Influence Of Prior Information Research Articles

External evaluation and systematic review of population pharmacokinetic models for high-dose methotrexate in cancer patients

Several population pharmacokinetic (PPK) models have been established to optimize the therapeutic regimen and reduce the toxicity of high-dose methotrexate (HDMTX) in patients with cancer. However, their predictive performance when extrapolated to different clinical centers was unknown. In this study, we aimed to externally evaluate the predictive ability of HDMTX PPK models and determine the potential influencing factors. We searched the literature and determined the predictive performance of the selected models using methotrexate concentrations in 721 samples from 60 patients in the First Affiliated Hospital of the Navy Medical University. Prediction-based diagnostics and simulation-based normalized prediction distribution errors (NPDE) were used to evaluate the predictive performance of the models. The influence of prior information was also assessed using Bayesian forecasting, and the potential factors affecting model predictability were investigated. Thirty models extracted from published PPK studies were assessed. Prediction-based diagnostics showed that the number of compartments potentially influenced model transferability, and simulation-based NPDE indicated model misspecification. Bayesian forecasting significantly improved the predictive performance of the models. Various factors, including bioassays, covariates, and population diagnosis, influence model extrapolation. The published models were unsatisfactory for all prediction-based diagnostics, except for the 24 h methotrexate concentration monitoring and simulation-based diagnostics, making them inappropriate for direct extrapolation. Moreover, Bayesian forecasting combined therapeutic drug monitoring could improve the predictive performance of the models.

Bayesian analysis of an M|M|1|∞ queueing model

In this paper, by considering an M|M|1|∞ queueing model, Bayes estimators of traffic intensity and measures of system performance are worked out under squared error loss function (SELF) based on observed data on the independent interarrival and service times. Further, minimum posterior risk associated with Bayes estimators of traffic intensity and system performance measures are obtained under SELF. Numerical illustration of the performance of the estimates is given through simulation study. It is shown that Bayes estimators perform better than the maximum likelihood estimators under the influence of prior information.

Perceptual inference, accuracy, and precision in temporal reproduction in schizophrenia

Accumulating evidence suggests that deficits in perceptual inference account for symptoms of schizophrenia. One manifestation of perceptual inference is the central bias, i.e., the tendency to put emphasis on prior experiences over actual events in perceiving incoming sensory stimuli. Using an interval reproduction task, this study aimed to determine whether patients with schizophrenia show a stronger central bias than participants without schizophrenia. In the interval reproduction task, participants were shown a cross on a screen. The cross was replaced with a Gaussian patch for a predetermined time interval, and participants were required to reproduce the interval duration by pressing and releasing the space key. We manipulated the uncertainty of prior information using different interval distributions. We found no difference in the influence of prior information on interval reproduction between patients and controls. However, patients with SZ showed a stronger central bias than healthy participants in the intermediate interval range (approximately 450 ms to 900 ms). It is possible that the patients in SZ have non-uniform deficits associated with interval range or uncertainty of prior information in perceptual inference. Further, the severity of avolition and alogia was correlated with the strength of central bias in SZ. This study provides some insights into the mechanisms underlying the association between schizophrenic symptoms and perceptual inference.

External evaluation of published population pharmacokinetic models of polymyxin B.

Several population pharmacokinetics (popPK) models for polymyxin B have been constructed to optimize therapeutic regimens. However, their predictive performance remains unclear when extrapolated to different clinical centers. Therefore, this study aimed to evaluate the predictive ability of polymyxin B popPK models. A literature search was conducted, and the predictive performance was determined for each selected model using an independent dataset of 20 patients (92 concentrations) from the Third Xiangya Hospital. Prediction- and simulation-based diagnostics were used to evaluate model predictability. The influence of prior information was assessed using Bayesian forecasting. Eight published studies were evaluated. In prediction-based diagnostics, the prediction error within ± 30% was over 50% in two models. In simulation-based diagnostics, the prediction- and variability-corrected visual predictive check (pvcVPC) showed satisfactory predictivity in three models, while the normalized prediction distribution error (NPDE) tests indicated model misspecification in all models. Bayesian forecasting demonstrated a substantially improvement in the model predictability even with one prior observation. Not all published models were satisfactory in prediction- and simulation-based diagnostics; however, Bayesian forecasting improved the predictability considerably with priors, which can be applied to guide polymyxin B dosing recommendations and adjustments for clinicians.

Long-term memory guides resource allocation in working memory

Working memory capacity is incredibly limited and thus it is important to use this resource wisely. Prior knowledge in long-term memory can aid in efficient encoding of information by allowing for the prioritization of novel stimuli over familiar ones. Here we used a full-report procedure in a visual working memory paradigm, where participants reported the location of six colored circles in any order, to examine the influence of prior information on resource allocation in working memory. Participants learned that one of the items appeared in a restricted range of locations, whereas the remaining items could appear in any location. We found that participants’ memory performance benefited from learning this prior information. Specifically, response precision increased for all items when prior information was available for one of the items. Responses for both familiar and novel items were systematically ordered from highest to lowest precision. Participants tended to report the familiar item in the second half of the six responses and did so with greater precision than for novel items. Moreover, novel items that appeared near the center of the prior location were reported with worse precision than novel items that appeared elsewhere. This shows that people strategically allocated working memory resources by ignoring information that appeared in predictable locations and prioritizing the encoding of information that appeared in unpredictable locations. Together these findings demonstrate that people rely on long-term memory not only for remembering familiar items, but also for the strategic allocation of their limited capacity working memory resources.

Dose-dependent modulation of the visually evoked N1/N170 by perceptual surprise: a clear demonstration of prediction-error signalling.

Prediction-error checking processes play a key role in predictive coding models of perception. However, neural indices of such processes have yet to be unambiguously demonstrated. To date, experimental paradigms aiming to study such phenomena have relied upon the relative frequency of stimulus repeats and/or 'unexpected' events that are physically different from 'expected' events. These features of experimental design leave open alternative explanations for the observed effects. A definitive demonstration requires that presumed prediction error-related responses should show contextual dependency (rather than simply effects of frequency or repetition) and should not be attributable to low-level stimulus differences. Most importantly, prediction-error signals should show dose dependency with respect to the degree to which expectations are violated. Here, we exploit a novel experimental paradigm specifically designed to address these issues, using it to interrogate early latency event-related potentials (ERPs) to contextually expected and unexpected visual stimuli. In two electroencephalography (EEG) experiments, we demonstrate that an N1/N170 evoked potential is robustly modulated by unexpected perceptual events ('perceptual surprise') and shows dose-dependent sensitivity with respect to both the influence of prior information and the extent to which expectations are violated. This advances our understanding of perceptual predictions in the visual domain by clearly identifying these evoked potentials as an index of visual surprise.

External evaluation of population pharmacokinetic models for ciclosporin in adult renal transplant recipients.

Several population pharmacokinetic (popPK) models for ciclosporin (CsA) in adult renal transplant recipients have been constructed to optimize the therapeutic regimen of CsA. However, little is known about their predictabilities when extrapolated to different clinical centres. Therefore, this study aimed to externally evaluate the predictive ability of CsA popPK models and determine the potential influencing factors. A literature search was conducted and the predictive performance was determined for each selected model using an independent data set of 62 patients (471 predose and 500 2-h postdose concentrations) from our hospital. Prediction-based diagnostics and simulation-based normalized prediction distribution error were used to evaluate model predictability. The influence of prior information was assessed using Bayesian forecasting. Additionally, potential factors influencing model predictability were investigated. Seventeen models extracted from 17 published popPK studies were assessed. Prediction-based diagnostics showed that ethnicity potentially influenced model transferability. Simulation-based normalized prediction distribution error analyses indicated misspecification in most of the models, especially regarding variance. Bayesian forecasting demonstrated that the predictive performance of the models substantially improved with 2-3 prior observations. The predictability of nonlinear Michaelis-Menten models was superior to that of linear compartmental models when evaluating the impact of structural models, indicating the underlying nonlinear kinetics of CsA. Structural model, ethnicity, covariates and prior observations potentially affected model predictability. Structural model is the predominant factor influencing model predictability. Incorporation of nonlinear kinetics in CsA popPK modelling should be considered. Moreover, Bayesian forecasting substantially improved model predictability.

A cost‐effective 3D electrical resistivity imaging approach applied to dike investigation

ABSTRACTAlthough DC electrical resistivity imaging is widely applied to dike investigation, either rapid 2D or high‐resolution 3D approaches fail to address actual needs. An intermediate electrical resistivity imaging approach referred to as “3D‐“ is introduced in this paper. The methodology is based on existing tools, and it offers useful and sufficiently reliable 3D images of the investigated structure within a cost‐effective and flexible procedure. The survey design, the model discretisation, and the thorough integration of a priori information are the main phases of this procedure. To demonstrate the benefits and limitations of this approach, it is applied to an existing stretch of embankment levee along the Loire River. A numerical study was carried out both on synthetic and real data to assess the 3D imaging capability of the approach and the influence of prior information on the inversion outputs. The important role of a priori information is shown to be even more essential here. The results demonstrate the efficiency and versatility of the 3D‐ approach for reliable and cost‐effective investigations of long dikes.

Basics for sensorimotor information processing: some implications for learning.

In sensorimotor activities, learning requires efficient information processing, whether in car driving, sport activities or human–machine interactions. Several factors may affect the efficiency of such processing: they may be extrinsic (i.e., task-related) or intrinsic (i.e., subjects-related). The effects of these factors are intimately related to the structure of human information processing. In the present article we will focus on some of them, which are poorly taken into account, even when minimizing errors or their consequences is an essential issue at stake. Among the extrinsic factors, we will discuss, first, the effects of the quantity and quality of information, secondly, the effects of instruction and thirdly motor program learning. Among the intrinsic factors, we will discuss first the influence of prior information, secondly how individual strategies affect performance and, thirdly, we will stress the fact that although the human brain is not structured to function errorless (which is not new) humans are able to detect their errors very quickly and (in most of the cases), fast enough to correct them before they result in an overt failure. Extrinsic and intrinsic factors are important to take into account for learning because (1) they strongly affect performance, either in terms of speed or accuracy, which facilitates or impairs learning, (2) the effect of certain extrinsic factors may be strongly modified by learning and (3) certain intrinsic factors might be exploited for learning strategies.

The Relationship of Uncertainty and Complexity with Observed Bias and Interindividual Differences When Timing Audiovisual Signals

Although in the last few decades there was an enormous progress in understanding the timing of auditory and visual signals, there are still three puzzling things yet to be unexplained: 1) often inconclusive results, 2) results depending on the task employed (such as synchrony judgment, SJ, or temporal order judgment, TOJ, tasks), and 3) high interindividual differences. Examples for the first point are studies investigating if the brain is capable of actively compensating for the different propagation speed of sound and light. Some studies finding support for such a mechanism and others do not. Given that our brain is, in opposite to a typical lab-situation, continuously bombarded with different audiovisual signals at a time it follows that the brain needs also to “decide” which auditory and visual neural activation belongs to the external event in question. Therefore, we will argue that an active compensation mechanism is insufficient and that, above all, the brain deals with an inverse problem when having to link neural signals in the presence of plenty of other competing ones. This inverse problem implies for the brain uncertainty about which of the neural signals belong together. In such a situation, and in combination with being “forced” for an action/conscious percept, information processing in the brain will lead to basically two general output alternatives: First, the output is based solely on present sensory data. In case incoming data are with regard to a decision ambiguous the output of the system (e.g., responses) will be random across trials. In this case no bias will be evident. Second, present sensory data are integrated with other data available in the system (e.g., gathered through past experience). In this case a specific bias will be evident. Such a mechanism might reduce decision time in ambiguous or complex situations.A brief overview about recent behavioral and electrophysiological findings in our lab (using SJs and TOJs) will be presented compatible with the view outlined above. I will emphasize how such a view might especially contribute to a better understanding of interindividual differences and individual bias by demonstrating: 1) influence of prior information, 2) a systematic relationship of prior information and the degree of uncertainty about present sensory data, 3) a systematic relation of task complexity (degree of freedom of possible cue or neural networks combinations) and interindividual differences.

Prior Information Biases Stimulus Representations during Vibrotactile Decision Making

Neurophysiological data suggest that the integration of prior information and incoming sensory evidence represents the neural basis of the decision-making process. Here, we aimed to identify the brain structures involved in the integration of prior information about the average magnitude of a stimulus set and current sensory evidence. Specifically, we investigated whether prior average information already biases vibrotactile decision making during stimulus perception and maintenance before the comparison process. For this purpose, we used a vibrotactile delayed discrimination task and fMRI. At the behavioral level, participants showed the time-order effect. This psychophysical phenomenon has been shown to result from the influence of prior information on the perception of and the memory for currently presented stimuli. Similarly, the fMRI signal reflected the integration of prior information about the average vibration frequency and the currently presented vibration frequency. During stimulus encoding, the fMRI signal in primary and secondary somatosensory (S2) cortex, thalamus, and ventral premotor cortex mirrored an integration process. During stimulus maintenance, only a region in the intraparietal sulcus showed this modulation by prior average information. Importantly, the fMRI signal in S2 and intraparietal sulcus correlated with individual differences in the degree to which participants integrated prior average information. This strongly suggests that these two regions play a pivotal role in the integration process. Taken together, these results support the notion that the integration of current sensory and prior average information is a major feature of how the human brain perceives, remembers, and judges magnitude stimuli.

An Adaptive Muscular Force Generation Mechanism Based on Prior Information of Handling Object

Evaluating the influences of human-machine interface (HMI) visual information is vital to developing the user-oriented and human-friendly equipment, robots, etc. We define HMI visual information as prior information, such as size, color, shape, etc. The relationship between prior information and the Kansei feeling is evaluated by surface electromyogram (sEMG). This study deals with object-grasping motion and measures sEMG signals during the motion. Prediction on object-grasping motion is predicted from sEMG signals and defined as Force Prediction (FP). Differences between prediction of HMI operation and actual results are assumed to influence on Kansei feeling concerning the operation. Subjects given different prior information calculate FP about plastic bottles when grasping them. Experimental results show that the FP differs even though the plastic bottles have the same weight. The influence of prior information on FP is visually plotted in a three-dimensional map which is called Size-Color-iEMG map, and its application is to HMI design.

BACKCALCULATION OF PAVEMENT LAYER MODULI USING EXTENDED BAYESIAN METHOD

FWD testing and backcalculation have been conducted on pavement evaluation for many years. However, none of the existing backcalculation procedure is guaranteed to give reasonable moduli values for every deflection basin measured. To increase the precision of the backcalculation moduli, a new backcalculation procedure based on Extended Bayesian Method (EBM) was described in this paper. The advantage of EBM is to utilize prior information of pavement layers, as well as deflection for backcalculation of pavement. The practical backcalculation of FWD common test measurements indicates that the layer moduli of pavement can be estimated properly by this procedure, and the results are stable and reasonable. Finally, the influence of prior information on backcalculated results is also discussed.

The Influence of Prior Information about Clients on Evaluations and Responses of Clinicians During Family Therapy

An experiment is described in which psychotherapists observed a videotape showing segments of a conjoint therapeutic assessment session with a father, mother, and son of 18 years. Prior to observing the tape the subjects received either negative information about the parents combined with positive information about the son; neutral information; or negative information about the son combined with positive information about the parents. The subjects were given the opportunity to “intervene” at six fixed points, by writing down exactly what they would say to each of the family members at that moment, and to describe their rationale in choosing a particular intervention. The behavioral interventions and the accompanying attitude were rated for amount of sympathy expressed toward each of the family members. It was predicted that the subjects would intervene in a relatively negative way and display a negative attitude toward the person about whom they had received negative prior information while positive prior information would lead to positive interventions and a positive attitude. Both attitude and behavior were significantly biased in the predicted direction, while the influence of prior information on the perceptual level appeared to be less strong. In the discussion, special attention is given to ambiguity of the behavior of targets, the relationship between the source of the prior information and the targets, the external validity of the study, and directives for future research.

Forewarning of a Threat and Prior Knowledge of Outcome Effects on Children's Emotional Responses to a Film Sequence

An experiment examined the influence of prior information on children's emotional responses to a frightening program. Children at two age levels (5–7 and 9–11 years) viewed a program that included a threatening scene and a happy resolution. Before viewing, they heard one of four audiotaped introductions created by factorially varying information about the threat (forewarning, no forewarning) and the happy outcome (prior knowledge, no prior knowledge). Emotional responses were assessed through self-reports, facial expressions (coded using hard's Affex coding scheme), and skin temperature (as an index of physiological arousal). Self-reports of emotion revealed that forewarning of the threat increased anticipatory fear but did not affect emotional responses to the threatening scene. Prior knowledge of the happy outcome tended to reduce anticipatory fear but had a somewhat inconsistent effect on fear during the threatening scene. Changes in skin temperature over time were consistent with predictions, but no effects of the manipulations emerged for facial expressions of negative affect. Expected age differences were not observed for either type of prior information. Responses to the happy outcome were also examined. Children's reports of coping strategies and the results of manipulation checks were considered in interpreting the findings.