Intrinsic Valuation of Information in Decision Making under Uncertainty

In a dynamic world, an accurate model of the environment is vital for survival, and agents ought regularly to seek out new information with which to update their world models. This aspect of behaviour is not captured well by classical theories of decision making, and the cognitive mechanisms of information seeking are poorly understood. In particular, it is not known whether information is valued only for its instrumental use, or whether humans also assign it a non-instrumental intrinsic value. To address this question, the present study assessed preference for non-instrumental information among 80 healthy participants in two experiments. Participants performed a novel information preference task in which they could choose to pay a monetary cost to receive advance information about the outcome of a monetary lottery. Importantly, acquiring information did not alter lottery outcome probabilities. We found that participants were willing to incur considerable monetary costs to acquire payoff-irrelevant information about the lottery outcome. This behaviour was well explained by a computational cognitive model in which information preference resulted from aversion to temporally prolonged uncertainty. These results strongly suggest that humans assign an intrinsic value to information in a manner inconsistent with normative accounts of decision making under uncertainty. This intrinsic value may be associated with adaptive behaviour in real-world environments by producing a bias towards exploratory and information-seeking behaviour.     

In Search of a Consistent Solution to Allocation of Joint Production

Three consistency problems are identified that arise when partitioning a product system with joint production according to an allocation key, such as revenue or mass of the joint products, namely: lacking consistency of rationales and procedures; lacking consistency of monetary, mass, and energy balances in the partitioned product systems; and lacking consistency of results across model resolution and classification of the intermediate flows. Different solutions to these consistency problems are described, including the attempt of ecoinvent to solve the third consistency problem with a system model that uses revenue allocation at the point of substitution. The problems with the different practical implementations are described. For each of the three consistency problems, a solution is proposed and combined into a single consistent solution. The consistency of rationales and procedures is ensured by asking only one question at a time and performing a separate allocation and calculation for each question. The problem of maintaining monetary, mass, and energy balances is solved by a generalized allocation correction. The identified problem with consistency of results across model resolution and classification is solved by redefining the point of substitution. It is described what consequences the solutions will have if their results are misused for decision making that will shift demand between products.     

Life Cycle Cost Disclosure, Consumer Behavior, and Business Implications

Comprehensive assessments of final consumption have identified "housing" as a major contributor to total environmental impacts. Within this category, electrical-energy-using products are important. Do consumers opt for more energy-efficient household appliances if they are provided with life cycle cost (LCC)—that is, the sum of purchase price and operating cost estimated over the life span of the appliance? And what consequences does LCC disclosure have for business? Physical energy figures shown on appliance labels may be cognitively demanding for consumers, whereas monetary information promises to simplify the decision problem. Despite the rising interest in monetary cost disclosure, its effectiveness relative to physical cost disclosure has not been rigorously evaluated. This research approached the question of effectiveness with an online field experiment for washing machines. Customers of a commercially operating online shop were randomly assigned to two groups. The control group was provided with regular product price information; the treatment group received additional LCC information. A total of 2,065 clicks were recorded and analyzed with multiple regression that controlled for several product characteristics. The evidence suggests that LCC disclosure decreases the mean specific energy use of chosen washing machines by 0.8% ( p < 0.01) and their mean specific water use by 0.7% ( p < 0.05). As to business implications, LCC disclosure had no effect on the indicator of retail volume, which makes it unattractive for retailers to provide LCC on their own initiative.     

Beta edge strands in protein structure prediction and aggregation

It is well established that recognition between exposed edges of beta-sheets is an important mode of protein-protein interaction and can have pathological consequences; for instance, it has been linked to the aggregation of proteins into a fibrillar structure, which is associated with a number of predominantly neurodegenerative disorders. A number of protective mechanisms have evolved in the edge strands of beta-sheets, preventing the aggregation and insolubility of most natural beta-sheet proteins. Such mechanisms are unfavorable in the interior of a beta-sheet. The problem of distinguishing edge strands from central strands based on sequence information alone is important in predicting residues and mutations likely to be involved in aggregation, and is also a first step in predicting folding topology. Here we report support vector machine (SVM) and decision tree methods developed to classify edge strands from central strands in a representative set of protein domains. Interestingly, rules generated by the decision tree method are in close agreement with our knowledge of protein structure and are potentially useful in a number of different biological applications. When trained on strands from proteins of known structure, using structure-based (Dictionary of Secondary Structure in Proteins) strand assignments, both methods achieved mean cross-validated, prediction accuracies of approximately 78%. These accuracies were reduced when strand assignments from secondary structure prediction were used. Further investigation of this effect revealed that it could be explained by a significant reduction in the accuracy of standard secondary structure prediction methods for edge strands, in comparison with central strands.     

On harvesting a structured ungulate population

Variation in demographic rates within a spatially structured population could have important consequences for management decisions, harvesting strategies and offtake rates. Although there is a growing body of evidence suggesting that demographic rates vary within populations over a range of spatial scales, there has been little research investigating the consequences of this variation for population management. In this paper, data on the dynamics of two female red deer sub-populations on Rum are analysed, and evidence is presented for differences between the fecundity and mortality rates of the two sub-populations. A simple harvesting model is developed to represent the dynamics of the two sub-populations, including density-independent migration between sub-populations and spatially correlated environmental variability. The highest monetary yield in the model is obtained by harvesting the more resilient sub-population at a higher rate. Surprisingly the losses involved in harvesting both sub-populations at the same rate are insignificant. However, if migration were density-dependent, the size of one sub-population would be more relevant to harvesting policy for the other sub-population. The results of this empirical study are compared to theoretical work on spatially structured populations; it is shown that when a species has complex age- and sex-structured population dynamics, previous theoretical results may not hold.     

The amplification of environmental noise in population models: causes and consequences

Environmental variability is a ubiquitous feature of every organism's habitat. However, the interaction between density dependence and those density-independent factors that are manifested as environmental noise is poorly understood. We are interested in the conditions under which noise interacts with the density dependence to cause amplification of that noise when filtered by the system. For a broad family of structured population models, we show that amplification occurs near the threshold from stable to unstable dynamics by deriving an analytic formula for the amplification under weak noise. We confirm that the effect of noise is to sustain oscillations that would otherwise decay, and we show that it is the amplitude and not the phase that is affected. This is a feature noted in several recent studies. We study this phenomenon in detail for the lurchin and LPA models of population dynamics. We find that the degree of amplification is sensitive to both the noise input and life-history stage through which it acts, that the results hold for surprisingly high levels of noise, and that stochastic chaos (as measured by local Lyapunov exponents) is a concomitant feature of amplification. Further, it is shown that the temporal autocorrelation, or "color," of the noise has a major impact on the system response. We discuss the conditions under which color increases population variance and hence the risk of extinction, and we show that periodicity is sharpened when the color of the noise and dynamics coincide. Otherwise, there is interference, which shows how difficult it is in practice to separate the effects of nonlinearity and noise in short time series. The sensitivity of the population dynamics to noise when close to a bifurcation has wide-ranging consequences for the evolution and ecology of population dynamics.     

On the decomposition of a dynamical system into non-interacting subsystems

It is shown that, under rather general conditions, it is possible to formally decompose the dynamics of ann-dimensional dynamical system into a number of non-interacting subsystems. It is shown that these decompositions are in general not simply related to the kinds of observational procedures in terms of which the original state variables of the system are defined. Some consequences of this construction for reductionism in biology are discussed.     

Wiener analysis of nonlinear systems using Poisson-Charlier crosscorrelation

Nonlinear systems with event-sequence input, such as are often encountered in neurophysiology, may be experimentally tested with all possible input sequences by stimulation with a Poisson process eventsequence. A complete predictive model of the system's response may be constructed from this data with the Wiener expansion based on the Poisson-Charlier polynomials. Here it is shown how this formulation leads to an efficient method for the evaluation of unknown systems by crosscorrelation, generalizing previous methods. The basic statistical properties of the procedure are demonstrated and the length of experiment required for accurate estimation of the model is computed. The procedure is translated into digital algorithms and the analogous procedures for white noise analysis are presented.     

Decision Analysis Utilizing Data from Multiple Life-Cycle Impact Assessment Methods Part I: A Theoretical Basis

Numerous methodologies for the life-cycle impact assessment (LCIA) step of life-cycle assessment (LCA) are currently in popular use. These methods, which are based on a single method or level of analysis, are limited to the environmental fates, impact categories, damage functions, and stressors included in the method or model. Because of this, it has been suggested within the LCA community that LCIA data from multiple methods and/or levels of analysis, that is, end-point and midpoint indicators, be used in LCA-based decision analysis to facilitate better or, at least more informed, decision making. In this (two-part) series of articles, we develop and present a series of LCA-based decision analysis models, based on multiattribute value theory (MAVT), which utilize data from multiple LCIA methods and/or levels of analysis. The key to accomplishing this is the recognition of what LCIA damage indicators represent with respect to decision analysis, namely, decision attributes and, in most cases, proxy attributes. The use of proxy attributes in a decision model, however, poses certain challenges, such as the assessment of decision-maker preferences for actual consequences that are only known imprecisely because of inherent limits of both LCA and scientific knowledge. In this article (part I), we provide a brief overview of MAVT and examine some of the decision-theoretic issues and implications of current LCIA methods. We illustrate the application of MAVT to develop a decision model utilizing damage indicators from a single LCIA methodology; and, we identify the decision-theoretic issues that arise when attempting to combine LCIA indicators from multiple methods and/or levels of analysis in a single decision model. Finally, we introduce the use in our methodology of constructed attributes to combine related end-point damage indicators into single decision attributes and the concept and evaluation of proxy attributes.     

Noise in attractor networks in the brain produced by graded firing rate representations

Representations in the cortex are often distributed with graded firing rates in the neuronal populations. The firing rate probability distribution of each neuron to a set of stimuli is often exponential or gamma. In processes in the brain, such as decision-making, that are influenced by the noise produced by the close to random spike timings of each neuron for a given mean rate, the noise with this graded type of representation may be larger than with the binary firing rate distribution that is usually investigated. In integrate-and-fire simulations of an attractor decision-making network, we show that the noise is indeed greater for a given sparseness of the representation for graded, exponential, than for binary firing rate distributions. The greater noise was measured by faster escaping times from the spontaneous firing rate state when the decision cues are applied, and this corresponds to faster decision or reaction times. The greater noise was also evident as less stability of the spontaneous firing state before the decision cues are applied. The implication is that spiking-related noise will continue to be a factor that influences processes such as decision-making, signal detection, short-term memory, and memory recall even with the quite large networks found in the cerebral cortex. In these networks there are several thousand recurrent collateral synapses onto each neuron. The greater noise with graded firing rate distributions has the advantage that it can increase the speed of operation of cortical circuitry.     

Bayesian estimation of fold-changes in the analysis of gene expression: the PFOLD algorithm.

A general and detailed noise model for the DNA microarray measurement of gene expression is presented and used to derive a Bayesian estimation scheme for expression ratios, implemented in a program called PFOLD, which provides not only an estimate of the fold-change in gene expression, but also confidence limits for the change and a P-value quantifying the significance of the change. Although the focus is on oligonucleotide microarray technologies, the scheme can also be applied to cDNA based technologies if parameters for the noise model are provided. The model unifies estimation for all signals in that it provides a seamless transition from very low to very high signal-to-noise ratios, an essential feature for current microarray technologies for which the median signal-to-noise ratios are always moderate. The dual use, as decision statistics in a two-dimensional space, of the P-value and the fold-change is shown to be effective in the ubiquitous problem of detecting changing genes against a background of unchanging genes, leading to markedly higher sensitivities, at equal selectivity, than detection and selection based on the fold-change alone, a current practice until now.     

Management procedures in a fishery based on highly variable stocks and with conflicting objectives: experiences in the South African pelagic fishery

The pelagic fishery in South Africa targets mainly anchovy, Engraulis capensis, and sardine, Sardinops sagax, both of which have varied substantially in abundance during the history of the fishery. Since 1988, there has been progress in this fishery towards the use of management procedures as the basis for determination of management regulations, where a management procedure is defined as a set of rules, derived by simulation and normally implemented for three to five years, specifying how the regulatory mechanism is set, the data collected for this purpose and how these data are to be analysed and used. Advantages of management procedures include formal consideration of uncertainty, the ability to choose decision rules based on their predicted medium-term consequences and a saving in workload compared with annual assessments.This paper discusses the lessons learned in application of management procedures and their precursors in this fishery. The high variability in abundance of the two stocks, the trend in their relative abundance, the substantial uncertainties in information, strong pressure to meet socio-economic goals and the conflicting objectives which arose between the directed anchovy and directed sardine fishery are identified as major problems in implementation of procedures and management of the resources. However, the use of management procedures is considered to have led to greatly improved communication with the industry and to substantial input by them into the management process. The procedures and the simulations upon which they were based also enabled consideration of the major sources of uncertainty in understanding of the resource dynamics and facilitated the development of procedures that were robust to them.It is argued that biological uncertainty greatly exacerbated the problems in application of the procedures but probably cannot be markedly reduced in the near future. Management procedures must be robust to likely variability and uncertainty. Of equal importance are identification and selection of achievable objectives, and allocation to the political decision makers and not to the scientists, of responsibility for determining acceptable trade-offs between conservation and socio-economic goals. Other issues, including the importance of long-term rights and allowance for flexibility in fishing practice, are also highlighted     

Prediction of gastric ulcers based on the change in electrical resistance of acupuncture points using fuzzy logic decision-making

Many theories of reflexology use ancient concepts which do not coincide with the modern medical terminology of anatomy, physiology and biophysics. This substantially reduces the trust of physicians in reflexology methods. During this research, several mathematical models for the interaction of the internal and biological active points of meridian structures have been proposed. The analysis of these models allows the specification of a list of gastric diseases for which reflex diagnostics and reflex therapy methods are most effective and also allows increasing the effectiveness of these procedures. It is shown that good results for the prediction and early diagnosis of diseases from the reaction energy of biologically active points (acupuncture points) are obtained using fuzzy logic decision making.     

Role of correlated noise in textural features extraction

Predictive models of tumor response based on heterogeneity metrics in medical images, such as textural features, are highly suggestive. However, the demonstrated sensitivity of these features to noise does affect the model being developed. An in-depth analysis of the noise influence on the extraction of texture features was performed based on the assumption that an improvement in information quality can also enhance the predictive model. A heuristic approach was used that recognizes from the beginning that the noise has its own texture and it was analysed how it affects the quantitative signal data. A simple procedure to obtain noise image estimation is shown; one which makes it possible to extract the noise-texture features at each observation. The distance measured between the textural features in signal and estimated noise images allows us to determine the features affected in each observation by the noise and, for example, to exclude some of them from the model. A demonstration was carried out using synthetic images applying realistic noise models found in medical images. Drawn conclusions were applied to a public cohort of clinical images obtained using FDG-PET to show how the predictive model could be improved. A gain in the area under the receiver operating characteristic curve between 10 and 20% when noise texture information is used was shown. An improvement between 20 and 30% can be appreciated in the estimated model quality.     

Evaluating options in LCA: The emergence of conflicting paradigms for impact assessment and evaluation

LCA aims to help direct decisions in an environmentally sustainable direction. It indicates the environmental effects of choices and evaluates these against this background. Approaches to evaluation in LCA differ substantially, related to the way of modelling environmental effects and to the way these effects are combined into an overall judgement on alternative options. Several approaches are now operational, which are linked to different paradigms in decision making. It is shown that the choice of paradigm is quite decisive on the outcome of the analysis. Also within similar paradigms, different methods now operational may lead to different outcomes. These latter differences may be alleviated more easily than those related to paradigmatic choices, as they are partly a matter of refinement, and they partly result from legitimate differences in subjective priorities. The more basic paradigmatic differences can hardly be bridged. The practical relevancy of the subject is proven by applying different operational methods to one case, showing widely differing outcomes. The paradigm behind evaluating environmental effects is either values based, directly or through policy decisions, or economics based, as individual preferences measured in the monetary terms of willingness-to-pay. Accordingly, the different methods are “policy-oriented” or “monetary”. It may be doubted if the differences between these can be overcome in standardisation.     

Detection Theory Applied to the Absolute Sensitivity of Sensory Systems

Mainly the skin senses touch and warmth have been investigated. It is shown that the decision model describes the experimental data better than the threshold model. The experiments lead to the assumption that an internal noise exists, which is a neural activity being undistinguishable from the neural activity caused by small stimuli and which adds to the neural activity caused by the stimulus. The probability distribution of this internal noise can be considered to be gaussian. The relation between stimulus and neural activity is alinear for the touch sense. The question of whether noise of a multiplicative nature must be assumed is discussed.     

Human Decision Making Based on Variations in Internal Noise: An EEG Study

Perceptual decision making is prone to errors, especially near threshold. Physiological, behavioural and modeling studies suggest this is due to the intrinsic or ‘internal’ noise in neural systems, which derives from a mixture of bottom-up and top-down sources. We show here that internal noise can form the basis of perceptual decision making when the external signal lacks the required information for the decision. We recorded electroencephalographic (EEG) activity in listeners attempting to discriminate between identical tones. Since the acoustic signal was constant, bottom-up and top-down influences were under experimental control. We found that early cortical responses to the identical stimuli varied in global field power and topography according to the perceptual decision made, and activity preceding stimulus presentation could predict both later activity and behavioural decision. Our results suggest that activity variations induced by internal noise of both sensory and cognitive origin are sufficient to drive discrimination judgments.     

Effects of restraint stress in gestation: implications for rodent developmental toxicology studies

Restraint has been used as a procedure to study the effects of stress on gestation outcome in rodents. The effects of restraint could potentially be used as a model for the impact of general stress produced by high doses of toxicants and other interventions. In mice, restraint in the peri-implantation period leads to implantation failure, and restraint at appropriate times in organogenesis produces cleft palate, supernumerary ribs, and resorption. In rats, there is some evidence for an association with restraint for implantation failure, but not for the morphological anomalies. Restraint in late gestation alters adult sexual behavior of male rat offspring, but consequences for their fertility are not known. Intrauterine growth retardation is not commonly associated with gestational restraint. In the few studies where they have been directly compared, different restraint procedures produced graded, qualitatively different, or no effects. Adrenocortical hormones have been implicated as mediating the effect of restraint on cleft palate, but not on supernumerary ribs, implantation failure, or sexual differentiation. Given the variety of restraint procedures and the varying species-dependent consequences, it is not possible to infer a generalizable pattern of developmental effects due to gestational stress from the restraint literature. As an alternative approach, contemporary methods in gene expression and developmental biology could profitably be applied to understanding different patterns of stress-mediated effects of toxicant exposures on intrauterine development.