critical value is entered, the device automatically generated a feedback message to guide LTR about when and what to report to their transplant coordinators. Their socio-demographics and clinical characteristics were obtained before discharge. Their use of Pocket PATH for health self-monitoring during 12 months was categorized as low (≤25% of days), moderate (>25% to ≤75% of days), and high (>75% of days) use. Following technology decision support was defined by the total number of critical feedback messages appropriately handled divided by the total number of critical feedback messages generated. This variable was dichotomized by whether or not all (100%) feedback messages were appropriately followed. Binary logistic regression was used to explore predictors of appropriately following decision support. Of the 96 participants, 53 had at least 1 critical feedback message generated during 12 months. Of these 53 participants, the average message response rate was 90% and 33 (62%) followed 100% decision support. LTR who moderately used Pocket PATH (n=23) were less likely to follow technology decision support than the high (odds ratio [OR]=0.11, p=0.02) and low (OR=0.04, p=0.02) use groups. The odds of following decision support were reduced in LTR whose income met basic needs (OR=0.01, p=0.01) or who had longer hospital stays (OR=0.94, p=0.004). A significant interaction was found between gender and past technology experience (OR=0.21, p=0.03), suggesting that with increased past technology experience, the odds of following decision support to report all critical values decreased in men but increased in women. The majority of LTR responded appropriately to mobile technology-based decision support for reporting recorded critical values. Appropriately following technology decision support was associated with gender, income, experience with technology, length of hospital stay, and frequency of use of technology for self-monitoring. Clinicians should monitor LTR, who are at risk for poor reporting of recorded critical values, more vigilantly even when LTR are provided with mobile technology decision support. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Reward and punishment enhance motor adaptation in stroke.

PubMed

Quattrocchi, Graziella; Greenwood, Richard; Rothwell, John C; Galea, Joseph M; Bestmann, Sven

2017-09-01

The effects of motor learning, such as motor adaptation, in stroke rehabilitation are often transient, thus mandating approaches that enhance the amount of learning and retention. Previously, we showed in young individuals that reward and punishment feedback have dissociable effects on motor adaptation, with punishment improving adaptation and reward enhancing retention. If these findings were able to generalise to patients with stroke, they would provide a way to optimise motor learning in these patients. Therefore, we tested this in 45 patients with chronic stroke allocated in three groups. Patients performed reaching movements with their paretic arm with a robotic manipulandum. After training (day 1), day 2 involved adaptation to a novel force field. During the adaptation phase, patients received performance-based feedback according to the group they were allocated: reward, punishment or no feedback (neutral). On day 3, patients readapted to the force field but all groups now received neutral feedback. All patients adapted, with reward and punishment groups displaying greater adaptation and readaptation than the neutral group, irrespective of demographic, cognitive or functional differences. Remarkably, the reward and punishment groups adapted to similar degree as healthy controls. Finally, the reward group showed greater retention. This study provides, for the first time, evidence that reward and punishment can enhance motor adaptation in patients with stroke. Further research on reinforcement-based motor learning regimes is warranted to translate these promising results into clinical practice and improve motor rehabilitation outcomes in patients with stroke. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

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

PubMed

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

2010-01-01

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

A qualitative assessment of cross-cultural adaptation of intermediate measures for schizophrenia in multisite international studies.

PubMed

Gonzalez, Jodi M; Rubin, Maureen; Fredrick, Megan M; Velligan, Dawn I

2013-04-30

In this substudy of the Measurement and Treatment Research to Improve Cognition in Schizophrenia we examined qualitative feedback on the cross-cultural adaptability of four intermediate measures of functional outcome (Independent Living Scales, UCSD Performance-Based Skills Assessment, Test of Adaptive Behavior in Schizophrenia, and Cognitive Assessment Interview). Feedback was provided by experienced English-fluent clinical researchers at 31 sites in eight countries familiar with medication trials. Researchers provided feedback on test subscales and items which were rated as having adaptation challenges. They noted the specific concern and made suggestions for adaptation to their culture. We analyzed the qualitative data using a modified Grounded Theory approach guided by the International Testing Commission Guidelines model for test adaptation. For each measure except the Cognitive Assessment Interview (CAI), the majority of subscales were reported to require major adaptations in terms of content and concepts contained in the subscale. In particular, social, financial, transportation and health care systems varied widely across countries-systems which are often used to assess performance capacity in the U.S. We provide suggestions for how to address future international test development and adaptation. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Neural responses to feedback information produced by self-generated or other-generated decision-making and their impairment in schizophrenia.

PubMed

Toyomaki, Atsuhito; Hashimoto, Naoki; Kako, Yuki; Murohashi, Harumitsu; Kusumi, Ichiro

2017-01-01

Several studies of self-monitoring dysfunction in schizophrenia have focused on the sense of agency to motor action using behavioral and psychophysiological techniques. So far, no study has ever tried to investigate whether the sense of agency or causal attribution for external events produced by self-generated decision-making is abnormal in schizophrenia. The purpose of this study was to investigate neural responses to feedback information produced by self-generated or other-generated decision-making in a multiplayer gambling task using even-related potentials and electroencephalogram synchronization. We found that the late positive component and theta/alpha synchronization were increased in response to feedback information in the self-decision condition in normal controls, but that these responses were significantly decreased in patients with schizophrenia. These neural activities thus reflect the self-reference effect that affects the cognitive appraisal of external events following decision-making and their impairment in schizophrenia.

Monitoring in the context of structured decision-making and adaptive management

USGS Publications Warehouse

Lyons, J.E.; Runge, M.C.; Laskowski, H.P.; Kendall, W.L.

2008-01-01

In a natural resource management setting, monitoring is a crucial component of an informed process for making decisions, and monitoring design should be driven by the decision context and associated uncertainties. Monitoring itself can play >3 roles. First, it is important for state-dependent decision-making, as when managers need to know the system state before deciding on the appropriate course of action during the ensuing management cycle. Second, monitoring is critical for evaluating the effectiveness of management actions relative to objectives. Third, in an adaptive management setting, monitoring provides the feedback loop for learning about the system; learning is sought not for its own sake but primarily to better achieve management objectives. In this case, monitoring should be designed to reduce the critical uncertainties in models of the managed system. The United States Geological Survey and United States Fish and Wildlife Service are conducting a large-scale management experiment on 23 National Wildlife Refuges across the Northeast and Midwest Regions. The primary management objective is to provide habitat for migratory waterbirds, particularly during migration, using water-level manipulations in managed wetlands. Key uncertainties are related to the potential trade-offs created by management for a specific waterbird guild (e.g., migratory shorebirds) and the response of waterbirds, plant communities, and invertebrates to specific experimental hydroperiods. We reviewed the monitoring program associated with this study, and the ways that specific observations fill >1 of the roles identified above. We used observations from our monitoring to improve state-dependent decisions to control undesired plants, to evaluate management performance relative to shallow-water habitat objectives, and to evaluate potential trade-offs between waterfowl and shorebird habitat management. With limited staff and budgets, management agencies need efficient monitoring programs that are used for decision-making, not comprehensive studies that elucidate all manner of ecological relationships.

A low cost, adaptive mixed reality system for home-based stroke rehabilitation.

PubMed

Chen, Yinpeng; Baran, Michael; Sundaram, Hari; Rikakis, Thanassis

2011-01-01

This paper presents a novel, low-cost, real-time adaptive multimedia environment for home-based upper extremity rehabilitation of stroke survivors. The primary goal of this system is to provide an interactive tool with which the stroke survivor can sustain gains achieved within the clinical phase of therapy and increase the opportunity for functional recovery. This home-based mediated system has low cost sensing, off the shelf components for the auditory and visual feedback, and remote monitoring capability. The system is designed to continue active learning by reducing dependency on real-time feedback and focusing on summary feedback after a single task and sequences of tasks. To increase system effectiveness through customization, we use data from the training strategy developed by the therapist at the clinic for each stroke survivor to drive automated system adaptation at the home. The adaptation includes changing training focus, selecting proper feedback coupling both in real-time and in summary, and constructing appropriate dialogues with the stroke survivor to promote more efficient use of the system. This system also allows the therapist to review participant's progress and adjust the training strategy weekly.

Cytopathology whole slide images and virtual microscopy adaptive tutorials: A software pilot

PubMed Central

Van Es, Simone L.; Pryor, Wendy M.; Belinson, Zack; Salisbury, Elizabeth L.; Velan, Gary M.

2015-01-01

Background: The constant growth in the body of knowledge in medicine requires pathologists and pathology trainees to engage in continuing education. Providing them with equitable access to efficient and effective forms of education in pathology (especially in remote and rural settings) is important, but challenging. Methods: We developed three pilot cytopathology virtual microscopy adaptive tutorials (VMATs) to explore a novel adaptive E-learning platform (AeLP) which can incorporate whole slide images for pathology education. We collected user feedback to further develop this educational material and to subsequently deploy randomized trials in both pathology specialist trainee and also medical student cohorts. Cytopathology whole slide images were first acquired then novel VMATs teaching cytopathology were created using the AeLP, an intelligent tutoring system developed by Smart Sparrow. The pilot was run for Australian pathologists and trainees through the education section of Royal College of Pathologists of Australasia website over a period of 9 months. Feedback on the usability, impact on learning and any technical issues was obtained using 5-point Likert scale items and open-ended feedback in online questionnaires. Results: A total of 181 pathologists and pathology trainees anonymously attempted the three adaptive tutorials, a smaller proportion of whom went on to provide feedback at the end of each tutorial. VMATs were perceived as effective and efficient E-learning tools for pathology education. User feedback was positive. There were no significant technical issues. Conclusion: During this pilot, the user feedback on the educational content and interface and the lack of technical issues were helpful. Large scale trials of similar online cytopathology adaptive tutorials were planned for the future. PMID:26605119

Integrated Flight/Structural Mode Control for Very Flexible Aircraft Using L1 Adaptive Output Feedback Controller

NASA Technical Reports Server (NTRS)

Che, Jiaxing; Cao, Chengyu; Gregory, Irene M.

2012-01-01

This paper explores application of adaptive control architecture to a light, high-aspect ratio, flexible aircraft configuration that exhibits strong rigid body/flexible mode coupling. Specifically, an L(sub 1) adaptive output feedback controller is developed for a semi-span wind tunnel model capable of motion. The wind tunnel mount allows the semi-span model to translate vertically and pitch at the wing root, resulting in better simulation of an aircraft s rigid body motion. The control objective is to design a pitch control with altitude hold while suppressing body freedom flutter. The controller is an output feedback nominal controller (LQG) augmented by an L(sub 1) adaptive loop. A modification to the L(sub 1) output feedback is proposed to make it more suitable for flexible structures. The new control law relaxes the required bounds on the unmatched uncertainty and allows dependence on the state as well as time, i.e. a more general unmatched nonlinearity. The paper presents controller development and simulated performance responses. Simulation is conducted by using full state flexible wing models derived from test data at 10 different dynamic pressure conditions. An L(sub 1) adaptive output feedback controller is designed for a single test point and is then applied to all the test cases. The simulation results show that the L(sub 1) augmented controller can stabilize and meet the performance requirements for all 10 test conditions ranging from 30 psf to 130 psf dynamic pressure.

Results of adaptive feedforward on GTA

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

Ziomek, C.D.; Denney, P.M.; Regan, A.H.

1993-01-01

This paper presents the results of the adaptive feedforward system in use on the Ground Test Accelerator (GTA). The adaptive feedforward system was shown to correct repetitive, high-frequency errors in the amplitude and phase of the RF field of the pulsed accelerator. The adaptive feedforward system was designed as an augmentation to the RF field feedback control system and was able to extend the closed-loop bandwidth and disturbance rejection by a factor of ten. Within a second implementation, the adaptive feedforward hardware was implemented in place of the feedback control system and was shown to negate both beam transients andmore » phase droop in the klystron amplifier.« less

Results of adaptive feedforward on GTA

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

Ziomek, C.D.; Denney, P.M.; Regan, A.H.

1993-06-01

This paper presents the results of the adaptive feedforward system in use on the Ground Test Accelerator (GTA). The adaptive feedforward system was shown to correct repetitive, high-frequency errors in the amplitude and phase of the RF field of the pulsed accelerator. The adaptive feedforward system was designed as an augmentation to the RF field feedback control system and was able to extend the closed-loop bandwidth and disturbance rejection by a factor of ten. Within a second implementation, the adaptive feedforward hardware was implemented in place of the feedback control system and was shown to negate both beam transients andmore » phase droop in the klystron amplifier.« less

Integration of auditory and somatosensory error signals in the neural control of speech movements.

PubMed

Feng, Yongqiang; Gracco, Vincent L; Max, Ludo

2011-08-01

We investigated auditory and somatosensory feedback contributions to the neural control of speech. In task I, sensorimotor adaptation was studied by perturbing one of these sensory modalities or both modalities simultaneously. The first formant (F1) frequency in the auditory feedback was shifted up by a real-time processor and/or the extent of jaw opening was increased or decreased with a force field applied by a robotic device. All eight subjects lowered F1 to compensate for the up-shifted F1 in the feedback signal regardless of whether or not the jaw was perturbed. Adaptive changes in subjects' acoustic output resulted from adjustments in articulatory movements of the jaw or tongue. Adaptation in jaw opening extent in response to the mechanical perturbation occurred only when no auditory feedback perturbation was applied or when the direction of adaptation to the force was compatible with the direction of adaptation to a simultaneous acoustic perturbation. In tasks II and III, subjects' auditory and somatosensory precision and accuracy were estimated. Correlation analyses showed that the relationships 1) between F1 adaptation extent and auditory acuity for F1 and 2) between jaw position adaptation extent and somatosensory acuity for jaw position were weak and statistically not significant. Taken together, the combined findings from this work suggest that, in speech production, sensorimotor adaptation updates the underlying control mechanisms in such a way that the planning of vowel-related articulatory movements takes into account a complex integration of error signals from previous trials but likely with a dominant role for the auditory modality.

Quality in Higher Education: The Need for Feedback from Students

ERIC Educational Resources Information Center

Okogbaa, Veronica

2016-01-01

Students in higher institutions are part and parcel of the system, thus their opinions should count in decision making concerning the quality of the education they are receiving. This study set out to examine from literature the place of feedback from students and its possible relevance in decision making on quality issues in higher education.…

Parental Rearing Behavior Prospectively Predicts Adolescents' Risky Decision-Making and Feedback-Related Electrical Brain Activity

ERIC Educational Resources Information Center

Euser, Anja S.; Evans, Brittany E.; Greaves-Lord, Kirstin; Huizink, Anja C.; Franken, Ingmar H. A.

2013-01-01

The present study examined the role of parental rearing behavior in adolescents' risky decision-making and the brain's feedback processing mechanisms. Healthy adolescent participants ("n" = 110) completed the EMBU-C, a self-report questionnaire on perceived parental rearing behaviors between 2006 and 2008 (T1). Subsequently, after an…

A Feedback Learning and Mental Models Perspective on Strategic Decision Making

ERIC Educational Resources Information Center

Capelo, Carlos; Dias, Joao Ferreira

2009-01-01

This study aims to be a contribution to a theoretical model that explains the effectiveness of the learning and decision-making processes by means of a feedback and mental models perspective. With appropriate mental models, managers should be able to improve their capacity to deal with dynamically complex contexts, in order to achieve long-term…

Chaotic Feedback Loops within Decision Making Groups: Towards an Integration of Chaos Theory and Cybernetics.

ERIC Educational Resources Information Center

Keaten, James A.

This paper offers a model that integrates chaos theory and cybernetics, which can be used to describe the structure of decision making within small groups. The paper begins with an overview of cybernetics and chaos. Definitional characteristics of cybernetics are reviewed along with salient constructs, such as goal-seeking, feedback, feedback…

Adaptive Neural Networks Decentralized FTC Design for Nonstrict-Feedback Nonlinear Interconnected Large-Scale Systems Against Actuator Faults.

PubMed

Li, Yongming; Tong, Shaocheng

The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small neighborhood of zero. Finally, numerical results of practical examples are presented to further demonstrate the effectiveness of the proposed control strategy.The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small neighborhood of zero. Finally, numerical results of practical examples are presented to further demonstrate the effectiveness of the proposed control strategy.

Minority game with arbitrary cutoffs

NASA Astrophysics Data System (ADS)

Johnson, N. F.; Hui, P. M.; Zheng, Dafang; Tai, C. W.

1999-07-01

We study a model of a competing population of N adaptive agents, with similar capabilities, repeatedly deciding whether to attend a bar with an arbitrary cutoff L. Decisions are based upon past outcomes. The agents are only told whether the actual attendance is above or below L. For L∼ N/2, the game reproduces the main features of Challet and Zhang's minority game. As L is lowered, however, the mean attendances in different runs tend to divide into two groups. The corresponding standard deviations for these two groups are very different. This grouping effect results from the dynamical feedback governing the game's time-evolution, and is not reproduced if the agents are fed a random history.

Calibration of visually guided reaching is driven by error-corrective learning and internal dynamics.

PubMed

Cheng, Sen; Sabes, Philip N

2007-04-01

The sensorimotor calibration of visually guided reaching changes on a trial-to-trial basis in response to random shifts in the visual feedback of the hand. We show that a simple linear dynamical system is sufficient to model the dynamics of this adaptive process. In this model, an internal variable represents the current state of sensorimotor calibration. Changes in this state are driven by error feedback signals, which consist of the visually perceived reach error, the artificial shift in visual feedback, or both. Subjects correct for > or =20% of the error observed on each movement, despite being unaware of the visual shift. The state of adaptation is also driven by internal dynamics, consisting of a decay back to a baseline state and a "state noise" process. State noise includes any source of variability that directly affects the state of adaptation, such as variability in sensory feedback processing, the computations that drive learning, or the maintenance of the state. This noise is accumulated in the state across trials, creating temporal correlations in the sequence of reach errors. These correlations allow us to distinguish state noise from sensorimotor performance noise, which arises independently on each trial from random fluctuations in the sensorimotor pathway. We show that these two noise sources contribute comparably to the overall magnitude of movement variability. Finally, the dynamics of adaptation measured with random feedback shifts generalizes to the case of constant feedback shifts, allowing for a direct comparison of our results with more traditional blocked-exposure experiments.

Rapid humanitarian assessments and rationality: a value-of-information study from Iraq, 2003-04.

PubMed

Benini, Aldo; Conley, Charles

2007-03-01

Rapid assessments are one of the standard informational tools in humanitarian response and are supposed to contribute to rational decision-making.(1) The extent to which the assessment organisation itself behaves rationally, however, is an open question. This can be evaluated against multiple criteria, such as the cost and value of the information it collects and its ability to adapt flexibly design or samples when the survey environment changes unforeseeably. An unusual data constellation from two concurrent recent (2003-04) rapid assessments in northern Iraq permits us to model part of the actual assessment behaviour in terms of geographical, community and prior substantive information attributes. The model correctly predicts the decisions, in 79 per cent of the 2,425 local communities in focus, that data collector teams in the Emergency Mine Action Survey made to visit or not to visit. The analysis demonstrates variably rational behaviour under conditions of insecurity, repeated regrouping and incomplete sampling frames. A pronounced bias towards very small rural settlements is irrational for the overall results, but may be a rational strategy of individual survey workers seeking to prolong their employment. Implications for future assessments are sketched in the areas of tools for urban surveys, greater adaptability, including early feedback from users, and sensibility to value-of-information concepts.

Bayesian versus politically motivated reasoning in human perception of climate anomalies

NASA Astrophysics Data System (ADS)

Ripberger, Joseph T.; Jenkins-Smith, Hank C.; Silva, Carol L.; Carlson, Deven E.; Gupta, Kuhika; Carlson, Nina; Dunlap, Riley E.

2017-11-01

In complex systems where humans and nature interact to produce joint outcomes, mitigation, adaptation, and resilience require that humans perceive feedback—signals of health and distress—from natural systems. In many instances, humans readily perceive feedback. In others, feedback is more difficult to perceive, so humans rely on experts, heuristics, biases, and/or identify confirming rationalities that may distort perceptions of feedback. This study explores human perception of feedback from natural systems by testing alternate conceptions about how individuals perceive climate anomalies, a form of feedback from the climate system. Results indicate that individuals generally perceive climate anomalies, especially when the anomalies are relatively extreme and persistent. Moreover, this finding is largely robust to political differences that generate predictable but small biases in feedback perception at extreme ends of the partisan spectrum. The subtlety of these biases bodes well for mitigation, adaptation, and resilience as human systems continue to interact with a changing climate 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.

Adaptive integral robust control and application to electromechanical servo systems.

PubMed

Deng, Wenxiang; Yao, Jianyong

2017-03-01

This paper proposes a continuous adaptive integral robust control with robust integral of the sign of the error (RISE) feedback for a class of uncertain nonlinear systems, in which the RISE feedback gain is adapted online to ensure the robustness against disturbances without the prior bound knowledge of the additive disturbances. In addition, an adaptive compensation integrated with the proposed adaptive RISE feedback term is also constructed to further reduce design conservatism when the system also exists parametric uncertainties. Lyapunov analysis reveals the proposed controllers could guarantee the tracking errors are asymptotically converging to zero with continuous control efforts. To illustrate the high performance nature of the developed controllers, numerical simulations are provided. At the end, an application case of an actual electromechanical servo system driven by motor is also studied, with some specific design consideration, and comparative experimental results are obtained to verify the effectiveness of the proposed controllers. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Observer-Based Adaptive Fault-Tolerant Tracking Control of Nonlinear Nonstrict-Feedback Systems.

PubMed

Wu, Chengwei; Liu, Jianxing; Xiong, Yongyang; Wu, Ligang

2017-06-28

This paper studies an output-based adaptive fault-tolerant control problem for nonlinear systems with nonstrict-feedback form. Neural networks are utilized to identify the unknown nonlinear characteristics in the system. An observer and a general fault model are constructed to estimate the unavailable states and describe the fault, respectively. Adaptive parameters are constructed to overcome the difficulties in the design process for nonstrict-feedback systems. Meanwhile, dynamic surface control technique is introduced to avoid the problem of ''explosion of complexity''. Furthermore, based on adaptive backstepping control method, an output-based adaptive neural tracking control strategy is developed for the considered system against actuator fault, which can ensure that all the signals in the resulting closed-loop system are bounded, and the system output signal can be regulated to follow the response of the given reference signal with a small error. Finally, the simulation results are provided to validate the effectiveness of the control strategy proposed in this paper.

Model-Based Adaptive Event-Triggered Control of Strict-Feedback Nonlinear Systems.

PubMed

Li, Yuan-Xin; Yang, Guang-Hong

2018-04-01

This paper is concerned with the adaptive event-triggered control problem of nonlinear continuous-time systems in strict-feedback form. By using the event-sampled neural network (NN) to approximate the unknown nonlinear function, an adaptive model and an associated event-triggered controller are designed by exploiting the backstepping method. In the proposed method, the feedback signals and the NN weights are aperiodically updated only when the event-triggered condition is violated. A positive lower bound on the minimum intersample time is guaranteed to avoid accumulation point. The closed-loop stability of the resulting nonlinear impulsive dynamical system is rigorously proved via Lyapunov analysis under an adaptive event sampling condition. In comparing with the traditional adaptive backstepping design with a fixed sample period, the event-triggered method samples the state and updates the NN weights only when it is necessary. Therefore, the number of transmissions can be significantly reduced. Finally, two simulation examples are presented to show the effectiveness of the proposed control method.

CSI feedback-based CS for underwater acoustic adaptive modulation OFDM system with channel prediction

NASA Astrophysics Data System (ADS)

Kuai, Xiao-yan; Sun, Hai-xin; Qi, Jie; Cheng, En; Xu, Xiao-ka; Guo, Yu-hui; Chen, You-gan

2014-06-01

In this paper, we investigate the performance of adaptive modulation (AM) orthogonal frequency division multiplexing (OFDM) system in underwater acoustic (UWA) communications. The aim is to solve the problem of large feedback overhead for channel state information (CSI) in every subcarrier. A novel CSI feedback scheme is proposed based on the theory of compressed sensing (CS). We propose a feedback from the receiver that only feedback the sparse channel parameters. Additionally, prediction of the channel state is proposed every several symbols to realize the AM in practice. We describe a linear channel prediction algorithm which is used in adaptive transmission. This system has been tested in the real underwater acoustic channel. The linear channel prediction makes the AM transmission techniques more feasible for acoustic channel communications. The simulation and experiment show that significant improvements can be obtained both in bit error rate (BER) and throughput in the AM scheme compared with the fixed Quadrature Phase Shift Keying (QPSK) modulation scheme. Moreover, the performance with standard CS outperforms the Discrete Cosine Transform (DCT) method.

Decoupling feedforward and feedback structures in hybrid active noise control systems for uncorrelated narrowband disturbances

NASA Astrophysics Data System (ADS)

Wu, Lifu; Qiu, Xiaojun; Burnett, Ian S.; Guo, Yecai

2015-08-01

Hybrid feedforward and feedback structures are useful for active noise control (ANC) applications where the noise can only be partially obtained with reference sensors. The traditional method uses the secondary signals of both the feedforward and feedback structures to synthesize a reference signal for the feedback structure in the hybrid structure. However, this approach introduces coupling between the feedforward and feedback structures and parameter changes in one structure affect the other during adaptation such that the feedforward and feedback structures must be optimized simultaneously in practical ANC system design. Two methods are investigated in this paper to remove such coupling effects. One is a simplified method, which uses the error signal directly as the reference signal in the feedback structure, and the second method generates the reference signal for the feedback structure by using only the secondary signal from the feedback structure and utilizes the generated reference signal as the error signal of the feedforward structure. Because the two decoupling methods can optimize the feedforward and feedback structures separately, they provide more flexibility in the design and optimization of the adaptive filters in practical ANC applications.

Walking Speed Influences the Effects of Implicit Visual Feedback Distortion on Modulation of Gait Symmetry

PubMed Central

Maestas, Gabrielle; Hu, Jiyao; Trevino, Jessica; Chunduru, Pranathi; Kim, Seung-Jae; Lee, Hyunglae

2018-01-01

The use of visual feedback in gait rehabilitation has been suggested to promote recovery of locomotor function by incorporating interactive visual components. Our prior work demonstrated that visual feedback distortion of changes in step length symmetry entails an implicit or unconscious adaptive process in the subjects’ spatial gait patterns. We investigated whether the effect of the implicit visual feedback distortion would persist at three different walking speeds (slow, self-preferred and fast speeds) and how different walking speeds would affect the amount of adaption. In the visual feedback distortion paradigm, visual vertical bars portraying subjects’ step lengths were distorted so that subjects perceived their step lengths to be asymmetric during testing. Measuring the adjustments in step length during the experiment showed that healthy subjects made spontaneous modulations away from actual symmetry in response to the implicit visual distortion, no matter the walking speed. In all walking scenarios, the effects of implicit distortion became more significant at higher distortion levels. In addition, the amount of adaptation induced by the visual distortion was significantly greater during walking at preferred or slow speed than at the fast speed. These findings indicate that although a link exists between supraspinal function through visual system and human locomotion, sensory feedback control for locomotion is speed-dependent. Ultimately, our results support the concept that implicit visual feedback can act as a dominant form of feedback in gait modulation, regardless of speed. PMID:29632481

Improved methods in neural network-based adaptive output feedback control, with applications to flight control

NASA Astrophysics Data System (ADS)

Kim, Nakwan

Utilizing the universal approximation property of neural networks, we develop several novel approaches to neural network-based adaptive output feedback control of nonlinear systems, and illustrate these approaches for several flight control applications. In particular, we address the problem of non-affine systems and eliminate the fixed point assumption present in earlier work. All of the stability proofs are carried out in a form that eliminates an algebraic loop in the neural network implementation. An approximate input/output feedback linearizing controller is augmented with a neural network using input/output sequences of the uncertain system. These approaches permit adaptation to both parametric uncertainty and unmodeled dynamics. All physical systems also have control position and rate limits, which may either deteriorate performance or cause instability for a sufficiently high control bandwidth. Here we apply a method for protecting an adaptive process from the effects of input saturation and time delays, known as "pseudo control hedging". This method was originally developed for the state feedback case, and we provide a stability analysis that extends its domain of applicability to the case of output feedback. The approach is illustrated by the design of a pitch-attitude flight control system for a linearized model of an R-50 experimental helicopter, and by the design of a pitch-rate control system for a 58-state model of a flexible aircraft consisting of rigid body dynamics coupled with actuator and flexible modes. A new approach to augmentation of an existing linear controller is introduced. It is especially useful when there is limited information concerning the plant model, and the existing controller. The approach is applied to the design of an adaptive autopilot for a guided munition. Design of a neural network adaptive control that ensures asymptotically stable tracking performance is also addressed.

Speed versus accuracy in decision-making ants: expediting politics and policy implementation.

PubMed

Franks, Nigel R; Dechaume-Moncharmont, François-Xavier; Hanmore, Emma; Reynolds, Jocelyn K

2009-03-27

Compromises between speed and accuracy are seemingly inevitable in decision-making when accuracy depends on time-consuming information gathering. In collective decision-making, such compromises are especially likely because information is shared to determine corporate policy. This political process will also take time. Speed-accuracy trade-offs occur among house-hunting rock ants, Temnothorax albipennis. A key aspect of their decision-making is quorum sensing in a potential new nest. Finding a sufficient number of nest-mates, i.e. a quorum threshold (QT), in a potential nest site indicates that many ants find it suitable. Quorum sensing collates information. However, the QT is also used as a switch, from recruitment of nest-mates to their new home by slow tandem running, to recruitment by carrying, which is three times faster. Although tandem running is slow, it effectively enables one successful ant to lead and teach another the route between the nests. Tandem running creates positive feedback; more and more ants are shown the way, as tandem followers become, in turn, tandem leaders. The resulting corps of trained ants can then quickly carry their nest-mates; but carried ants do not learn the route. Therefore, the QT seems to set both the amount of information gathered and the speed of the emigration. Low QTs might cause more errors and a slower emigration--the worst possible outcome. This possible paradox of quick decisions leading to slow implementation might be resolved if the ants could deploy another positive-feedback recruitment process when they have used a low QT. Reverse tandem runs occur after carrying has begun and lead ants back from the new nest to the old one. Here we show experimentally that reverse tandem runs can bring lost scouts into an active role in emigrations and can help to maintain high-speed emigrations. Thus, in rock ants, although quick decision-making and rapid implementation of choices are initially in opposition, a third recruitment method can restore rapid implementation after a snap decision. This work reveals a principle of widespread importance: the dynamics of collective decision-making (i.e. the politics) and the dynamics of policy implementation are sometimes intertwined, and only by analysing the mechanisms of both can we understand certain forms of adaptive organization.

Coastal Resilience and Adaptation:Working Together to go from Information to Action on Alaska's Coasts

NASA Astrophysics Data System (ADS)

Holman, A.; Poe, A.; Murphy, K.; Littell, J. S.; Pletnikoff, K.; Holen, D.

2016-12-01

The phrases "coastal resilience" and "climate adaptation" appear everywhere now—but how do they meet the needs of communities and natural resource managers on Alaska's coast? A regional consortium of The Aleutian Pribilof Islands Association, four of Alaska's Landscape Conservation Cooperatives (LCCs), NOAA, University of Alaska Fairbanks and the Alaska Climate Science Center joined numerous local partners including several Tribes and Alaska Native Organizations to host workshops in five regions to find out.The project brought together audiences from Tribal and local government, State and Federal agencies, scientists and local experts to share the state of existing knowledge on current and anticipated environmental changes and impacts and discuss potential response actions. Targeting information and tools needed for decision making and resource management, the hundreds of workshop participants identified gaps in available data, information and knowledge that needs to be filled to help communities and managers better respond to climate change. Each of the workshops built upon the other and connected stakeholders and increase resiliency by bringing local decision makers together with the researchers who can fill their needs, consolidating and leveraging research being done in the region by many different parties (western and traditional) and ensuring those results get to those who need them, and creating an adaptive, collaborative process of identifying needs, conducting work, gathering the latest science from local to national sources, presenting results for evaluation and feedback, and using that information to drive future research and management investments. The resulting "toolbox" will help management agencies and others to better understand the dynamic changes Alaska is experiencing, their impacts on communities and habitats, as well as tools and information that can help managers and community leaders work better together to adapt to climate change.

A Charge-Based Low-Power High-SNR Capacitive Sensing Interface Circuit

PubMed Central

Peng, Sheng-Yu; Qureshi, Muhammad S.; Hasler, Paul E.; Basu, Arindam; Degertekin, F. L.

2008-01-01

This paper describes a low-power approach to capacitive sensing that achieves a high signal-to-noise ratio. The circuit is composed of a capacitive feedback charge amplifier and a charge adaptation circuit. Without the adaptation circuit, the charge amplifier only consumes 1 μW to achieve the audio band SNR of 69.34dB. An adaptation scheme using Fowler-Nordheim tunneling and channel hot electron injection mechanisms to stabilize the DC output voltage is demonstrated. This scheme provides a very low frequency pole at 0.2Hz. The measured noise spectrums show that this slow-time scale adaptation does not degrade the circuit performance. The DC path can also be provided by a large feedback resistance without causing extra power consumption. A charge amplifier with a MOS-bipolar pseudo-resistor feedback scheme is interfaced with a capacitive micromachined ultrasonic transducer to demonstrate the feasibility of this approach for ultrasound applications. PMID:18787650

A Bayesian Account of Vocal Adaptation to Pitch-Shifted Auditory Feedback

PubMed Central

Hahnloser, Richard H. R.

2017-01-01

Motor systems are highly adaptive. Both birds and humans compensate for synthetically induced shifts in the pitch (fundamental frequency) of auditory feedback stemming from their vocalizations. Pitch-shift compensation is partial in the sense that large shifts lead to smaller relative compensatory adjustments of vocal pitch than small shifts. Also, compensation is larger in subjects with high motor variability. To formulate a mechanistic description of these findings, we adapt a Bayesian model of error relevance. We assume that vocal-auditory feedback loops in the brain cope optimally with known sensory and motor variability. Based on measurements of motor variability, optimal compensatory responses in our model provide accurate fits to published experimental data. Optimal compensation correctly predicts sensory acuity, which has been estimated in psychophysical experiments as just-noticeable pitch differences. Our model extends the utility of Bayesian approaches to adaptive vocal behaviors. PMID:28135267

Adaptive Output-Feedback Neural Control of Switched Uncertain Nonlinear Systems With Average Dwell Time.

PubMed

Long, Lijun; Zhao, Jun

2015-07-01

This paper investigates the problem of adaptive neural tracking control via output-feedback for a class of switched uncertain nonlinear systems without the measurements of the system states. The unknown control signals are approximated directly by neural networks. A novel adaptive neural control technique for the problem studied is set up by exploiting the average dwell time method and backstepping. A switched filter and different update laws are designed to reduce the conservativeness caused by adoption of a common observer and a common update law for all subsystems. The proposed controllers of subsystems guarantee that all closed-loop signals remain bounded under a class of switching signals with average dwell time, while the output tracking error converges to a small neighborhood of the origin. As an application of the proposed design method, adaptive output feedback neural tracking controllers for a mass-spring-damper system are constructed.

Observed-Based Adaptive Fuzzy Tracking Control for Switched Nonlinear Systems With Dead-Zone.

PubMed

Tong, Shaocheng; Sui, Shuai; Li, Yongming

2015-12-01

In this paper, the problem of adaptive fuzzy output-feedback control is investigated for a class of uncertain switched nonlinear systems in strict-feedback form. The considered switched systems contain unknown nonlinearities, dead-zone, and immeasurable states. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, a switched fuzzy state observer is designed and thus the immeasurable states are obtained by it. By applying the adaptive backstepping design principle and the average dwell time method, an adaptive fuzzy output-feedback tracking control approach is developed. It is proved that the proposed control approach can guarantee that all the variables in the closed-loop system are bounded under a class of switching signals with average dwell time, and also that the system output can track a given reference signal as closely as possible. The simulation results are given to check the effectiveness of the proposed approach.

Adaptive Fuzzy Tracking Control for a Class of MIMO Nonlinear Systems in Nonstrict-Feedback Form.

PubMed

Chen, Bing; Lin, Chong; Liu, Xiaoping; Liu, Kefu

2015-12-01

This paper focuses on the problem of fuzzy adaptive control for a class of multiinput and multioutput (MIMO) nonlinear systems in nonstrict-feedback form, which contains the strict-feedback form as a special case. By the condition of variable partition, a new fuzzy adaptive backstepping is proposed for such a class of nonlinear MIMO systems. The suggested fuzzy adaptive controller guarantees that the proposed control scheme can guarantee that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking errors eventually converge to a small neighborhood around the origin. The main advantage of this paper is that a control approach is systematically derived for nonlinear systems with strong interconnected terms which are the functions of all states of the whole system. Simulation results further illustrate the effectiveness of the suggested approach.

Adaptive Fuzzy Output Feedback Control for Switched Nonlinear Systems With Unmodeled Dynamics.

PubMed

Tong, Shaocheng; Li, Yongming

2017-02-01

This paper investigates a robust adaptive fuzzy control stabilization problem for a class of uncertain nonlinear systems with arbitrary switching signals that use an observer-based output feedback scheme. The considered switched nonlinear systems possess the unstructured uncertainties, unmodeled dynamics, and without requiring the states being available for measurement. A state observer which is independent of switching signals is designed to solve the problem of unmeasured states. Fuzzy logic systems are used to identify unknown lumped nonlinear functions so that the problem of unstructured uncertainties can be solved. By combining adaptive backstepping design principle and small-gain approach, a novel robust adaptive fuzzy output feedback stabilization control approach is developed. The stability of the closed-loop system is proved via the common Lyapunov function theory and small-gain theorem. Finally, the simulation results are given to demonstrate the validity and performance of the proposed control strategy.

Adaptive output-feedback control for switched stochastic uncertain nonlinear systems with time-varying delay.

PubMed

Song, Zhibao; Zhai, Junyong

2018-04-01

This paper addresses the problem of adaptive output-feedback control for a class of switched stochastic time-delay nonlinear systems with uncertain output function, where both the control coefficients and time-varying delay are unknown. The drift and diffusion terms are subject to unknown homogeneous growth condition. By virtue of adding a power integrator technique, an adaptive output-feedback controller is designed to render that the closed-loop system is bounded in probability, and the state of switched stochastic nonlinear system can be globally regulated to the origin almost surely. A numerical example is provided to demonstrate the validity of the proposed control method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Contextual cuing contributes to the independent modification of multiple internal models for vocal control

PubMed Central

Keough, Dwayne

2011-01-01

Research on the control of visually guided limb movements indicates that the brain learns and continuously updates an internal model that maps the relationship between motor commands and sensory feedback. A growing body of work suggests that an internal model that relates motor commands to sensory feedback also supports vocal control. There is evidence from arm-reaching studies that shows that when provided with a contextual cue, the motor system can acquire multiple internal models, which allows an animal to adapt to different perturbations in diverse contexts. In this study we show that trained singers can rapidly acquire multiple internal models regarding voice fundamental frequency (F0). These models accommodate different perturbations to ongoing auditory feedback. Participants heard three musical notes and reproduced each one in succession. The musical targets could serve as a contextual cue to indicate which direction (up or down) feedback would be altered on each trial; however, participants were not explicitly instructed to use this strategy. When participants were gradually exposed to altered feedback adaptation was observed immediately following vocal onset. Aftereffects were target specific and did not influence vocal productions on subsequent trials. When target notes were no longer a contextual cue, adaptation occurred during altered feedback trials and evidence for trial-by-trial adaptation was found. These findings indicate that the brain is exceptionally sensitive to the deviations between auditory feedback and the predicted consequence of a motor command during vocalization. Moreover, these results indicate that, with contextual cues, the vocal control system may maintain multiple internal models that are capable of independent modification during different tasks or environments. PMID:21346208

Fast sensory–motor reactions in echolocating bats to sudden changes during the final buzz and prey intercept

PubMed Central

Geberl, Cornelia; Brinkløv, Signe; Wiegrebe, Lutz; Surlykke, Annemarie

2015-01-01

Echolocation is an active sense enabling bats and toothed whales to orient in darkness through echo returns from their ultrasonic signals. Immediately before prey capture, both bats and whales emit a buzz with such high emission rates (≥180 Hz) and overall duration so short that its functional significance remains an enigma. To investigate sensory–motor control during the buzz of the insectivorous bat Myotis daubentonii, we removed prey, suspended in air or on water, before expected capture. The bats responded by shortening their echolocation buzz gradually; the earlier prey was removed down to approximately 100 ms (30 cm) before expected capture, after which the full buzz sequence was emitted both in air and over water. Bats trawling over water also performed the full capture behavior, but in-air capture motions were aborted, even at very late prey removals (<20 ms = 6 cm before expected contact). Thus, neither the buzz nor capture movements are stereotypical, but dynamically adapted based on sensory feedback. The results indicate that echolocation is controlled mainly by acoustic feedback, whereas capture movements are adjusted according to both acoustic and somatosensory feedback, suggesting separate (but coordinated) central motor control of the two behaviors based on multimodal input. Bat echolocation, especially the terminal buzz, provides a unique window to extremely fast decision processes in response to sensory feedback and modulation through attention in a naturally behaving animal. PMID:25775538

Observations to support adaptation: Principles, scales and decision-making

NASA Astrophysics Data System (ADS)

Pulwarty, R. S.

2012-12-01

As has been long noted, a comprehensive, coordinated observing system is the backbone of any Earth information system. Demands are increasingly placed on earth observation and prediction systems and attendant services to address the needs of economically and environmentally vulnerable sectors and investments, including energy, water, human health, transportation, agriculture, fisheries, tourism, biodiversity, and national security. Climate services include building capacity to interpret information and recognize standards and limitations of data in the promotion of social and economic development in a changing climate. This includes improving the understanding of climate in the context of a variety of temporal and spatial scales (including the influence of decadal scale forcings and land surface feedbacks on seasonal forecast reliability). Climate data and information are central for developing decision options that are sensitive to climate-related uncertainties and the design of flexible adaptation pathways. Ideally monitoring should be action oriented to support climate risk assessment and adaptation including informing robust decision making to multiple risks over the long term. Based on the experience of global observations programs and empirical research we outline- Challenges in developing effective monitoring and climate information systems to support adaptation. The types of observations of critical importance needed for sector planning to enhance food, water and energy security, and to improve early warning for disaster risk reduction Observations needed for ecosystem-based adaptation including the identification of thresholds, maintenance of biological diversity and land degradation The benefits and limits of linking regional model output to local observations including analogs and verification for adaptation planning To support these goals a robust systems of integrated observations are needed to characterize the uncertainty surrounding emergent risks including overcoming unrealistically precise information demands. While monitoring systems design and operation should be guided by the standards and requirements of management, those who provide information to the system (e.g. hydromet services) should also derive benefits. Drawing on identified information needs to support climate risk management (in drought, water resources and other areas) we outline principles of effective monitoring and develop preliminary strategic guidance for information systems being developed through the GEO, GCOS and Global and national frameworks for climate services. The efficacy of such services are improved by a problem-solving orientation, participatory planning, extension management and improvements in the use and value of existing data to legitimize new investments.

Engaging Students with Feedback through Adaptive Release

ERIC Educational Resources Information Center

Irwin, Brian; Hepplestone, Stuart; Holden, Graham; Parkin, Helen J.; Thorpe, Louise

2013-01-01

Feedback to students has been highlighted in the literature as an area where improvements are needed. Students need high quality, prompt feedback, but they also need guidance and tools to help them engage with and learn from that feedback. This case study explores staff and student perceptions of a tool at Sheffield Hallam University which…

Contributions to workload of rotational optical transformations

NASA Technical Reports Server (NTRS)

Atkinson, R. P.; Harrington, T. L.

1985-01-01

An investigation of visuomotor adaptation to optical rotation and optical inversion was conducted. Experiment 1 examined the visuomotor adaptability of subjects to an optically rotating visual world with a univariate repeated measures design. Experiment 1A tested one major prediction of a model of adaptation put forth by Welch who predicted that the aversive drive state that triggers adaptation would be habituated to fairly rapidly. Experiment 2 was conducted to investigate the role of motor activity in adaptation to optical rotation. Specifically, this experiment contrasted the reafference hypothesis and the proprioceptive change hypothesis. Experiment 3 examined the role of cognition, error-corrective feedback, and proprioceptive and/or reafferent feedback in visuomotor adaptation to optical inversion. Implications for research and implications for practice were suggested for all experiments.

Anti-windup adaptive PID control design for a class of uncertain chaotic systems with input saturation.

PubMed

Tahoun, A H

2017-01-01

In this paper, the stabilization problem of actuators saturation in uncertain chaotic systems is investigated via an adaptive PID control method. The PID control parameters are auto-tuned adaptively via adaptive control laws. A multi-level augmented error is designed to account for the extra terms appearing due to the use of PID and saturation. The proposed control technique uses both the state-feedback and the output-feedback methodologies. Based on Lyapunov׳s stability theory, new anti-windup adaptive controllers are proposed. Demonstrative examples with MATLAB simulations are studied. The simulation results show the efficiency of the proposed adaptive PID controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Designing an Alternative Teaching Approach (Feedback Lecture) through the Use of Guided Decision-Making.

ERIC Educational Resources Information Center

Osterman, Dean

This chapter explains how the Guided Design method of teaching can be used to solve problems, and how this method was used in the development of a new method of teaching. Called the Feedback Lecture, this method is illustrated through an example, and research data on its effectiveness is presented. The Guided Decision-Making Process is also…

Semantic richness effects in lexical decision: The role of feedback.

PubMed

Yap, Melvin J; Lim, Gail Y; Pexman, Penny M

2015-11-01

Across lexical processing tasks, it is well established that words with richer semantic representations are recognized faster. This suggests that the lexical system has access to meaning before a word is fully identified, and is consistent with a theoretical framework based on interactive and cascaded processing. Specifically, semantic richness effects are argued to be produced by feedback from semantic representations to lower-level representations. The present study explores the extent to which richness effects are mediated by feedback from lexical- to letter-level representations. In two lexical decision experiments, we examined the joint effects of stimulus quality and four semantic richness dimensions (imageability, number of features, semantic neighborhood density, semantic diversity). With the exception of semantic diversity, robust additive effects of stimulus quality and richness were observed for the targeted dimensions. Our results suggest that semantic feedback does not typically reach earlier levels of representation in lexical decision, and further reinforces the idea that task context modulates the processing dynamics of early word recognition processes.

Impaired Feedforward Control and Enhanced Feedback Control of Speech in Patients with Cerebellar Degeneration

PubMed Central

Agnew, Zarinah; Nagarajan, Srikantan; Houde, John; Ivry, Richard B.

2017-01-01

The cerebellum has been hypothesized to form a crucial part of the speech motor control network. Evidence for this comes from patients with cerebellar damage, who exhibit a variety of speech deficits, as well as imaging studies showing cerebellar activation during speech production in healthy individuals. To date, the precise role of the cerebellum in speech motor control remains unclear, as it has been implicated in both anticipatory (feedforward) and reactive (feedback) control. Here, we assess both anticipatory and reactive aspects of speech motor control, comparing the performance of patients with cerebellar degeneration and matched controls. Experiment 1 tested feedforward control by examining speech adaptation across trials in response to a consistent perturbation of auditory feedback. Experiment 2 tested feedback control, examining online corrections in response to inconsistent perturbations of auditory feedback. Both male and female patients and controls were tested. The patients were impaired in adapting their feedforward control system relative to controls, exhibiting an attenuated anticipatory response to the perturbation. In contrast, the patients produced even larger compensatory responses than controls, suggesting an increased reliance on sensory feedback to guide speech articulation in this population. Together, these results suggest that the cerebellum is crucial for maintaining accurate feedforward control of speech, but relatively uninvolved in feedback control. SIGNIFICANCE STATEMENT Speech motor control is a complex activity that is thought to rely on both predictive, feedforward control as well as reactive, feedback control. While the cerebellum has been shown to be part of the speech motor control network, its functional contribution to feedback and feedforward control remains controversial. Here, we use real-time auditory perturbations of speech to show that patients with cerebellar degeneration are impaired in adapting feedforward control of speech but retain the ability to make online feedback corrections; indeed, the patients show an increased sensitivity to feedback. These results indicate that the cerebellum forms a crucial part of the feedforward control system for speech but is not essential for online, feedback control. PMID:28842410

Animal personality and state-behaviour feedbacks: a review and guide for empiricists.

PubMed

Sih, Andrew; Mathot, Kimberley J; Moirón, María; Montiglio, Pierre-Olivier; Wolf, Max; Dingemanse, Niels J

2015-01-01

An exciting area in behavioural ecology focuses on understanding why animals exhibit consistent among-individual differences in behaviour (animal personalities). Animal personality has been proposed to emerge as an adaptation to individual differences in state variables, leading to the question of why individuals differ consistently in state. Recent theory emphasizes the role that positive feedbacks between state and behaviour can play in producing consistent among-individual covariance between state and behaviour, hence state-dependent personality. We review the role of feedbacks in recent models of adaptive personalities, and provide guidelines for empirical testing of model assumptions and predictions. We discuss the importance of the mediating effects of ecology on these feedbacks, and provide a roadmap for including state-behaviour feedbacks in behavioural ecology research. Copyright © 2014 Elsevier Ltd. All rights reserved.

To what extent can behaviour change techniques be identified within an adaptable implementation package for primary care? A prospective directed content analysis.

PubMed

Glidewell, Liz; Willis, Thomas A; Petty, Duncan; Lawton, Rebecca; McEachan, Rosemary R C; Ingleson, Emma; Heudtlass, Peter; Davies, Andrew; Jamieson, Tony; Hunter, Cheryl; Hartley, Suzanne; Gray-Burrows, Kara; Clamp, Susan; Carder, Paul; Alderson, Sarah; Farrin, Amanda J; Foy, Robbie

2018-02-17

Interpreting evaluations of complex interventions can be difficult without sufficient description of key intervention content. We aimed to develop an implementation package for primary care which could be delivered using typically available resources and could be adapted to target determinants of behaviour for each of four quality indicators: diabetes control, blood pressure control, anticoagulation for atrial fibrillation and risky prescribing. We describe the development and prospective verification of behaviour change techniques (BCTs) embedded within the adaptable implementation packages. We used an over-lapping multi-staged process. We identified evidence-based, candidate delivery mechanisms-mainly audit and feedback, educational outreach and computerised prompts and reminders. We drew upon interviews with primary care professionals using the Theoretical Domains Framework to explore likely determinants of adherence to quality indicators. We linked determinants to candidate BCTs. With input from stakeholder panels, we prioritised likely determinants and intervention content prior to piloting the implementation packages. Our content analysis assessed the extent to which embedded BCTs could be identified within the packages and compared them across the delivery mechanisms and four quality indicators. Each implementation package included at least 27 out of 30 potentially applicable BCTs representing 15 of 16 BCT categories. Whilst 23 BCTs were shared across all four implementation packages (e.g. BCTs relating to feedback and comparing behaviour), some BCTs were unique to certain delivery mechanisms (e.g. 'graded tasks' and 'problem solving' for educational outreach). BCTs addressing the determinants 'environmental context' and 'social and professional roles' (e.g. 'restructuring the social and 'physical environment' and 'adding objects to the environment') were indicator specific. We found it challenging to operationalise BCTs targeting 'environmental context', 'social influences' and 'social and professional roles' within our chosen delivery mechanisms. We have demonstrated a transparent process for selecting, operationalising and verifying the BCT content in implementation packages adapted to target four quality indicators in primary care. There was considerable overlap in BCTs identified across the four indicators suggesting core BCTs can be embedded and verified within delivery mechanisms commonly available to primary care. Whilst feedback reports can include a wide range of BCTs, computerised prompts can deliver BCTs at the time of decision making, and educational outreach can allow for flexibility and individual tailoring in delivery.

Neural signatures of economic parameters during decision-making: a functional MRI (FMRI), electroencephalography (EEG) and autonomic monitoring study.

PubMed

Minati, Ludovico; Grisoli, Marina; Franceschetti, Silvana; Epifani, Francesca; Granvillano, Alice; Medford, Nick; Harrison, Neil A; Piacentini, Sylvie; Critchley, Hugo D

2012-01-01

Adaptive behaviour requires an ability to obtain rewards by choosing between different risky options. Financial gambles can be used to study effective decision-making experimentally, and to distinguish processes involved in choice option evaluation from outcome feedback and other contextual factors. Here, we used a paradigm where participants evaluated 'mixed' gambles, each presenting a potential gain and a potential loss and an associated variable outcome probability. We recorded neural responses using autonomic monitoring, electroencephalography (EEG) and functional neuroimaging (fMRI), and used a univariate, parametric design to test for correlations with the eleven economic parameters that varied across gambles, including expected value (EV) and amount magnitude. Consistent with behavioural economic theory, participants were risk-averse. Gamble evaluation generated detectable autonomic responses, but only weak correlations with outcome uncertainty were found, suggesting that peripheral autonomic feedback does not play a major role in this task. Long-latency stimulus-evoked EEG potentials were sensitive to expected gain and expected value, while alpha-band power reflected expected loss and amount magnitude, suggesting parallel representations of distinct economic qualities in cortical activation and central arousal. Neural correlates of expected value representation were localized using fMRI to ventromedial prefrontal cortex, while the processing of other economic parameters was associated with distinct patterns across lateral prefrontal, cingulate, insula and occipital cortices including default-mode network and early visual areas. These multimodal data provide complementary evidence for distributed substrates of choice evaluation across multiple, predominantly cortical, brain systems wherein distinct regions are preferentially attuned to specific economic features. Our findings extend biologically-plausible models of risky decision-making while providing potential biomarkers of economic representations that can be applied to the study of deficits in motivational behaviour in neurological and psychiatric patients.

Eye-Hand Coordination during Visuomotor Adaptation with Different Rotation Angles: Effects of Terminal Visual Feedback

PubMed Central

Rand, Miya K.; Rentsch, Sebastian

2016-01-01

This study examined adaptive changes of eye-hand coordination during a visuomotor rotation task under the use of terminal visual feedback. Young adults made reaching movements to targets on a digitizer while looking at targets on a monitor where the rotated feedback (a cursor) of hand movements appeared after each movement. Three rotation angles (30°, 75° and 150°) were examined in three groups in order to vary the task difficulty. The results showed that the 30° group gradually reduced direction errors of reaching with practice and adapted well to the visuomotor rotation. The 75° group made large direction errors of reaching, and the 150° group applied a 180° reversal shift from early practice. The 75°and 150° groups, however, overcompensated the respective rotations at the end of practice. Despite these group differences in adaptive changes of reaching, all groups gradually adapted gaze directions prior to reaching from the target area to the areas related to the final positions of reaching during the course of practice. The adaptive changes of both hand and eye movements in all groups mainly reflected adjustments of movement directions based on explicit knowledge of the applied rotation acquired through practice. Only the 30° group showed small implicit adaptation in both effectors. The results suggest that by adapting gaze directions from the target to the final position of reaching based on explicit knowledge of the visuomotor rotation, the oculomotor system supports the limb-motor system to make precise preplanned adjustments of reaching directions during learning of visuomotor rotation under terminal visual feedback. PMID:27812093

Feedback-related potentials in a gambling task with randomised reward.

PubMed

Mushtaq, Faisal; Guillen, Pablo Puente; Wilkie, Richard M; Mon-Williams, Mark A; Schaefer, Alexandre

2016-03-01

Event-related potentials (ERPs) time-locked to decision outcomes are reported. Participants engaged in a gambling task (see [1] for details) in which they decided between a risky and a safe option (presented as different coloured shapes) on each trial (416 in total). Each decision was associated with (fully randomised) feedback about the reward outcome (Win/Loss) and its magnitude (varying as a function of decision response; 5-9 points for Risky decisions and 1-4 points for Safe decisions). Here, we show data demonstrating: (a) the influence of Win feedback in the preceding outcome (Outcome t-1) on activity related to the current outcome (Outcome t ); (b) difference wave analysis for outcome expectancy- separating Expected Outcomes (consecutive Loss trials subtracted from consecutive reward) from Unexpected Outcomes (subtracting Loss t-1Win t trials from Win t-1Loss t trials); (c) difference waves separating Switch and Stay responses for Outcome Expectancy; (d) the effect of magnitude induced by decisions (Risk t vs. Safe t ) on Outcome Expectancy; and finally, (e) expectations reflected by response switch direction (Risk to Safe responses vs. Safe to Risk t ) on the FRN at Outcome t .

Simulating closed- and open-loop voluntary movement: a nonlinear control-systems approach.

PubMed

Davidson, Paul R; Jones, Richard D; Andreae, John H; Sirisena, Harsha R

2002-11-01

In many recent human motor control models, including feedback-error learning and adaptive model theory (AMT), feedback control is used to correct errors while an inverse model is simultaneously tuned to provide accurate feedforward control. This popular and appealing hypothesis, based on a combination of psychophysical observations and engineering considerations, predicts that once the tuning of the inverse model is complete the role of feedback control is limited to the correction of disturbances. This hypothesis was tested by looking at the open-loop behavior of the human motor system during adaptation. An experiment was carried out involving 20 normal adult subjects who learned a novel visuomotor relationship on a pursuit tracking task with a steering wheel for input. During learning, the response cursor was periodically blanked, removing all feedback about the external system (i.e., about the relationship between hand motion and response cursor motion). Open-loop behavior was not consistent with a progressive transfer from closed- to open-loop control. Our recently developed computational model of the brain--a novel nonlinear implementation of AMT--was able to reproduce the observed closed- and open-loop results. In contrast, other control-systems models exhibited only minimal feedback control following adaptation, leading to incorrect open-loop behavior. This is because our model continues to use feedback to control slow movements after adaptation is complete. This behavior enhances the internal stability of the inverse model. In summary, our computational model is currently the only motor control model able to accurately simulate the closed- and open-loop characteristics of the experimental response trajectories.

Self Adapted Testing as Formative Assessment: Effects of Feedback and Scoring on Engagement and Performance

ERIC Educational Resources Information Center

Arieli-Attali, Meirav

2016-01-01

This dissertation investigated the feasibility of self-adapted testing (SAT) as a formative assessment tool with the focus on learning. Under two different orientation goals--to excel on a test (performance goal) or to learn from the test (learning goal)--I examined the effect of different scoring rules provided as interactive feedback, on test…

Who Do You Think I Am? Modeling Individual Differences for More Adaptive and Effective Instruction

ERIC Educational Resources Information Center

Allen, Laura K.

2015-01-01

The purpose of intelligent tutoring systems is to provide students with personalized instruction and feedback. The focus of these systems typically rests in the adaptability of the feedback provided to students, which relies on automated assessments of performance in the system. A large focus of my previous work has been to determine how natural…

Agent-based modeling in ecological economics.

PubMed

Heckbert, Scott; Baynes, Tim; Reeson, Andrew

2010-01-01

Interconnected social and environmental systems are the domain of ecological economics, and models can be used to explore feedbacks and adaptations inherent in these systems. Agent-based modeling (ABM) represents autonomous entities, each with dynamic behavior and heterogeneous characteristics. Agents interact with each other and their environment, resulting in emergent outcomes at the macroscale that can be used to quantitatively analyze complex systems. ABM is contributing to research questions in ecological economics in the areas of natural resource management and land-use change, urban systems modeling, market dynamics, changes in consumer attitudes, innovation, and diffusion of technology and management practices, commons dilemmas and self-governance, and psychological aspects to human decision making and behavior change. Frontiers for ABM research in ecological economics involve advancing the empirical calibration and validation of models through mixed methods, including surveys, interviews, participatory modeling, and, notably, experimental economics to test specific decision-making hypotheses. Linking ABM with other modeling techniques at the level of emergent properties will further advance efforts to understand dynamics of social-environmental systems.

Prefrontal Neural Activity When Feedback Is Not Relevant to Adjust Performance

PubMed Central

Özyurt, Jale; Rietze, Mareike; Thiel, Christiane M.

2012-01-01

It has been shown that the rostral cingulate zone (RCZ) in humans uses both positive and negative feedback to evaluate performance and to flexibly adjust behaviour. Less is known on how the feedback types are processed by the RCZ and other prefrontal brain areas, when feedback can only be used to evaluate performance, but cannot be used to adjust behaviour. The present fMRI study aimed at investigating feedback that can only be used to evaluate performance in a word-learning paradigm. One group of volunteers (N = 17) received informative, performance-dependent positive or negative feedback after each trial. Since new words had to be learnt in each trial, the feedback could not be used for task-specific adaptations. The other group (N = 17) always received non-informative feedback, providing neither information about performance nor about possible task-specific adaptations. Effects of the informational value of feedback were assessed between-subjects, comparing trials with positive and negative informative feedback to non-informative feedback. Effects of feedback valence were assessed by comparing neural activity to positive and negative feedback within the informative-feedback group. Our results show that several prefrontal regions, including the pre-SMA, the inferior frontal cortex and the insula were sensitive to both, the informational value and the valence aspect of the feedback with stronger activations to informative as compared to non-informative feedback and to informative negative compared to informative positive feedback. The only exception was RCZ which was sensitive to the informational value of the feedback, but not to feedback valence. The findings indicate that outcome information per se is sufficient to activate prefrontal brain regions, with the RCZ being the only prefrontal brain region which is equally sensitive to positive and negative feedback. PMID:22615774

Independent voluntary correction and savings in locomotor learning.

PubMed

Leech, Kristan A; Roemmich, Ryan T

2018-06-14

People can acquire new walking patterns in many different ways. For example, we can change our gait voluntarily in response to instruction or adapt by sensing our movement errors. Here we investigated how acquisition of a new walking pattern through simultaneous voluntary correction and adaptive learning affected the resulting motor memory of the learned pattern. We studied adaptation to split-belt treadmill walking with and without visual feedback of stepping patterns. As expected, visual feedback enabled faster acquisition of the new walking pattern. However, upon later re-exposure to the same split-belt perturbation, participants exhibited similar motor memories whether they had learned with or without visual feedback. Participants who received feedback did not re-engage the mechanism used to accelerate initial acquisition of the new walking pattern to similarly accelerate subsequent relearning. These findings reveal that voluntary correction neither benefits nor interferes with the ability to save a new walking pattern over time. © 2018. Published by The Company of Biologists Ltd.

Adaptive disengagement buffers self-esteem from negative social feedback.

PubMed

Leitner, Jordan B; Hehman, Eric; Deegan, Matthew P; Jones, James M

2014-11-01

The degree to which self-esteem hinges on feedback in a domain is known as a contingency of self-worth, or engagement. Although previous research has conceptualized engagement as stable, it would be advantageous for individuals to dynamically regulate engagement. The current research examined whether the tendency to disengage from negative feedback accounts for variability in self-esteem. We created the Adaptive Disengagement Scale (ADS) to capture individual differences in the tendency to disengage self-esteem from negative outcomes. Results demonstrated that the ADS is reliable and valid (Studies 1 and 2). Furthermore, in response to negative social feedback, higher scores on the ADS predicted greater state self-esteem (Study 3), and this relationship was mediated by disengagement (Study 4). These findings demonstrate that adaptive disengagement protects self-esteem from negative outcomes and that the ADS is a valid measure of individual differences in the implementation of this process. © 2014 by the Society for Personality and Social Psychology, Inc.

Development of an evidence-based decision pathway for vestibular schwannoma treatment options.

PubMed

Linkov, Faina; Valappil, Benita; McAfee, Jacob; Goughnour, Sharon L; Hildrew, Douglas M; McCall, Andrew A; Linkov, Igor; Hirsch, Barry; Snyderman, Carl

To integrate multiple sources of clinical information with patient feedback to build evidence-based decision support model to facilitate treatment selection for patients suffering from vestibular schwannomas (VS). This was a mixed methods study utilizing focus group and survey methodology to solicit feedback on factors important for making treatment decisions among patients. Two 90-minute focus groups were conducted by an experienced facilitator. Previously diagnosed VS patients were recruited by clinical investigators at the University of Pittsburgh Medical Center (UPMC). Classical content analysis was used for focus group data analysis. Providers were recruited from practices within the UPMC system and were surveyed using Delphi methods. This information can provide a basis for multi-criteria decision analysis (MCDA) framework to develop a treatment decision support system for patients with VS. Eight themes were derived from these data (focus group + surveys): doctor/health care system, side effects, effectiveness of treatment, anxiety, mortality, family/other people, quality of life, and post-operative symptoms. These data, as well as feedback from physicians were utilized in building a multi-criteria decision model. The study illustrated steps involved in the development of a decision support model that integrates evidence-based data and patient values to select treatment alternatives. Studies focusing on the actual development of the decision support technology for this group of patients are needed, as decisions are highly multifactorial. Such tools have the potential to improve decision making for complex medical problems with alternate treatment pathways. Copyright © 2016 Elsevier Inc. All rights reserved.

Improving Human Resources for Health means Retaining Health-Workers: Application of the WHO-Recommendations for the Retention of Health-Workers in Rural Northern-Nigeria.

PubMed

Afenyadu, Godwin Y; Adegoke, Adetoro A; Findley, Sally

2017-01-01

Nigeria is one of 57 countries with critical shortage of health workers (HWs). Strategies to increase and equitably distribute HWs are critical to the achievement of Health Millennium/Sustainable Development Goals. We describe how three Northern Nigeria states adapted World Health Organisation (WHO)-recommended incentives to attract, recruit, and retain midwives. Secondary analysis of data from two surveys assessing midwife motivation, retention, and attrition in Northern Nigeria; and expert consultations. Midwives highlighted financial and non-financial incentives as key factors in their decisions to renew their contracts. Their perspectives informed the consensus positions of health managers, policymakers and heads of institutions, and led to the adaptation of the WHO recommendations into appropriate state-specific incentive packages. The feedback from midwives combined with an expert consultation approach allowed stakeholders to consider and use available evidence to select appropriate incentive packages that offer the greatest potential for helping to address inadequate numbers of rural midwives.

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.

Division of labor by dual feedback regulators controls JAK2/STAT5 signaling over broad ligand range.

PubMed

Bachmann, Julie; Raue, Andreas; Schilling, Marcel; Böhm, Martin E; Kreutz, Clemens; Kaschek, Daniel; Busch, Hauke; Gretz, Norbert; Lehmann, Wolf D; Timmer, Jens; Klingmüller, Ursula

2011-07-19

Cellular signal transduction is governed by multiple feedback mechanisms to elicit robust cellular decisions. The specific contributions of individual feedback regulators, however, remain unclear. Based on extensive time-resolved data sets in primary erythroid progenitor cells, we established a dynamic pathway model to dissect the roles of the two transcriptional negative feedback regulators of the suppressor of cytokine signaling (SOCS) family, CIS and SOCS3, in JAK2/STAT5 signaling. Facilitated by the model, we calculated the STAT5 response for experimentally unobservable Epo concentrations and provide a quantitative link between cell survival and the integrated response of STAT5 in the nucleus. Model predictions show that the two feedbacks CIS and SOCS3 are most effective at different ligand concentration ranges due to their distinct inhibitory mechanisms. This divided function of dual feedback regulation enables control of STAT5 responses for Epo concentrations that can vary 1000-fold in vivo. Our modeling approach reveals dose-dependent feedback control as key property to regulate STAT5-mediated survival decisions over a broad range of ligand concentrations.

Toward an Expanded Definition of Adaptive Decision Making.

ERIC Educational Resources Information Center

Phillips, Susan D.

1997-01-01

Uses the lifespan, life-space model to examine the definition of adaptive decision making. Reviews the existing definition of adaptive decision making as "rational" decision making and offers alternate perspectives on decision making with an emphasis on the implications of using the model. Makes suggestions for future theory, research,…

An Extension to the Constructivist Coding Hypothesis as a Learning Model for Selective Feedback when the Base Rate Is High

ERIC Educational Resources Information Center

Ghaffarzadegan, Navid; Stewart, Thomas R.

2011-01-01

Elwin, Juslin, Olsson, and Enkvist (2007) and Henriksson, Elwin, and Juslin (2010) offered the constructivist coding hypothesis to describe how people code the outcomes of their decisions when availability of feedback is conditional on the decision. They provided empirical evidence only for the 0.5 base rate condition. This commentary argues that…

Employing a teen advisory board to adapt an evidence-based HIV/STD intervention for incarcerated African-American adolescent women.

PubMed

Latham, Teaniese P; Sales, Jessica M; Renfro, Tiffaney L; Boyce, Lorin S; Rose, Eve; Murray, Colleen C; Wingood, Gina M; DiClemente, Ralph J

2012-10-01

This manuscript assesses priorities and challenges of adolescent females by conducting a meeting with teen advisory board (TAB) members to collect information regarding their lives and experiences pre-, during and post-incarceration in a juvenile detention facility. Multiple themes emerged regarding the impact of incarceration on young African-American females, including experiencing a loss of personal liberties, the importance of making money upon release, unfaithfulness by partners on the 'outside', substance use and lack of control over their environment upon release, including parents, peers and male sexual partners. Based on feedback from TAB members, unique barriers and challenges were identified that suggested areas where adaptations to an evidenced-based HIV/sexually transmitted disease (STD) intervention would be justified to more adequately meet the needs of this particular subgroup of young African-American women. Adaptations to the evidence-based interventions included enhancing activities related to goal setting, emotion regulation skills, decision-making, recognizing and utilizing support networks and addressing the relationship between substance use and risky sexual behavior. Future health education efforts focusing on either the creation of new HIV/STD interventions or adaptations to existing interventions should consider utilizing advisory boards with members of the priority population at the earliest stages of intervention planning.

Information-theoretic approach to interactive learning

NASA Astrophysics Data System (ADS)

Still, S.

2009-01-01

The principles of statistical mechanics and information theory play an important role in learning and have inspired both theory and the design of numerous machine learning algorithms. The new aspect in this paper is a focus on integrating feedback from the learner. A quantitative approach to interactive learning and adaptive behavior is proposed, integrating model- and decision-making into one theoretical framework. This paper follows simple principles by requiring that the observer's world model and action policy should result in maximal predictive power at minimal complexity. Classes of optimal action policies and of optimal models are derived from an objective function that reflects this trade-off between prediction and complexity. The resulting optimal models then summarize, at different levels of abstraction, the process's causal organization in the presence of the learner's actions. A fundamental consequence of the proposed principle is that the learner's optimal action policies balance exploration and control as an emerging property. Interestingly, the explorative component is present in the absence of policy randomness, i.e. in the optimal deterministic behavior. This is a direct result of requiring maximal predictive power in the presence of feedback.

The Effects of Social Context and Acute Stress on Decision Making Under Uncertainty.

PubMed

FeldmanHall, Oriel; Raio, Candace M; Kubota, Jennifer T; Seiler, Morgan G; Phelps, Elizabeth A

2015-12-01

Uncertainty preferences are typically studied in neutral, nonsocial contexts. This approach, however, fails to capture the dynamic factors that influence choices under uncertainty in the real world. Our goal was twofold: to test whether uncertainty valuation is similar across social and nonsocial contexts, and to investigate the effects of acute stress on uncertainty preferences. Subjects completed matched gambling and trust games following either a control or a stress manipulation. Those who were not under stress exhibited no differences between the amount of money gambled and the amount of money entrusted to partners. In comparison, stressed subjects gambled more money but entrusted less money to partners. We further found that irrespective of stress, subjects were highly attuned to irrelevant feedback in the nonsocial, gambling context, believing that every loss led to a greater chance of winning (the gamblers' fallacy). However, when deciding to trust a stranger, control subjects behaved rationally, treating each new interaction as independent. Stress compromised this adaptive behavior, increasing sensitivity to irrelevant social feedback. © The Author(s) 2015.

Adaptation of handwriting size under distorted visual feedback in patients with Parkinson's disease and elderly and young controls

PubMed Central

Teulings, H; Contreras-Vidal, J; Stelmach, G; Adler, C

2002-01-01

Objective: The ability to use visual feedback to control handwriting size was compared in patients with Parkinson's disease (PD), elderly people, and young adults to better understand factors playing a part in parkinsonian micrographia. Methods: The participants wrote sequences of eight cursive l loops with visual target sizes of 0.5 and 2 cm on a flat panel display digitiser which both recorded and displayed the pen movements. In the pre-exposure and postexposure conditions, the display digitiser showed the actual pen trace in real time and real size. In the distortion exposure conditions, the gain of the vertical dimension of the visual feedback was either reduced to 70% or enlarged to 140%. Results: The young controls showed a gradual visuomotor adaptation that compensated for the visual feedback distortions during the exposure conditions. They also showed significant after effects during the postexposure conditions. The elderly controls marginally corrected for the size distortions and showed small after effects. The patients with PD, however, showed no trial by trial adaptations or after effects but instead, a progressive amplification of the distortion effect in each individual trial. Conclusion: The young controls used visual feedback to update their visuomotor map. The elderly controls seemed to make little use of visual feedback. The patients with Parkinson's disease rely on the visual feedback of previous or of ongoing strokes to programme subsequent strokes. This recursive feedback may play a part in the progressive reductions in handwriting size found in parkinsonian micrographia. PMID:11861687

Linking biogeomorphic feedbacks from ecosystem engineer to landscape scale: a panarchy approach

NASA Astrophysics Data System (ADS)

Eichel, Jana

2017-04-01

Scale is a fundamental concept in both ecology and geomorphology. Therefore, scale-based approaches are a valuable tool to bridge the disciplines and improve the understanding of feedbacks between geomorphic processes, landforms, material and organisms and ecological processes in biogeomorphology. Yet, linkages between biogeomorphic feedbacks on different scales, e.g. between ecosystem engineering and landscape scale patterns and dynamics, are not well understood. A panarchy approach sensu Holling et al. (2002) can help to close this research gap and explain how structure and function are created in biogeomorphic ecosystems. Based on results from previous biogeomorphic research in Turtmann glacier foreland (Switzerland; Eichel, 2017; Eichel et al. 2013, 2016), a panarchy concept is presented for lateral moraine slope biogeomorphic ecosystems. It depicts biogeomorphic feedbacks on different spatiotemporal scales as a set of nested adaptive cycles and links them by 'remember' and 'revolt' connections. On a small scale (cm2 - m2; seconds to years), the life cycle of the ecosystem engineer Dryas octopetala L. is considered as an adaptive cycle. Biogeomorphic succession within patches created by geomorphic processes represents an intermediate scale adaptive cycle (m2 - ha, years to decades), while geomorphic and ecologic pattern development at a landscape scale (ha - km2, decades to centuries) can be illustrated by an adaptive cycle of ‚biogeomorphic patch dynamics' (Eichel, 2017). In the panarchy, revolt connections link the smaller scale adaptive cycles to larger scale cycles: on lateral moraine slopes, the development of ecosystem engineer biomass and cover controls the engineering threshold of the biogeomorphic feedback window (Eichel et al., 2016) and therefore the onset of the biogeomorphic phase during biogeomorphic succession. In this phase, engineer patches and biogeomorphic structures can be created in the patch mosaic of the landscape. Remember connections link larger scale adaptive cycles to smaller scale cycles: configuration and properties of the lateral moraine slope patch mosaic control patch recolonization during biogeomorphic succession, while the patch-internal disturbance regime determines when the engineer can establish (establishment threshold of the biogeomorphic feedback window). Jointly, biogeomorphic feedback adaptive cycles and their connections in the panarchy create structure and function in the lateral moraine slope biogeomorphic ecosystem. Thus, by linking feedbacks on different spatiotemporal scales in biogeomorphic ecosystems and explaining the creation of ecosystem structure and function, the panarchy concept represents a useful tool for future biogeomorphic research. Eichel, J. 2017. Biogeomorphic dynamics in the Turtmann glacier forefield, Switzerland. PhD thesis, University of Bonn. Eichel J, Corenblit D, Dikau R. 2016. Conditions for feedbacks between geomorphic and vegetation dynamics on lateral moraine slopes: a biogeomorphic feedback window. Earth Surface Processes and Landforms 41: 406-419. DOI: 10.1002/esp.3859 Eichel J, Krautblatter M, Schmidtlein S, Dikau R. 2013. Biogeomorphic interactions in the Turtmann glacier forefield, Switzerland. Geomorphology 201 : 98-110. DOI: 10.1016/j.geomorph.2013.06.012 Holling CS, Gunderson LH, Peterson GD. 2002. Sustainability and Panarchies. In Panarchy: Understanding Transformations in Human and Natural Systems , . Island Press: Washington, D.C.; 63-102.

Adaptation Design Tool for Climate-Smart Management of Coral Reefs and Other Natural Resources.

PubMed

West, Jordan M; Courtney, Catherine A; Hamilton, Anna T; Parker, Britt A; Gibbs, David A; Bradley, Patricia; Julius, Susan H

2018-06-22

Scientists and managers of natural resources have recognized an urgent need for improved methods and tools to enable effective adaptation of management measures in the face of climate change. This paper presents an Adaptation Design Tool that uses a structured approach to break down an otherwise overwhelming and complex process into tractable steps. The tool contains worksheets that guide users through a series of design considerations for adapting their planned management actions to be more climate-smart given changing environmental stressors. Also provided with other worksheets is a framework for brainstorming new adaptation options in response to climate threats not yet addressed in the current plan. Developed and tested in collaboration with practitioners in Hawai'i and Puerto Rico using coral reefs as a pilot ecosystem, the tool and associated reference materials consist of worksheets, instructions and lessons-learned from real-world examples. On the basis of stakeholder feedback from expert consultations during tool development, we present insights and recommendations regarding how to maximize tool efficiency, gain the greatest value from the thought process, and deal with issues of scale and uncertainty. We conclude by reflecting on how the tool advances the theory and practice of assessment and decision-making science, informs higher level strategic planning, and serves as a platform for a systematic, transparent and inclusive process to tackle the practical implications of climate change for management of natural resources.

A kinesthetic washout filter for force-feedback rendering.

PubMed

Danieau, Fabien; Lecuyer, Anatole; Guillotel, Philippe; Fleureau, Julien; Mollet, Nicolas; Christie, Marc

2015-01-01

Today haptic feedback can be designed and associated to audiovisual content (haptic-audiovisuals or HAV). Although there are multiple means to create individual haptic effects, the issue of how to properly adapt such effects on force-feedback devices has not been addressed and is mostly a manual endeavor. We propose a new approach for the haptic rendering of HAV, based on a washout filter for force-feedback devices. A body model and an inverse kinematics algorithm simulate the user's kinesthetic perception. Then, the haptic rendering is adapted in order to handle transitions between haptic effects and to optimize the amplitude of effects regarding the device capabilities. Results of a user study show that this new haptic rendering can successfully improve the HAV experience.

Age Differences in Adaptive Decision Making: The Role of Numeracy

ERIC Educational Resources Information Center

Chen, Yiwei; Wang, Jiaxi; Kirk, Robert M.; Pethtel, Olivia L.; Kiefner, Allison E.

2014-01-01

The primary purposes of the present study were to examine age differences in adaptive decision making and to evaluate the role of numeracy in mediating the relationship between age and adaptive decision making. Adaptive decision making was assessed by the Cups task (Levin, Weller, Pederson, & Harshman, 2007). Forty-six younger (18 to 24 years…

Climate-Smart Design for Ecosystem Management: A Test Application for Coral Reefs.

PubMed

West, Jordan M; Courtney, Catherine A; Hamilton, Anna T; Parker, Britt A; Julius, Susan H; Hoffman, Jennie; Koltes, Karen H; MacGowan, Petra

2017-01-01

The interactive and cumulative impacts of climate change on natural resources such as coral reefs present numerous challenges for conservation planning and management. Climate change adaptation is complex due to climate-stressor interactions across multiple spatial and temporal scales. This leaves decision makers worldwide faced with local, regional, and global-scale threats to ecosystem processes and services, occurring over time frames that require both near-term and long-term planning. Thus there is a need for structured approaches to adaptation planning that integrate existing methods for vulnerability assessment with design and evaluation of effective adaptation responses. The Corals and Climate Adaptation Planning project of the U.S. Coral Reef Task Force seeks to develop guidance for improving coral reef management through tailored application of a climate-smart approach. This approach is based on principles from a recently-published guide which provides a framework for adopting forward-looking goals, based on assessing vulnerabilities to climate change and applying a structured process to design effective adaptation strategies. Work presented in this paper includes: (1) examination of the climate-smart management cycle as it relates to coral reefs; (2) a compilation of adaptation strategies for coral reefs drawn from a comprehensive review of the literature; (3) in-depth demonstration of climate-smart design for place-based crafting of robust adaptation actions; and (4) feedback from stakeholders on the perceived usefulness of the approach. We conclude with a discussion of lessons-learned on integrating climate-smart design into real-world management planning processes and a call from stakeholders for an "adaptation design tool" that is now under development.

DELPHI AND VALUES,

DTIC Science & Technology

MANAGEMENT PLANNING AND CONTROL, DECISION MAKING), (* DECISION MAKING , GROUP DYNAMICS), (*GROUP DYNAMICS, ATTITUDES(PSYCHOLOGY)), REASONING, REACTION(PSYCHOLOGY), PUBLIC OPINION, PERFORMANCE(HUMAN), QUESTIONNAIRES, FEEDBACK

Towards autonomous neuroprosthetic control using Hebbian reinforcement learning.

PubMed

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

2013-12-01

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

Fuzzy Adaptive Decentralized Optimal Control for Strict Feedback Nonlinear Large-Scale Systems.

PubMed

Sun, Kangkang; Sui, Shuai; Tong, Shaocheng

2018-04-01

This paper considers the optimal decentralized fuzzy adaptive control design problem for a class of interconnected large-scale nonlinear systems in strict feedback form and with unknown nonlinear functions. The fuzzy logic systems are introduced to learn the unknown dynamics and cost functions, respectively, and a state estimator is developed. By applying the state estimator and the backstepping recursive design algorithm, a decentralized feedforward controller is established. By using the backstepping decentralized feedforward control scheme, the considered interconnected large-scale nonlinear system in strict feedback form is changed into an equivalent affine large-scale nonlinear system. Subsequently, an optimal decentralized fuzzy adaptive control scheme is constructed. The whole optimal decentralized fuzzy adaptive controller is composed of a decentralized feedforward control and an optimal decentralized control. It is proved that the developed optimal decentralized controller can ensure that all the variables of the control system are uniformly ultimately bounded, and the cost functions are the smallest. Two simulation examples are provided to illustrate the validity of the developed optimal decentralized fuzzy adaptive control scheme.

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.

Feedback and Feedforward Control During Walking in Individuals With Chronic Ankle Instability.

PubMed

Yen, Sheng-Che; Corkery, Marie B; Donohoe, Amy; Grogan, Maddison; Wu, Yi-Ning

2016-09-01

Study Design Controlled laboratory study. Background Recurrent ankle sprains associated with chronic ankle instability (CAI) occur not only in challenging sports but also in daily walking. Understanding whether and how CAI alters feedback and feedforward controls during walking may be important for developing interventions for CAI prevention or treatment. Objective To understand whether CAI is associated with changes in feedback and feedforward control when individuals with CAI are subjected to experimental perturbation during walking. Methods Twelve subjects with CAI and 12 control subjects walked on a treadmill while adapting to external loading that generated inversion perturbation at the ankle joint. Ankle kinematics around heel contact during and after the adaptation were compared between the 2 groups. Results Both healthy and CAI groups showed an increase in eversion around heel contact in early adaptation to the external loading. However, the CAI group adapted back toward the baseline, while the healthy controls showed further increase in eversion in late adaptation. When the external loading was removed in the postadaptation period, healthy controls showed an aftereffect consisting of an increase in eversion around heel contact, but the CAI group showed no aftereffect. Conclusion The results provide preliminary evidence that CAI may alter individuals' feedback and feedforward control during walking. J Orthop Sports Phys Ther 2016;46(9):775-783. Epub 5 Aug 2016. doi:10.2519/jospt.2016.6403.

Adaptive Feedback in Local Coordinates for Real-time Vision-Based Motion Control Over Long Distances

NASA Astrophysics Data System (ADS)

Aref, M. M.; Astola, P.; Vihonen, J.; Tabus, I.; Ghabcheloo, R.; Mattila, J.

2018-03-01

We studied the differences in noise-effects, depth-correlated behavior of sensors, and errors caused by mapping between coordinate systems in robotic applications of machine vision. In particular, the highly range-dependent noise densities for semi-unknown object detection were considered. An equation is proposed to adapt estimation rules to dramatic changes of noise over longer distances. This algorithm also benefits the smooth feedback of wheels to overcome variable latencies of visual perception feedback. Experimental evaluation of the integrated system is presented with/without the algorithm to highlight its effectiveness.

Computer-supported feedback message tailoring: theory-informed adaptation of clinical audit and feedback for learning and behavior change.

PubMed

Landis-Lewis, Zach; Brehaut, Jamie C; Hochheiser, Harry; Douglas, Gerald P; Jacobson, Rebecca S

2015-01-21

Evidence shows that clinical audit and feedback can significantly improve compliance with desired practice, but it is unclear when and how it is effective. Audit and feedback is likely to be more effective when feedback messages can influence barriers to behavior change, but barriers to change differ across individual health-care providers, stemming from differences in providers' individual characteristics. The purpose of this article is to invite debate and direct research attention towards a novel audit and feedback component that could enable interventions to adapt to barriers to behavior change for individual health-care providers: computer-supported tailoring of feedback messages. We argue that, by leveraging available clinical data, theory-informed knowledge about behavior change, and the knowledge of clinical supervisors or peers who deliver feedback messages, a software application that supports feedback message tailoring could improve feedback message relevance for barriers to behavior change, thereby increasing the effectiveness of audit and feedback interventions. We describe a prototype system that supports the provision of tailored feedback messages by generating a menu of graphical and textual messages with associated descriptions of targeted barriers to behavior change. Supervisors could use the menu to select messages based on their awareness of each feedback recipient's specific barriers to behavior change. We anticipate that such a system, if designed appropriately, could guide supervisors towards giving more effective feedback for health-care providers. A foundation of evidence and knowledge in related health research domains supports the development of feedback message tailoring systems for clinical audit and feedback. Creating and evaluating computer-supported feedback tailoring tools is a promising approach to improving the effectiveness of clinical audit and feedback.

[Requirements for and expectations of health technology assessment in Galicia (Spain). A qualitative study from the perspective of decision-makers and clinicians].

PubMed

Varela-Lema, Leonor; Merino, Gerardo Atienza; García, Marisa López; Martínez, María Vidal; Triana, Elena Gervas; Mota, Teresa Cerdá

2011-01-01

To explore perceptions of the use of health technology assessment (HTA) in the Galician public health system, identify opinions on the usefulness of the products and services developed by the Galician Health Technology Assessment Agency (avalia-t), and determine the barriers and facilitators to the transfer of results to clinical practice. We performed a qualitative study based on in-depth semi-structured interviews of 20 intentionally selected experts (10 health care professionals and 10 hospital decision makers). The interviews were tape recorded and transcribed for inductive thematic analysis. Interest in HTA activities was high, but most informants considered these activities to be underused as a tool to aid decision making in clinical practice. A series of key factors was identified to guarantee HTA use: greater dissemination of HTA activities and availability of the results, increased involvement and communication among health care professionals in the selection and prioritization of relevant research, contextualization and adaptation of results to the local context, increased organizational support and greater financial resources. The present study allows end-userś opinions on the utility of the various products/services offered by HTA agencies to be contrasted in order to adapt HTA activity to their needs and requirements. The involvement of health care professionals in all HTA fields is perceived as one of the main lines of action for HTA agencies. Such involvement could be achieved by reinforcing personal contact and increasing feedback to collaborators. Copyright © 2010 SESPAS. Published by Elsevier Espana. All rights reserved.

The fundamental role of ecological feedback mechanisms for the adaptive management of seagrass ecosystems - a review.

PubMed

Maxwell, Paul S; Eklöf, Johan S; van Katwijk, Marieke M; O'Brien, Katherine R; de la Torre-Castro, Maricela; Boström, Christoffer; Bouma, Tjeerd J; Krause-Jensen, Dorte; Unsworth, Richard K F; van Tussenbroek, Brigitta I; van der Heide, Tjisse

2017-08-01

Seagrass meadows are vital ecosystems in coastal zones worldwide, but are also under global threat. One of the major hurdles restricting the success of seagrass conservation and restoration is our limited understanding of ecological feedback mechanisms. In these ecosystems, multiple, self-reinforcing feedbacks can undermine conservation efforts by masking environmental impacts until the decline is precipitous, or alternatively they can inhibit seagrass recovery in spite of restoration efforts. However, no clear framework yet exists for identifying or dealing with feedbacks to improve the management of seagrass ecosystems. Here we review the causes and consequences of multiple feedbacks between seagrass and biotic and/or abiotic processes. We demonstrate how feedbacks have the potential to impose or reinforce regimes of either seagrass dominance or unvegetated substrate, and how the strength and importance of these feedbacks vary across environmental gradients. Although a myriad of feedbacks have now been identified, the co-occurrence and likely interaction among feedbacks has largely been overlooked to date due to difficulties in analysis and detection. Here we take a fundamental step forward by modelling the interactions among two distinct above- and belowground feedbacks to demonstrate that interacting feedbacks are likely to be important for ecosystem resilience. On this basis, we propose a five-step adaptive management plan to address feedback dynamics for effective conservation and restoration strategies. The management plan provides guidance to aid in the identification and prioritisation of likely feedbacks in different seagrass ecosystems. © 2016 Cambridge Philosophical Society.

Feedback (F) Fueling Adaptation (A) Network Growth (N) and Self-Organization (S): A Complex Systems Design and Evaluation Approach to Professional Development

ERIC Educational Resources Information Center

Yoon, Susan A.; Klopfer, Eric

2006-01-01

This paper reports on the efficacy of a professional development framework premised on four complex systems design principles: Feedback, Adaptation, Network Growth and Self-organization (FANS). The framework is applied to the design and delivery of the first 2 years of a 3-year study aimed at improving teacher and student understanding of…

Simulation in Urology to Train Non-Technical Skills in Ward Rounds.

PubMed

Somasundram, K; Spence, H; Colquhoun, A J; Mcilhenny, C; Biyani, C S; Jain, S

2018-05-19

We have designed an exercise to train newly appointed Urology trainees in non-technical skills on ward rounds as a part of a simulation 'boot camp'. This paper reports our experience, including a qualitative analysis of participant feedback on the utility of this method of training. The simulations took place in a high-fidelity simulated ward bay. Forty-eight doctors with formal Urology training ranging between 2-60 months (mean 19.1 ± 11.6 months) took part. Thirty-one participants were on a formal Urology specialty training pathway. The remaining participants were core (pre-specialty) surgical trainees. The entry requirement was that participants must be junior-level urologists, ideally at the beginning of specialty training. Participants individually led a simulated ward round, which was devised using actors to play as patients and a simulated 'switchboard' for telephone conversations. Distractions were introduced deliberately for participants to manage an emergent urology-related scenario. 'Freeze-frames' were used to 'pause' the ward-round, whereby observing consultants provided feedback on performance. Following the simulated exercises, a whole-group structured debrief took place. Non-technical skills for surgeons (NOTSS) scores were generated for participants by seven consultant urologists. Participants completed a two-part feedback form. Part-one involved nine questions scored on a Likert scale, and part-two required free-text responses. The mean itemised NOTSS scores for situational awareness, decision-making, communication and teamwork and leadership were 3.01 (SD ± 0.15), 2.95 (SD ± 0.16), 3.05 (SD ± 0.19), 2.98 (SD ± 0.15), respectively. From the thematic analysis, participants commented positively on the number of scenarios per participant, the use of real patient-actors and staff, and the use of 'freeze-frames' for immediate feedback. Residents also provided suggestions for distractions to be considered in the future. This simulated ward round was generally well received by participants, and the obtained feedback provides an insight into how this can be adapted to maximise the benefits for new specialty residents. The mean NOTSS scores indicated that non-technical skills performances could be improved. This supports our rationale to train non-technical skills in a safe environment to bolster career transition into positions of greater decision-making autonomy. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

How Ecosystem Services Knowledge and Values Influence Farmers' Decision-Making

PubMed Central

Lamarque, Pénélope; Meyfroidt, Patrick; Nettier, Baptiste; Lavorel, Sandra

2014-01-01

The ecosystem services (ES) concept has emerged and spread widely recently, to enhance the importance of preserving ecosystems through global change in order to maintain their benefits for human well-being. Numerous studies consider various dimensions of the interactions between ecosystems and land use via ES, but integrated research addressing the complete feedback loop between biodiversity, ES and land use has remained mostly theoretical. Few studies consider feedbacks from ecosystems to land use systems through ES, exploring how ES are taken into account in land management decisions. To fill this gap, we carried out a role-playing game to explore how ES cognition mediates feedbacks from environmental change on farmers' behaviors in a mountain grassland system. On a close to real landscape game board, farmers were faced with changes in ES under climatic and socio-economic scenarios and prompted to plan for the future and to take land management decisions as they deemed necessary. The outcomes of role-playing game were complemented with additional agronomic and ecological data from interviews and fieldwork. The effects of changes in ES on decision were mainly direct, i.e. not affecting knowledge and values, when they constituted situations with which farmers were accustomed. For example, a reduction of forage quantity following droughts led farmers to shift from mowing to grazing. Sometimes, ES cognitions were affected by ES changes or by external factors, leading to an indirect feedback. This happened when fertilization was stopped after farmers learned that it was inefficient in a drought context. Farmers' behaviors did not always reflect their attitudes towards ES because other factors including topographic constraints, social value of farming or farmer individual and household characteristics also influenced land-management decisions. Those results demonstrated the interest to take into account the complete feedback loop between ES and land management decisions to favor more sustainable ES management. PMID:25268490

How ecosystem services knowledge and values influence farmers' decision-making.

PubMed

Lamarque, Pénélope; Meyfroidt, Patrick; Nettier, Baptiste; Lavorel, Sandra

2014-01-01

The ecosystem services (ES) concept has emerged and spread widely recently, to enhance the importance of preserving ecosystems through global change in order to maintain their benefits for human well-being. Numerous studies consider various dimensions of the interactions between ecosystems and land use via ES, but integrated research addressing the complete feedback loop between biodiversity, ES and land use has remained mostly theoretical. Few studies consider feedbacks from ecosystems to land use systems through ES, exploring how ES are taken into account in land management decisions. To fill this gap, we carried out a role-playing game to explore how ES cognition mediates feedbacks from environmental change on farmers' behaviors in a mountain grassland system. On a close to real landscape game board, farmers were faced with changes in ES under climatic and socio-economic scenarios and prompted to plan for the future and to take land management decisions as they deemed necessary. The outcomes of role-playing game were complemented with additional agronomic and ecological data from interviews and fieldwork. The effects of changes in ES on decision were mainly direct, i.e. not affecting knowledge and values, when they constituted situations with which farmers were accustomed. For example, a reduction of forage quantity following droughts led farmers to shift from mowing to grazing. Sometimes, ES cognitions were affected by ES changes or by external factors, leading to an indirect feedback. This happened when fertilization was stopped after farmers learned that it was inefficient in a drought context. Farmers' behaviors did not always reflect their attitudes towards ES because other factors including topographic constraints, social value of farming or farmer individual and household characteristics also influenced land-management decisions. Those results demonstrated the interest to take into account the complete feedback loop between ES and land management decisions to favor more sustainable ES management.

Robust adaptive control modeling of human arm movements subject to altered gravity and mechanical loads

NASA Astrophysics Data System (ADS)

Tryfonidis, Michail

It has been observed that during orbital spaceflight the absence of gravitation related sensory inputs causes incongruence between the expected and the actual sensory feedback resulting from voluntary movements. This incongruence results in a reinterpretation or neglect of gravity-induced sensory input signals. Over time, new internal models develop, gradually compensating for the loss of spatial reference. The study of adaptation of goal-directed movements is the main focus of this thesis. The hypothesis is that during the adaptive learning process the neural connections behave in ways that can be described by an adaptive control method. The investigation presented in this thesis includes two different sets of experiments. A series of dart throwing experiments took place onboard the space station Mir. Experiments also took place at the Biomechanics lab at MIT, where the subjects performed a series of continuous trajectory tracking movements while a planar robotic manipulandum exerted external torques on the subjects' moving arms. The experimental hypothesis for both experiments is that during the first few trials the subjects will perform poorly trying to follow a prescribed trajectory, or trying to hit a target. A theoretical framework is developed that is a modification of the sliding control method used in robotics. The new control framework is an attempt to explain the adaptive behavior of the subjects. Numerical simulations of the proposed framework are compared with experimental results and predictions from competitive models. The proposed control methodology extends the results of the sliding mode theory to human motor control. The resulting adaptive control model of the motor system is robust to external dynamics, even those of negative gain, uses only position and velocity feedback, and achieves bounded steady-state error without explicit knowledge of the system's nonlinearities. In addition, the experimental and modeling results demonstrate that visuomotor learning is important not only for error correction through internal model adaptation on ground or in microgravity, but also for the minimization of the total mean-square error in the presence of random variability. Thus human intelligent decision displays certain attributes that seem to conform to Bayesian statistical games. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)

A pan-Canadian practice guideline and algorithm: screening, assessment, and supportive care of adults with cancer-related fatigue

PubMed Central

Howell, D.; Keller–Olaman, S.; Oliver, T.K.; Hack, T.F.; Broadfield, L.; Biggs, K.; Chung, J.; Gravelle, D.; Green, E.; Hamel, M.; Harth, T.; Johnston, P.; McLeod, D.; Swinton, N.; Syme, A.; Olson, K.

2013-01-01

Purpose The purpose of the present systematic review was to develop a practice guideline to inform health care providers about screening, assessment, and effective management of cancer-related fatigue (crf) in adults. Methods The internationally endorsed adapte methodology was used to develop a practice guideline for pan-Canadian use. A systematic search of the literature identified a broad range of evidence: clinical practice guidelines, systematic reviews, and other guidance documents on the screening, assessment, and management of crf. The search included medline, embase, cinahl, the Cochrane Library, and other guideline and data sources to December 2009. Results Two clinical practice guidelines were identified for adaptation. Seven guidance documents and four systematic reviews also provided supplementary evidence to inform guideline recommendations. Health professionals across Canada provided expert feedback on the adapted recommendations in the practice guideline and algorithm through a participatory external review process. Conclusions Practice guidelines can facilitate the adoption of evidence-based assessment and interventions for adult cancer patients experiencing fatigue. Development of an algorithm to guide decision-making in practice may also foster the uptake of a guideline into routine care. PMID:23737693

Adaptive Fuzzy Bounded Control for Consensus of Multiple Strict-Feedback Nonlinear Systems.

PubMed

Wang, Wei; Tong, Shaocheng

2018-02-01

This paper studies the adaptive fuzzy bounded control problem for leader-follower multiagent systems, where each follower is modeled by the uncertain nonlinear strict-feedback system. Combining the fuzzy approximation with the dynamic surface control, an adaptive fuzzy control scheme is developed to guarantee the output consensus of all agents under directed communication topologies. Different from the existing results, the bounds of the control inputs are known as a priori, and they can be determined by the feedback control gains. To realize smooth and fast learning, a predictor is introduced to estimate each error surface, and the corresponding predictor error is employed to learn the optimal fuzzy parameter vector. It is proved that the developed adaptive fuzzy control scheme guarantees the uniformly ultimate boundedness of the closed-loop systems, and the tracking error converges to a small neighborhood of the origin. The simulation results and comparisons are provided to show the validity of the control strategy presented in this paper.

Adaptive Neural Control for a Class of Pure-Feedback Nonlinear Systems via Dynamic Surface Technique.

PubMed

Liu, Zongcheng; Dong, Xinmin; Xue, Jianping; Li, Hongbo; Chen, Yong

2016-09-01

This brief addresses the adaptive control problem for a class of pure-feedback systems with nonaffine functions possibly being nondifferentiable. Without using the mean value theorem, the difficulty of the control design for pure-feedback systems is overcome by modeling the nonaffine functions appropriately. With the help of neural network approximators, an adaptive neural controller is developed by combining the dynamic surface control (DSC) and minimal learning parameter (MLP) techniques. The key features of our approach are that, first, the restrictive assumptions on the partial derivative of nonaffine functions are removed, second, the DSC technique is used to avoid "the explosion of complexity" in the backstepping design, and the number of adaptive parameters is reduced significantly using the MLP technique, third, smooth robust compensators are employed to circumvent the influences of approximation errors and disturbances. Furthermore, it is proved that all the signals in the closed-loop system are semiglobal uniformly ultimately bounded. Finally, the simulation results are provided to demonstrate the effectiveness of the designed method.

Cohesion in Military and Aviation Psychology: An Annotated Bibliography and Suggestions for US Army Aviation

DTIC Science & Technology

2005-06-01

serve a significant influence upon perceptions. Strategies for mitigating the detrimental effects of racism and sexism are suggested. Leaders need to...Hedlund, J. (1998). Extending the multilevel theory of team decision making: Effects of feedback and experience in hierarchical teams. Academy of...Colquitt, J.A., & Hedlund, J. (1998). Extending the multilevel theory of team decision making: Effects of feedback and experience in hierarchical

Uncover it, students would learn leadership from Team-Based Learning (TBL): The effect of guided reflection and feedback.

PubMed

Alizadeh, Maryam; Mirzazadeh, Azim; Parmelee, Dean X; Peyton, Elizabeth; Janani, Leila; Hassanzadeh, Gholamreza; Nedjat, Saharnaz

2017-04-01

Little is known about best practices for teaching and learning leadership through Team-Based learning™ (TBL™) with medical students. We hypothesized that guided reflection and feedback would improve shared leadership and shared leadership capacity, and enhance team decision quality in TBL teams. We used the Kolb experiential learning theory as the theoretical framework. The study was conducted at Tehran University of Medical Sciences. Three TBL sessions with 206 students (39 teams) participated in the study. Using a quasi-experimental design, one batch received guided reflection and feedback on their team leadership processes (n = 20 teams) and the other received only TBL (n = 19 teams). Observers measured shared leadership using a checklist. Shared leadership capacity was measured using a questionnaire. Scores on a team application exercise were used to assess quality of team decisions. Evidence did not support our first hypothesis that reflection and feedback enhance shared leadership in TBL teams. Percentages of teams displaying shared leadership did not differ between intervention and control groups in sessions 1 (p = 0.6), 2 (p = 1) or 3 (p = 1). The results did not support the second hypothesis. We found no difference in quality of decision making between the intervention and control groups for sessions 1 (p = 0.77), 2 (p = 0.23), or 3 (p = 0.07). The third hypothesis that the reflection and feedback would have an effect on shared leadership capacity was supported (T = -8.55, p > 0.001 adjusted on baseline; T = -8.55, p > 0.001 adjusted on gender). We found that reflection and feedback improved shared leadership capacity but not shared leadership behaviors or team decision quality. We propose medical educators who apply TBL, should provide guided exercise in reflection and feedback so that students may better understand the benefits of working in teams as preparation for their future roles as leaders and members of health care teams.

Social provocation modulates decision making and feedback processing: Examining the trajectory of development in adolescent participants.

PubMed

Pincham, Hannah L; Wu, Claire; Killikelly, Clare; Vuillier, Laura; Fearon, R M Pasco

2015-10-01

Increasingly, research is turning to the ways in which social context impacts decision making and feedback processing in adolescents. The current study recorded electroencephalography to examine the trajectory of development across adolescence, with a focus on how social context impacts cognition and behaviour. To that end, younger (10-12 years) and older (14-16 years) adolescents played a modified Taylor Aggression Paradigm against two virtual opponents: a low-provoker and a high-provoker. During the task's decision phase (where participants select punishment for their opponent), we examined two event-related potentials: the N2 and the late positive potential (LPP). During the outcome phase (where participants experience win or loss feedback), we measured the feedback related negativity (FRN). Although N2 amplitudes did not vary with provocation, LPP amplitudes were enhanced under high provocation for the younger group, suggesting that emotional reactivity during the decision phase was heightened for early adolescents. During the outcome phase, the FRN was reduced following win outcomes under high provocation for both groups, suggesting that a highly provocative social opponent may influence the reward response. Collectively, the data argue that social context is an important factor modulating neural responses in adolescent behavioural and brain development. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Design and test of a Microsoft Kinect-based system for delivering adaptive visual feedback to stroke patients during training of upper limb movement.

PubMed

Simonsen, Daniel; Popovic, Mirjana B; Spaich, Erika G; Andersen, Ole Kæseler

2017-11-01

The present paper describes the design and test of a low-cost Microsoft Kinect-based system for delivering adaptive visual feedback to stroke patients during the execution of an upper limb exercise. Eleven sub-acute stroke patients with varying degrees of upper limb function were recruited. Each subject participated in a control session (repeated twice) and a feedback session (repeated twice). In each session, the subjects were presented with a rectangular pattern displayed on a vertical mounted monitor embedded in the table in front of the patient. The subjects were asked to move a marker inside the rectangular pattern by using their most affected hand. During the feedback session, the thickness of the rectangular pattern was changed according to the performance of the subject, and the color of the marker changed according to its position, thereby guiding the subject's movements. In the control session, the thickness of the rectangular pattern and the color of the marker did not change. The results showed that the movement similarity and smoothness was higher in the feedback session than in the control session while the duration of the movement was longer. The present study showed that adaptive visual feedback delivered by use of the Kinect sensor can increase the similarity and smoothness of upper limb movement in stroke patients.

Adolescents' Perspectives on Personalized E-Feedback in the Context of Health Risk Behavior Screening for Primary Care: Qualitative Study.

PubMed

Zieve, Garret G; Richardson, Laura P; Katzman, Katherine; Spielvogle, Heather; Whitehouse, Sandy; McCarty, Carolyn A

2017-07-20

Electronic health screening tools for primary care present an opportunity to go beyond data collection to provide education and feedback to adolescents in order to motivate behavior change. However, there is limited research to guide feedback message development. The aim of this study was to explore youth perceptions of and preferences for receiving personalized feedback for multiple health risk behaviors and reinforcement for health promoting behaviors from an electronic health screening tool for primary care settings, using qualitative methodology. In total, 31 adolescents aged 13-18 years completed the screening tool, received the electronic feedback, and subsequently participated in individual, semistructured, qualitative interviews lasting approximately 60 min. Participants were queried about their overall impressions of the tool, perceptions regarding various types of feedback messages, and additional features that would help motivate health behavior change. Using thematic analysis, interview transcripts were coded to identify common themes expressed across participants. Overall, the tool was well-received by participants who perceived it as a way to enhance-but not replace-their interactions with providers. They appreciated receiving nonjudgmental feedback from the tool and responded positively to information regarding the consequences of behaviors, comparisons with peer norms and health guidelines, tips for behavior change, and reinforcement of healthy choices. A small but noteworthy minority of participants dismissed the peer norms as not real or relevant and national guidelines as not valid or reasonable. When prompted for possible adaptations to the tool, adolescents expressed interest in receiving follow-up information, setting health-related goals, tracking their behaviors over time, and communicating with providers electronically between appointments. Adolescents in this qualitative study desired feedback that validates their healthy behavior choices and supports them as independent decision makers by neutrally presenting health information, facilitating goal setting, and offering ongoing technological supports. ©Garret G Zieve, Laura P Richardson, Katherine Katzman, Heather Spielvogle, Sandy Whitehouse, Carolyn A McCarty. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 20.07.2017.

Using interviews and focus groups with resource managers to explore risk perceptions and responses to climate scenarios

NASA Astrophysics Data System (ADS)

Clifford, K. R.; Travis, W.; Rangwala, I.; Rondeau, R.; Young, L.

2016-12-01

Resource managers in the western U.S. are increasingly tasked to incorporate climate change into management decisions and long-term planning, but this task is complicated by multiple challenges, among them the need to bridge between the differing perspectives and prerogatives of scientists and resource managers. As part of a larger, iterative, interdisciplinary, multi-landscape research project that built on a prior climate vulnerability research, we conducted more than 50 semi-structured interviews and four focus groups with resource managers in the Gunnison Basin in western Colorado. The interviews addressed the managers' risk perceptions and knowledge about the resources and landscapes, while the focus groups asked resource managers to reflect on their own resource decision-making in light of three narrative future climate scenarios created by scientists on the research team. While time-intensive, the interviews and focus groups produced important insights into the managers' understanding of both the resources in question and the future climate scenarios. We found that the managers' mental models of their systems, and their conceptions of landscape changes and future threats, were diverse and sometimes in conflict with those held by the research team. The managers' responses to the climate scenarios reflected divergent and nuanced perceptions of risk, adaptation and uncertainty, heavily shaped by personal experience—which could be a constraint under rapidly changing future conditions. Our deployment of social science methodologies facilitated the co-production of climate adaptation strategies and a bridge between and among scientists and managers. The participants found the focus groups helpful since they (1) provided space to focus on decision-making under climate change, rather than fixate on details of the science, and (2) facilitated interaction with colleagues from other agencies. Climate scientists used participant feedback to inform future scenario development. The use of small focus groups to engage with climate scenarios could add value to other ongoing efforts to promote landscape-scale adaptation.

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

PubMed

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

2018-02-01

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

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

PubMed

Tanaka, Hirokazu; Homma, Kazuhiro; Imamizu, Hiroshi

2012-01-01

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

Risky decision making from childhood through adulthood: Contributions of learning and sensitivity to negative feedback.

PubMed

Humphreys, Kathryn L; Telzer, Eva H; Flannery, Jessica; Goff, Bonnie; Gabard-Durnam, Laurel; Gee, Dylan G; Lee, Steve S; Tottenham, Nim

2016-02-01

Decision making in the context of risk is a complex and dynamic process that changes across development. Here, we assessed the influence of sensitivity to negative feedback (e.g., loss) and learning on age-related changes in risky decision making, both of which show unique developmental trajectories. In the present study, we examined risky decision making in 216 individuals, ranging in age from 3-26 years, using the balloon emotional learning task (BELT), a computerized task in which participants pump up a series of virtual balloons to earn points, but risk balloon explosion on each trial, which results in no points. It is important to note that there were 3 balloon conditions, signified by different balloon colors, ranging from quick- to slow-to-explode, and participants could learn the color-condition pairings through task experience. Overall, we found age-related increases in pumps made and points earned. However, in the quick-to-explode condition, there was a nonlinear adolescent peak for points earned. Follow-up analyses indicated that this adolescent phenotype occurred at the developmental intersection of linear age-related increases in learning and decreases in sensitivity to negative feedback. Adolescence was marked by intermediate values on both these processes. These findings show that a combination of linearly changing processes can result in nonlinear changes in risky decision making, the adolescent-specific nature of which is associated with developmental improvements in learning and reduced sensitivity to negative feedback. (c) 2016 APA, all rights reserved).

WeightLifter: Visual Weight Space Exploration for Multi-Criteria Decision Making.

PubMed

Pajer, Stephan; Streit, Marc; Torsney-Weir, Thomas; Spechtenhauser, Florian; Muller, Torsten; Piringer, Harald

2017-01-01

A common strategy in Multi-Criteria Decision Making (MCDM) is to rank alternative solutions by weighted summary scores. Weights, however, are often abstract to the decision maker and can only be set by vague intuition. While previous work supports a point-wise exploration of weight spaces, we argue that MCDM can benefit from a regional and global visual analysis of weight spaces. Our main contribution is WeightLifter, a novel interactive visualization technique for weight-based MCDM that facilitates the exploration of weight spaces with up to ten criteria. Our technique enables users to better understand the sensitivity of a decision to changes of weights, to efficiently localize weight regions where a given solution ranks high, and to filter out solutions which do not rank high enough for any plausible combination of weights. We provide a comprehensive requirement analysis for weight-based MCDM and describe an interactive workflow that meets these requirements. For evaluation, we describe a usage scenario of WeightLifter in automotive engineering and report qualitative feedback from users of a deployed version as well as preliminary feedback from decision makers in multiple domains. This feedback confirms that WeightLifter increases both the efficiency of weight-based MCDM and the awareness of uncertainty in the ultimate decisions.

Electrophysiological correlates reflect the integration of model-based and model-free decision information.

PubMed

Eppinger, Ben; Walter, Maik; Li, Shu-Chen

2017-04-01

In this study, we investigated the interplay of habitual (model-free) and goal-directed (model-based) decision processes by using a two-stage Markov decision task in combination with event-related potentials (ERPs) and computational modeling. To manipulate the demands on model-based decision making, we applied two experimental conditions with different probabilities of transitioning from the first to the second stage of the task. As we expected, when the stage transitions were more predictable, participants showed greater model-based (planning) behavior. Consistent with this result, we found that stimulus-evoked parietal (P300) activity at the second stage of the task increased with the predictability of the state transitions. However, the parietal activity also reflected model-free information about the expected values of the stimuli, indicating that at this stage of the task both types of information are integrated to guide decision making. Outcome-related ERP components only reflected reward-related processes: Specifically, a medial prefrontal ERP component (the feedback-related negativity) was sensitive to negative outcomes, whereas a component that is elicited by reward (the feedback-related positivity) increased as a function of positive prediction errors. Taken together, our data indicate that stimulus-locked parietal activity reflects the integration of model-based and model-free information during decision making, whereas feedback-related medial prefrontal signals primarily reflect reward-related decision processes.

ComPAIR: A New Online Tool Using Adaptive Comparative Judgement to Support Learning with Peer Feedback

ERIC Educational Resources Information Center

Potter, Tiffany; Englund, Letitia; Charbonneau, James; MacLean, Mark Thompson; Newell, Jonathan; Roll, Ido

2017-01-01

Peer feedback is a useful strategy in teaching and learning, but its effectiveness particularly in introductory courses can be limited by the relative newness of students to both the body of knowledge upon which they are being asked to provide feedback and the skill set involved in providing good feedback. This paper applies a novel approach to…

Effectiveness of Instruction and Video Feedback on Staff's Use of Prompts and Children's Adaptive Responses during One-to-One Training in Children with Severe to Profound Intellectual Disability

ERIC Educational Resources Information Center

van Vonderen, Annemarie; de Swart, Charlotte; Didden, Robert

2010-01-01

Although relatively many studies have addressed staff training and its effect on trainer behavior, the effects of staff training on trainee's adaptive behaviors have seldomly been examined. We therefore assessed effectiveness of staff training, consisting of instruction and video feedback, on (a) staff's response prompting, and (b) staff's trainer…

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

Self-reinnervated muscles lose autogenic length feedback, but intermuscular feedback can recover functional connectivity

PubMed Central

Prilutsky, Boris I.; Gregor, Robert J.; Abelew, Thomas A.; Nichols, T. Richard

2016-01-01

In this study, we sought to identify sensory circuitry responsible for motor deficits or compensatory adaptations after peripheral nerve cut and repair. Self-reinnervation of the ankle extensor muscles abolishes the stretch reflex and increases ankle yielding during downslope walking, but it remains unknown whether this finding generalizes to other muscle groups and whether muscles become completely deafferented. In decerebrate cats at least 19 wk after nerve cut and repair, we examined the influence of quadriceps (Q) muscles' self-reinnervation on autogenic length feedback, as well as intermuscular length and force feedback, among the primary extensor muscles in the cat hindlimb. Effects of gastrocnemius and soleus self-reinnervation on intermuscular circuitry were also evaluated. We found that autogenic length feedback was lost after Q self-reinnervation, indicating that loss of the stretch reflex appears to be a generalizable consequence of muscle self-reinnervation. However, intermuscular force and length feedback, evoked from self-reinnervated muscles, was preserved in most of the interactions evaluated with similar relative inhibitory or excitatory magnitudes. These data indicate that intermuscular spinal reflex circuitry has the ability to regain functional connectivity, but the restoration is not absolute. Explanations for the recovery of intermuscular feedback are discussed, based on identified mechanisms responsible for lost autogenic length feedback. Functional implications, due to permanent loss of autogenic length feedback and potential for compensatory adaptations from preserved intermuscular feedback, are discussed. PMID:27306676

Impaired Feedforward Control and Enhanced Feedback Control of Speech in Patients with Cerebellar Degeneration.

PubMed

Parrell, Benjamin; Agnew, Zarinah; Nagarajan, Srikantan; Houde, John; Ivry, Richard B

2017-09-20

The cerebellum has been hypothesized to form a crucial part of the speech motor control network. Evidence for this comes from patients with cerebellar damage, who exhibit a variety of speech deficits, as well as imaging studies showing cerebellar activation during speech production in healthy individuals. To date, the precise role of the cerebellum in speech motor control remains unclear, as it has been implicated in both anticipatory (feedforward) and reactive (feedback) control. Here, we assess both anticipatory and reactive aspects of speech motor control, comparing the performance of patients with cerebellar degeneration and matched controls. Experiment 1 tested feedforward control by examining speech adaptation across trials in response to a consistent perturbation of auditory feedback. Experiment 2 tested feedback control, examining online corrections in response to inconsistent perturbations of auditory feedback. Both male and female patients and controls were tested. The patients were impaired in adapting their feedforward control system relative to controls, exhibiting an attenuated anticipatory response to the perturbation. In contrast, the patients produced even larger compensatory responses than controls, suggesting an increased reliance on sensory feedback to guide speech articulation in this population. Together, these results suggest that the cerebellum is crucial for maintaining accurate feedforward control of speech, but relatively uninvolved in feedback control. SIGNIFICANCE STATEMENT Speech motor control is a complex activity that is thought to rely on both predictive, feedforward control as well as reactive, feedback control. While the cerebellum has been shown to be part of the speech motor control network, its functional contribution to feedback and feedforward control remains controversial. Here, we use real-time auditory perturbations of speech to show that patients with cerebellar degeneration are impaired in adapting feedforward control of speech but retain the ability to make online feedback corrections; indeed, the patients show an increased sensitivity to feedback. These results indicate that the cerebellum forms a crucial part of the feedforward control system for speech but is not essential for online, feedback control. Copyright © 2017 the authors 0270-6474/17/379249-10$15.00/0.

Examining Challenges Related to the Production of Actionable Climate Knowledge for Adaptation Decision-Making: A Focus on Climate Knowledge System Producers

NASA Astrophysics Data System (ADS)

Ernst, K.; Preston, B. L.; Tenggren, S.; Klein, R.; Gerger-Swartling, Å.

2017-12-01

Many challenges to adaptation decision-making and action have been identified across peer-reviewed and gray literature. These challenges have primarily focused on the use of climate knowledge for adaptation decision-making, the process of adaptation decision-making, and the needs of the decision-maker. Studies on climate change knowledge systems often discuss the imperative role of climate knowledge producers in adaptation decision-making processes and stress the need for producers to engage in knowledge co-production activities and to more effectively meet decision-maker needs. While the influence of climate knowledge producers on the co-production of science for adaptation decision-making is well-recognized, hardly any research has taken a direct approach to analyzing the challenges that climate knowledge producers face when undertaking science co-production. Those challenges can influence the process of knowledge production and may hinder the creation, utilization, and dissemination of actionable knowledge for adaptation decision-making. This study involves semi-structured interviews, focus groups, and participant observations to analyze, identify, and contextualize the challenges that climate knowledge producers in Sweden face as they endeavor to create effective climate knowledge systems for multiple contexts, scales, and levels across the European Union. Preliminary findings identify complex challenges related to education, training, and support; motivation, willingness, and culture; varying levels of prioritization; professional roles and responsibilities; the type and amount of resources available; and professional incentive structures. These challenges exist at varying scales and levels across individuals, organizations, networks, institutions, and disciplines. This study suggests that the creation of actionable knowledge for adaptation decision-making is not supported across scales and levels in the climate knowledge production landscape. Additionally, enabling the production of actionable knowledge for adaptation decision-making requires multi-level effort beyond the individual level.

An Intervention Based on Video Feedback and Questioning to Improve Tactical Knowledge in Expert Female Volleyball Players.

PubMed

Moreno, M Perla; Moreno, Alberto; García-González, Luis; Ureña, Aurelio; Hernández, César; Del Villar, Fernando

2016-06-01

This study applied an intervention program, based on video feedback and questioning, to expert female volleyball players to improve their tactical knowledge. The sample consisted of eight female attackers (26 ± 2.6 years old) from the Spanish National Volleyball Team, who were divided into an experimental group (n = 4) and a control group (n = 4). The video feedback and questioning program applied in the study was developed over eight reflective sessions and consisted of three phases: viewing of the selected actions, self-analysis and reflection by the attacker, and joint player-coach analysis. The attackers were videotaped in an actual game and four clips (situations) of each of the attackers were chosen for each reflective session. Two of the clips showed a correct action by the attacker, and two showed an incorrect decision. Tactical knowledge was measured by problem representation with a verbal protocol. The members of the experimental group showed adaptations in long-term memory, significantly improving their tactical knowledge. With respect to conceptual content, there was an increase in the total number of conditions verbalized by the players; with respect to conceptual sophistication, there was an increase in the indication of appropriate conditions with two or more details; and finally, with respect to conceptual structure, there was an increase in the use of double or triple conceptual structures. The intervention program, based on video feedback and questioning, in addition to on-court training sessions of expert volleyball players, appears to improve the athletes' tactical knowledge. © The Author(s) 2016.

Sensitivity of emergent sociohydrologic dynamics to internal system properties and external sociopolitical factors: Implications for water management

NASA Astrophysics Data System (ADS)

Elshafei, Y.; Tonts, M.; Sivapalan, M.; Hipsey, M. R.

2016-06-01

It is increasingly acknowledged that effective management of water resources requires a holistic understanding of the coevolving dynamics inherent in the coupled human-hydrology system. One of the fundamental information gaps concerns the sensitivity of coupled system feedbacks to various endogenous system properties and exogenous societal contexts. This paper takes a previously calibrated sociohydrology model and applies an idealized implementation, in order to: (i) explore the sensitivity of emergent dynamics resulting from bidirectional feedbacks to assumptions regarding (a) internal system properties that control the internal dynamics of the coupled system and (b) the external sociopolitical context; and (ii) interpret the results within the context of water resource management decision making. The analysis investigates feedback behavior in three ways, (a) via a global sensitivity analysis on key parameters and assessment of relevant model outputs, (b) through a comparative analysis based on hypothetical placement of the catchment along various points on the international sociopolitical gradient, and (c) by assessing the effects of various direct management intervention scenarios. Results indicate the presence of optimum windows that might offer the greatest positive impact per unit of management effort. Results further advocate management tools that encourage an adaptive learning, community-based approach with respect to water management, which are found to enhance centralized policy measures. This paper demonstrates that it is possible to use a place-based sociohydrology model to make abstractions as to the dynamics of bidirectional feedback behavior, and provide insights as to the efficacy of water management tools under different circumstances.

Decision-Making for Systemic Water Risks: Insights From a Participatory Risk Assessment Process in Vietnam

NASA Astrophysics Data System (ADS)

Wyrwoll, Paul R.; Grafton, R. Quentin; Daniell, Katherine A.; Chu, Hoang Long; Ringler, Claudia; Lien, Le Thi Ha; Khoi, Dang Kim; Do, Thang Nam; Tuan, Nguyen Do Anh

2018-03-01

Systemic threats to food-energy-environment-water systems require national policy responses. Yet complete control of these complex systems is impossible and attempts to mitigate systemic risks can generate unexpected feedback effects. Perverse outcomes from national policy can emerge from the diverse responses of decision-makers across different levels and scales of resource governance. Participatory risk assessment processes can help planners to understand subnational dynamics and ensure that policies do not undermine the resilience of social-ecological systems and infrastructure networks. Researchers can play an important role in participatory processes as both technical specialists and brokers of stakeholder knowledge on the feedbacks generated by systemic risks and policy decisions. Here, we evaluate the use of causal modeling and participatory risk assessment to develop national policy on systemic water risks. We present an application of the Risks and Options Assessment for Decision-Making (ROAD) process to a district of Vietnam where national agricultural water reforms are being piloted. The methods and results of this project provide general insights about how to support resilient decision-making, including the transfer of knowledge across administrative levels, identification of feedback effects, and the effective implementation of risk assessment processes.

Reinforcement learning for partially observable dynamic processes: adaptive dynamic programming using measured output data.

PubMed

Lewis, F L; Vamvoudakis, Kyriakos G

2011-02-01

Approximate dynamic programming (ADP) is a class of reinforcement learning methods that have shown their importance in a variety of applications, including feedback control of dynamical systems. ADP generally requires full information about the system internal states, which is usually not available in practical situations. In this paper, we show how to implement ADP methods using only measured input/output data from the system. Linear dynamical systems with deterministic behavior are considered herein, which are systems of great interest in the control system community. In control system theory, these types of methods are referred to as output feedback (OPFB). The stochastic equivalent of the systems dealt with in this paper is a class of partially observable Markov decision processes. We develop both policy iteration and value iteration algorithms that converge to an optimal controller that requires only OPFB. It is shown that, similar to Q -learning, the new methods have the important advantage that knowledge of the system dynamics is not needed for the implementation of these learning algorithms or for the OPFB control. Only the order of the system, as well as an upper bound on its "observability index," must be known. The learned OPFB controller is in the form of a polynomial autoregressive moving-average controller that has equivalent performance with the optimal state variable feedback gain.

Pedagogical Knowledge Base Underlying EFL Teachers' Provision of Oral Corrective Feedback in Grammar Instruction

ERIC Educational Resources Information Center

Atai, Mahmood Reza; Shafiee, Zahra

2017-01-01

The present study investigated the pedagogical knowledge base underlying EFL teachers' provision of oral corrective feedback in grammar instruction. More specifically, we explored the consistent thought patterns guiding the decisions of three Iranian teachers regarding oral corrective feedback on grammatical errors. We also examined the potential…

Adaptive neural network output feedback control for stochastic nonlinear systems with unknown dead-zone and unmodeled dynamics.

PubMed

Tong, Shaocheng; Wang, Tong; Li, Yongming; Zhang, Huaguang

2014-06-01

This paper discusses the problem of adaptive neural network output feedback control for a class of stochastic nonlinear strict-feedback systems. The concerned systems have certain characteristics, such as unknown nonlinear uncertainties, unknown dead-zones, unmodeled dynamics and without the direct measurements of state variables. In this paper, the neural networks (NNs) are employed to approximate the unknown nonlinear uncertainties, and then by representing the dead-zone as a time-varying system with a bounded disturbance. An NN state observer is designed to estimate the unmeasured states. Based on both backstepping design technique and a stochastic small-gain theorem, a robust adaptive NN output feedback control scheme is developed. It is proved that all the variables involved in the closed-loop system are input-state-practically stable in probability, and also have robustness to the unmodeled dynamics. Meanwhile, the observer errors and the output of the system can be regulated to a small neighborhood of the origin by selecting appropriate design parameters. Simulation examples are also provided to illustrate the effectiveness of the proposed approach.

Nonlinear filter based decision feedback equalizer for optical communication systems.

PubMed

Han, Xiaoqi; Cheng, Chi-Hao

2014-04-07

Nonlinear impairments in optical communication system have become a major concern of optical engineers. In this paper, we demonstrate that utilizing a nonlinear filter based Decision Feedback Equalizer (DFE) with error detection capability can deliver a better performance compared with the conventional linear filter based DFE. The proposed algorithms are tested in simulation using a coherent 100 Gb/sec 16-QAM optical communication system in a legacy optical network setting.

Cooperative Solutions in Multi-Person Quadratic Decision Problems: Finite-Horizon and State-Feedback Cost-Cumulant Control Paradigm

DTIC Science & Technology

2007-01-01

CONTRACT NUMBER Problems: Finite -Horizon and State-Feedback Cost-Cumulant Control Paradigm (PREPRINT) 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER...cooperative cost-cumulant control regime for the class of multi-person single-objective decision problems characterized by quadratic random costs and... finite -horizon integral quadratic cost associated with a linear stochastic system . Since this problem formation is parameterized by the number of cost

Scattering Control Using Nonlinear Smart Metasurface with Internal Feedback

NASA Astrophysics Data System (ADS)

Semenikhina, D. V.; Semenikhin, A. I.

2017-05-01

The ideology of creation of a nonlinear smart metasurface with internal feedback for the adaptive control by spectral composition of scattered field is offered. The metasurface contains a lattice of strip elements with nonlinear loads-sensors. They are included in a circuit of internal feedback for the adaptive control of scattered field. Numerically it is shown that maximal levels of the second harmonic in the spectrum of scattered far field correspond to maximum of voltage rectified on metasurface. Experimentally the prototype of the plane smart covering on the basis of the metasurface in the form of strip lattice with controlled nonlinear loads-sensors is investigated for an idea confirmation.

Effects of kinesthetic and cutaneous stimulation during the learning of a viscous force field.

PubMed

Rosati, Giulio; Oscari, Fabio; Pacchierotti, Claudio; Prattichizzo, Domenico

2014-01-01

Haptic stimulation can help humans learn perceptual motor skills, but the precise way in which it influences the learning process has not yet been clarified. This study investigates the role of the kinesthetic and cutaneous components of haptic feedback during the learning of a viscous curl field, taking also into account the influence of visual feedback. We present the results of an experiment in which 17 subjects were asked to make reaching movements while grasping a joystick and wearing a pair of cutaneous devices. Each device was able to provide cutaneous contact forces through a moving platform. The subjects received visual feedback about joystick's position. During the experiment, the system delivered a perturbation through (1) full haptic stimulation, (2) kinesthetic stimulation alone, (3) cutaneous stimulation alone, (4) altered visual feedback, or (5) altered visual feedback plus cutaneous stimulation. Conditions 1, 2, and 3 were also tested with the cancellation of the visual feedback of position error. Results indicate that kinesthetic stimuli played a primary role during motor adaptation to the viscous field, which is a fundamental premise to motor learning and rehabilitation. On the other hand, cutaneous stimulation alone appeared not to bring significant direct or adaptation effects, although it helped in reducing direct effects when used in addition to kinesthetic stimulation. The experimental conditions with visual cancellation of position error showed slower adaptation rates, indicating that visual feedback actively contributes to the formation of internal models. However, modest learning effects were detected when the visual information was used to render the viscous field.

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

ERIC Educational Resources Information Center

Strang, Harold R.

1996-01-01

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

Adaptive Disturbance Tracking Theory with State Estimation and State Feedback for Region II Control of Large Wind Turbines

NASA Technical Reports Server (NTRS)

Balas, Mark J.; Thapa Magar, Kaman S.; Frost, Susan A.

2013-01-01

A theory called Adaptive Disturbance Tracking Control (ADTC) is introduced and used to track the Tip Speed Ratio (TSR) of 5 MW Horizontal Axis Wind Turbine (HAWT). Since ADTC theory requires wind speed information, a wind disturbance generator model is combined with lower order plant model to estimate the wind speed as well as partial states of the wind turbine. In this paper, we present a proof of stability and convergence of ADTC theory with lower order estimator and show that the state feedback can be adaptive.

They all do it, will you? Event-related potential evidence of herding behavior in online peer-to-peer lending.

PubMed

Yu, Haihong; Dan, MengHan; Ma, Qingguo; Jin, Jia

2018-05-14

As herding is a typical characteristic of human behavior, many researchers have found the existence of herding behavior in online peer-to-peer lending through empirical surveys. However, the underlying neural basis of this phenomenon is still unclear. In the current study, we studied the neural activities of herding at decision-making stage and feedback stage using event-related potentials (ERPs). Our results showed that at decision-making stage, larger error related negativity (ERN) amplitude was induced under low-proportion conditions than that of high-proportion conditions. Meanwhile, during feedback stage, negative feedback elicited larger feedback related negativity (FRN) amplitude than that of positive feedback under low-proportion conditions, however, there was no significant FRN difference under high-proportion conditions. The current study suggests that herding behavior in online peer-to-peer lending is related to individual's risk perception and is possible to avoid negative emotions brought by failed investments. Copyright © 2018 Elsevier B.V. All rights reserved.

Toolbox or Adjustable Spanner? A Critical Comparison of Two Metaphors for Adaptive Decision Making

ERIC Educational Resources Information Center

Söllner, Anke; Bröder, Arndt

2016-01-01

For multiattribute decision tasks, different metaphors exist that describe the process of decision making and its adaptation to diverse problems and situations. Multiple strategy models (MSMs) assume that decision makers choose adaptively from a set of different strategies (toolbox metaphor), whereas evidence accumulation models (EAMs) hold that a…

Eco-evolutionary feedbacks, adaptive dynamics and evolutionary rescue theory

PubMed Central

Ferriere, Regis; Legendre, Stéphane

2013-01-01

Adaptive dynamics theory has been devised to account for feedbacks between ecological and evolutionary processes. Doing so opens new dimensions to and raises new challenges about evolutionary rescue. Adaptive dynamics theory predicts that successive trait substitutions driven by eco-evolutionary feedbacks can gradually erode population size or growth rate, thus potentially raising the extinction risk. Even a single trait substitution can suffice to degrade population viability drastically at once and cause ‘evolutionary suicide’. In a changing environment, a population may track a viable evolutionary attractor that leads to evolutionary suicide, a phenomenon called ‘evolutionary trapping’. Evolutionary trapping and suicide are commonly observed in adaptive dynamics models in which the smooth variation of traits causes catastrophic changes in ecological state. In the face of trapping and suicide, evolutionary rescue requires that the population overcome evolutionary threats generated by the adaptive process itself. Evolutionary repellors play an important role in determining how variation in environmental conditions correlates with the occurrence of evolutionary trapping and suicide, and what evolutionary pathways rescue may follow. In contrast with standard predictions of evolutionary rescue theory, low genetic variation may attenuate the threat of evolutionary suicide and small population sizes may facilitate escape from evolutionary traps. PMID:23209163

Public Health Climate Change Adaptation Planning Using Stakeholder Feedback.

PubMed

Eidson, Millicent; Clancy, Kathleen A; Birkhead, Guthrie S

2016-01-01

Public health climate change adaptation planning is an urgent priority requiring stakeholder feedback. The 10 Essential Public Health Services can be applied to adaptation activities. To develop a state health department climate and health adaptation plan as informed by stakeholder feedback. With Centers for Disease Control and Prevention (CDC) funding, the New York State Department of Health (NYSDOH) implemented a 2010-2013 climate and health planning process, including 7 surveys on perceptions and adaptation priorities. New York State Department of Health program managers participated in initial (n = 41, denominator unknown) and follow-up (72.2%) needs assessments. Surveillance system information was collected from 98.1% of surveillance system managers. For adaptation prioritization surveys, participants included 75.4% of NYSDOH leaders; 60.3% of local health departments (LHDs); and 53.7% of other stakeholders representing environmental, governmental, health, community, policy, academic, and business organizations. Interviews were also completed with 38.9% of other stakeholders. In 2011 surveys, 34.1% of state health program directors believed that climate change would impact their program priorities. However, 84.6% of state health surveillance system managers provided ideas for using databases for climate and health monitoring/surveillance. In 2012 surveys, 46.5% of state health leaders agreed they had sufficient information about climate and health compared to 17.1% of LHDs (P = .0046) and 40.9% of other stakeholders (nonsignificant difference). Significantly fewer (P < .0001) LHDs (22.9%) were incorporating or considering incorporating climate and health into planning compared to state health leaders (55.8%) and other stakeholders (68.2%). Stakeholder groups agreed on the 4 highest priority adaptation categories including core public health activities such as surveillance, coordination/collaboration, education, and policy development. Feedback from diverse stakeholders was utilized by NYSDOH to develop its Climate and Health Strategic Map in 2013. The CDC Building Resilience Against Climate Effects (BRACE) framework and funding provides a collaborative model for state climate and health adaptation planning.

A Study of Adaptive Relevance Feedback - UIUC TREC-2008 Relevance Feedback Experiments

DTIC Science & Technology

2008-11-01

terms. Journal of the American Society for Information Science, 27(3):129–146, 1976. [7] J . J . Rocchio. Relevance feedback in information retrieval. In...In The SMART Retrieval System: Experiments in Automatic Document Processing, pages 313–323. Prentice-Hall Inc., 1971. [8] Gerard Salton and Chris

Adaptive History Biases Result from Confidence-Weighted Accumulation of past Choices

PubMed Central

2018-01-01

Perceptual decision-making is biased by previous events, including the history of preceding choices: observers tend to repeat (or alternate) their judgments of the sensory environment more often than expected by chance. Computational models postulate that these so-called choice history biases result from the accumulation of internal decision signals across trials. Here, we provide psychophysical evidence for such a mechanism and its adaptive utility. Male and female human observers performed different variants of a challenging visual motion discrimination task near psychophysical threshold. In a first experiment, we decoupled categorical perceptual choices and motor responses on a trial-by-trial basis. Choice history bias was explained by previous perceptual choices, not motor responses, highlighting the importance of internal decision signals in action-independent formats. In a second experiment, observers performed the task in stimulus environments containing different levels of autocorrelation and providing no external feedback about choice correctness. Despite performing under overall high levels of uncertainty, observers adjusted both the strength and the sign of their choice history biases to these environments. When stimulus sequences were dominated by either repetitions or alternations, the individual degree of this adjustment of history bias was about as good a predictor of individual performance as individual perceptual sensitivity. The history bias adjustment scaled with two proxies for observers' confidence about their previous choices (accuracy and reaction time). Together, our results are consistent with the idea that action-independent, confidence-modulated decision variables are accumulated across choices in a flexible manner that depends on decision-makers' model of their environment. SIGNIFICANCE STATEMENT Decisions based on sensory input are often influenced by the history of one's preceding choices, manifesting as a bias to systematically repeat (or alternate) choices. We here provide support for the idea that such choice history biases arise from the context-dependent accumulation of a quantity referred to as the decision variable: the variable's sign dictates the choice and its magnitude the confidence about choice correctness. We show that choices are accumulated in an action-independent format and a context-dependent manner, weighted by the confidence about their correctness. This confidence-weighted accumulation of choices enables decision-makers to flexibly adjust their behavior to different sensory environments. The bias adjustment can be as important for optimizing performance as one's sensitivity to the momentary sensory input. PMID:29371318

Adaptive History Biases Result from Confidence-weighted Accumulation of Past Choices.

PubMed

Braun, Anke; Urai, Anne E; Donner, Tobias H

2018-01-25

Perceptual decision-making is biased by previous events, including the history of preceding choices: Observers tend to repeat (or alternate) their judgments of the sensory environment more often than expected by chance. Computational models postulate that these so-called choice history biases result from the accumulation of internal decision signals across trials. Here, we provide psychophysical evidence for such a mechanism and its adaptive utility. Male and female human observers performed different variants of a challenging visual motion discrimination task near psychophysical threshold. In a first experiment, we decoupled categorical perceptual choices and motor responses on a trial-by-trial basis. Choice history bias was explained by previous perceptual choices, not motor responses, highlighting the importance of internal decision signals in action-independent formats. In a second experiment, observers performed the task in stimulus environments containing different levels of auto-correlation and providing no external feedback about choice correctness. Despite performing under overall high levels of uncertainty, observers adjusted both the strength and the sign of their choice history biases to these environments. When stimulus sequences were dominated by either repetitions or alternations, the individual degree of this adjustment of history bias was about as good a predictor of individual performance as individual perceptual sensitivity. The history bias adjustment scaled with two proxies for observers' confidence about their previous choices (accuracy and reaction time). Taken together, our results are consistent with the idea that action-independent, confidence-modulated decision variables are accumulated across choices in a flexible manner that depends on decision-makers' model of their environment. Significance statement: Decisions based on sensory input are often influenced by the history of one's preceding choices, manifesting as a bias to systematically repeat (or alternate) choices. We here provide support for the idea that such choice history biases arise from the context-dependent accumulation of a quantity referred to as the decision variable: the variable's sign dictates the choice and its magnitude the confidence about choice correctness. We show that choices are accumulated in an action-independent format and a context-dependent manner, weighted by the confidence about their correctness. This confidence-weighted accumulation of choices enables decision-makers to flexibly adjust their behavior to different sensory environments. The bias adjustment can be as important for optimizing performance as one's sensitivity to the momentary sensory input. Copyright © 2018 Braun et al.

Effects of emotional preferences on value-based decision making are mediated by mentalizing not reward networks

PubMed Central

Evans, Simon; Fleming, Stephen M.; Dolan, Raymond J.; Averbeck, Bruno B.

2012-01-01

Real-world decision-making often involves social considerations. Consequently, the social value of stimuli can induce preferences in choice behavior. However, it is unknown how financial and social values are integrated in the brain. Here, we investigated how smiling and angry face stimuli interacted with financial reward feedback in a stochastically-rewarded decision-making task. Subjects reliably preferred the smiling faces despite equivalent reward feedback, demonstrating a socially driven bias. We fit a Bayesian reinforcement learning model to factor the effects of financial rewards and emotion preferences in individual subjects, and regressed model predictions on the trial-by-trial fMRI signal. Activity in the sub-callosal cingulate and the ventral striatum, both involved in reward learning, correlated with financial reward feedback, whereas the differential contribution of social value activated dorsal temporo-parietal junction and dorsal anterior cingulate cortex, previously proposed as components of a mentalizing network. We conclude that the impact of social stimuli on value-based decision processes is mediated by effects in brain regions partially separable from classical reward circuitry. PMID:20946058

Implementation of Real-Time Feedback Flow Control Algorithms on a Canonical Testbed

NASA Technical Reports Server (NTRS)

Tian, Ye; Song, Qi; Cattafesta, Louis

2005-01-01

This report summarizes the activities on "Implementation of Real-Time Feedback Flow Control Algorithms on a Canonical Testbed." The work summarized consists primarily of two parts. The first part summarizes our previous work and the extensions to adaptive ID and control algorithms. The second part concentrates on the validation of adaptive algorithms by applying them to a vibration beam test bed. Extensions to flow control problems are discussed.

Adaptive positive position feedback control with a feedforward compensator of a magnetostrictive beam for vibration suppression

NASA Astrophysics Data System (ADS)

Bian, Leixiang; Zhu, Wei

2018-07-01

In this paper, a Fe–Ga alloy magnetostrictive beam is designed as an actuator to restrain the vibration of a supported mass. Dynamic modeling of the system based on the transfer matrix method of multibody system is first shown, and then a hybrid controller is developed to achieve vibration control. The proposed vibration controller combines a multi-mode adaptive positive position feedback (APPF) with a feedforward compensator. In the APPF control, an adaptive natural frequency estimator based on the recursive least-square method is developed to be used. In the feedforward compensator, the hysteresis of the magnetostrictive beam is linearized based on a Bouc–Wen model. The further remarkable vibration suppression capability of the proposed hybrid controller is demonstrated experimentally and compared with the positive position feedback controller. Experiment results show that the proposed controller is applicable to the magnetostrictive beam for improving vibration control effectiveness.

Fuzzy Adaptive Output Feedback Control of Uncertain Nonlinear Systems With Prescribed Performance.

PubMed

Zhang, Jin-Xi; Yang, Guang-Hong

2018-05-01

This paper investigates the tracking control problem for a family of strict-feedback systems in the presence of unknown nonlinearities and immeasurable system states. A low-complexity adaptive fuzzy output feedback control scheme is proposed, based on a backstepping method. In the control design, a fuzzy adaptive state observer is first employed to estimate the unmeasured states. Then, a novel error transformation approach together with a new modification mechanism is introduced to guarantee the finite-time convergence of the output error to a predefined region and ensure the closed-loop stability. Compared with the existing methods, the main advantages of our approach are that: 1) without using extra command filters or auxiliary dynamic surface control techniques, the problem of explosion of complexity can still be addressed and 2) the design procedures are independent of the initial conditions. Finally, two practical examples are performed to further illustrate the above theoretic findings.

Sensorimotor adaptation is influenced by background music.

PubMed

Bock, Otmar

2010-06-01

It is well established that listening to music can modify subjects' cognitive performance. The present study evaluates whether this so-called Mozart Effect extends beyond cognitive tasks and includes sensorimotor adaptation. Three subject groups listened to musical pieces that in the author's judgment were serene, neutral, or sad, respectively. This judgment was confirmed by the subjects' introspective reports. While listening to music, subjects engaged in a pointing task that required them to adapt to rotated visual feedback. All three groups adapted successfully, but the speed and magnitude of adaptive improvement was more pronounced with serene music than with the other two music types. In contrast, aftereffects upon restoration of normal feedback were independent of music type. These findings support the existence of a "Mozart effect" for strategic movement control, but not for adaptive recalibration. Possibly, listening to music modifies neural activity in an intertwined cognitive-emotional network.

Learning-Based Adaptive Optimal Tracking Control of Strict-Feedback Nonlinear Systems.

PubMed

Gao, Weinan; Jiang, Zhong-Ping; Weinan Gao; Zhong-Ping Jiang; Gao, Weinan; Jiang, Zhong-Ping

2018-06-01

This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods. This paper proposes a novel policy iteration technique for solving positive semidefinite HJB equations with rigorous convergence analysis. A two-phase data-driven learning method is developed and implemented online by ADP. The efficacy of the proposed adaptive optimal tracking control methodology is demonstrated via a Van der Pol oscillator with time-varying exogenous signals.

Age-Related Changes in Decision Making: Comparing Informed and Noninformed Situations

ERIC Educational Resources Information Center

Van Duijvenvoorde, Anna C. K.; Jansen, Brenda R. J.; Bredman, Joren C.; Huizenga, Hilde M.

2012-01-01

Advantageous decision making progressively develops into early adulthood, most specifically in complex and motivationally salient decision situations in which direct feedback on gains and losses is provided (Figner & Weber, 2011). However, the factors that underlie this developmental improvement in decision making are still not well understood.…

Echolocating bats rely on audiovocal feedback to adapt sonar signal design.

PubMed

Luo, Jinhong; Moss, Cynthia F

2017-10-10

Many species of bat emit acoustic signals and use information carried by echoes reflecting from nearby objects to navigate and forage. It is widely documented that echolocating bats adjust the features of sonar calls in response to echo feedback; however, it remains unknown whether audiovocal feedback contributes to sonar call design. Audiovocal feedback refers to the monitoring of one's own vocalizations during call production and has been intensively studied in nonecholocating animals. Audiovocal feedback not only is a necessary component of vocal learning but also guides the control of the spectro-temporal structure of vocalizations. Here, we show that audiovocal feedback is directly involved in the echolocating bat's control of sonar call features. As big brown bats tracked targets from a stationary position, we played acoustic jamming signals, simulating calls of another bat, timed to selectively perturb audiovocal feedback or echo feedback. We found that the bats exhibited the largest call-frequency adjustments when the jamming signals occurred during vocal production. By contrast, bats did not show sonar call-frequency adjustments when the jamming signals coincided with the arrival of target echoes. Furthermore, bats rapidly adapted sonar call design in the first vocalization following the jamming signal, revealing a response latency in the range of 66 to 94 ms. Thus, bats, like songbirds and humans, rely on audiovocal feedback to structure sonar signal design.

Augmented feedback of COM and COP modulates the regulation of quiet human standing relative to the stability boundary.

PubMed

Kilby, Melissa C; Slobounov, Semyon M; Newell, Karl M

2016-06-01

The experiment manipulated real-time kinematic feedback of the motion of the whole body center of mass (COM) and center of pressure (COP) in anterior-posterior (AP) and medial-lateral (ML) directions to investigate the variables actively controlled in quiet standing of young adults. The feedback reflected the current 2D postural positions within the 2D functional stability boundary that was scaled to 75%, 30% and 12% of its original size. The findings showed that the distance of both COP and COM to the respective stability boundary was greater during the feedback trials compared to a no feedback condition. However, the temporal safety margin of the COP, that is, the virtual time-to-contact (VTC), was higher without feedback. The coupling relation of COP-COM showed stable in-phase synchronization over all of the feedback conditions for frequencies below 1Hz. For higher frequencies (up to 5Hz), there was progressive reduction of COP-COM synchronization and local adaptation under the presence of augmented feedback. The findings show that the augmented feedback of COM and COP motion differentially and adaptively influences spatial and temporal properties of postural motion relative to the stability boundary while preserving the organization of the COM-COP coupling in postural control. Copyright © 2016. Published by Elsevier B.V.

Adaptation to delayed auditory feedback induces the temporal recalibration effect in both speech perception and production.

PubMed

Yamamoto, Kosuke; Kawabata, Hideaki

2014-12-01

We ordinarily speak fluently, even though our perceptions of our own voices are disrupted by various environmental acoustic properties. The underlying mechanism of speech is supposed to monitor the temporal relationship between speech production and the perception of auditory feedback, as suggested by a reduction in speech fluency when the speaker is exposed to delayed auditory feedback (DAF). While many studies have reported that DAF influences speech motor processing, its relationship to the temporal tuning effect on multimodal integration, or temporal recalibration, remains unclear. We investigated whether the temporal aspects of both speech perception and production change due to adaptation to the delay between the motor sensation and the auditory feedback. This is a well-used method of inducing temporal recalibration. Participants continually read texts with specific DAF times in order to adapt to the delay. Then, they judged the simultaneity between the motor sensation and the vocal feedback. We measured the rates of speech with which participants read the texts in both the exposure and re-exposure phases. We found that exposure to DAF changed both the rate of speech and the simultaneity judgment, that is, participants' speech gained fluency. Although we also found that a delay of 200 ms appeared to be most effective in decreasing the rates of speech and shifting the distribution on the simultaneity judgment, there was no correlation between these measurements. These findings suggest that both speech motor production and multimodal perception are adaptive to temporal lag but are processed in distinct ways.

Performing a reaching task with one arm while adapting to a visuomotor rotation with the other can lead to complete transfer of motor learning across the arms

PubMed Central

Lei, Yuming; Binder, Jeffrey R.

2015-01-01

The extent to which motor learning is generalized across the limbs is typically very limited. Here, we investigated how two motor learning hypotheses could be used to enhance the extent of interlimb transfer. According to one hypothesis, we predicted that reinforcement of successful actions by providing binary error feedback regarding task success or failure, in addition to terminal error feedback, during initial training would increase the extent of interlimb transfer following visuomotor adaptation (experiment 1). According to the other hypothesis, we predicted that performing a reaching task repeatedly with one arm without providing performance feedback (which prevented learning the task with this arm), while concurrently adapting to a visuomotor rotation with the other arm, would increase the extent of transfer (experiment 2). Results indicate that providing binary error feedback, compared with continuous visual feedback that provided movement direction and amplitude information, had no influence on the extent of transfer. In contrast, repeatedly performing (but not learning) a specific task with one arm while visuomotor adaptation occurred with the other arm led to nearly complete transfer. This suggests that the absence of motor instances associated with specific effectors and task conditions is the major reason for limited interlimb transfer and that reinforcement of successful actions during initial training is not beneficial for interlimb transfer. These findings indicate crucial contributions of effector- and task-specific motor instances, which are thought to underlie (a type of) model-free learning, to optimal motor learning and interlimb transfer. PMID:25632082

A Symbiotic Brain-Machine Interface through Value-Based Decision Making

PubMed Central

Mahmoudi, Babak; Sanchez, Justin C.

2011-01-01

Background In the development of Brain Machine Interfaces (BMIs), there is a great need to enable users to interact with changing environments during the activities of daily life. It is expected that the number and scope of the learning tasks encountered during interaction with the environment as well as the pattern of brain activity will vary over time. These conditions, in addition to neural reorganization, pose a challenge to decoding neural commands for BMIs. We have developed a new BMI framework in which a computational agent symbiotically decoded users' intended actions by utilizing both motor commands and goal information directly from the brain through a continuous Perception-Action-Reward Cycle (PARC). Methodology The control architecture designed was based on Actor-Critic learning, which is a PARC-based reinforcement learning method. Our neurophysiology studies in rat models suggested that Nucleus Accumbens (NAcc) contained a rich representation of goal information in terms of predicting the probability of earning reward and it could be translated into an evaluative feedback for adaptation of the decoder with high precision. Simulated neural control experiments showed that the system was able to maintain high performance in decoding neural motor commands during novel tasks or in the presence of reorganization in the neural input. We then implanted a dual micro-wire array in the primary motor cortex (M1) and the NAcc of rat brain and implemented a full closed-loop system in which robot actions were decoded from the single unit activity in M1 based on an evaluative feedback that was estimated from NAcc. Conclusions Our results suggest that adapting the BMI decoder with an evaluative feedback that is directly extracted from the brain is a possible solution to the problem of operating BMIs in changing environments with dynamic neural signals. During closed-loop control, the agent was able to solve a reaching task by capturing the action and reward interdependency in the brain. PMID:21423797

Pupil dilation signals uncertainty and surprise in a learning gambling task.

PubMed

Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo

2013-01-01

Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes' feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans.

Pupil dilation signals uncertainty and surprise in a learning gambling task

PubMed Central

Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo

2014-01-01

Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes’ feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans. PMID:24427126

Energy management and attitude control for spacecraft

NASA Astrophysics Data System (ADS)

Costic, Bret Thomas

2001-07-01

This PhD dissertation describes the design and implementation of various control strategies centered around spacecraft applications: (i) an attitude control system for spacecraft, (ii) flywheels used for combined attitude and energy tracking, and (iii) an adaptive autobalancing control algorithm. The theory found in each of these sections is demonstrated through simulation or experimental results. An introduction to each of these three primary chapters can be found in chapter one. The main problem addressed in the second chapter is the quaternion-based, attitude tracking control of rigid spacecraft without angular velocity measurements and in the presence of an unknown inertia matrix. As a stepping-stone, an adaptive, full-state feedback controller that compensates for parametric uncertainty while ensuring asymptotic attitude tracking errors is designed. The adaptive, full-state feedback controller is then redesigned such that the need for angular velocity measurements is eliminated. The proposed adaptive, output feedback controller ensures asymptotic attitude tracking. This work uses a four-parameter representation of the spacecraft attitude that does not exhibit singular orientations as in the case of the previous three-parameter representation-based results. To the best of my knowledge, this represents the first solution to the adaptive, output feedback, attitude tracking control problem for the quaternion representation. Simulation results are included to illustrate the performance of the proposed output feedback control strategy. The third chapter is devoted to the use of multiple flywheels that integrate the energy storage and attitude control functions in space vehicles. This concept, which is referred to as an Integrated Energy Management and Attitude Control (IEMAC) system, reduces the space vehicle bus mass, volume, cost, and maintenance requirements while maintaining or improving the space vehicle performance. To this end, two nonlinear IEMAC strategies (model-based and adaptive) that simultaneously track a desired attitude trajectory and desired energy/power profile are presented. Both strategies ensure asymptotic tracking while the adaptive controller compensates for uncertain spacecraft inertia. In the final chapter, a control strategy is designed for a rotating, unbalanced disk. The control strategy, which is composed of a control torque and two control forces, regulates the disk displacement and ensures angular velocity tracking. The controller uses a desired compensation adaptation law and a gain adjusted forgetting factor to achieve exponential stability despite the lack of knowledge of the imbalance-related parameters, provided a mild persistency of excitation condition is satisfied.

A framework to investigate drivers of adaptation decisions in marine fishing: Evidence from urban, semi-urban and rural communities.

PubMed

Malakar, Krishna; Mishra, Trupti; Patwardhan, Anand

2018-05-11

Traditional fishing livelihoods need to adapt to changing fish catch/populations, led by numerous anthropogenic, environmental and climatic stressors. The decision to adapt can be influenced by a variety of socio-economic and perceptual factors. However, adaptation decision-making in fishing communities has rarely been studied. Based on previous literature and focus group discussions with community, this study identifies few prominent adaptation responses in marine fishing and proposes credible factors driving decisions to adopt them. Further, a household survey is conducted, and the association of these drivers with various adaptation strategies is examined among fisherfolk of Maharashtra (India). This statistical analysis is based on 601 responses collected across three regional fishing groups: urban, semi-urban and rural. Regional segregation is done to understand variability in decision-making among groups which might be having different socio-economic and perceptual attributes. The survey reveals that only few urban fishing households have been able to diversify into other livelihoods. While having economic capital increases the likelihood of adaptation among urban and semi-urban communities, rural fishermen are significantly driven by social capital. Perception of climate change affecting fish catch drives adoption of mechanized boats solely in urban region. But increasing number of extreme events affects decisions of semi-urban and rural fishermen. Further, rising pollution and trade competition is associated with adaptation responses in the urban and semi-urban community. Higher education might help fishermen choose convenient forms of adaptation. Also, cooperative membership and subsidies are critical in adaptation decisions. The framework and insights of the study suggest the importance of acknowledging differential decision-making of individuals and communities, for designing effective adaptation and capacity-building policies. Copyright © 2018 Elsevier B.V. All rights reserved.

Survey Feedback as an Organization Development Strategy in a Public School District.

ERIC Educational Resources Information Center

Rosenbach, William E.; And Others

1983-01-01

Survey feedback can be applied as an organization development (OD) technique in public school systems. The technique, if suited to goals of an OD effort, can result in multiple positive outcomes. In addition to improvements characteristic of OD, the results of survey feedback can be utilized in making strategic decisions. (Author/MH)

Development of a methodology for selecting criteria and indicators of sustainable forest management: a case study on participatory assessment.

PubMed

Mendoza, G A; Prabhu, R

2000-12-01

This paper describes an application of multiple criteria analysis (MCA) in assessing criteria and indicators adapted for a particular forest management unit. The methods include: ranking, rating, and pairwise comparisons. These methods were used in a participatory decision-making environment where a team representing various stakeholders and professionals used their expert opinions and judgements in assessing different criteria and indicators (C&I) on the one hand, and how suitable and applicable they are to a forest management unit on the other. A forest concession located in Kalimantan, Indonesia, was used as the site for the case study. Results from the study show that the multicriteria methods are effective tools that can be used as structured decision aids to evaluate, prioritize, and select sets of C&I for a particular forest management unit. Ranking and rating approaches can be used as a screening tool to develop an initial list of C&I. Pairwise comparison, on the other hand, can be used as a finer filter to further reduce the list. In addition to using these three MCA methods, the study also examines two commonly used group decision-making techniques, the Delphi method and the nominal group technique. Feedback received from the participants indicates that the methods are transparent, easy to implement, and provide a convenient environment for participatory decision-making.

Feasibility and acceptability of shared decision-making to promote alcohol behavior change among women Veterans: Results from focus groups.

PubMed

Abraham, Traci H; Wright, Patricia; White, Penny; Booth, Brenda M; Cucciare, Michael A

2017-01-01

Although rates of unhealthy drinking are high among women Veterans with mental health comorbidities, most women Veterans with mental comorbidities who present to primary care with unhealthy drinking do not receive alcohol-related care. Barriers to alcohol-related treatment could be reduced through patient-centered approaches to care, such as shared decision-making. We assessed the feasibility and acceptability of a telephone-delivered shared decision-making intervention for promoting alcohol behavior change in women Veterans with unhealthy drinking and co-morbid depression and/or probable post-traumatic stress disorder. We used 3, 2-hour focus group discussions with 19 women Veterans to identify barriers and solicit recommendations for using the intervention with women Veterans who present to primary care with unhealthy drinking and mental health comorbidities. Transcripts from the focus groups were qualitatively analyzed using template analysis. Although participants perceived that the intervention was feasible and acceptable for the targeted patient population, they identified the treatment delivery modality, length of telephone sessions, and some of the option grid content as potential barriers. Facilitators included strategies for enhancing the telephone-delivered shared decision-making sessions and diversifying the treatment options contained in the option grids. Focus group feedback resulted in preliminary adaptations to the intervention that are mindful of women Veterans' individual preferences for care and realistic in the everyday context of their busy lives.

Interference and Shaping in Sensorimotor Adaptations with Rewards

PubMed Central

Darshan, Ran; Leblois, Arthur; Hansel, David

2014-01-01

When a perturbation is applied in a sensorimotor transformation task, subjects can adapt and maintain performance by either relying on sensory feedback, or, in the absence of such feedback, on information provided by rewards. For example, in a classical rotation task where movement endpoints must be rotated to reach a fixed target, human subjects can successfully adapt their reaching movements solely on the basis of binary rewards, although this proves much more difficult than with visual feedback. Here, we investigate such a reward-driven sensorimotor adaptation process in a minimal computational model of the task. The key assumption of the model is that synaptic plasticity is gated by the reward. We study how the learning dynamics depend on the target size, the movement variability, the rotation angle and the number of targets. We show that when the movement is perturbed for multiple targets, the adaptation process for the different targets can interfere destructively or constructively depending on the similarities between the sensory stimuli (the targets) and the overlap in their neuronal representations. Destructive interferences can result in a drastic slowdown of the adaptation. As a result of interference, the time to adapt varies non-linearly with the number of targets. Our analysis shows that these interferences are weaker if the reward varies smoothly with the subject's performance instead of being binary. We demonstrate how shaping the reward or shaping the task can accelerate the adaptation dramatically by reducing the destructive interferences. We argue that experimentally investigating the dynamics of reward-driven sensorimotor adaptation for more than one sensory stimulus can shed light on the underlying learning rules. PMID:24415925

Modeling Common-Sense Decisions

NASA Astrophysics Data System (ADS)

Zak, Michail

This paper presents a methodology for efficient synthesis of dynamical model simulating a common-sense decision making process. The approach is based upon the extension of the physics' First Principles that includes behavior of living systems. The new architecture consists of motor dynamics simulating actual behavior of the object, and mental dynamics representing evolution of the corresponding knowledge-base and incorporating it in the form of information flows into the motor dynamics. The autonomy of the decision making process is achieved by a feedback from mental to motor dynamics. This feedback replaces unavailable external information by an internal knowledgebase stored in the mental model in the form of probability distributions.

Robust adaptive fuzzy tracking control for pure-feedback stochastic nonlinear systems with input constraints.

PubMed

Wang, Huanqing; Chen, Bing; Liu, Xiaoping; Liu, Kefu; Lin, Chong

2013-12-01

This paper is concerned with the problem of adaptive fuzzy tracking control for a class of pure-feedback stochastic nonlinear systems with input saturation. To overcome the design difficulty from nondifferential saturation nonlinearity, a smooth nonlinear function of the control input signal is first introduced to approximate the saturation function; then, an adaptive fuzzy tracking controller based on the mean-value theorem is constructed by using backstepping technique. The proposed adaptive fuzzy controller guarantees that all signals in the closed-loop system are bounded in probability and the system output eventually converges to a small neighborhood of the desired reference signal in the sense of mean quartic value. Simulation results further illustrate the effectiveness of the proposed control scheme.

Effects of video-feedback intervention on harmonious parent-child interaction and sensitive discipline of parents with intellectual disabilities: A randomized controlled trial.

PubMed

Hodes, M W; Meppelder, M; de Moor, M; Kef, S; Schuengel, C

2018-03-01

This study tested whether video-feedback intervention based on attachment and coercion theory increased harmonious parent-child interaction and sensitive discipline of parents with mild intellectual disabilities or borderline intellectual functioning. Observer ratings of video-recorded structured interaction tasks at home formed pretest, post-test, and 3-month follow-up outcome data in a randomized controlled trial with 85 families. Repeated measures analyses of variance and covariance were conducted to test for the intervention effect and possible moderation by IQ and adaptive functioning. The intervention effect on harmonious parent-child interaction was conditional on parental social adaptive behaviour at pretest, with lower adaptive functioning associated with stronger intervention benefit at post-test and follow-up compared to care as usual. Intervention effects were not conditional on parental IQ. Intervention effects for sensitive discipline were not found. Although the video-feedback intervention did not affect observed parenting for the average parent, it may benefit interaction between children and parents with lower parental adaptive functioning. © 2017 John Wiley & Sons Ltd.

Intelligent robust tracking control for a class of uncertain strict-feedback nonlinear systems.

PubMed

Chang, Yeong-Chan

2009-02-01

This paper addresses the problem of designing robust tracking controls for a large class of strict-feedback nonlinear systems involving plant uncertainties and external disturbances. The input and virtual input weighting matrices are perturbed by bounded time-varying uncertainties. An adaptive fuzzy-based (or neural-network-based) dynamic feedback tracking controller will be developed such that all the states and signals of the closed-loop system are bounded and the trajectory tracking error should be as small as possible. First, the adaptive approximators with linearly parameterized models are designed, and a partitioned procedure with respect to the developed adaptive approximators is proposed such that the implementation of the fuzzy (or neural network) basis functions depends only on the state variables but does not depend on the tuning approximation parameters. Furthermore, we extend to design the nonlinearly parameterized adaptive approximators. Consequently, the intelligent robust tracking control schemes developed in this paper possess the properties of computational simplicity and easy implementation. Finally, simulation examples are presented to demonstrate the effectiveness of the proposed control algorithms.

Physician Attitudes toward Adopting Genome-Guided Prescribing through Clinical Decision Support

PubMed Central

Overby, Casey Lynnette; Erwin, Angelika Ludtke; Abul-Husn, Noura S.; Ellis, Stephen B.; Scott, Stuart A.; Obeng, Aniwaa Owusu; Kannry, Joseph L.; Hripcsak, George; Bottinger, Erwin P.; Gottesman, Omri

2014-01-01

This study assessed physician attitudes toward adopting genome-guided prescribing through clinical decision support (CDS), prior to enlisting in the Clinical Implementation of Personalized Medicine through Electronic Health Records and Genomics pilot pharmacogenomics project (CLIPMERGE PGx). We developed a survey instrument that includes the Evidence Based Practice Attitude Scale, adapted to measure attitudes toward adopting genome-informed interventions (EBPAS-GII). The survey also includes items to measure physicians’ characteristics (awareness, experience, and perceived usefulness), attitudes about personal genome testing (PGT) services, and comfort using technology. We surveyed 101 General Internal Medicine physicians from the Icahn School of Medicine at Mount Sinai (ISMMS). The majority were residency program trainees (~88%). Prior to enlisting into CLIPMERGE PGx, most physicians were aware of and had used decision support aids. Few physicians, however, were aware of and had used genome-guided prescribing. The majority of physicians viewed decision support aids and genotype data as being useful for making prescribing decisions. Most physicians had not heard of, but were willing to use, PGT services and felt comfortable interpreting PGT results. Most physicians were comfortable with technology. Physicians who perceived genotype data to be useful in making prescribing decisions, had more positive attitudes toward adopting genome-guided prescribing through CDS. Our findings suggest that internal medicine physicians have a deficit in their familiarity and comfort interpreting and using genomic information. This has reinforced the importance of gathering feedback and guidance from our enrolled physicians when designing genome-guided CDS and the importance of prioritizing genomic medicine education at our institutions. PMID:25562141

Higher Trait Psychopathy Is Associated with Increased Risky Decision-Making and Less Coincident Insula and Striatal Activity

PubMed Central

Sutherland, Matthew T.; Fishbein, Diana H.

2017-01-01

Higher trait levels of psychopathy have been associated with both a tendency to maintain disadvantageous decision-making strategies and aberrant cortico-limbic neural activity. To explore the neural mechanisms associated with the psychopathy-related propensity to continue selecting risky choices, a non-forensic sample of participants completed a self-report psychopathy questionnaire and two runs of a risky decision-making task during H215O positron emission tomography (PET) scanning. In this secondary data analysis study, we leveraged data previously collected to examine the impact of previous drug use on risky decision-making to explore the relations between self-reported psychopathy and behavioral and brain metrics during performance of the Cambridge Decision-Making Task (CDMT), in which volunteers chose between small/likely or large/unlikely potential reward outcomes. Behaviorally, we observed that psychopathy scores were differentially correlated with the percent of risky decisions made in run 1 vs. run 2 of the task. Specifically, higher levels of psychopathy, above and beyond that attributable to drug use or sex, were associated with greater tendencies to make risky selections only in the second half (run 2) of the task. In parallel, psychopathy scores negatively correlated with regional cerebral blood flow (rCBF) in the right insula and right ventral striatum during run 2 of the CDMT. These exploratory outcomes suggest that greater levels of psychopathy may be associated with an inability to translate experience with negative outcomes into behavioral adaptations possibly due to decreased neural efficiency in regions related to somatic and/or reward feedback processes. PMID:29311863

Adaptive hybrid control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

Simple methods for the design of adaptive force and position controllers for robot manipulators within the hybrid control architecuture is presented. The force controller is composed of an adaptive PID feedback controller, an auxiliary signal and a force feedforward term, and it achieves tracking of desired force setpoints in the constraint directions. The position controller consists of adaptive feedback and feedforward controllers and an auxiliary signal, and it accomplishes tracking of desired position trajectories in the free directions. The controllers are capable of compensating for dynamic cross-couplings that exist between the position and force control loops in the hybrid control architecture. The adaptive controllers do not require knowledge of the complex dynamic model or parameter values of the manipulator or the environment. The proposed control schemes are computationally fast and suitable for implementation in on-line control with high sampling rates.

Grand challenges in understanding the interplay of climate and land changes

DOE PAGES

Liu, Shuguang; Bond-Lamberty, Ben; Boysen, Lena R.; ...

2017-03-28

Half of the Earth s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affects a myriad of land surface processes and our adaptation behaviors. We here review the status and major knowledge gaps of studying the interactions of land and atmospheric changes and present eleven grand challenge areas for scientific research and adaptation communities in the coming decade: (1) collective and separate impacts of major land changes and the interactions with non-land-change factors such as atmospheric CO2 increase, (2) carbon and other biogeochemicalmore » cycles, (3) climatically relevant biospheric emissions such as aerosols, (4) water cycle, (5) agriculture, (6) urbanization, (7) gradual acclimation of plants, communities, and ecosystems to climate and environmental changes, (8) plant migration, (9) land use projections, (10) reduction of uncertainties in models and data, and finally (11) adaptation strategies. We conclude that we need to create and maintain a close cross-disciplinary coordination between measurements and process representation in models to analyze complex multi-facet interrelated perturbations and feedbacks between land and climate changes. Along with major scientific research thrusts, land-use and land cover change mitigation and adaptation assessments should be strengthened to identify barriers that need to be overcome, evaluate and prioritize opportunities, and examine how decision making processes work in specific contexts.« less

Grand challenges in understanding the interplay of climate and land changes

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

Liu, Shuguang; Bond-Lamberty, Ben; Boysen, Lena R.

Half of the Earth s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affects a myriad of land surface processes and our adaptation behaviors. We here review the status and major knowledge gaps of studying the interactions of land and atmospheric changes and present eleven grand challenge areas for scientific research and adaptation communities in the coming decade: (1) collective and separate impacts of major land changes and the interactions with non-land-change factors such as atmospheric CO2 increase, (2) carbon and other biogeochemicalmore » cycles, (3) climatically relevant biospheric emissions such as aerosols, (4) water cycle, (5) agriculture, (6) urbanization, (7) gradual acclimation of plants, communities, and ecosystems to climate and environmental changes, (8) plant migration, (9) land use projections, (10) reduction of uncertainties in models and data, and finally (11) adaptation strategies. We conclude that we need to create and maintain a close cross-disciplinary coordination between measurements and process representation in models to analyze complex multi-facet interrelated perturbations and feedbacks between land and climate changes. Along with major scientific research thrusts, land-use and land cover change mitigation and adaptation assessments should be strengthened to identify barriers that need to be overcome, evaluate and prioritize opportunities, and examine how decision making processes work in specific contexts.« less

Counterfactual Evaluation of Outcomes in Social Risk Decision-Making Situations: The Cognitive Developmental Paradox Revisited.

PubMed

Padrón, Iván; Rodrigo, María Jose; de Vega, Manuel

2016-01-01

We report a study that examined the existence of a cognitive developmental paradox in the counterfactual evaluation of decision-making outcomes. According to this paradox adolescents and young adults could be able to apply counterfactual reasoning and, yet, their counterfactual evaluation of outcomes could be biased in a salient socio-emotional context. To this aim, we analyzed the impact of health and social feedback on the counterfactual evaluation of outcomes in a laboratory decision-making task involving short narratives with the presence of peers. Forty risky (e.g., taking or refusing a drug), forty neutral decisions (e.g., eating a hamburger or a hotdog), and emotions felt following positive or negative outcomes were examined in 256 early, mid- and late adolescents, and young adults, evenly distributed. Results showed that emotional ratings to negative outcomes (regret and disappointment) but not to positive outcomes (relief and elation) were attenuated when feedback was provided. Evidence of development of cognitive decision-making capacities did also exist, as the capacity to perform faster emotional ratings and to differentially allocate more resources to the elaboration of emotional ratings when no feedback information was available increased with age. Overall, we interpret these findings as challenging the traditional cognitive developmental assumption that development necessarily proceeds from lesser to greater capacities, reflecting the impact of socio-emotional processes that could bias the counterfactual evaluation of social decision-making outcomes.

Bringing a Time-Depth Perspective to Collective Animal Behaviour.

PubMed

Biro, Dora; Sasaki, Takao; Portugal, Steven J

2016-07-01

The field of collective animal behaviour examines how relatively simple, local interactions between individuals in groups combine to produce global-level outcomes. Existing mathematical models and empirical work have identified candidate mechanisms for numerous collective phenomena but have typically focused on one-off or short-term performance. We argue that feedback between collective performance and learning - giving the former the capacity to become an adaptive, and potentially cumulative, process - is a currently poorly explored but crucial mechanism in understanding collective systems. We synthesise material ranging from swarm intelligence in social insects through collective movements in vertebrates to collective decision making in animal and human groups, to propose avenues for future research to identify the potential for changes in these systems to accumulate over time. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nonlinear adaptive control of an elastic robotic arm

NASA Technical Reports Server (NTRS)

Singh, S. N.

1986-01-01

An approach to control of a class of nonlinear flexible robotic systems is presented. For simplicity, a robot arm (PUMA-type) with three rotational joints is considered. The third link is assumed to be elastic. An adaptive torquer control law is derived for controlling the joint angles. This controller includes a dynamic system in the feedback path, requires only joint angle and rate for feedback, and asymptotically decomposes the elastic dynamics into two subsystems representing the transverse vibrations of the elastic link in two orthogonal planes. To damp out the elastic vibration, a force control law using modal feedback is synthesized. The combination of the torque and force control laws accomplishes joint angle control and elastic mode stabilization.

A coupled human-natural systems analysis of irrigated agriculture under changing climate

NASA Astrophysics Data System (ADS)

Giuliani, M.; Li, Y.; Castelletti, A.; Gandolfi, C.

2016-09-01

Exponentially growing water demands and increasingly uncertain hydrologic regimes due to changes in climate and land use are challenging the sustainability of agricultural water systems. Farmers must adapt their management strategies in order to secure food production and avoid crop failures. Investigating the potential for adaptation policies in agricultural systems requires accounting for their natural and human components, along with their reciprocal interactions. Yet this feedback is generally overlooked in the water resources systems literature. In this work, we contribute a novel modeling approach to study the coevolution of irrigated agriculture under changing climate, advancing the representation of the human component within agricultural systems by using normative meta-models to describe the behaviors of groups of farmers or institutional decisions. These behavioral models, validated against observational data, are then integrated into a coupled human-natural system simulation model to better represent both systems and their coevolution under future changing climate conditions, assuming the adoption of different policy adaptation options, such as cultivating less water demanding crops. The application to the pilot study of the Adda River basin in northern Italy shows that the dynamic coadaptation of water supply and demand allows farmers to avoid estimated potential losses of more than 10 M€/yr under projected climate changes, while unilateral adaptation of either the water supply or the demand are both demonstrated to be less effective. Results also show that the impact of the different policy options varies as function of drought intensity, with water demand adaptation outperforming water supply adaptation when drought conditions become more severe.

Advances in adaptive control theory: Gradient- and derivative-free approaches

NASA Astrophysics Data System (ADS)

Yucelen, Tansel

In this dissertation, we present new approaches to improve standard designs in adaptive control theory, and novel adaptive control architectures. We first present a novel Kalman filter based approach for approximately enforcing a linear constraint in standard adaptive control design. One application is that this leads to alternative forms for well known modification terms such as e-modification. In addition, it leads to smaller tracking errors without incurring significant oscillations in the system response and without requiring high modification gain. We derive alternative forms of e- and adaptive loop recovery (ALR-) modifications. Next, we show how to use Kalman filter optimization to derive a novel adaptation law. This results in an optimization-based time-varying adaptation gain that reduces the need for adaptation gain tuning. A second major contribution of this dissertation is the development of a novel derivative-free, delayed weight update law for adaptive control. The assumption of constant unknown ideal weights is relaxed to the existence of time-varying weights, such that fast and possibly discontinuous variation in weights are allowed. This approach is particulary advantageous for applications to systems that can undergo a sudden change in dynamics, such as might be due to reconfiguration, deployment of a payload, docking, or structural damage, and for rejection of external disturbance processes. As a third and final contribution, we develop a novel approach for extending all the methods developed in this dissertation to the case of output feedback. The approach is developed only for the case of derivative-free adaptive control, and the extension of the other approaches developed previously for the state feedback case to output feedback is left as a future research topic. The proposed approaches of this dissertation are illustrated in both simulation and flight test.

Development of an Integrated Team Training Design and Assessment Architecture to Support Adaptability in Healthcare Teams

DTIC Science & Technology

2016-10-01

and implementation of embedded, adaptive feedback and performance assessment. The investigators also initiated work designing a Bayesian Belief ...training; Teamwork; Adaptive performance; Leadership; Simulation; Modeling; Bayesian belief networks (BBN) 16. SECURITY CLASSIFICATION OF: 17. LIMITATION...Trauma teams Team training Teamwork Adaptability Adaptive performance Leadership Simulation Modeling Bayesian belief networks (BBN) 6

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-01-01

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

More heads choose better than one: Group decision making can eliminate probability matching.

PubMed

Schulze, Christin; Newell, Ben R

2016-06-01

Probability matching is a robust and common failure to adhere to normative predictions in sequential decision making. We show that this choice anomaly is nearly eradicated by gathering individual decision makers into small groups and asking the groups to decide. The group choice advantage emerged both when participants generated responses for an entire sequence of choices without outcome feedback (Exp. 1a) and when participants made trial-by-trial predictions with outcome feedback after each decision (Exp. 1b). We show that the dramatic improvement observed in group settings stands in stark contrast to a complete lack of effective solitary deliberation. These findings suggest a crucial role of group discussion in alleviating the impact of hasty intuitive responses in tasks better suited to careful deliberation.

Anticipatory stress influences decision making under explicit risk conditions.

PubMed

Starcke, Katrin; Wolf, Oliver T; Markowitsch, Hans J; Brand, Matthias

2008-12-01

Recent research has suggested that stress may affect memory, executive functioning, and decision making on the basis of emotional feedback processing. The current study examined whether anticipatory stress affects decision making measured with the Game of Dice Task (GDT), a decision-making task with explicit and stable rules that taps both executive functioning and feedback learning. The authors induced stress in 20 participants by having them anticipate giving a public speech and also examined 20 comparison subjects. The authors assessed the level of stress with questionnaires and endocrine markers (salivary cortisol and alpha-amylase), both revealing that speech anticipation led to increased stress. Results of the GDT showed that participants under stress scored significantly lower than the comparison group and that GDT performance was negatively correlated with the increase of cortisol. Our results indicate that stress can lead to disadvantageous decision making even when explicit and stable information about outcome contingencies is provided.

Training of perceptual-cognitive skills in offside decision making.

PubMed

Catteeuw, Peter; Gilis, Bart; Jaspers, Arne; Wagemans, Johan; Helsen, Werner

2010-12-01

This study investigates the effect of two off-field training formats to improve offside decision making. One group trained with video simulations and another with computer animations. Feedback after every offside situation allowed assistant referees to compensate for the consequences of the flash-lag effect and to improve their decision-making accuracy. First, response accuracy improved and flag errors decreased for both training groups implying that training interventions with feedback taught assistant referees to better deal with the flash-lag effect. Second, the results demonstrated no effect of format, although assistant referees rated video simulations higher for fidelity than computer animations. This implies that a cognitive correction to a perceptual effect can be learned also when the format does not correspond closely with the original perceptual situation. Off-field offside decision-making training should be considered as part of training because it is a considerable help to gain more experience and to improve overall decision-making performance.

Quantum decision-maker theory and simulation

NASA Astrophysics Data System (ADS)

Zak, Michail; Meyers, Ronald E.; Deacon, Keith S.

2000-07-01

A quantum device simulating the human decision making process is introduced. It consists of quantum recurrent nets generating stochastic processes which represent the motor dynamics, and of classical neural nets describing the evolution of probabilities of these processes which represent the mental dynamics. The autonomy of the decision making process is achieved by a feedback from the mental to motor dynamics which changes the stochastic matrix based upon the probability distribution. This feedback replaces unavailable external information by an internal knowledge- base stored in the mental model in the form of probability distributions. As a result, the coupled motor-mental dynamics is described by a nonlinear version of Markov chains which can decrease entropy without an external source of information. Applications to common sense based decisions as well as to evolutionary games are discussed. An example exhibiting self-organization is computed using quantum computer simulation. Force on force and mutual aircraft engagements using the quantum decision maker dynamics are considered.

Saccadic adaptation to a systematically varying disturbance.

PubMed

Cassanello, Carlos R; Ohl, Sven; Rolfs, Martin

2016-08-01

Saccadic adaptation maintains the correct mapping between eye movements and their targets, yet the dynamics of saccadic gain changes in the presence of systematically varying disturbances has not been extensively studied. Here we assessed changes in the gain of saccade amplitudes induced by continuous and periodic postsaccadic visual feedback. Observers made saccades following a sequence of target steps either along the horizontal meridian (Two-way adaptation) or with unconstrained saccade directions (Global adaptation). An intrasaccadic step-following a sinusoidal variation as a function of the trial number (with 3 different frequencies tested in separate blocks)-consistently displaced the target along its vector. The oculomotor system responded to the resulting feedback error by modifying saccade amplitudes in a periodic fashion with similar frequency of variation but lagging the disturbance by a few tens of trials. This periodic response was superimposed on a drift toward stronger hypometria with similar asymptotes and decay rates across stimulus conditions. The magnitude of the periodic response decreased with increasing frequency and was smaller and more delayed for Global than Two-way adaptation. These results suggest that-in addition to the well-characterized return-to-baseline response observed in protocols using constant visual feedback-the oculomotor system attempts to minimize the feedback error by integrating its variation across trials. This process resembles a convolution with an internal response function, whose structure would be determined by coefficients of the learning model. Our protocol reveals this fast learning process in single short experimental sessions, qualifying it for the study of sensorimotor learning in health and disease. Copyright © 2016 the American Physiological Society.

Differential flatness properties and adaptive control of the hypothalamic-pituitary-adrenal axis model

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos

2016-12-01

It is shown that the model of the hypothalamic-pituitary-adrenal gland axis is a differentially flat one and this permits to transform it to the so-called linear canonical form. For the new description of the system's dynamics the transformed control inputs contain unknown terms which depend on the system's parameters. To identify these terms an adaptive fuzzy approximator is used in the control loop. Thus an adaptive fuzzy control scheme is implemented in which the unknown or unmodeled system dynamics is approximated by neurofuzzy networks and next this information is used by a feedback controller that makes the state variables (CRH - corticotropin releasing hormone, adenocortocotropic hormone - ACTH, cortisol) of the hypothalamic-pituitary-adrenal gland axis model converge to the desirable levels (setpoints). This adaptive control scheme is exclusively implemented with the use of output feedback, while the state vector elements which are not directly measured are estimated with the use of a state observer that operates in the control loop. The learning rate of the adaptive fuzzy system is suitably computed from Lyapunov analysis, so as to assure that both the learning procedure for the unknown system's parameters, the dynamics of the observer and the dynamics of the control loop will remain stable. The performed Lyapunov stability analysis depends on two Riccati equations, one associated with the feedback controller and one associated with the state observer. Finally, it is proven that for the control scheme that comprises the feedback controller, the state observer and the neurofuzzy approximator, an H-infinity tracking performance can be succeeded.

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.

Adaptation Planning for Water Resources Management in the Context of Scientific Uncertainty

NASA Astrophysics Data System (ADS)

Lowrey, J.; Kenney, D.

2008-12-01

Several municipalities are beginning to create policies and plans in order to adapt to potential impacts from climate change. A 2007 report from the Heinz Center for Science, Economics, and the Environment, 'A Survey of Climate Change Adaptation Planning,' surveyed fourteen cities or counties across the U.S. and Canada that have created or are working towards creating climate change adaptation plans. Informal interactions with water managers in the Intermountain West indicate an eagerness to learn from those who have already begun adapting to potential climate change. Many of those without plans do not feel comfortable making potentially expensive long-term policy decisions based on impacts derived from uncertain climate change projections. This research identifies how decision makers currently consider climate change in adaptation planning despite imperfect information about climate change impacts, particularly in the water sector. Insights are offered into how best to provide information on climate change projections to regional decision makers so that they can begin adaptation planning for a changing climate. This research analyzes how a subset of the fourteen municipalities justified adaptive planning in the face of scientific uncertainty, paying particular attention to water resource adaptation, using the adaptation approaches studied in the 2007 Heinz Center Report. Interviews will be conducted with decision makers to learn how policies will be implemented and evaluated, and to explore resulting changes in policy or planning. Adaptation strategies are not assessed, but are used to identify how the decision makers plan to evaluate their own adaptation policies. In addition to looking at information use in adaptation plans, we compare how the plans orient themselves (adapting to projected impacts vs. increasing resiliency to current climate variability), how they address barriers and opportunities for adaptation, and whether they follow some key steps for successful adaptation as outlined in the literature. This part of the study will identify any consensus among the municipalities already adapting, and see of the decision makers tend to agree with the points of views expressed in the literature. The conclusions here will not only help decision makers trying to adapt, but it will help researchers orient future research to the informational needs of the decision makers. The work is intended to provide useful information for the Western Water Assessment, a NOAA-funded research boundary organization, which provides climate information to water resource managers in the Intermountain West, including the Colorado River Basin.

Fostering Synergies Among Organizations to put Climate in Context for Use in Decision Making

NASA Astrophysics Data System (ADS)

Garfin, G. M.; Parris, A.; Dow, K.; Meyer, R.; Close, S.

2016-12-01

Making science usable for decision making requires a knowledge of the social and institutional contexts of decision making, an ability to develop or tap into networks for sharing information and developing knowledge, a capacity for innovating or providing services, and a program for social learning to inform decisions and improve the processes of engagement and collaboration (i.e., mechanisms for feedback, evaluation, and changes in policy or practices). Active participation by and partnerships between researchers, practitioners, and decision-makers provides a foundation for making progress in each of the aforementioned areas of endeavor. In twenty years of incubating experimental climate services, the NOAA Regional Integrated Sciences and Assessments program offers not a few ideas and examples of practices to foster synergies among organizations, that result in tangible benefits to decision-makers. Strategies include (a) designing explicit mutual learning through temporary institutions, such as workshop series, in order to develop social capital and knowledge networks (e.g., to co-develop and disseminate experimental forecasts); (b) articulating ground rules, roles, and responsibilities in managing the boundary between scientists and practitioners (e.g., in multi-partner climate adaptation planning processes); and (c) cross-training between scientists and practitioners, by embedding team members in other organizations or recruiting members from those organizations (e.g., Cooperative Extension). A promising strategy is boundary chaining, pioneered by the Great Lakes Integrated Sciences and Assessments, in which science information and service providers partner with other boundary organizations, to leverage networks, expertise, resources, and to reduce transaction costs. Partners with complementary strengths and roles can then, work iteratively and synergize to mediate the co-production of a combination of services for decision making, such as data and information, facilitation, and evaluation.

Research priorities in land use and land-cover change for the Earth system and integrated assessment modelling

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

Hibbard, Kathleen A.; Janetos, Anthony C.; Van Vuuren, Detlef

2010-11-15

This special issue has highlighted recent and innovative methods and results that integrate observations and AQ3 modelling analyses of regional to global aspect of biophysical and biogeochemical interactions of land-cover change with the climate system. Both the Earth System and the Integrated Assessment modeling communities recognize the importance of an accurate representation of land use and land-cover change to understand and quantify the interactions and feedbacks with the climate and socio-economic systems, respectively. To date, cooperation between these communities has been limited. Based on common interests, this work discusses research priorities in representing land use and land-cover change for improvedmore » collaboration across modelling, observing and measurement communities. Major research topics in land use and land-cover change are those that help us better understand (1) the interaction of land use and land cover with the climate system (e.g. carbon cycle feedbacks), (2) the provision of goods and ecosystem services by terrestrial (natural and anthropogenic) land-cover types (e.g. food production), (3) land use and management decisions and (4) opportunities and limitations for managing climate change (for both mitigation and adaptation strategies).« less

Utilizing feedback in adaptive SAR ATR systems

NASA Astrophysics Data System (ADS)

Horsfield, Owen; Blacknell, David

2009-05-01

Existing SAR ATR systems are usually trained off-line with samples of target imagery or CAD models, prior to conducting a mission. If the training data is not representative of mission conditions, then poor performance may result. In addition, it is difficult to acquire suitable training data for the many target types of interest. The Adaptive SAR ATR Problem Set (AdaptSAPS) program provides a MATLAB framework and image database for developing systems that adapt to mission conditions, meaning less reliance on accurate training data. A key function of an adaptive system is the ability to utilise truth feedback to improve performance, and it is this feature which AdaptSAPS is intended to exploit. This paper presents a new method for SAR ATR that does not use training data, based on supervised learning. This is achieved by using feature-based classification, and several new shadow features have been developed for this purpose. These features allow discrimination of vehicles from clutter, and classification of vehicles into two classes: targets, comprising military combat types, and non-targets, comprising bulldozers and trucks. The performance of the system is assessed using three baseline missions provided with AdaptSAPS, as well as three additional missions. All performance metrics indicate a distinct learning trend over the course of a mission, with most third and fourth quartile performance levels exceeding 85% correct classification. It has been demonstrated that these performance levels can be maintained even when truth feedback rates are reduced by up to 55% over the course of a mission.

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

Adaptive NN control for discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints.

PubMed

Chen, Weisheng

2009-07-01

This paper focuses on the problem of adaptive neural network tracking control for a class of discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints. Two novel state-feedback and output-feedback dynamic control laws are established where the function tanh(.) is employed to solve the saturation constraint problem. Implicit function theorem and mean value theorem are exploited to deal with non-affine variables that are used as actual control. Radial basis function neural networks are used to approximate the desired input function. Discrete Nussbaum gain is used to estimate the unknown sign of control gain. The uniform boundedness of all closed-loop signals is guaranteed. The tracking error is proved to converge to a small residual set around the origin. A simulation example is provided to illustrate the effectiveness of control schemes proposed in this paper.

Adaptive integral feedback controller for pitch and yaw channels of an AUV with actuator saturations.

PubMed

Sarhadi, Pouria; Noei, Abolfazl Ranjbar; Khosravi, Alireza

2016-11-01

Input saturations and uncertain dynamics are among the practical challenges in control of autonomous vehicles. Adaptive control is known as a proper method to deal with the uncertain dynamics of these systems. Therefore, incorporating the ability to confront with input saturation in adaptive controllers can be valuable. In this paper, an adaptive autopilot is presented for the pitch and yaw channels of an autonomous underwater vehicle (AUV) in the presence of input saturations. This will be performed by combination of a model reference adaptive control (MRAC) with integral state feedback with a modern anti-windup (AW) compensator. MRAC with integral state feedback is commonly used in autonomous vehicles. However, some proper modifications need to be taken into account in order to cope with the saturation problem. To this end, a Riccati-based anti-windup (AW) compensator is employed. The presented technique is applied to the non-linear six degrees of freedom (DOF) model of an AUV and the obtained results are compared with that of its baseline method. Several simulation scenarios are executed in the pitch and yaw channels to evaluate the controller performance. Moreover, effectiveness of proposed adaptive controller is comprehensively investigated by implementing Monte Carlo simulations. The obtained results verify the performance of proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Reintroduction of Lake Sturgeon (Acipenser fulvescens) into the St. Regis River, NY: Post-release assessment of habitat use and growth

USGS Publications Warehouse

Dittman, Dawn E.; Chalupnicki, Marc A.; Johnson, James H.; Snyder, James

2015-01-01

One of the depleted endemic fish species of the Great Lakes, Acipenser fulvescens (Lake Sturgeon), has been the target of extensive conservation efforts. One strategy is reintroduction into historically productive waters. The St. Regis River, NY, represents one such adaptive-management effort, with shared management between New York and the St. Regis Mohawk Tribe. Between 1998 and 2004, a total of 4977 young-of-year Lake Sturgeon were released. Adaptive management requires intermediate progress metrics. During 2004 and 2005, we measured growth, habitat use, and survivorship metrics of the released fish. We captured a total of 95 individuals of all stocked ages. Year-class minimal-survival rates ranged from 0.19–2.1%. The size-at-age and length/biomass relationships were comparable to those reported for juveniles in other Great Lakes waters. These intermediate assessment metrics can provide feedback to resource managers who make restoration-program decisions on a much shorter time-scale than the time-frame in which the ultimate goal of a self-sustaining population can be attained.

Neural-network-based state feedback control of a nonlinear discrete-time system in nonstrict feedback form.

PubMed

Jagannathan, Sarangapani; He, Pingan

2008-12-01

In this paper, a suite of adaptive neural network (NN) controllers is designed to deliver a desired tracking performance for the control of an unknown, second-order, nonlinear discrete-time system expressed in nonstrict feedback form. In the first approach, two feedforward NNs are employed in the controller with tracking error as the feedback variable whereas in the adaptive critic NN architecture, three feedforward NNs are used. In the adaptive critic architecture, two action NNs produce virtual and actual control inputs, respectively, whereas the third critic NN approximates certain strategic utility function and its output is employed for tuning action NN weights in order to attain the near-optimal control action. Both the NN control methods present a well-defined controller design and the noncausal problem in discrete-time backstepping design is avoided via NN approximation. A comparison between the controller methodologies is highlighted. The stability analysis of the closed-loop control schemes is demonstrated. The NN controller schemes do not require an offline learning phase and the NN weights can be initialized at zero or random. Results show that the performance of the proposed controller schemes is highly satisfactory while meeting the closed-loop stability.

People adopt optimal policies in simple decision-making, after practice and guidance.

PubMed

Evans, Nathan J; Brown, Scott D

2017-04-01

Organisms making repeated simple decisions are faced with a tradeoff between urgent and cautious strategies. While animals can adopt a statistically optimal policy for this tradeoff, findings about human decision-makers have been mixed. Some studies have shown that people can optimize this "speed-accuracy tradeoff", while others have identified a systematic bias towards excessive caution. These issues have driven theoretical development and spurred debate about the nature of human decision-making. We investigated a potential resolution to the debate, based on two factors that routinely differ between human and animal studies of decision-making: the effects of practice, and of longer-term feedback. Our study replicated the finding that most people, by default, are overly cautious. When given both practice and detailed feedback, people moved rapidly towards the optimal policy, with many participants reaching optimality with less than 1 h of practice. Our findings have theoretical implications for cognitive and neural models of simple decision-making, as well as methodological implications.

The influence of cooperation and defection on social decision making in depression: A study of the iterated Prisoner's Dilemma Game.

PubMed

Sorgi, Kristen M; van 't Wout, Mascha

2016-12-30

This study evaluated the influence of self-reported levels of depression on interpersonal strategic decision making when interacting with partners who differed in their predetermined tendency to cooperate in three separate computerized iterated Prisoner's Dilemma Games (iPDGs). Across 29 participants, cooperation was lowest when interacting with a predominantly defecting partner and highest when interacting with a predominantly cooperating partner. Greater depression severity was related to steadier and continued cooperation over trials with the cooperating partner, seeming to reflect a prosocial response tendency when interacting with this partner. With the unbiased partner, depression severity was associated with a more volatile response pattern in reaction to cooperation and defection by this partner. Severity of depression did not influence cooperation with a defecting partner or expectations about partner cooperation reported before the task began. Taken together, these data appear to show that in predominately positive interactions, as in the cooperating partner condition, depression is associated with less volatile, more consistent cooperation. When such clear feedback is absent, as in the unbiased partner condition, depression is associated with more volatile behavior. Nonetheless, participants were generally able to adapt their behavior accordingly in this dynamic interpersonal decision making context. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The mechanisms of feature inheritance as predicted by a systems-level model of visual attention and decision making.

PubMed

Hamker, Fred H

2008-07-15

Feature inheritance provides evidence that properties of an invisible target stimulus can be attached to a following mask. We apply a systemslevel model of attention and decision making to explore the influence of memory and feedback connections in feature inheritance. We find that the presence of feedback loops alone is sufficient to account for feature inheritance. Although our simulations do not cover all experimental variations and focus only on the general principle, our result appears of specific interest since the model was designed for a completely different purpose than to explain feature inheritance. We suggest that feedback is an important property in visual perception and provide a description of its mechanism and its role in perception.

Adaptive Intelligent Support to Improve Peer Tutoring in Algebra

ERIC Educational Resources Information Center

Walker, Erin; Rummel, Nikol; Koedinger, Kenneth R.

2014-01-01

Adaptive collaborative learning support (ACLS) involves collaborative learning environments that adapt their characteristics, and sometimes provide intelligent hints and feedback, to improve individual students' collaborative interactions. ACLS often involves a system that can automatically assess student dialogue, model effective and…

Adaptive Locomotor Behavior in Larval Zebrafish

PubMed Central

Portugues, Ruben; Engert, Florian

2011-01-01

In this study we report that larval zebrafish display adaptive locomotor output that can be driven by unexpected visual feedback. We develop a new assay that addresses visuomotor integration in restrained larval zebrafish. The assay involves a closed-loop environment in which the visual feedback a larva receives depends on its own motor output in a way that resembles freely swimming conditions. The experimenter can control the gain of this closed feedback loop, so that following a given motor output the larva experiences more or less visual feedback depending on whether the gain is high or low. We show that increases and decreases in this gain setting result in adaptive changes in behavior that lead to a generalized decrease or increase of motor output, respectively. Our behavioral analysis shows that both the duration and tail beat frequency of individual swim bouts can be modified, as well as the frequency with which bouts are elicited. These changes can be implemented rapidly, following an exposure to a new gain of just 175 ms. In addition, modifications in some behavioral parameters accumulate over tens of seconds and effects last for at least 30 s from trial to trial. These results suggest that larvae establish an internal representation of the visual feedback expected from a given motor output and that the behavioral modifications are driven by an error signal that arises from the discrepancy between this expectation and the actual visual feedback. The assay we develop presents a unique possibility for studying visuomotor integration using imaging techniques available in the larval zebrafish. PMID:21909325

Adaptive locomotor behavior in larval zebrafish.

PubMed

Portugues, Ruben; Engert, Florian

2011-01-01

In this study we report that larval zebrafish display adaptive locomotor output that can be driven by unexpected visual feedback. We develop a new assay that addresses visuomotor integration in restrained larval zebrafish. The assay involves a closed-loop environment in which the visual feedback a larva receives depends on its own motor output in a way that resembles freely swimming conditions. The experimenter can control the gain of this closed feedback loop, so that following a given motor output the larva experiences more or less visual feedback depending on whether the gain is high or low. We show that increases and decreases in this gain setting result in adaptive changes in behavior that lead to a generalized decrease or increase of motor output, respectively. Our behavioral analysis shows that both the duration and tail beat frequency of individual swim bouts can be modified, as well as the frequency with which bouts are elicited. These changes can be implemented rapidly, following an exposure to a new gain of just 175 ms. In addition, modifications in some behavioral parameters accumulate over tens of seconds and effects last for at least 30 s from trial to trial. These results suggest that larvae establish an internal representation of the visual feedback expected from a given motor output and that the behavioral modifications are driven by an error signal that arises from the discrepancy between this expectation and the actual visual feedback. The assay we develop presents a unique possibility for studying visuomotor integration using imaging techniques available in the larval zebrafish.

Interactive genetic algorithm for user-centered design of distributed conservation practices in a watershed: An examination of user preferences in objective space and user behavior

NASA Astrophysics Data System (ADS)

Piemonti, Adriana Debora; Babbar-Sebens, Meghna; Mukhopadhyay, Snehasis; Kleinberg, Austin

2017-05-01

Interactive Genetic Algorithms (IGA) are advanced human-in-the-loop optimization methods that enable humans to give feedback, based on their subjective and unquantified preferences and knowledge, during the algorithm's search process. While these methods are gaining popularity in multiple fields, there is a critical lack of data and analyses on (a) the nature of interactions of different humans with interfaces of decision support systems (DSS) that employ IGA in water resources planning problems and on (b) the effect of human feedback on the algorithm's ability to search for design alternatives desirable to end-users. In this paper, we present results and analyses of observational experiments in which different human participants (surrogates and stakeholders) interacted with an IGA-based, watershed DSS called WRESTORE to identify plans of conservation practices in a watershed. The main goal of this paper is to evaluate how the IGA adapts its search process in the objective space to a user's feedback, and identify whether any similarities exist in the objective space of plans found by different participants. Some participants focused on the entire watershed, while others focused only on specific local subbasins. Additionally, two different hydrology models were used to identify any potential differences in interactive search outcomes that could arise from differences in the numerical values of benefits displayed to participants. Results indicate that stakeholders, in comparison to their surrogates, were more likely to use multiple features of the DSS interface to collect information before giving feedback, and dissimilarities existed among participants in the objective space of design alternatives.

Feedback in Videogame-Based Adaptive Training

ERIC Educational Resources Information Center

Rivera, Iris Daliz

2010-01-01

The field of training has been changing rapidly due to advances in technology such as videogame-based adaptive training. Videogame-based adaptive training has provided flexibility and adaptability for training in cost-effective ways. Although this method of training may have many benefits for the trainee, current research has not kept up to pace…

Rolling bearing fault diagnosis based on time-delayed feedback monostable stochastic resonance and adaptive minimum entropy deconvolution

NASA Astrophysics Data System (ADS)

Li, Jimeng; Li, Ming; Zhang, Jinfeng

2017-08-01

Rolling bearings are the key components in the modern machinery, and tough operation environments often make them prone to failure. However, due to the influence of the transmission path and background noise, the useful feature information relevant to the bearing fault contained in the vibration signals is weak, which makes it difficult to identify the fault symptom of rolling bearings in time. Therefore, the paper proposes a novel weak signal detection method based on time-delayed feedback monostable stochastic resonance (TFMSR) system and adaptive minimum entropy deconvolution (MED) to realize the fault diagnosis of rolling bearings. The MED method is employed to preprocess the vibration signals, which can deconvolve the effect of transmission path and clarify the defect-induced impulses. And a modified power spectrum kurtosis (MPSK) index is constructed to realize the adaptive selection of filter length in the MED algorithm. By introducing the time-delayed feedback item in to an over-damped monostable system, the TFMSR method can effectively utilize the historical information of input signal to enhance the periodicity of SR output, which is beneficial to the detection of periodic signal. Furthermore, the influence of time delay and feedback intensity on the SR phenomenon is analyzed, and by selecting appropriate time delay, feedback intensity and re-scaling ratio with genetic algorithm, the SR can be produced to realize the resonance detection of weak signal. The combination of the adaptive MED (AMED) method and TFMSR method is conducive to extracting the feature information from strong background noise and realizing the fault diagnosis of rolling bearings. Finally, some experiments and engineering application are performed to evaluate the effectiveness of the proposed AMED-TFMSR method in comparison with a traditional bistable SR method.

The predictive roles of neural oscillations in speech motor adaptability.

PubMed

Sengupta, Ranit; Nasir, Sazzad M

2016-06-01

The human speech system exhibits a remarkable flexibility by adapting to alterations in speaking environments. While it is believed that speech motor adaptation under altered sensory feedback involves rapid reorganization of speech motor networks, the mechanisms by which different brain regions communicate and coordinate their activity to mediate adaptation remain unknown, and explanations of outcome differences in adaption remain largely elusive. In this study, under the paradigm of altered auditory feedback with continuous EEG recordings, the differential roles of oscillatory neural processes in motor speech adaptability were investigated. The predictive capacities of different EEG frequency bands were assessed, and it was found that theta-, beta-, and gamma-band activities during speech planning and production contained significant and reliable information about motor speech adaptability. It was further observed that these bands do not work independently but interact with each other suggesting an underlying brain network operating across hierarchically organized frequency bands to support motor speech adaptation. These results provide novel insights into both learning and disorders of speech using time frequency analysis of neural oscillations. Copyright © 2016 the American Physiological Society.

Using Hi-FAME (High Feedback-Assessment-Multimedia-Environment) Instructional Model in WBI: A Case Study for Biology Teacher Education.

ERIC Educational Resources Information Center

Wang, Tzu-Hua; Wang, Wei-Lung; Wang, Kuo-Hua; Huang, Shih-Chieh

The study attempted to adapt two web tools, FFS system (Frontpage Feedback System) and WATA system (Web-based Assessment and Test Analysis System), to construct a Hi-FAME (High Feedback-Assessment-Multimedia-Environment) Model in WBI (Web-based Instruction) to facilitate pre-service teacher training. Participants were 30 junior pre-service…

Functional relationships among monitoring performance: Subjective report of thought process and compromising states of awareness

NASA Technical Reports Server (NTRS)

Freeman, Frederick

1995-01-01

A biocybernetic system for use in adaptive automation was evaluated using EEG indices based on the beta, alpha, and theta bandwidths. Subjects performed a compensatory tracking task while their EEG was recorded and one of three engagement indices was derived: beta/(alpha + theta), beta/alpha, or 1/alpha. The task was switched between manual and automatic modes as a function of the subjects' level of engagement and whether they were under a positive or negative feedback condition. It was hypothesized that negative feedback would produce more switches between manual and automatic modes, and that the beta/(alpha + theta) index would produce the strongest effect. The results confirmed these hypotheses. There were no systematic changes in these effects over three 16-minute trials. Tracking performance was found to be better under negative feedback. An analysis of the different EEG bands under positive and negative feedback in manual and automatic modes found more beta power in the positive feedback/manual condition and less in the positive feedback/automatic condition. The opposite effect was observed for alpha and theta power. The implications of biocybernetic systems for adaptive automation are discussed.

Application of Adaptive Decision Aiding Systems to Computer-Assisted Instruction. Final Report, January-December 1974.

ERIC Educational Resources Information Center

May, Donald M.; And Others

The minicomputer-based Computerized Diagnostic and Decision Training (CDDT) system described combines the principles of artificial intelligence, decision theory, and adaptive computer assisted instruction for training in electronic troubleshooting. The system incorporates an adaptive computer program which learns the student's diagnostic and…

Cross-cultural adaptation of an environmental health measurement instrument: Brazilian version of the health-care waste management • rapid assessment tool.

PubMed

Cozendey-Silva, Eliana Napoleão; da Silva, Cintia Ribeiro; Larentis, Ariane Leites; Wasserman, Julio Cesar; Rozemberg, Brani; Teixeira, Liliane Reis

2016-09-05

Periodic assessment is one of the recommendations for improving health-care waste management worldwide. This study aimed at translating and adapting the Health-Care Waste Management - Rapid Assessment Tool (HCWM-RAT), proposed by the World Health Organization, to a Brazilian Portuguese version, and resolving its cultural and legal issues. The work focused on the evaluation of the concepts, items and semantic equivalence between the original tool and the Brazilian Portuguese version. A cross-cultural adaptation methodology was used, including: initial translation to Brazilian Portuguese; back translation to English; syntheses of these translation versions; formation of an expert committee to achieve consensus about the preliminary version; and evaluation of the target audience's comprehension. Both the translated and the original versions' concepts, items and semantic equivalence are presented. The constructs in the original instrument were considered relevant and applicable to the Brazilian context. The Brazilian version of the tool has the potential to generate indicators, develop official database, feedback and subsidize political decisions at many geographical and organizational levels strengthening the Monitoring and evaluation (M&E) mechanism. Moreover, the cross-cultural translation expands the usefulness of the instrument to Portuguese-speaking countries in developing regions. The translated and original versions presented concept, item and semantic equivalence and can be applied to Brazil.

Adaptive control of Parkinson's state based on a nonlinear computational model with unknown parameters.

PubMed

Su, Fei; Wang, Jiang; Deng, Bin; Wei, Xi-Le; Chen, Ying-Yuan; Liu, Chen; Li, Hui-Yan

2015-02-01

The objective here is to explore the use of adaptive input-output feedback linearization method to achieve an improved deep brain stimulation (DBS) algorithm for closed-loop control of Parkinson's state. The control law is based on a highly nonlinear computational model of Parkinson's disease (PD) with unknown parameters. The restoration of thalamic relay reliability is formulated as the desired outcome of the adaptive control methodology, and the DBS waveform is the control input. The control input is adjusted in real time according to estimates of unknown parameters as well as the feedback signal. Simulation results show that the proposed adaptive control algorithm succeeds in restoring the relay reliability of the thalamus, and at the same time achieves accurate estimation of unknown parameters. Our findings point to the potential value of adaptive control approach that could be used to regulate DBS waveform in more effective treatment of PD.

Brain-wide neuronal dynamics during motor adaptation in zebrafish.

PubMed

Ahrens, Misha B; Li, Jennifer M; Orger, Michael B; Robson, Drew N; Schier, Alexander F; Engert, Florian; Portugues, Ruben

2012-05-09

A fundamental question in neuroscience is how entire neural circuits generate behaviour and adapt it to changes in sensory feedback. Here we use two-photon calcium imaging to record the activity of large populations of neurons at the cellular level, throughout the brain of larval zebrafish expressing a genetically encoded calcium sensor, while the paralysed animals interact fictively with a virtual environment and rapidly adapt their motor output to changes in visual feedback. We decompose the network dynamics involved in adaptive locomotion into four types of neuronal response properties, and provide anatomical maps of the corresponding sites. A subset of these signals occurred during behavioural adjustments and are candidates for the functional elements that drive motor learning. Lesions to the inferior olive indicate a specific functional role for olivocerebellar circuitry in adaptive locomotion. This study enables the analysis of brain-wide dynamics at single-cell resolution during behaviour.

Brain-wide neuronal dynamics during motor adaptation in zebrafish

PubMed Central

Ahrens, Misha B; Li, Jennifer M; Orger, Michael B; Robson, Drew N; Schier, Alexander F; Engert, Florian; Portugues, Ruben

2013-01-01

A fundamental question in neuroscience is how entire neural circuits generate behavior and adapt it to changes in sensory feedback. Here we use two-photon calcium imaging to record activity of large populations of neurons at the cellular level throughout the brain of larval zebrafish expressing a genetically-encoded calcium sensor, while the paralyzed animals interact fictively with a virtual environment and rapidly adapt their motor output to changes in visual feedback. We decompose the network dynamics involved in adaptive locomotion into four types of neural response properties, and provide anatomical maps of the corresponding sites. A subset of these signals occurred during behavioral adjustments and are candidates for the functional elements that drive motor learning. Lesions to the inferior olive indicate a specific functional role for olivocerebellar circuitry in adaptive locomotion. This study enables the analysis of brain-wide dynamics at single-cell resolution during behavior. PMID:22622571

Incoherent feedforward control governs adaptation of activated ras in a eukaryotic chemotaxis pathway.

PubMed

Takeda, Kosuke; Shao, Danying; Adler, Micha; Charest, Pascale G; Loomis, William F; Levine, Herbert; Groisman, Alex; Rappel, Wouter-Jan; Firtel, Richard A

2012-01-03

Adaptation in signaling systems, during which the output returns to a fixed baseline after a change in the input, often involves negative feedback loops and plays a crucial role in eukaryotic chemotaxis. We determined the dynamical response to a uniform change in chemoattractant concentration of a eukaryotic chemotaxis pathway immediately downstream from G protein-coupled receptors. The response of an activated Ras showed near-perfect adaptation, leading us to attempt to fit the results using mathematical models for the two possible simple network topologies that can provide perfect adaptation. Only the incoherent feedforward network accurately described the experimental results. This analysis revealed that adaptation in this Ras pathway is achieved through the proportional activation of upstream components and not through negative feedback loops. Furthermore, these results are consistent with a local excitation, global inhibition mechanism for gradient sensing, possibly with a Ras guanosine triphosphatase-activating protein acting as a global inhibitor.

From Paris to Iowa and Back: Global Temperature Targets, Agricultural Impacts, and Producer Response

NASA Astrophysics Data System (ADS)

Anderson, C.; Hayhoe, K.; Terando, A. J.

2016-12-01

Traditionally, assessments such as those produced by IPCC and USGCRP have been structured to provide a one-way flow of information from scientists to national and international policy makers. Because the Paris Agreement will ultimately require corresponding domestic policies, the traditional one-way information flow could be inadequate, since it lacks both direct participation and informed feedback from many of the important entities that influence domestic policy. We have engaged Iowa row crop producers in identifying impacts and feasibility of adaptation under global warming of 1.0 and 2.0OC. Our engagement seeks to create within climate impacts assessment a decision-maker feedback loop. We have engaged an expert panel by using yield data modeling as a first step to communicate vividly the potential yield impacts of global average temperature targets. This engagement included validation with historical global average temperature before presenting yield impact under global mean surface temperature increase of 1.0 and 2.0OC. The expert panel requested further analysis of targets at 0.25 and 0.50OC increase and of possible impacts should they pursue adaptation by increasing maize plant population density and soil moisture storage. Several clear messages have emerged that can be voiced by Iowa agribusiness leaders to national and international decision-makers. While Iowa soybean agriculture may remain robust for the foreseeable future, the Paris Agreement is insufficient to protect Iowa maize production from substantial changes in productivity and volatility. These effects could be largely (though not entirely) mitigated by moving from the current +2OC to the "high ambition" +1.5OC target. The projected spring rainfall increase of 10% under +1OC would increase the cost of spring planting. The data model predicts a 5-day reduction in average number of fieldwork days, which requires the addition of one half-time person or larger planting equipment. The current annual rate of increase in maize plant density will maintain historical yield increase through +1OC but by +2OC is substantially reduced and results in unprecedented yield volatility. By increasing soil moisture during July, Iowa maize production can reduce markedly the impacts of +2OC.

Impaired decision making under ambiguity but not under risk in individuals with pathological buying-behavioral and psychophysiological evidence.

PubMed

Trotzke, Patrick; Starcke, Katrin; Pedersen, Anya; Müller, Astrid; Brand, Matthias

2015-09-30

Pathological buying (PB) is described as dysfunctional buying behavior, associated with harmful consequences. It is discussed whether decision-making deficits are related to PB, because affected individuals often choose the short-term rewarding option of buying despite persistent negative long-term consequences. We investigated 30 patients suffering from PB and 30 matched control participants with two different decision-making tasks: the Iowa Gambling Task (IGT) measures decisions under ambiguity and involves emotional feedback processing, whereas the Game of Dice Task (GDT) measures decisions under risk and can be solved strategically. Potential emotional and cognitive correlates of decision making were investigated by assessing skin conductance response (SCR) and executive functioning. In comparison to the control participants, the patients showed more disadvantageous decisions under ambiguity in the IGT. These data were supported by the SCR results: patients failed to generate SCRs that usually occur before disadvantageous decisions. The physiological and behavioral performance on decisions under risk and executive functioning did not differ between groups. Thus, deficits in emotional feedback processing might be one potential factor in etiology and pathogenesis of PB and should be considered in theory and treatment. Copyright © 2015. Published by Elsevier Ireland Ltd.

Water Plan 2030: A Dynamic Education Model for Teaching Water Management Issues

NASA Astrophysics Data System (ADS)

Rupprecht, C.; Washburne, J.; Lansey, K.; Williams, A.

2006-12-01

Dynamic educational tools to assist teachers and students in recognizing the impacts of water management decisions in a realistic context are not readily available. Water policy issues are often complex and difficult for students trying to make meaningful connections between system components. To fill this need, we have developed a systems modeling-based educational decision support system (DSS) with supplementary materials. This model, called Water Plan 2030, represents a general semi-arid watershed; it allows users to examine water management alternatives by changing input values for various water uses and basin conditions and immediately receive graphical outputs to compare decisions. The main goal of our DSS model is to foster students' abilities to make knowledgeable decisions with regard to water resources issues. There are two reasons we have developed this model for traditional classroom settings. First, the DSS model provides teachers with a mechanism for educating students about inter-related hydrologic concepts, complex systems and facilitates discussion of water resources issues. Second, Water Plan 2030 encourages student discovery of cause/effect relationships in a dynamic, hands-on environment and develops the ability to realize the implications of water management alternatives. The DSS model has been utilized in an undergraduate, non-major science class for 5 course hours, each of the past 4 semesters. Accompanying the PC-based model are supplementary materials to improve the effectiveness of implementation by emphasizing important concepts and guiding learners through the model components. These materials include in-class tutorials, introductory questions, role-playing activities and homework extensions that have been revised after each user session, based on student and instructor feedback. Most recently, we have developed individual lessons that teach specific model functions and concepts. These modules provide teachers the flexibility to adapt the model to meet numerous teaching goals. Evaluation results indicate that students improved their understanding of fundamental concepts and system interactions and showed the most improvement in questions related to water use by sector and sustainability issues. Model modifications have also improved student feedback of the model effectiveness and user- friendliness. Positive results from this project have created the demand for a web-based version, which will be online in late 2006.

Performance of a modified feedback loop adaptive array with TVRO satellite signals

NASA Technical Reports Server (NTRS)

Steadman, Karl N.; Gupta, Inder J.; Walton, Eric K.

1990-01-01

Performance of an experimental adaptive antenna array system is evaluated using television receive-only (TVRO) satellite signals. The experimental system is a sidelobe canceller with two auxiliary channels. Modified feedback loops are used to enhance the suppression of weak interfering signals. The modified feedback loops used two spatialy separated antennas, each with an individual amplifier for each auxiliary channel. Thus, the experimental system uses five antenna elements. Instead of using five separate antennas, a reflector antenna with multiple feeds is used to receive signals from various TVRO satellites. The details of the earth station are given. It is shown that the experimental system can null up to two signals originating from interfering TVRO satellites while receiving the signals from a desired TVRO satellite.

Integrating Household Risk Mitigation Behavior in Flood Risk Analysis: An Agent-Based Model Approach.

PubMed

Haer, Toon; Botzen, W J Wouter; de Moel, Hans; Aerts, Jeroen C J H

2017-10-01

Recent studies showed that climate change and socioeconomic trends are expected to increase flood risks in many regions. However, in these studies, human behavior is commonly assumed to be constant, which neglects interaction and feedback loops between human and environmental systems. This neglect of human adaptation leads to a misrepresentation of flood risk. This article presents an agent-based model that incorporates human decision making in flood risk analysis. In particular, household investments in loss-reducing measures are examined under three economic decision models: (1) expected utility theory, which is the traditional economic model of rational agents; (2) prospect theory, which takes account of bounded rationality; and (3) a prospect theory model, which accounts for changing risk perceptions and social interactions through a process of Bayesian updating. We show that neglecting human behavior in flood risk assessment studies can result in a considerable misestimation of future flood risk, which is in our case study an overestimation of a factor two. Furthermore, we show how behavior models can support flood risk analysis under different behavioral assumptions, illustrating the need to include the dynamic adaptive human behavior of, for instance, households, insurers, and governments. The method presented here provides a solid basis for exploring human behavior and the resulting flood risk with respect to low-probability/high-impact risks. © 2016 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

Neural signatures of trust in reciprocity: a coordinate-based meta-analysis

PubMed Central

Bellucci, Gabriele; Chernyak, Sergey V.; Goodyear, Kimberly; Eickhoff, Simon B.; Krueger, Frank

2017-01-01

Trust in reciprocity (TR) is defined as the risky decision to invest valued resources in another party with the hope of mutual benefit. Several fMRI studies have investigated the neural correlates of TR in one-shot and multi-round versions of the investment game (IG). However, an overall characterization of the underlying neural networks remains elusive. Here, we employed a coordinate-based meta-analysis (activation likelihood estimation method, 30 papers) to investigate consistent brain activations in each of the IG stages (i.e., the trust, reciprocity and feedback stage). Our results showed consistent activations in the anterior insula (AI) during trust decisions in the one-shot IG and decisions to reciprocate in the multi-round IG, likely related to representations of aversive feelings. Moreover, decisions to reciprocate also consistently engaged the intraparietal sulcus, probably involved in evaluations of the reciprocity options. On the contrary, trust decisions in the multi-round IG consistently activated the ventral striatum, likely associated with reward prediction error signals. Finally, the dorsal striatum was found consistently recruited during the feedback stage of the multi-round IG, likely related to reinforcement learning. In conclusion, our results indicate different neural networks underlying trust, reciprocity and feedback learning. These findings suggest that although decisions to trust and reciprocate may elicit aversive feelings likely evoked by the uncertainty about the decision outcomes and the pressing requirements of social standards, multiple interactions allow people to build interpersonal trust for cooperation via a learning mechanism by which they arguably learn to distinguish trustworthy from untrustworthy partners. PMID:27859899

Neural signatures of trust in reciprocity: A coordinate-based meta-analysis.

PubMed

Bellucci, Gabriele; Chernyak, Sergey V; Goodyear, Kimberly; Eickhoff, Simon B; Krueger, Frank

2017-03-01

Trust in reciprocity (TR) is defined as the risky decision to invest valued resources in another party with the hope of mutual benefit. Several fMRI studies have investigated the neural correlates of TR in one-shot and multiround versions of the investment game (IG). However, an overall characterization of the underlying neural networks remains elusive. Here, a coordinate-based meta-analysis was employed (activation likelihood estimation method, 30 articles) to investigate consistent brain activations in each of the IG stages (i.e., the trust, reciprocity and feedback stage). Results showed consistent activations in the anterior insula (AI) during trust decisions in the one-shot IG and decisions to reciprocate in the multiround IG, likely related to representations of aversive feelings. Moreover, decisions to reciprocate also consistently engaged the intraparietal sulcus, probably involved in evaluations of the reciprocity options. On the contrary, trust decisions in the multiround IG consistently activated the ventral striatum, likely associated with reward prediction error signals. Finally, the dorsal striatum was found consistently recruited during the feedback stage of the multiround IG, likely related to reinforcement learning. In conclusion, our results indicate different neural networks underlying trust, reciprocity, and feedback learning. These findings suggest that although decisions to trust and reciprocate may elicit aversive feelings likely evoked by the uncertainty about the decision outcomes and the pressing requirements of social standards, multiple interactions allow people to build interpersonal trust for cooperation via a learning mechanism by which they arguably learn to distinguish trustworthy from untrustworthy partners. Hum Brain Mapp 38:1233-1248, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Decision aid prototype development for parents considering adenotonsillectomy for their children with sleep disordered breathing.

PubMed

Maguire, Erin; Hong, Paul; Ritchie, Krista; Meier, Jeremy; Archibald, Karen; Chorney, Jill

2016-11-04

To describe the process involved in developing a decision aid prototype for parents considering adenotonsillectomy for their children with sleep disordered breathing. A paper-based decision aid prototype was developed using the framework proposed by the International Patient Decision Aids Standards Collaborative. The decision aid focused on two main treatment options: watchful waiting and adenotonsillectomy. Usability was assessed with parents of pediatric patients and providers with qualitative content analysis of semi-structured interviews, which included open-ended user feedback. A steering committee composed of key stakeholders was assembled. A needs assessment was then performed, which confirmed the need for a decision support tool. A decision aid prototype was developed and modified based on semi-structured qualitative interviews and a scoping literature review. The prototype provided information on the condition, risk and benefits of treatments, and values clarification. The prototype underwent three cycles of accessibility, feasibility, and comprehensibility testing, incorporating feedback from all stakeholders to develop the final decision aid prototype. A standardized, iterative methodology was used to develop a decision aid prototype for parents considering adenotonsillectomy for their children with sleep disordered breathing. The decision aid prototype appeared feasible, acceptable and comprehensible, and may serve as an effective means of improving shared decision-making.

Synchrony suppression in ensembles of coupled oscillators via adaptive vanishing feedback.

PubMed

Montaseri, Ghazal; Yazdanpanah, Mohammad Javad; Pikovsky, Arkady; Rosenblum, Michael

2013-09-01

Synchronization and emergence of a collective mode is a general phenomenon, frequently observed in ensembles of coupled self-sustained oscillators of various natures. In several circumstances, in particular in cases of neurological pathologies, this state of the active medium is undesirable. Destruction of this state by a specially designed stimulation is a challenge of high clinical relevance. Typically, the precise effect of an external action on the ensemble is unknown, since the microscopic description of the oscillators and their interactions are not available. We show that, desynchronization in case of a large degree of uncertainty about important features of the system is nevertheless possible; it can be achieved by virtue of a feedback loop with an additional adaptation of parameters. The adaptation also ensures desynchronization of ensembles with non-stationary, time-varying parameters. We perform the stability analysis of the feedback-controlled system and demonstrate efficient destruction of synchrony for several models, including those of spiking and bursting neurons.

Synchrony suppression in ensembles of coupled oscillators via adaptive vanishing feedback

NASA Astrophysics Data System (ADS)

Montaseri, Ghazal; Javad Yazdanpanah, Mohammad; Pikovsky, Arkady; Rosenblum, Michael

2013-09-01

Synchronization and emergence of a collective mode is a general phenomenon, frequently observed in ensembles of coupled self-sustained oscillators of various natures. In several circumstances, in particular in cases of neurological pathologies, this state of the active medium is undesirable. Destruction of this state by a specially designed stimulation is a challenge of high clinical relevance. Typically, the precise effect of an external action on the ensemble is unknown, since the microscopic description of the oscillators and their interactions are not available. We show that, desynchronization in case of a large degree of uncertainty about important features of the system is nevertheless possible; it can be achieved by virtue of a feedback loop with an additional adaptation of parameters. The adaptation also ensures desynchronization of ensembles with non-stationary, time-varying parameters. We perform the stability analysis of the feedback-controlled system and demonstrate efficient destruction of synchrony for several models, including those of spiking and bursting neurons.

Formation tracker design of multiple mobile robots with wheel perturbations: adaptive output-feedback approach

NASA Astrophysics Data System (ADS)

Yoo, Sung Jin

2016-11-01

This paper presents a theoretical design approach for output-feedback formation tracking of multiple mobile robots under wheel perturbations. It is assumed that these perturbations are unknown and the linear and angular velocities of the robots are unmeasurable. First, adaptive state observers for estimating unmeasurable velocities of the robots are developed under the robots' kinematics and dynamics including wheel perturbation effects. Then, we derive a virtual-structure-based formation tracker scheme according to the observer dynamic surface design procedure. The main difficulty of the output-feedback control design is to manage the coupling problems between unmeasurable velocities and unknown wheel perturbation effects. These problems are avoided by using the adaptive technique and the function approximation property based on fuzzy logic systems. From the Lyapunov stability analysis, it is shown that point tracking errors of each robot and synchronisation errors for the desired formation converge to an adjustable neighbourhood of the origin, while all signals in the controlled closed-loop system are semiglobally uniformly ultimately bounded.

Adaptive neural control of MIMO nonlinear systems with a block-triangular pure-feedback control structure.

PubMed

Chen, Zhenfeng; Ge, Shuzhi Sam; Zhang, Yun; Li, Yanan

2014-11-01

This paper presents adaptive neural tracking control for a class of uncertain multiinput-multioutput (MIMO) nonlinear systems in block-triangular form. All subsystems within these MIMO nonlinear systems are of completely nonaffine pure-feedback form and allowed to have different orders. To deal with the nonaffine appearance of the control variables, the mean value theorem is employed to transform the systems into a block-triangular strict-feedback form with control coefficients being couplings among various inputs and outputs. A systematic procedure is proposed for the design of a new singularity-free adaptive neural tracking control strategy. Such a design procedure can remove the couplings among subsystems and hence avoids the possible circular control construction problem. As a consequence, all the signals in the closed-loop system are guaranteed to be semiglobally uniformly ultimately bounded. Moreover, the outputs of the systems are ensured to converge to a small neighborhood of the desired trajectories. Simulation studies verify the theoretical findings revealed in this paper.

Adaptive restoration of a partially coherent blurred image using an all-optical feedback interferometer with a liquid-crystal device.

PubMed

Shirai, Tomohiro; Barnes, Thomas H

2002-02-01

A liquid-crystal adaptive optics system using all-optical feedback interferometry is applied to partially coherent imaging through a phase disturbance. A theoretical analysis based on the propagation of the cross-spectral density shows that the blurred image due to the phase disturbance can be restored, in principle, irrespective of the state of coherence of the light illuminating the object. Experimental verification of the theory has been performed for two cases when the object to be imaged is illuminated by spatially coherent light originating from a He-Ne laser and by spatially incoherent white light from a halogen lamp. We observed in both cases that images blurred by the phase disturbance were successfully restored, in agreement with the theory, immediately after the adaptive optics system was activated. The origin of the deviation of the experimental results from the theory, together with the effect of the feedback misalignment inherent in our optical arrangement, is also discussed.

Risky decision-making under risk in schizophrenia: A deliberate choice?

PubMed

Pedersen, Anya; Göder, Robert; Tomczyk, Samuel; Ohrmann, Patricia

2017-09-01

Patients with schizophrenia reveal impaired decision-making strategies causing social, financial and health care problems. The extent to which deficits in decision-making reflect intentional risky choices in schizophrenia is still under debate. Based on previous studies we expected patients with schizophrenia to reveal a riskier performance on the GDT and to make more disadvantageous decisions on the IGT. In the present study, we investigated 38 patients with schizophrenia and 38 matched healthy control subjects with two competing paradigms regarding feedback: (1) The Game of Dice Task (GDT), in which the probabilities of winning or losing are stable and explicitly disclosed to the subject, to assess decision-making under risk and (2) the Iowa Gambling Task (IGT), which requires subjects to infer the probabilities of winning or losing from feedback, to investigate decision-making under ambiguity. Patients with schizophrenia revealed an overall riskier performance on the GDT; although they adjusted their strategy over the course of the GDT, they still made significantly more disadvantageous choices than controls. More positive symptoms in patients with schizophrenia indicated by higher PANSS positive scores were associated with riskier choices and less use of negative feedback. Compared to healthy controls, they were not impaired in net score but chose more disadvantageous cards than controls on the first block of the IGT. Effects of medication at the time of testing cannot be ruled out. Our findings suggest that patients with schizophrenia make riskier decisions and are less able to regulate their decision-making to implement advantageous strategies, even when the probabilities of winning or losing are explicitly disclosed. The dissociation between performance on the GDT and IGT suggests a pronounced impairment of executive functions related to the dorsolateral prefrontal cortex. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nonlatching positive feedback enables robust bimodality by decoupling expression noise from the mean

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

Razooky, Brandon S.; Cao, Youfang; Hansen, Maike M. K.

Fundamental to biological decision-making is the ability to generate bimodal expression patterns where two alternate expression states simultaneously exist. Here in this study, we use a combination of single-cell analysis and mathematical modeling to examine the sources of bimodality in the transcriptional program controlling HIV’s fate decision between active replication and viral latency. We find that the HIV Tat protein manipulates the intrinsic toggling of HIV’s promoter, the LTR, to generate bimodal ON-OFF expression, and that transcriptional positive feedback from Tat shifts and expands the regime of LTR bimodality. This result holds for both minimal synthetic viral circuits and full-lengthmore » virus. Strikingly, computational analysis indicates that the Tat circuit’s non-cooperative ‘non-latching’ feedback architecture is optimized to slow the promoter’s toggling and generate bimodality by stochastic extinction of Tat. In contrast to the standard Poisson model, theory and experiment show that non-latching positive feedback substantially dampens the inverse noise-mean relationship to maintain stochastic bimodality despite increasing mean-expression levels. Given the rapid evolution of HIV, the presence of a circuit optimized to robustly generate bimodal expression appears consistent with the hypothesis that HIV’s decision between active replication and latency provides a viral fitness advantage. More broadly, the results suggest that positive-feedback circuits may have evolved not only for signal amplification but also for robustly generating bimodality by decoupling expression fluctuations (noise) from mean expression levels.« less

Extracting an evaluative feedback from the brain for adaptation of motor neuroprosthetic decoders.

PubMed

Mahmoudi, Babak; Principe, Jose C; Sanchez, Justin C

2010-01-01

The design of Brain-Machine Interface (BMI) neural decoders that have robust performance in changing environments encountered in daily life activity is a challenging problem. One solution to this problem is the design of neural decoders that are able to assist and adapt to the user by participating in their perception-action-reward cycle (PARC). Using inspiration both from artificial intelligence and neurobiology reinforcement learning theories, we have designed a novel decoding architecture that enables a symbiotic relationship between the user and an Intelligent Assistant (IA). By tapping into the motor and reward centers in the brain, the IA adapts the process of decoding neural motor commands into prosthetic actions based on the user's goals. The focus of this paper is on extraction of goal information directly from the brain and making it accessible to the IA as an evaluative feedback for adaptation. We have recorded the neural activity of the Nucleus Accumbens in behaving rats during a reaching task. The peri-event time histograms demonstrate a rich representation of the reward prediction in this subcortical structure that can be modeled on a single trial basis as a scalar evaluative feedback with high precision.

First impressions count: does FAIRness affect adaptation of clinical clerks in their first clinical placement?

PubMed

Edafe, Ovie; Mistry, Natasha; Chan, Philip

2013-09-01

FAIRness (Feedback, Activity, Individualisation, Relevance) teaching is a structured program, comprising series of classes in which student work is anonymised and reviewed by the whole class, as well as students receiving private feedback on their written work. The class work emphasises logic, structure and order in history and examination, with a diagnostic and management focus. The effect of FAIRness teaching methods on the adaptation of medical students entering their first clinical rotations was studied. 18 students in FAIRness placements and 72 students in conventional placements, all in medical/surgical units in the same University teaching hospital were studied. They completed questionnaires relating to effectiveness and quality of clinical teaching. Some students additionally attended focus groups, at the start of placement to discuss their expectations, and after 3 weeks, to discuss their adaptation to the clinical learning environment. All students entering clinical placements had low expectations of their future teaching. Students in standard placements still expressed negative attitudes after 3 weeks, while students on FAIRness placements felt positive. Students in FAIRness placements scored significantly higher on questions related to feedback and review of student work. FAIRness teaching practices help students to adapt to their first clinical placements.

Application of Physiological Self-Regulation and Adaptive Task Allocation Techniques for Controlling Operator Hazardous States of Awareness

NASA Technical Reports Server (NTRS)

Prinzel, Lawrence J., III; Pope, Alan T.; Freeman, Frederick G.

2001-01-01

Prinzel, Hadley, Freeman, and Mikulka found that adaptive task allocation significantly enhanced performance only when used at the endpoints of the task workload continuum (i.e., very low or high workload), but that the technique degraded performance if invoked during other levels of task demand. These researchers suggested that other techniques should be used in conjunction with adaptive automation to help minimize the onset of hazardous states of awareness (HSA) and keep the operator 'in-the-loop.' The paper reports on such a technique that uses psychophysiological self-regulation to modulate the level of task engagement. Eighteen participants were assigned to three groups (self-regulation, false feedback, and control) and performed a compensatory tracking task that was cycled between three levels of task difficulty on the basis of the electroencephalogram (EEG) record. Those participants who had received self-regulation training performed significantly better and reported lower NASA-TLX scores than participants in the false feedback and control groups. Furthermore, the false feedback and control groups had significantly more task allocations resulting in return-to-manual performance decrements and higher EEG difference scores. Theoretical and practical implications of these results for adaptive automation are discussed.

Spacecraft Formation Flying near Sun-Earth L2 Lagrange Point: Trajectory Generation and Adaptive Full-State Feedback Control

NASA Technical Reports Server (NTRS)

Wong, Hong; Kapila, Vikram

2004-01-01

In this paper, we present a method for trajectory generation and adaptive full-state feedback control to facilitate spacecraft formation flying near the Sun-Earth L2 Lagrange point. Specifically, the dynamics of a spacecraft in the neighborhood of a Halo orbit reveals that there exist quasi-periodic orbits surrounding the Halo orbit. Thus, a spacecraft formation is created by placing a leader spacecraft on a desired Halo orbit and placing follower spacecraft on desired quasi-periodic orbits. To produce a formation maintenance controller, we first develop the nonlinear dynamics of a follower spacecraft relative to the leader spacecraft. We assume that the leader spacecraft is on a desired Halo orbit trajectory and the follower spacecraft is to track a desired quasi-periodic orbit surrounding the Halo orbit. Then, we design an adaptive, full-state feedback position tracking controller for the follower spacecraft providing an adaptive compensation for the unknown mass of the follower spacecraft. The proposed control law is simulated for the case of the leader and follower spacecraft pair and is shown to yield global, asymptotic convergence of the relative position tracking errors.

The Influence of Feedback on Task-Switching Performance: A Drift Diffusion Modeling Account.

PubMed

Cohen Hoffing, Russell; Karvelis, Povilas; Rupprechter, Samuel; Seriès, Peggy; Seitz, Aaron R

2018-01-01

Task-switching is an important cognitive skill that facilitates our ability to choose appropriate behavior in a varied and changing environment. Task-switching training studies have sought to improve this ability by practicing switching between multiple tasks. However, an efficacious training paradigm has been difficult to develop in part due to findings that small differences in task parameters influence switching behavior in a non-trivial manner. Here, for the first time we employ the Drift Diffusion Model (DDM) to understand the influence of feedback on task-switching and investigate how drift diffusion parameters change over the course of task switch training. We trained 316 participants on a simple task where they alternated sorting stimuli by color or by shape. Feedback differed in six different ways between subjects groups, ranging from No Feedback (NFB) to a variety of manipulations addressing trial-wise vs. Block Feedback (BFB), rewards vs. punishments, payment bonuses and different payouts depending upon the trial type (switch/non-switch). While overall performance was found to be affected by feedback, no effect of feedback was found on task-switching learning. Drift Diffusion Modeling revealed that the reductions in reaction time (RT) switch cost over the course of training were driven by a continually decreasing decision boundary. Furthermore, feedback effects on RT switch cost were also driven by differences in decision boundary, but not in drift rate. These results reveal that participants systematically modified their task-switching performance without yielding an overall gain in performance.

Reinforcement-learning-based dual-control methodology for complex nonlinear discrete-time systems with application to spark engine EGR operation.

PubMed

Shih, Peter; Kaul, Brian C; Jagannathan, S; Drallmeier, James A

2008-08-01

A novel reinforcement-learning-based dual-control methodology adaptive neural network (NN) controller is developed to deliver a desired tracking performance for a class of complex feedback nonlinear discrete-time systems, which consists of a second-order nonlinear discrete-time system in nonstrict feedback form and an affine nonlinear discrete-time system, in the presence of bounded and unknown disturbances. For example, the exhaust gas recirculation (EGR) operation of a spark ignition (SI) engine is modeled by using such a complex nonlinear discrete-time system. A dual-controller approach is undertaken where primary adaptive critic NN controller is designed for the nonstrict feedback nonlinear discrete-time system whereas the secondary one for the affine nonlinear discrete-time system but the controllers together offer the desired performance. The primary adaptive critic NN controller includes an NN observer for estimating the states and output, an NN critic, and two action NNs for generating virtual control and actual control inputs for the nonstrict feedback nonlinear discrete-time system, whereas an additional critic NN and an action NN are included for the affine nonlinear discrete-time system by assuming the state availability. All NN weights adapt online towards minimization of a certain performance index, utilizing gradient-descent-based rule. Using Lyapunov theory, the uniformly ultimate boundedness (UUB) of the closed-loop tracking error, weight estimates, and observer estimates are shown. The adaptive critic NN controller performance is evaluated on an SI engine operating with high EGR levels where the controller objective is to reduce cyclic dispersion in heat release while minimizing fuel intake. Simulation and experimental results indicate that engine out emissions drop significantly at 20% EGR due to reduction in dispersion in heat release thus verifying the dual-control approach.

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

PubMed

Ong, M L; Ng, E Y K

2005-12-01

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

Modafinil alters decision making based on feedback history - a randomized placebo-controlled double blind study in humans.

PubMed

Bellebaum, Christian; Kuchinke, Lars; Roser, Patrik

2017-02-01

Modafinil is becoming increasingly popular as a cognitive enhancer. Research on the effects of modafinil on cognitive function have yielded mixed results, with negative findings for simple memory and attention tasks and enhancing effects for more complex tasks. In the present study we examined whether modafinil, due to its known effect on the dopamine level in the striatum, alters feedback-related choice behaviour. We applied a task that separately tests the choice of previously rewarded behaviours (approach) and avoidance of previously punished behaviours. 18 participants received a single dose of 200 mg modafinil. Their performance was compared to a group of 22 participants who received placebo in a double-blind design. Modafinil but not placebo induced a significant bias towards approach behaviour as compared to the frequency of avoidance behaviour. General attention, overall feedback-based acquisition of choice behaviour and reaction times in high vs low conflict choices were not significantly affected by modafinil. This finding suggests that modafinil has a specific effect on dopamine-mediated choice behaviour based on the history of feedback, while a contribution of noradrenaline is also conceivable. The described change in decision making cannot be considered as cognitive enhancement, but might rather have detrimental effects on decisions in everyday life.

The Future of Adaptive Learning: Does the Crowd Hold the Key?

ERIC Educational Resources Information Center

Heffernan, Neil T.; Ostrow, Korinn S.; Kelly, Kim; Selent, Douglas; Van Inwegen, Eric G.; Xiong, Xiaolu; Williams, Joseph Jay

2016-01-01

Due to substantial scientific and practical progress, learning technologies can effectively adapt to the characteristics and needs of students. This article considers how learning technologies can adapt over time by crowdsourcing contributions from teachers and students--explanations, feedback, and other pedagogical interactions. Considering the…

Measurement-based care for refractory depression: a clinical decision support model for clinical research and practice.

PubMed

Trivedi, Madhukar H; Daly, Ella J

2007-05-01

Despite years of antidepressant drug development and patient and provider education, suboptimal medication dosing and duration of exposure resulting in incomplete remission of symptoms remains the norm in the treatment of depression. Additionally, since no one treatment is effective for all patients, optimal implementation focusing on the measurement of symptoms, side effects, and function is essential to determine effective sequential treatment approaches. There is a need for a paradigm shift in how clinical decision making is incorporated into clinical practice and for a move away from the trial-and-error approach that currently determines the "next best" treatment. This paper describes how our experience with the Texas Medication Algorithm Project (TMAP) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial has confirmed the need for easy-to-use clinical support systems to ensure fidelity to guidelines. To further enhance guideline fidelity, we have developed an electronic decision support system that provides critical feedback and guidance at the point of patient care. We believe that a measurement-based care (MBC) approach is essential to any decision support system, allowing physicians to individualize and adapt decisions about patient care based on symptom progress, tolerability of medication, and dose optimization. We also believe that successful integration of sequential algorithms with MBC into real-world clinics will facilitate change that will endure and improve patient outcomes. Although we use major depression to illustrate our approach, the issues addressed are applicable to other chronic psychiatric conditions including comorbid depression and substance use disorder as well as other medical illnesses.

Measurement-Based Care for Refractory Depression: A Clinical Decision Support Model for Clinical Research and Practice

PubMed Central

Trivedi, Madhukar H.; Daly, Ella J.

2009-01-01

Despite years of antidepressant drug development and patient and provider education, suboptimal medication dosing and duration of exposure resulting in incomplete remission of symptoms remains the norm in the treatment of depression. Additionally, since no one treatment is effective for all patients, optimal implementation focusing on the measurement of symptoms, side effects, and function is essential to determine effective sequential treatment approaches. There is a need for a paradigm shift in how clinical decision making is incorporated into clinical practice and for a move away from the trial-and-error approach that currently determines the “next best” treatment. This paper describes how our experience with the Texas Medication Algorithm Project (TMAP) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial has confirmed the need for easy-to-use clinical support systems to ensure fidelity to guidelines. To further enhance guideline fidelity, we have developed an electronic decision support system that provides critical feedback and guidance at the point of patient care. We believe that a measurement-based care (MBC) approach is essential to any decision support system, allowing physicians to individualize and adapt decisions about patient care based on symptom progress, tolerability of medication, and dose optimization. We also believe that successful integration of sequential algorithms with MBC into real-world clinics will facilitate change that will endure and improve patient outcomes. Although we use major depression to illustrate our approach, the issues addressed are applicable to other chronic psychiatric conditions including comorbid depression and substance use disorder as well as other medical illnesses. PMID:17320312

Diagnostic Machine Learning Models for Acute Abdominal Pain: Towards an e-Learning Tool for Medical Students.

PubMed

Khumrin, Piyapong; Ryan, Anna; Judd, Terry; Verspoor, Karin

2017-01-01

Computer-aided learning systems (e-learning systems) can help medical students gain more experience with diagnostic reasoning and decision making. Within this context, providing feedback that matches students' needs (i.e. personalised feedback) is both critical and challenging. In this paper, we describe the development of a machine learning model to support medical students' diagnostic decisions. Machine learning models were trained on 208 clinical cases presenting with abdominal pain, to predict five diagnoses. We assessed which of these models are likely to be most effective for use in an e-learning tool that allows students to interact with a virtual patient. The broader goal is to utilise these models to generate personalised feedback based on the specific patient information requested by students and their active diagnostic hypotheses.

Modeling trial by trial and block feedback in perceptual learning

PubMed Central

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

2014-01-01

Feedback has been shown to play a complex role in visual perceptual learning. It is necessary for performance improvement in some conditions while not others. Different forms of feedback, such as trial-by-trial feedback or block feedback, may both facilitate learning, but with different mechanisms. False feedback can abolish learning. We account for all these results with the Augmented Hebbian Reweight Model (AHRM). Specifically, three major factors in the model advance performance improvement: the external trial-by-trial feedback when available, the self-generated output as an internal feedback when no external feedback is available, and the adaptive criterion control based on the block feedback. Through simulating a comprehensive feedback study (Herzog & Fahle 1997, Vision Research, 37 (15), 2133–2141), we show that the model predictions account for the pattern of learning in seven major feedback conditions. The AHRM can fully explain the complex empirical results on the role of feedback in visual perceptual learning. PMID:24423783

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

PubMed

Dempsey, Rachael; Fisher, Ann

2005-12-01

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

Adaptive Control for Microgravity Vibration Isolation System

NASA Technical Reports Server (NTRS)

Yang, Bong-Jun; Calise, Anthony J.; Craig, James I.; Whorton, Mark S.

2005-01-01

Most active vibration isolation systems that try to a provide quiescent acceleration environment for space science experiments have utilized linear design methods. In this paper, we address adaptive control augmentation of an existing classical controller that employs a high-gain acceleration feedback together with a low-gain position feedback to center the isolated platform. The control design feature includes parametric and dynamic uncertainties because the hardware of the isolation system is built as a payload-level isolator, and the acceleration Sensor exhibits a significant bias. A neural network is incorporated to adaptively compensate for the system uncertainties, and a high-pass filter is introduced to mitigate the effect of the measurement bias. Simulations show that the adaptive control improves the performance of the existing acceleration controller and keep the level of the isolated platform deviation to that of the existing control system.

Adaptive Time Stepping for Transient Network Flow Simulation in Rocket Propulsion Systems

NASA Technical Reports Server (NTRS)

Majumdar, Alok K.; Ravindran, S. S.

2017-01-01

Fluid and thermal transients found in rocket propulsion systems such as propellant feedline system is a complex process involving fast phases followed by slow phases. Therefore their time accurate computation requires use of short time step initially followed by the use of much larger time step. Yet there are instances that involve fast-slow-fast phases. In this paper, we present a feedback control based adaptive time stepping algorithm, and discuss its use in network flow simulation of fluid and thermal transients. The time step is automatically controlled during the simulation by monitoring changes in certain key variables and by feedback. In order to demonstrate the viability of time adaptivity for engineering problems, we applied it to simulate water hammer and cryogenic chill down in pipelines. Our comparison and validation demonstrate the accuracy and efficiency of this adaptive strategy.

Adaptive Inner-Loop Rover Control

NASA Technical Reports Server (NTRS)

Kulkarni, Nilesh; Ippolito, Corey; Krishnakumar, Kalmanje; Al-Ali, Khalid M.

2006-01-01

Adaptive control technology is developed for the inner-loop speed and steering control of the MAX Rover. MAX, a CMU developed rover, is a compact low-cost 4-wheel drive, 4-wheel steer (double Ackerman), high-clearance agile durable chassis, outfitted with sensors and electronics that make it ideally suited for supporting research relevant to intelligent teleoperation and as a low-cost autonomous robotic test bed and appliance. The design consists of a feedback linearization based controller with a proportional - integral (PI) feedback that is augmented by an online adaptive neural network. The adaptation law has guaranteed stability properties for safe operation. The control design is retrofit in nature so that it fits inside the outer-loop path planning algorithms. Successful hardware implementation of the controller is illustrated for several scenarios consisting of actuator failures and modeling errors in the nominal design.

Automatic Adaptation to Fast Input Changes in a Time-Invariant Neural Circuit

PubMed Central

Bharioke, Arjun; Chklovskii, Dmitri B.

2015-01-01

Neurons must faithfully encode signals that can vary over many orders of magnitude despite having only limited dynamic ranges. For a correlated signal, this dynamic range constraint can be relieved by subtracting away components of the signal that can be predicted from the past, a strategy known as predictive coding, that relies on learning the input statistics. However, the statistics of input natural signals can also vary over very short time scales e.g., following saccades across a visual scene. To maintain a reduced transmission cost to signals with rapidly varying statistics, neuronal circuits implementing predictive coding must also rapidly adapt their properties. Experimentally, in different sensory modalities, sensory neurons have shown such adaptations within 100 ms of an input change. Here, we show first that linear neurons connected in a feedback inhibitory circuit can implement predictive coding. We then show that adding a rectification nonlinearity to such a feedback inhibitory circuit allows it to automatically adapt and approximate the performance of an optimal linear predictive coding network, over a wide range of inputs, while keeping its underlying temporal and synaptic properties unchanged. We demonstrate that the resulting changes to the linearized temporal filters of this nonlinear network match the fast adaptations observed experimentally in different sensory modalities, in different vertebrate species. Therefore, the nonlinear feedback inhibitory network can provide automatic adaptation to fast varying signals, maintaining the dynamic range necessary for accurate neuronal transmission of natural inputs. PMID:26247884

Design of robust adaptive controller and feedback error learning for rehabilitation in Parkinson's disease: a simulation study.

PubMed

Rouhollahi, Korosh; Emadi Andani, Mehran; Karbassi, Seyed Mahdi; Izadi, Iman

2017-02-01

Deep brain stimulation (DBS) is an efficient therapy to control movement disorders of Parkinson's tremor. Stimulation of one area of basal ganglia (BG) by DBS with no feedback is the prevalent opinion. Reduction of additional stimulatory signal delivered to the brain is the advantage of using feedback. This results in reduction of side effects caused by the excessive stimulation intensity. In fact, the stimulatory intensity of controllers is decreased proportional to reduction of hand tremor. The objective of this study is to design a new controller structure to decrease three indicators: (i) the hand tremor; (ii) the level of delivered stimulation in disease condition; and (iii) the ratio of the level of delivered stimulation in health condition to disease condition. For this purpose, the authors offer a new closed-loop control structure to stimulate two areas of BG simultaneously. One area (STN: subthalamic nucleus) is stimulated by an adaptive controller with feedback error learning. The other area (GPi: globus pallidus internal) is stimulated by a partial state feedback (PSF) controller. Considering the three indicators, the results show that, stimulating two areas simultaneously leads to better performance compared with stimulating one area only. It is shown that both PSF and adaptive controllers are robust regarding system parameter uncertainties. In addition, a method is proposed to update the parameters of the BG model in real time. As a result, the parameters of the controllers can be updated based on the new parameters of the BG model.

Environmentally friendly driving feedback systems research and development for heavy duty trucks.

DOT National Transportation Integrated Search

2016-03-31

In this research project, the research team developed an environmentally-friendly driving feedback system for heavy-duty trucks, which was : adapted from a similar system previously developed for light-duty cars. The system consists of: 1) Eco-Routin...

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

A Post-Transcriptional Feedback Mechanism for Noise Suppression and Fate Stabilization

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

Hansen, Maike M. K.; Wen, Winnie Y.; Ingerman, Elena

Diverse biological systems utilize fluctuations (“noise”) in gene expression to drive lineage-commitment decisions. However, once a commitment is made, noise becomes detrimental to reliable function, and the mechanisms enabling post-commitment noise suppression are unclear. Here, we find that architectural constraints on noise suppression are overcome to stabilize fate commitment. Using single-molecule and time-lapse imaging, we find that—after a noise-driven event—human immunodeficiency virus (HIV) strongly attenuates expression noise through a non-transcriptional negative-feedback circuit. Feedback is established through a serial cascade of post-transcriptional splicing, whereby proteins generated from spliced mRNAs auto-deplete their own precursor unspliced mRNAs. Strikingly, this auto-depletion circuitry minimizes noisemore » to stabilize HIV’s commitment decision, and a noise-suppression molecule promotes stabilization. Lastly, this feedback mechanism for noise suppression suggests a functional role for delayed splicing in other systems and may represent a generalizable architecture of diverse homeostatic signaling circuits.« less

A Post-Transcriptional Feedback Mechanism for Noise Suppression and Fate Stabilization

DOE PAGES

Hansen, Maike M. K.; Wen, Winnie Y.; Ingerman, Elena; ...

2018-05-10

Diverse biological systems utilize fluctuations (“noise”) in gene expression to drive lineage-commitment decisions. However, once a commitment is made, noise becomes detrimental to reliable function, and the mechanisms enabling post-commitment noise suppression are unclear. Here, we find that architectural constraints on noise suppression are overcome to stabilize fate commitment. Using single-molecule and time-lapse imaging, we find that—after a noise-driven event—human immunodeficiency virus (HIV) strongly attenuates expression noise through a non-transcriptional negative-feedback circuit. Feedback is established through a serial cascade of post-transcriptional splicing, whereby proteins generated from spliced mRNAs auto-deplete their own precursor unspliced mRNAs. Strikingly, this auto-depletion circuitry minimizes noisemore » to stabilize HIV’s commitment decision, and a noise-suppression molecule promotes stabilization. Lastly, this feedback mechanism for noise suppression suggests a functional role for delayed splicing in other systems and may represent a generalizable architecture of diverse homeostatic signaling circuits.« less

The persistence of a visual dominance effect in a telemanipulator task: A comparison between visual and electrotactile feedback

NASA Technical Reports Server (NTRS)

Gaillard, J. P.

1981-01-01

The possibility to use an electrotactile stimulation in teleoperation and to observe the interpretation of such information as a feedback to the operator was investigated. It is proposed that visual feedback is more informative than an electrotactile one; and that complex electrotactile feedback slows down both the motor decision and motor response processes, is processed as an all or nothing signal, and bypasses the receptive structure and accesses directly in a working memory where information is sequentially processed and where memory is limited in treatment capacity. The electrotactile stimulation is used as an alerting signal. It is suggested that the visual dominance effect is the result of the advantage of both a transfer function and a sensory memory register where information is pretreated and memorized for a short time. It is found that dividing attention has an effect on the acquisition of the information but not on the subsequent decision processes.

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.

Future planning and evaluation for automated adaptive minehunting: a roadmap for mine countermeasures theory modernization

NASA Astrophysics Data System (ADS)

Garcia, Gregory A.; Wettergren, Thomas A.

2012-06-01

This paper presents a discussion of U.S. naval mine countermeasures (MCM) theory modernization in light of advances in the areas of autonomy, tactics, and sensor processing. The unifying theme spanning these research areas concerns the capability for in situ adaptation of processing algorithms, plans, and vehicle behaviors enabled through run-time situation assessment and performance estimation. Independently, each of these technology developments impact the MCM Measures of Effectiveness1 [MOE(s)] of time and risk by improving one or more associated Measures of Performance2 [MOP(s)]; the contribution of this paper is to outline an integrated strategy for realizing the cumulative benefits of these technology enablers to the United States Navy's minehunting capability. An introduction to the MCM problem is provided to frame the importance of the foundational research and the ramifications of the proposed strategy on the MIW community. We then include an overview of current and future adaptive capability research in the aforementioned areas, highlighting a departure from the existing rigid assumption-based approaches while identifying anticipated technology acceptance issues. Consequently, the paper describes an incremental strategy for transitioning from the current minehunting paradigm where tactical decision aids rely on a priori intelligence and there is little to no in situ adaptation or feedback to a future vision where unmanned systems3, equipped with a representation of the commander's intent, are afforded the authority and ability to adapt to environmental perturbations with minimal human-in-the-loop supervision. The discussion concludes with an articulation of the science and technology issues which the MCM research community must continue to address.

Acute effects of verbal feedback on upper-body performance in elite athletes.

PubMed

Argus, Christos K; Gill, Nicholas D; Keogh, Justin Wl; Hopkins, Will G

2011-12-01

Argus, CK, Gill, ND, Keogh, JWL, and Hopkins, WG. Acute effects of verbal feedback on upper-body performance in elite athletes. J Strength Cond Res 25(12): 3282-3287, 2011-Improved training quality has the potential to enhance training adaptations. Previous research suggests that receiving feedback improves single-effort maximal strength and power tasks, but whether quality of a training session with repeated efforts can be improved remains unclear. The purpose of this investigation was to determine the effects of verbal feedback on upper-body performance in a resistance training session consisting of multiple sets and repetitions in well-trained athletes. Nine elite rugby union athletes were assessed using the bench throw exercise on 4 separate occasions each separated by 7 days. Each athlete completed 2 sessions consisting of 3 sets of 4 repetitions of the bench throw with feedback provided after each repetition and 2 identical sessions where no feedback was provided after each repetition. When feedback was received, there was a small increase of 1.8% (90% confidence limits, ±2.7%) and 1.3% (±0.7%) in mean peak power and velocity when averaged over the 3 sets. When individual sets were compared, there was a tendency toward the improvements in mean peak power being greater in the second and third sets. These results indicate that providing verbal feedback produced acute improvements in upper-body power output of well-trained athletes. The benefits of feedback may be greatest in the latter sets of training and could improve training quality and result in greater long-term adaptation.

Design for an Adaptive Library Catalog.

ERIC Educational Resources Information Center

Buckland, Michael K.; And Others

1992-01-01

Describes OASIS, a prototype adaptive online catalog implemented as a front end to the University of California MELVYL catalog. Topics addressed include the concept of adaptive retrieval systems, strategic search commands, feedback, prototyping using a front-end, the problem of excessive retrieval, commands to limit or increase search results, and…

On the dynamic nature of response criterion in recognition memory: effects of base rate, awareness, and feedback.

PubMed

Rhodes, Matthew G; Jacoby, Larry L

2007-03-01

The authors examined whether participants can shift their criterion for recognition decisions in response to the probability that an item was previously studied. Participants in 3 experiments were given recognition tests in which the probability that an item was studied was correlated with its location during the test. Results from all 3 experiments indicated that participants' response criteria were sensitive to the probability that an item was previously studied and that shifts in criterion were robust. In addition, awareness of the bases for criterion shifts and feedback on performance were key factors contributing to the observed shifts in decision criteria. These data suggest that decision processes can operate in a dynamic fashion, shifting from item to item.

Reducing uncertainty about objective functions in adaptive management

USGS Publications Warehouse

Williams, B.K.

2012-01-01

This paper extends the uncertainty framework of adaptive management to include uncertainty about the objectives to be used in guiding decisions. Adaptive decision making typically assumes explicit and agreed-upon objectives for management, but allows for uncertainty as to the structure of the decision process that generates change through time. Yet it is not unusual for there to be uncertainty (or disagreement) about objectives, with different stakeholders expressing different views not only about resource responses to management but also about the appropriate management objectives. In this paper I extend the treatment of uncertainty in adaptive management, and describe a stochastic structure for the joint occurrence of uncertainty about objectives as well as models, and show how adaptive decision making and the assessment of post-decision monitoring data can be used to reduce uncertainties of both kinds. Different degrees of association between model and objective uncertainty lead to different patterns of learning about objectives. ?? 2011.

Adaptive antenna arrays for satellite communication

NASA Technical Reports Server (NTRS)

Gupta, Inder J.

1989-01-01

The feasibility of using adaptive antenna arrays to provide interference protection in satellite communications was studied. The feedback loops as well as the sample matric inversion (SMI) algorithm for weight control were studied. Appropriate modifications in the two were made to achieve the required interference suppression. An experimental system was built to test the modified feedback loops and the modified SMI algorithm. The performance of the experimental system was evaluated using bench generated signals and signals received from TVRO geosynchronous satellites. A summary of results is given. Some suggestions for future work are also presented.

Interoceptive awareness moderates neural activity during decision-making.

PubMed

Werner, Natalie S; Schweitzer, Nicola; Meindl, Thomas; Duschek, Stefan; Kambeitz, Joseph; Schandry, Rainer

2013-12-01

The current study examined the relationship between conscious perception of somatic feedback (interoceptive awareness) and neural responses preceding decision-making. Previous research has suggested that decision-making is influenced by body signals from the periphery or the central representation of the periphery. Using event-related fMRI, participants whose interoceptive awareness was assessed using a heartbeat perception paradigm performed the Iowa Gambling Task. The results show a positive relationship between the degree of interoceptive awareness and selection related activity in the right anterior insula and the left postcentral gyrus. Neural activity within the right anterior insula was associated with decision-making performance only in individuals with accurate but not in those with non-accurate interoceptive awareness. These findings support the role of somatic feedback in decision-making processes. They indicate that the right anterior insula holds a representation of somatic markers and that these are more strongly processed with increased interoceptive awareness. Copyright © 2013 Elsevier B.V. All rights reserved.

Adaptive Decision Aiding in Computer-Assisted Instruction: Adaptive Computerized Training System (ACTS).

ERIC Educational Resources Information Center

Hopf-Weichel, Rosemarie; And Others

This report describes results of the first year of a three-year program to develop and evaluate a new Adaptive Computerized Training System (ACTS) for electronics maintenance training. (ACTS incorporates an adaptive computer program that learns the student's diagnostic and decision value structure, compares it to that of an expert, and adapts the…

Adaptation to Coriolis force perturbation of movement trajectory; role of proprioceptive and cutaneous somatosensory feedback

NASA Technical Reports Server (NTRS)

Lackner, James R.; DiZio, Paul

2002-01-01

Subjects exposed to constant velocity rotation in a large fully-enclosed room that rotates initially make large reaching errors in pointing to targets. The paths and endpoints of their reaches are deviated in the direction of the transient lateral Coriolis forces generated by the forward velocity of their reaches. With additional reaches, subjects soon reach in straighter paths and become more accurate at landing on target even in the absence of visual feedback about their movements. Two factors contribute to this adaptation: first, muscle spindle and golgi tendon organ feedback interpreted in relation to efferent commands provide information about movement trajectory, and second, somatosensory stimulation of the fingertip at the completion of a reach provides information about the location of the fingertip relative to the torso.

Performance of a modified feedback loop adaptive array with TVRO satellite signals

NASA Technical Reports Server (NTRS)

Steadman, K.; Gupta, I. J.; Walton, E. K.

1990-01-01

The performance of an experimental adaptive antenna array system is evaluated using television-receive-only (TVRO) satellite signals. The experimental system is a sidelobe canceler with two auxiliary channels. Modified feedback loops are used to enhance the suppression of weak interfering signals. The modified feedback loops use two spatially separate antennas, each with an individual amplifier for each auxiliary channel. Thus, the experimental system uses five antenna elements. Instead of using five separate antennas, a reflector antenna with multiple feeds is used to receive signals from various TVRO satellites. The details of the earth station are given. It is shown that the experimental system can null up to two signals originating from interfering TVRO satellites while receiving the signals from a desired TVRO satellite.

Data for improvement and clinical excellence: protocol for an audit with feedback intervention in long-term care.

PubMed

Sales, Anne E; Schalm, Corinne

2010-10-13

There is considerable evidence about the effectiveness of audit coupled with feedback, although few audit with feedback interventions have been conducted in long-term care (LTC) settings to date. In general, the effects have been found to be modest at best, although in settings where there has been little history of audit and feedback, the effects may be greater, at least initially. The primary purpose of the Data for Improvement and Clinical Excellence (DICE) Long-Term Care project is to assess the effects of an audit with feedback intervention delivered monthly over 13 months in four LTC facilities. The research questions we addressed are:1. What effects do feedback reports have on processes and outcomes over time?2. How do different provider groups in LTC and home care respond to feedback reports based on data targeted at improving quality of care? The research team conducting this study comprises researchers and decision makers in continuing care in the province of Alberta, Canada. The intervention consists of monthly feedback reports in nine LTC units in four facilities in Edmonton, Alberta. Data for the feedback reports comes from the Resident Assessment Instrument Minimum Data Set (RAI) version 2.0, a standardized instrument mandated for use in LTC facilities throughout Alberta. Feedback reports consist of one page, front and back, presenting both graphic and textual information. Reports are delivered to all staff working in the four LTC facilities. The primary evaluation uses a controlled interrupted time series design both adjusted and unadjusted for covariates. The concurrent process evaluation uses observation and self-report to assess uptake of the feedback reports. Following the project phase described in this protocol, a similar intervention will be conducted in home care settings in Alberta. Depending on project findings, if they are judged useful by decision makers participating in this research team, we plan dissemination and spread of the feedback report approach throughout Alberta.

Automated feedback to foster safe driving in young drivers : Phase 2.

DOT National Transportation Integrated Search

2015-12-01

Intelligent Speed Adaptation (ISA) represents a promising approach to reduce speeding. A core principle for ISA systems is that they provide real-time feedback to drivers, prompting them to reduce speed when some threshold at or above the limit is re...

Video-feedback intervention increases sensitive parenting in ethnic minority mothers: a randomized control trial.

PubMed

Yagmur, Sengul; Mesman, Judi; Malda, Maike; Bakermans-Kranenburg, Marian J; Ekmekci, Hatice

2014-01-01

Using a randomized control trial design we tested the effectiveness of a culturally sensitive adaptation of the Video-feedback Intervention to promote Positive Parenting and Sensitive Discipline (VIPP-SD) in a sample of 76 Turkish minority families in the Netherlands. The VIPP-SD was adapted based on a pilot with feedback of the target mothers, resulting in the VIPP-TM (VIPP-Turkish Minorities). The sample included families with 20-47-month-old children with high levels of externalizing problems. Maternal sensitivity, nonintrusiveness, and discipline strategies were observed during pretest and posttest home visits. The VIPP-TM was effective in increasing maternal sensitivity and nonintrusiveness, but not in enhancing discipline strategies. Applying newly learned sensitivity skills in discipline situations may take more time, especially in a cultural context that favors more authoritarian strategies. We conclude that the VIPP-SD program and its video-feedback approach can be successfully applied in immigrant families with a non-Western cultural background, with demonstrated effects on parenting sensitivity and nonintrusiveness.

Vibration suppression for large scale adaptive truss structures using direct output feedback control

NASA Technical Reports Server (NTRS)

Lu, Lyan-Ywan; Utku, Senol; Wada, Ben K.

1993-01-01

In this article, the vibration control of adaptive truss structures, where the control actuation is provided by length adjustable active members, is formulated as a direct output feedback control problem. A control method named Model Truncated Output Feedback (MTOF) is presented. The method allows the control feedback gain to be determined in a decoupled and truncated modal space in which only the critical vibration modes are retained. The on-board computation required by MTOF is minimal; thus, the method is favorable for the applications of vibration control of large scale structures. The truncation of the modal space inevitably introduces spillover effect during the control process. In this article, the effect is quantified in terms of active member locations, and it is shown that the optimal placement of active members, which minimizes the spillover effect (and thus, maximizes the control performance) can be sought. The problem of optimally selecting the locations of active members is also treated.

Clinical Decision Making of Rural Novice Nurses

ERIC Educational Resources Information Center

Seright, Teresa J.

2010-01-01

The purpose of this study was to develop substantive theory regarding decision making by the novice nurse in a rural hospital setting. Interviews were guided by the following research questions: What cues were used by novice rural registered nurses in order to make clinical decisions? What were the sources of feedback which influenced subsequent…

Simulations and the Curriculum.

ERIC Educational Resources Information Center

Ediger, Marlow

Microcomputers can be used with simulation software to provide students both with experience in the "real world" of decision making and feedback on the decisions made. Such software allows individual students to choose the roles they wish to play from a menu of diverse roles and provides alternatives for them to consider for each decision to be…

High Expectations: Untenured Teacher Involvement in School Decision-Making

ERIC Educational Resources Information Center

Turnbull, Barbara

2004-01-01

Findings from the current study show that new teacher expectations for involvement in school decision-making are not being actualized. Based on feedback from elementary and secondary teachers (n=504) in 87 schools, the results show significant differences between actual and preferred levels of participation in 16 areas of school decision-making.…

Diversity in School Performance Feedback Systems

ERIC Educational Resources Information Center

Verhaeghe, Goedele; Schildkamp, Kim; Luyten, Hans; Valcke, Martin

2015-01-01

As data-based decision making is receiving increased attention in education, more and more school performance feedback systems (SPFSs) are being developed and used worldwide. These systems provide schools with data on their functioning. However, little research is available on the characteristics of the different SPFSs. Therefore, this study…

Keys to success for data-driven decision making: Lessons from participatory monitoring and collaborative adaptive management

USDA-ARS?s Scientific Manuscript database

Recent years have witnessed a call for evidence-based decisions in conservation and natural resource management, including data-driven decision-making. Adaptive management (AM) is one prevalent model for integrating scientific data into decision-making, yet AM has faced numerous challenges and limit...

Reasoning and Action: Implementation of a Decision-Making Program in Sport.

PubMed

Gil-Arias, Alexander; Moreno, M Perla; García-Mas, Alex; Moreno, Alberto; García-González, Luíz; Del Villar, Fernando

2016-09-20

The objective of this study was to apply a decision training programme, based on the use of video-feedback and questioning, in real game time, in order to improve decision-making in volleyball attack actions. A three-phase quasi-experimental design was implemented: Phase A (pre-test), Phase B (Intervention) and Phase C (Retention). The sample was made up of 8 female Under-16 volleyball players, who were divided into two groups: experimental group (n = 4) and control group (n = 4). The independent variable was the decision training program, which was applied for 11 weeks in a training context, more specifically in a 6x6 game situation. The player had to analyze the reasons and causes of the decision taken. The dependent variable was decision-making, which was assessed based on systematic observation, using the "Game Performance Assessment Instrument" (GPAI) (Oslin, Mitchell, & Griffin, 1998). Results showed that, after applying the decision training program, the experimental group showed a significantly higher average percentage of successful decisions than the control group F(1, 6) = 11.26; p = .015; η2 p = .652; 95% CI [056, 360]. These results highlight the need to complement the training process with cognitive tools such as video-feedback and questioning in order to improve athletes' decision-making.

Passive and active adaptive management: Approaches and an example

USGS Publications Warehouse

Williams, B.K.

2011-01-01

Adaptive management is a framework for resource conservation that promotes iterative learning-based decision making. Yet there remains considerable confusion about what adaptive management entails, and how to actually make resource decisions adaptively. A key but somewhat ambiguous distinction in adaptive management is between active and passive forms of adaptive decision making. The objective of this paper is to illustrate some approaches to active and passive adaptive management with a simple example involving the drawdown of water impoundments on a wildlife refuge. The approaches are illustrated for the drawdown example, and contrasted in terms of objectives, costs, and potential learning rates. Some key challenges to the actual practice of AM are discussed, and tradeoffs between implementation costs and long-term benefits are highlighted. ?? 2010 Elsevier Ltd.

Effect of Concurrent Visual Feedback Frequency on Postural Control Learning in Adolescents.

PubMed

Marco-Ahulló, Adrià; Sánchez-Tormo, Alexis; García-Pérez, José A; Villarrasa-Sapiña, Israel; González, Luis M; García-Massó, Xavier

2018-04-13

The purpose was to find better augmented visual feedback frequency (100% or 67%) for learning a balance task in adolescents. Thirty subjects were divided randomly into a control group, and 100% and 67% feedback groups. The three groups performed pretest (3 trials), practice (12 trials), posttest (3 trials) and retention (3 trials, 24 hours later). The reduced feedback group showed lower RMS in the posttest than in the pretest (p = 0.04). The control and reduced feedback groups showed significant lower median frequency in the posttest than in the pretest (p < 0.05). Both feedback groups showed lower values in retention than in the pretest (p < 0.05). Even when the effect of feedback frequency could not be detected in motor learning, 67% of the feedback was recommended for motor adaptation.

Hierarchical decision processes that operate over distinct timescales underlie choice and changes in strategy

PubMed Central

Purcell, Braden A.; Kiani, Roozbeh

2016-01-01

Decision-making in a natural environment depends on a hierarchy of interacting decision processes. A high-level strategy guides ongoing choices, and the outcomes of those choices determine whether or not the strategy should change. When the right decision strategy is uncertain, as in most natural settings, feedback becomes ambiguous because negative outcomes may be due to limited information or bad strategy. Disambiguating the cause of feedback requires active inference and is key to updating the strategy. We hypothesize that the expected accuracy of a choice plays a crucial rule in this inference, and setting the strategy depends on integration of outcome and expectations across choices. We test this hypothesis with a task in which subjects report the net direction of random dot kinematograms with varying difficulty while the correct stimulus−response association undergoes invisible and unpredictable switches every few trials. We show that subjects treat negative feedback as evidence for a switch but weigh it with their expected accuracy. Subjects accumulate switch evidence (in units of log-likelihood ratio) across trials and update their response strategy when accumulated evidence reaches a bound. A computational framework based on these principles quantitatively explains all aspects of the behavior, providing a plausible neural mechanism for the implementation of hierarchical multiscale decision processes. We suggest that a similar neural computation—bounded accumulation of evidence—underlies both the choice and switches in the strategy that govern the choice, and that expected accuracy of a choice represents a key link between the levels of the decision-making hierarchy. PMID:27432960

Hierarchical decision processes that operate over distinct timescales underlie choice and changes in strategy.

PubMed

Purcell, Braden A; Kiani, Roozbeh

2016-08-02

Decision-making in a natural environment depends on a hierarchy of interacting decision processes. A high-level strategy guides ongoing choices, and the outcomes of those choices determine whether or not the strategy should change. When the right decision strategy is uncertain, as in most natural settings, feedback becomes ambiguous because negative outcomes may be due to limited information or bad strategy. Disambiguating the cause of feedback requires active inference and is key to updating the strategy. We hypothesize that the expected accuracy of a choice plays a crucial rule in this inference, and setting the strategy depends on integration of outcome and expectations across choices. We test this hypothesis with a task in which subjects report the net direction of random dot kinematograms with varying difficulty while the correct stimulus-response association undergoes invisible and unpredictable switches every few trials. We show that subjects treat negative feedback as evidence for a switch but weigh it with their expected accuracy. Subjects accumulate switch evidence (in units of log-likelihood ratio) across trials and update their response strategy when accumulated evidence reaches a bound. A computational framework based on these principles quantitatively explains all aspects of the behavior, providing a plausible neural mechanism for the implementation of hierarchical multiscale decision processes. We suggest that a similar neural computation-bounded accumulation of evidence-underlies both the choice and switches in the strategy that govern the choice, and that expected accuracy of a choice represents a key link between the levels of the decision-making hierarchy.

Characterizing Decision-Analysis Performances of Risk Prediction Models Using ADAPT Curves.

PubMed

Lee, Wen-Chung; Wu, Yun-Chun

2016-01-01

The area under the receiver operating characteristic curve is a widely used index to characterize the performance of diagnostic tests and prediction models. However, the index does not explicitly acknowledge the utilities of risk predictions. Moreover, for most clinical settings, what counts is whether a prediction model can guide therapeutic decisions in a way that improves patient outcomes, rather than to simply update probabilities.Based on decision theory, the authors propose an alternative index, the "average deviation about the probability threshold" (ADAPT).An ADAPT curve (a plot of ADAPT value against the probability threshold) neatly characterizes the decision-analysis performances of a risk prediction model.Several prediction models can be compared for their ADAPT values at a chosen probability threshold, for a range of plausible threshold values, or for the whole ADAPT curves. This should greatly facilitate the selection of diagnostic tests and prediction models.

Using Instructive Feedback to Increase Response Variability During Intraverbal Training for Children with Autism Spectrum Disorder.

PubMed

Carroll, Regina A; Kodak, Tiffany

2015-10-01

We evaluated the effects of instructive feedback on the variability of intraverbal responses for two children with autism spectrum disorder. Specifically, we used an adapted alternating treatments design to compare participants' novel responses and response combinations during an intraverbal category program across conditions with and without instructive feedback. During instructive feedback, secondary targets were presented during the consequence event of the learning trial and consisted of a therapist's model of response variability. The results showed that participants engaged in more novel response combinations during instructive feedback conditions. We discussed the clinical implications of these results as well as areas for future research.

Adaptive wing static aeroelastic roll control

NASA Astrophysics Data System (ADS)

Ehlers, Steven M.; Weisshaar, Terrence A.

1993-09-01

Control of the static aeroelastic characteristics of a swept uniform wing in roll using an adaptive structure is examined. The wing structure is modeled as a uniform beam with bending and torsional deformation freedom. Aerodynamic loads are obtained from strip theory. The structure model includes coefficients representing torsional and bending actuation provided by embedded piezoelectric material layers. The wing is made adaptive by requiring the electric field applied to the piezoelectric material layers to be proportional to the wing root loads. The proportionality factor, or feedback gain, is used to control static aeroelastic rolling properties. Example wing configurations are used to illustrate the capabilities of the adaptive structure. The results show that rolling power, damping-in-roll and aileron effectiveness can be controlled by adjusting the feedback gain. And that dynamic pressure affects the gain required. Gain scheduling can be used to set and maintain rolling properties over a range of dynamic pressures. An adaptive wing provides a method for active aeroelastic tailoring of structural response to meet changing structural performance requirements during a roll maneuver.

Adaptive Neural Tracking Control for Switched High-Order Stochastic Nonlinear Systems.

PubMed

Zhao, Xudong; Wang, Xinyong; Zong, Guangdeng; Zheng, Xiaolong

2017-10-01

This paper deals with adaptive neural tracking control design for a class of switched high-order stochastic nonlinear systems with unknown uncertainties and arbitrary deterministic switching. The considered issues are: 1) completely unknown uncertainties; 2) stochastic disturbances; and 3) high-order nonstrict-feedback system structure. The considered mathematical models can represent many practical systems in the actual engineering. By adopting the approximation ability of neural networks, common stochastic Lyapunov function method together with adding an improved power integrator technique, an adaptive state feedback controller with multiple adaptive laws is systematically designed for the systems. Subsequently, a controller with only two adaptive laws is proposed to solve the problem of over parameterization. Under the designed controllers, all the signals in the closed-loop system are bounded-input bounded-output stable in probability, and the system output can almost surely track the target trajectory within a specified bounded error. Finally, simulation results are presented to show the effectiveness of the proposed approaches.

Iterative inversion of deformation vector fields with feedback control.

PubMed

Dubey, Abhishek; Iliopoulos, Alexandros-Stavros; Sun, Xiaobai; Yin, Fang-Fang; Ren, Lei

2018-05-14

Often, the inverse deformation vector field (DVF) is needed together with the corresponding forward DVF in four-dimesional (4D) reconstruction and dose calculation, adaptive radiation therapy, and simultaneous deformable registration. This study aims at improving both accuracy and efficiency of iterative algorithms for DVF inversion, and advancing our understanding of divergence and latency conditions. We introduce a framework of fixed-point iteration algorithms with active feedback control for DVF inversion. Based on rigorous convergence analysis, we design control mechanisms for modulating the inverse consistency (IC) residual of the current iterate, to be used as feedback into the next iterate. The control is designed adaptively to the input DVF with the objective to enlarge the convergence area and expedite convergence. Three particular settings of feedback control are introduced: constant value over the domain throughout the iteration; alternating values between iteration steps; and spatially variant values. We also introduce three spectral measures of the displacement Jacobian for characterizing a DVF. These measures reveal the critical role of what we term the nontranslational displacement component (NTDC) of the DVF. We carry out inversion experiments with an analytical DVF pair, and with DVFs associated with thoracic CT images of six patients at end of expiration and end of inspiration. The NTDC-adaptive iterations are shown to attain a larger convergence region at a faster pace compared to previous nonadaptive DVF inversion iteration algorithms. By our numerical experiments, alternating control yields smaller IC residuals and inversion errors than constant control. Spatially variant control renders smaller residuals and errors by at least an order of magnitude, compared to other schemes, in no more than 10 steps. Inversion results also show remarkable quantitative agreement with analysis-based predictions. Our analysis captures properties of DVF data associated with clinical CT images, and provides new understanding of iterative DVF inversion algorithms with a simple residual feedback control. Adaptive control is necessary and highly effective in the presence of nonsmall NTDCs. The adaptive iterations or the spectral measures, or both, may potentially be incorporated into deformable image registration methods. © 2018 American Association of Physicists in Medicine.

2D/3D video content adaptation decision engine based on content classification and user assessment

NASA Astrophysics Data System (ADS)

Fernandes, Rui; Andrade, M. T.

2017-07-01

Multimedia adaptation depends on several factors, such as the content itself, the consumption device and its characteristics, the transport and access networks and the user. An adaptation decision engine, in order to provide the best possible Quality of Experience to a user, needs to have information about all variables that may influence its decision. For the aforementioned factors, we implement content classification, define device classes, consider limited bandwidth scenarios and categorize user preferences based on a subjective quality evaluation test. The results of these actions generate vital information to pass to the adaptation decision engine so that its operation may provide the indication of the most suitable adaptation to perform that delivers the best possible outcome for the user under the existing constraints.

Automated feedback to foster safe driving in young drivers: phase 2 : traffic tech.

DOT National Transportation Integrated Search

2015-12-01

Intelligent Speed Adaptation (ISA) provides a promising approach to reduce speeding. A core principle of ISA is real-time feedback that lets drivers know when they are driving over the speed limit. The overall goal of the study was to provide insight...

Personalized Multi-Student Improvement Based on Bayesian Cybernetics

ERIC Educational Resources Information Center

Kaburlasos, Vassilis G.; Marinagi, Catherine C.; Tsoukalas, Vassilis Th.

2008-01-01

This work presents innovative cybernetics (feedback) techniques based on Bayesian statistics for drawing questions from an Item Bank towards personalized multi-student improvement. A novel software tool, namely "Module for Adaptive Assessment of Students" (or, "MAAS" for short), implements the proposed (feedback) techniques. In conclusion, a pilot…

Conceptual Problems.

ERIC Educational Resources Information Center

Foley, Walter J.

A systems theory approach to information requirements in education and in evaluation strategies is applied to decision making. Educational decision making itself involves long range planning, system structuring to implement goals, system allocation (cost), and system monitoring which provides the feedback. Each level requires differential…

Annual Forest Inventory: An Industry Perspective

Treesearch

Roger Lord

2000-01-01

The Forest Inventory and Analysis Program serves important public interests by providing credible data for informed public forest policy debates as well as feedback to the forest-based economic market. This feedback, which affects timber price expectations, helps ensure resource sustainability by promoting better investment decision making within the forest products...

Waves of regret: a meg study of emotion and decision-making.

PubMed

Giorgetta, Cinzia; Grecucci, Alessandro; Bonini, Nicolao; Coricelli, Giorgio; Demarchi, Gianpaolo; Braun, Christoph; Sanfey, Alan G

2013-01-01

Recent fMRI studies have investigated brain activity involved in the feeling of regret and disappointment by manipulating the feedback participants saw after making a decision to play certain gambles: full-feedback (regret: participant sees the outcomes from both the chosen and unchosen gamble) vs. partial-feedback (disappointment: participant only sees the outcome from chosen gamble). However, regret and disappointment are also characterized by differential agency attribution: personal agency for regret, external agency for disappointment. In this study, we investigate the neural correlates of these two characterizations of regret and disappointment using magnetoencephalography (MEG). To do this, we experimentally induced each emotion by manipulating feedback (chosen gamble vs. unchosen gamble), agency (human vs. computer choice) and outcomes (win vs. loss) in a fully randomized design. At the behavioral level the emotional experience of regret and disappointment were indeed affected by both feedback and agency manipulations. These emotions also differentially affect subsequent choices, with regret leading to riskier behavior. At the neural level both feedback and agency affected the brain responses associated with regret and disappointment, demonstrating differential localization in the brain for each. Notably, feedback regret showed greater brain activity in the right anterior and posterior regions, with agency regret producing greater activity in the left anterior region. These findings extend the evidence for neural activity in processing both regret and disappointment by highlighting for the first time the respective importance of feedback and agency, as well as outlining the temporal dynamics of these emotions. Copyright © 2012 Elsevier Ltd. All rights reserved.

Electronic filters, hearing aids and methods

NASA Technical Reports Server (NTRS)

Engebretson, A. Maynard (Inventor)

1995-01-01

An electronic filter for an electroacoustic system. The system has a microphone for generating an electrical output from external sounds and an electrically driven transducer for emitting sound. Some of the sound emitted by the transducer returns to the microphone means to add a feedback contribution to its electrical output. The electronic filter includes a first circuit for electronic processing of the electrical output of the microphone to produce a first signal. An adaptive filter, interconnected with the first circuit, performs electronic processing of the first signal to produce an adaptive output to the first circuit to substantially offset the feedback contribution in the electrical output of the microphone, and the adaptive filter includes means for adapting only in response to polarities of signals supplied to and from the first circuit. Other electronic filters for hearing aids, public address systems and other electroacoustic systems, as well as such systems and methods of operating them are also disclosed.

Electronic filters, hearing aids and methods

NASA Technical Reports Server (NTRS)

Engebretson, A. Maynard (Inventor); O'Connell, Michael P. (Inventor); Zheng, Baohua (Inventor)

1991-01-01

An electronic filter for an electroacoustic system. The system has a microphone for generating an electrical output from external sounds and an electrically driven transducer for emitting sound. Some of the sound emitted by the transducer returns to the microphone means to add a feedback contribution to its electical output. The electronic filter includes a first circuit for electronic processing of the electrical output of the microphone to produce a filtered signal. An adaptive filter, interconnected with the first circuit, performs electronic processing of the filtered signal to produce an adaptive output to the first circuit to substantially offset the feedback contribution in the electrical output of the microphone, and the adaptive filter includes means for adapting only in response to polarities of signals supplied to and from the first circuit. Other electronic filters for hearing aids, public address systems and other electroacoustic systems, as well as such systems, and methods of operating them are also disclosed.

Controller design for a class of nonlinear MIMO coupled system using multiple models and second level adaptation.

PubMed

Pandey, Vinay Kumar; Kar, Indrani; Mahanta, Chitralekha

2017-07-01

In this paper, an adaptive control method using multiple models with second level adaptation is proposed for a class of nonlinear multi-input multi-output (MIMO) coupled systems. Multiple estimation models are used to tune the unknown parameters at the first level. The second level adaptation provides a single parameter vector for the controller. A feedback linearization technique is used to design a state feedback control. The efficacy of the designed controller is validated by conducting real time experiment on a laboratory setup of twin rotor MIMO system (TRMS). The TRMS setup is discussed in detail and the experiments were performed for regulation and tracking problem for pitch and yaw control using different reference signals. An Extended Kalman Filter (EKF) has been used to observe the unavailable states of the TRMS. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Neuro-adaptive backstepping control of SISO non-affine systems with unknown gain sign.

PubMed

Ramezani, Zahra; Arefi, Mohammad Mehdi; Zargarzadeh, Hassan; Jahed-Motlagh, Mohammad Reza

2016-11-01

This paper presents two neuro-adaptive controllers for a class of uncertain single-input, single-output (SISO) nonlinear non-affine systems with unknown gain sign. The first approach is state feedback controller, so that a neuro-adaptive state-feedback controller is constructed based on the backstepping technique. The second approach is an observer-based controller and K-filters are designed to estimate the system states. The proposed method relaxes a priori knowledge of control gain sign and therefore by utilizing the Nussbaum-type functions this problem is addressed. In these methods, neural networks are employed to approximate the unknown nonlinear functions. The proposed adaptive control schemes guarantee that all the closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB). Finally, the theoretical results are numerically verified through simulation examples. Simulation results show the effectiveness of the proposed methods. Copyright © 2016 ISA. All rights reserved.

Autism: the micro-movement perspective

PubMed Central

Torres, Elizabeth B.; Brincker, Maria; Isenhower, Robert W.; Yanovich, Polina; Stigler, Kimberly A.; Nurnberger, John I.; Metaxas, Dimitris N.; José, Jorge V.

2013-01-01

The current assessment of behaviors in the inventories to diagnose autism spectrum disorders (ASD) focus on observation and discrete categorizations. Behaviors require movements, yet measurements of physical movements are seldom included. Their inclusion however, could provide an objective characterization of behavior to help unveil interactions between the peripheral and the central nervous systems (CNSs). Such interactions are critical for the development and maintenance of spontaneous autonomy, self-regulation, and voluntary control. At present, current approaches cannot deal with the heterogeneous, dynamic and stochastic nature of development. Accordingly, they leave no avenues for real time or longitudinal assessments of change in a coping system continuously adapting and developing compensatory mechanisms. We offer a new unifying statistical framework to reveal re-afferent kinesthetic features of the individual with ASD. The new methodology is based on the non-stationary stochastic patterns of minute fluctuations (micro-movements) inherent to our natural actions. Such patterns of behavioral variability provide re-entrant sensory feedback contributing to the autonomous regulation and coordination of the motor output. From an early age, this feedback supports centrally driven volitional control and fluid, flexible transitions between intentional and spontaneous behaviors. We show that in ASD there is a disruption in the maturation of this form of proprioception. Despite this disturbance, each individual has unique adaptive compensatory capabilities that we can unveil and exploit to evoke faster and more accurate decisions. Measuring the kinesthetic re-afference in tandem with stimuli variations we can detect changes in their micro-movements indicative of a more predictive and reliable kinesthetic percept. Our methods address the heterogeneity of ASD with a personalized approach grounded in the inherent sensory-motor abilities that the individual has already developed. PMID:23898241

Neural control and adaptive neural forward models for insect-like, energy-efficient, and adaptable locomotion of walking machines

PubMed Central

Manoonpong, Poramate; Parlitz, Ulrich; Wörgötter, Florentin

2013-01-01

Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs) and sensory feedback (afferent-based control) but also on internal forward models (efference copies). They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines. PMID:23408775

Proprioceptive loss and the perception, control and learning of arm movements in humans: evidence from sensory neuronopathy.

PubMed

Miall, R Chris; Kitchen, Nick M; Nam, Se-Ho; Lefumat, Hannah; Renault, Alix G; Ørstavik, Kristin; Cole, Jonathan D; Sarlegna, Fabrice R

2018-05-19

It is uncertain how vision and proprioception contribute to adaptation of voluntary arm movements. In normal participants, adaptation to imposed forces is possible with or without vision, suggesting that proprioception is sufficient; in participants with proprioceptive loss (PL), adaptation is possible with visual feedback, suggesting that proprioception is unnecessary. In experiment 1 adaptation to, and retention of, perturbing forces were evaluated in three chronically deafferented participants. They made rapid reaching movements to move a cursor toward a visual target, and a planar robot arm applied orthogonal velocity-dependent forces. Trial-by-trial error correction was observed in all participants. Such adaptation has been characterized with a dual-rate model: a fast process that learns quickly, but retains poorly and a slow process that learns slowly and retains well. Experiment 2 showed that the PL participants had large individual differences in learning and retention rates compared to normal controls. Experiment 3 tested participants' perception of applied forces. With visual feedback, the PL participants could report the perturbation's direction as well as controls; without visual feedback, thresholds were elevated. Experiment 4 showed, in healthy participants, that force direction could be estimated from head motion, at levels close to the no-vision threshold for the PL participants. Our results show that proprioceptive loss influences perception, motor control and adaptation but that proprioception from the moving limb is not essential for adaptation to, or detection of, force fields. The differences in learning and retention seen between the three deafferented participants suggest that they achieve these tasks in idiosyncratic ways after proprioceptive loss, possibly integrating visual and vestibular information with individual cognitive strategies.

Network adaptation improves temporal representation of naturalistic stimuli in Drosophila eye: II mechanisms.

PubMed

Nikolaev, Anton; Zheng, Lei; Wardill, Trevor J; O'Kane, Cahir J; de Polavieja, Gonzalo G; Juusola, Mikko

2009-01-01

Retinal networks must adapt constantly to best present the ever changing visual world to the brain. Here we test the hypothesis that adaptation is a result of different mechanisms at several synaptic connections within the network. In a companion paper (Part I), we showed that adaptation in the photoreceptors (R1-R6) and large monopolar cells (LMC) of the Drosophila eye improves sensitivity to under-represented signals in seconds by enhancing both the amplitude and frequency distribution of LMCs' voltage responses to repeated naturalistic contrast series. In this paper, we show that such adaptation needs both the light-mediated conductance and feedback-mediated synaptic conductance. A faulty feedforward pathway in histamine receptor mutant flies speeds up the LMC output, mimicking extreme light adaptation. A faulty feedback pathway from L2 LMCs to photoreceptors slows down the LMC output, mimicking dark adaptation. These results underline the importance of network adaptation for efficient coding, and as a mechanism for selectively regulating the size and speed of signals in neurons. We suggest that concert action of many different mechanisms and neural connections are responsible for adaptation to visual stimuli. Further, our results demonstrate the need for detailed circuit reconstructions like that of the Drosophila lamina, to understand how networks process information.

Adaptive Neural Output-Feedback Control for a Class of Nonlower Triangular Nonlinear Systems With Unmodeled Dynamics.

PubMed

Wang, Huanqing; Liu, Peter Xiaoping; Li, Shuai; Wang, Ding

2017-08-29

This paper presents the development of an adaptive neural controller for a class of nonlinear systems with unmodeled dynamics and immeasurable states. An observer is designed to estimate system states. The structure consistency of virtual control signals and the variable partition technique are combined to overcome the difficulties appearing in a nonlower triangular form. An adaptive neural output-feedback controller is developed based on the backstepping technique and the universal approximation property of the radial basis function (RBF) neural networks. By using the Lyapunov stability analysis, the semiglobally and uniformly ultimate boundedness of all signals within the closed-loop system is guaranteed. The simulation results show that the controlled system converges quickly, and all the signals are bounded. This paper is novel at least in the two aspects: 1) an output-feedback control strategy is developed for a class of nonlower triangular nonlinear systems with unmodeled dynamics and 2) the nonlinear disturbances and their bounds are the functions of all states, which is in a more general form than existing results.

Plasticity in the Human Speech Motor System Drives Changes in Speech Perception

PubMed Central

Lametti, Daniel R.; Rochet-Capellan, Amélie; Neufeld, Emily; Shiller, Douglas M.

2014-01-01

Recent studies of human speech motor learning suggest that learning is accompanied by changes in auditory perception. But what drives the perceptual change? Is it a consequence of changes in the motor system? Or is it a result of sensory inflow during learning? Here, subjects participated in a speech motor-learning task involving adaptation to altered auditory feedback and they were subsequently tested for perceptual change. In two separate experiments, involving two different auditory perceptual continua, we show that changes in the speech motor system that accompany learning drive changes in auditory speech perception. Specifically, we obtained changes in speech perception when adaptation to altered auditory feedback led to speech production that fell into the phonetic range of the speech perceptual tests. However, a similar change in perception was not observed when the auditory feedback that subjects' received during learning fell into the phonetic range of the perceptual tests. This indicates that the central motor outflow associated with vocal sensorimotor adaptation drives changes to the perceptual classification of speech sounds. PMID:25080594

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

Incidental emotions influence risk preference and outcome evaluation.

PubMed

Zhao, Ding; Gu, Ruolei; Tang, Ping; Yang, Qiwei; Luo, Yue-Jia

2016-10-01

Incidental emotions, which are irrelevant to the current decision, play a significant role in the decision-making process. In this study, to investigate the influence of incidental emotions on behavioral, psychological, and electrophysiological responses in the process of decision making, participants were required to perform a monetary gambling task. During the selection stage, an emotional picture, which was chosen from the Chinese Affective Picture System and fell into one of three categories: negative, neutral, and positive, was presented between two alternatives (small/large amount of bet). The pictures were provided to induce incidental emotions. ERPs and self-rating emotional experiences to outcome feedback were recorded during the task. Behavioral results showed that positive incidental emotions elicited risk preference, but emotional experiences to outcome feedback were not influenced by incidental emotions. The feedback-related negativity amplitudes were larger in the positive emotion condition than in the negative and neutral emotion conditions for small outcomes (including wins and losses), whereas there was no difference between the three conditions for large outcomes. In addition, the amplitudes of P3 were reduced overall in the negative emotion condition. We suggest that incidental emotions have modulated both the option assessment stage (manifested in behavioral choices) and the outcome evaluation stage (manifested in ERP amplitudes) of decision making unconsciously (indicated by unchanged subjective emotional experiences). The current findings have expanded our understanding of the role of incidental emotion in decision making. © 2016 Society for Psychophysiological Research.

Adaptation to Laterally Displacing Prisms in Anisometropic Amblyopia.

PubMed

Sklar, Jaime C; Goltz, Herbert C; Gane, Luke; Wong, Agnes M F

2015-06-01

Using visual feedback to modify sensorimotor output in response to changes in the external environment is essential for daily function. Prism adaptation is a well-established experimental paradigm to quantify sensorimotor adaptation; that is, how the sensorimotor system adapts to an optically-altered visuospatial environment. Amblyopia is a neurodevelopmental disorder characterized by spatiotemporal deficits in vision that impacts manual and oculomotor function. This study explored the effects of anisometropic amblyopia on prism adaptation. Eight participants with anisometropic amblyopia and 11 visually-normal adults, all right-handed, were tested. Participants pointed to visual targets and were presented with feedback of hand position near the terminus of limb movement in three blocks: baseline, adaptation, and deadaptation. Adaptation was induced by viewing with binocular 11.4° (20 prism diopter [PD]) left-shifting prisms. All tasks were performed during binocular viewing. Participants with anisometropic amblyopia required significantly more trials (i.e., increased time constant) to adapt to prismatic optical displacement than visually-normal controls. During the rapid error correction phase of adaptation, people with anisometropic amblyopia also exhibited greater variance in motor output than visually-normal controls. Amblyopia impacts on the ability to adapt the sensorimotor system to an optically-displaced visual environment. The increased time constant and greater variance in motor output during the rapid error correction phase of adaptation may indicate deficits in processing of visual information as a result of degraded spatiotemporal vision in amblyopia.

Designing Dynamic Adaptive Policy Pathways using Many-Objective Robust Decision Making

NASA Astrophysics Data System (ADS)

Kwakkel, Jan; Haasnoot, Marjolijn

2017-04-01

Dealing with climate risks in water management requires confronting a wide variety of deeply uncertain factors, while navigating a many dimensional space of trade-offs amongst objectives. There is an emerging body of literature on supporting this type of decision problem, under the label of decision making under deep uncertainty. Two approaches within this literature are Many-Objective Robust Decision Making, and Dynamic Adaptive Policy Pathways. In recent work, these approaches have been compared. One of the main conclusions of this comparison was that they are highly complementary. Many-Objective Robust Decision Making is a model based decision support approach, while Dynamic Adaptive Policy Pathways is primarily a conceptual framework for the design of flexible strategies that can be adapted over time in response to how the future is actually unfolding. In this research we explore this complementarity in more detail. Specifically, we demonstrate how Many-Objective Robust Decision Making can be used to design adaptation pathways. We demonstrate this combined approach using a water management problem, in the Netherlands. The water level of Lake IJselmeer, the main fresh water resource of the Netherlands, is currently managed through discharge by gravity. Due to climate change, this won't be possible in the future, unless water levels are changed. Changing the water level has undesirable flood risk and spatial planning consequences. The challenge is to find promising adaptation pathways that balance objectives related to fresh water supply, flood risk, and spatial issues, while accounting for uncertain climatic and land use change. We conclude that the combination of Many-Objective Robust Decision Making and Dynamic Adaptive Policy Pathways is particularly suited for dealing with deeply uncertain climate risks.

Computerized Aid Improves Safety Decision Process for Survivors of Intimate Partner Violence

ERIC Educational Resources Information Center

Glass, Nancy; Eden, Karen B.; Bloom, Tina; Perrin, Nancy

2010-01-01

A computerized safety decision aid was developed and tested with Spanish or English-speaking abused women in shelters or domestic violence (DV) support groups (n = 90). The decision aid provides feedback about risk for lethal violence, options for safety, assistance with setting priorities for safety, and a safety plan personalized to the user.…

Prosodic Adaptations to Pitch Perturbation in Running Speech

ERIC Educational Resources Information Center

Patel, Rupal; Niziolek, Caroline; Reilly, Kevin; Guenther, Frank H.

2011-01-01

Purpose: A feedback perturbation paradigm was used to investigate whether prosodic cues are controlled independently or in an integrated fashion during sentence production. Method: Twenty-one healthy speakers of American English were asked to produce sentences with emphatic stress while receiving real-time auditory feedback of their productions.…

Methods & Strategies: Teaching in Real Time

ERIC Educational Resources Information Center

Miranda, Rommel J.; Hermann, Ronald S.

2015-01-01

Any assessment activity can help student learning if it provides information that both teachers and students can use as feedback in assessing themselves. However, such assessment only becomes "formative" assessment when teachers actually use the feedback to adapt their teaching to meet the learning needs of students. This column provides…

[The adaptive biological control system with electromyographic feedback in the treatment of Bell's palsy].

PubMed

Lobzin, V S; Tsatskina, N D

1989-01-01

A total of 192 patients with Bell paralysis were studied. In 32 a technique of biofeedback training was applied to accelerate the restoration of mimetic muscles with EMG feedback. Clinical and electrophysiological data confirmed the efficiency of this technique in terms of considerably accelerated rehabilitation.

Cell Phone-Based Expert Systems for Smoking Cessation

DTIC Science & Technology

2011-09-01

computerized tailored intervention (CTI) with feedback messages delivered via cell phone . CTIs have shown increasing promise as useful behavior change programs...behaviors. This will be the first study to adapt a smoking cessation Internet-based CTI to provide personalized feedback on a cell phone to reduce smoking behaviors in military veterans.