How Prior Reward Experience Biases Exploratory Movements: A Probabilistic Model

2007 ◽  
Vol 97 (3) ◽  
pp. 2083-2093 ◽  
Author(s):  
Paul W. German ◽  
Howard L. Fields

Animals return to rewarded locations. An example of this is conditioned place preference (CPP), which is widely used in studies of drug reward. Although CPP is expressed as increased time spent in a previously rewarded location, the behavioral strategy underlying this change is unknown. We continuously monitored rats ( n = 22) in a three-room in-line configuration, before and after morphine conditioning in one end room. Although sequential room visit durations were variable, their probability distribution was exponential, indicating that the processes controlling visit durations can be modeled by instantaneous room exit probabilities. Further analysis of room transitions and computer simulations of probabilistic models revealed that the exploratory bias toward the morphine room is best explained by an increase in the probability of a subset of rapid, direct transitions from the saline- to the morphine-paired room by the central room. This finding sharply delineates and constrains possible neural mechanisms for a class of self-initiated, goal-directed behaviors toward previously rewarded locations.

Author(s):  
Philippe Cambos ◽  
Guy Parmentier

During ship life, operating conditions may change, tanker may be converted into FPSO, and flag requirements may be modified. Generally these modifications have few impacts on existing structures; flag requirements only rarely are to be applied retroactively. Nevertheless in some cases modifications of operating condition may induce considerable consequences, making in the worst cases impossible any reengineering. For example converting a common tanker, built with plain steel of grade A into an Offshore Floating Unit able operating in cold region, may require a grade change corresponding to a grade B. It is obviously meaningless to replace all material just because material certificates. Steels used by shipyards have to fulfill Classification society’s requirements dealing with mechanical strength; generally shipbuilding corresponds to a small part of steelmaker’s production. For this reason steelmakers are reluctant to produce steels with mechanical properties corresponding exactly to the minima required. They generally deliver steels already in stock, with higher mechanical characteristics than required. In this case it can be taken advantage of this common practice. In order to demonstrate that the material fulfill the requirements of grade B it has been decided to adopt a statistic approach. At this stage there are two main issues, the first one is that it is needed to provide evidences that the actual material Charpy V characteristics fulfill the requirements of grade B; the second one is to provide these evidences with a minimum testing. To assess this assumption a random check has been carried out. Different probabilistic model have been tested in order to check common approaches and probabilistic model based on physical considerations. In the paper the main assumptions for estimating the minimum Charpy value main assumption in the probabilistic models are recalled, the behavior of empirical sample is examined, the parameters of probability laws fitting the empirical distribution and definitely as accuracy of probability law parameters determination is not perfect with a finite number of specimens the uncertainty in the determination of parameters is taken into account with confidence limits. According to the selected probabilistic model the minimum value corresponds to an acceptable probability of failure, taking into account the target confidence level, or is independent of any acceptable probability of failure and is defined with the same confidence level. At the end it is concluded that a random check with a data treatment assuming a random distribution of Charpy V test results distributed according to a Weibull probability law of the minimum allows providing evidences that with a sufficient confidence level the steel used for the considered structure fulfill the requirements of the new operating conditions.


Nutrients ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1627
Author(s):  
Lisa Kilpatrick ◽  
Teodora Pribic ◽  
Barbara Ciccantelli ◽  
Carolina Malagelada ◽  
Dan M. Livovsky ◽  
...  

The neural mechanisms underlying subjective responses to meal ingestion remain incompletely understood. We previously showed in healthy men an increase in thalamocortical, and a decrease in insular-cortical connectivity in response to a palatable meal. As sex is increasingly recognized as an important biological variable, we aimed to evaluate sex differences and commonalities in the impact of a well-liked meal on thalamic and anterior insular connectivity in healthy individuals. Participants (20 women and 20 age-matched men) underwent resting-state magnetic resonance imaging (rsMRI) before and after ingesting a palatable meal. In general, the insula showed extensive postprandial reductions in connectivity with sensorimotor and prefrontal cortices, while the thalamus showed increases in connectivity with insular, frontal, and occipital cortices, in both women and men. However, reductions in insular connectivity were more prominent in men, and were related to changes in meal-related sensations (satiety and digestive well-being) in men only. In contrast, increases in thalamic connectivity were more prominent in women, and were related to changes in satiety and digestive well-being in women only. These results suggest that brain imaging may provide objective and sex-specific biomarkers of the subjective feelings associated with meal ingestion.


Fractals ◽  
1995 ◽  
Vol 03 (01) ◽  
pp. 113-122 ◽  
Author(s):  
FRANCK PLOURABOUÉ ◽  
STÉPHANE ROUX ◽  
JEAN SCHMITTBUHL ◽  
JEAN-PIERRE VILOTTE

We study the geometry of the contact between two rigid self-affine surfaces. We investigate the mean shape of the surface in the vicinity of the contact point as well as the probability distribution of apertures a as a function of the distance to the contact point. The latter reveals two distinct scaling regimes which are characterized. We show that as the two surfaces are shifted with respect to each other, the contact point on one surface undergoes a “Levy walk”. If u is the relative shift of the surfaces, the distance d between the two contact points (before and after the shift), scales as d ∝ uα where the exponent α is shown to be equal to the roughness exponent of the surfaces.


1985 ◽  
Vol 249 (4) ◽  
pp. F542-F545 ◽  
Author(s):  
R. Vandongen ◽  
H. McGowan ◽  
H. Anderson ◽  
A. Barden

The contribution of the renal nerves in maintaining blood pressure and modulating renal prostanoid synthesis was examined in established (less than 8 wk in duration) one-kidney, one-clip (1K,1C) hypertension in the rat. Systolic blood pressure was measured for 7 days after renal denervation, at which time the renal artery clip was removed. Twenty-four-hour urinary excretion of PGE2 and 6-keto-PGF1 alpha (stable degradation product of PGI2) was determined before and after denervation and unclipping. Compared with sham-denervated rats, denervation (n = 15) resulted in a small but significant fall in blood pressure (from 216 +/- 4 to 182 +/- 4 mmHg after 48 h) and an increase in urinary 6-keto-PGF1 alpha (from 31 +/- 4 to 43 +/- 5 ng/24 h after 24 h). There was no change in PGE2 excretion. Seven days after surgery, blood pressures were similar in denervated (202 +/- 4 mmHg) and sham-denervated (211 +/- 5 mmHg) rats and fell to a similar extent 24 h after unclipping (142 +/- 3 and 147 +/- 4 mmHg, respectively). Urinary 6-keto-PGF1 alpha increased from 25 +/- 5 to 74 +/- 11 in denervated and 21 +/- 2 to 72 +/- 9 ng/24 h in sham-denervated rats in the 24 h after unclipping. PGE2 excretion increased approximately twofold over this period. These findings indicate that the renal nerves have only a minor role in established hypertension in the 1K,1C rat and that the reversal of hypertension and stimulation of renal prostanoid synthesis following unclipping is not dependent on neural mechanisms.


2005 ◽  
Vol 19 (4) ◽  
pp. 475-488 ◽  
Author(s):  
Ian Dobson ◽  
Benjamin A. Carreras ◽  
Vickie E. Lynch ◽  
Bertrand Nkei ◽  
David E. Newman

We compare and test statistical estimates of failure propagation in data from versions of a probabilistic model of loading-dependent cascading failure and a power system blackout model of cascading transmission line overloads. The comparisons suggest mechanisms affecting failure propagation and are an initial step toward monitoring failure propagation from practical system data. Approximations to the probabilistic model describe the forms of probability distribution of cascade sizes.


Author(s):  
Niraja Jain, Dr B Raghu, Dr V Khanaa

Dynamic cloud infrastructure provisioning is possible with the virtualization technology. Cost, agility and time to market are the key elements of the cloud services. Virtualization is the software layer responsible for interaction with multiple servers, bringing entire IT resources together and provide standardized Virtual compute centers that drives the entire infrastructure. The increased pooling of shared resources helps in improving self-provisioning and automation of service delivery. Probabilistic model proposed in this article is based on the hypothesis that the accurate resource demand predictions can benefit in improving the virtualization layer efficiency. The probabilistic method, uses the laws of combinatorics. The probability space gives an idea about both the partial certainty and randomness of the variable. The method is popular in theoretical computer science. The probabilistic models provide the predictions considering the randomness of the variables. In the cloud environment there are multiple factors dynamically affecting the resource demand needs. The resource demand has a certain degree of certainty but the randomness of requirements. This further leads to decrease in risk related to leveraging cloud services. It accelerates development and implementation of cloud services that overall improves the services pertaining to SLA.


10.14311/1055 ◽  
2008 ◽  
Vol 48 (5) ◽  
Author(s):  
M. Svítek

This paper presents the theory of wave probabilistic models, together with important features, such as the inclusion-exclusion rule, the product rule, the complementary principle and entanglement. These features are mathematically described, and an illustrative example of binary time series is shown to demonstrate possible applications of the theory. 


2021 ◽  
Vol 2021 (2) ◽  
pp. 3-12
Author(s):  
N.A. Shidlovska ◽  
◽  
S.M. Zakharchenko ◽  

Two strategies for constructing nonlinear-probabilistic models of the equivalent electrical resistance of a layer of metal granules at their spark-erosion and plasma-erosion treatment and algorithms for their implementation are presented. A method for taking into account the parametric properties of such loads in their nonlinear and nonlinear-probabilistic models is described. Based on the data of direct experiments, the distributions of the electrical resistance of a layer of aluminum granules in tap water were obtained for eleven fixed values of the discharge current in it for both the leading and trailing edges of its pulses. The features of these distributions are described for different edges of the discharge current pulses. It has been proved that the obtained distributions can be adequately described by the normal law. The parameters of the normal law for each distribution obtained as a result of direct experiments are founded by the method of moments. A nonlinear-probabilistic model of the equivalent electrical resistance of a layer of aluminum granules in tap water is created, taking into account the main hysteresis of the dependence of resistance on current. It is shown that at large values of discharge currents, the nonlinear-probabilistic model of the equivalent electrical resistance of the layers of metal granules tends to degenerate into a nonlinear model. References 27, figures 4


2020 ◽  
Vol 109 (5) ◽  
pp. 939-972
Author(s):  
Yu Nishiyama ◽  
Motonobu Kanagawa ◽  
Arthur Gretton ◽  
Kenji Fukumizu

AbstractKernel Bayesian inference is a principled approach to nonparametric inference in probabilistic graphical models, where probabilistic relationships between variables are learned from data in a nonparametric manner. Various algorithms of kernel Bayesian inference have been developed by combining kernelized basic probabilistic operations such as the kernel sum rule and kernel Bayes’ rule. However, the current framework is fully nonparametric, and it does not allow a user to flexibly combine nonparametric and model-based inferences. This is inefficient when there are good probabilistic models (or simulation models) available for some parts of a graphical model; this is in particular true in scientific fields where “models” are the central topic of study. Our contribution in this paper is to introduce a novel approach, termed the model-based kernel sum rule (Mb-KSR), to combine a probabilistic model and kernel Bayesian inference. By combining the Mb-KSR with the existing kernelized probabilistic rules, one can develop various algorithms for hybrid (i.e., nonparametric and model-based) inferences. As an illustrative example, we consider Bayesian filtering in a state space model, where typically there exists an accurate probabilistic model for the state transition process. We propose a novel filtering method that combines model-based inference for the state transition process and data-driven, nonparametric inference for the observation generating process. We empirically validate our approach with synthetic and real-data experiments, the latter being the problem of vision-based mobile robot localization in robotics, which illustrates the effectiveness of the proposed hybrid approach.


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