Assessment of fitness for surgical procedures and the variability of anaesthetists' judgments.

Ten anaesthetists were asked to make judgments on fitness for elective operation on data derived from 200 patients. The extent of their agreement was measured using a kappa statistic, and clusters of anaesthetists who agreed well with each other were identified. Using an alternative technique, the "true" fitness category of each patient was estimated using a maximum likelihood method which estimated the error involved in making judgments on limited amounts of information. It was possible to compare the performance of each anaesthetist against the consensus and to measure deviation on an "optimism--pessimism" continuum. A simple questionnaire predicted fitness for operation by all 10 anaesthetists in 96% of cases.     

Estimating effective population size from samples of sequences: a bootstrap Monte Carlo integration method.

We would like to use maximum likelihood to estimate parameters such as the effective population size N(e) or, if we do not know mutation rates, the product 4N(e) mu of mutation rate per site and effective population size. To compute the likelihood for a sample of unrecombined nucleotide sequences taken from a random-mating population it is necessary to sum over all genealogies that could have led to the sequences, computing for each one the probability that it would have yielded the sequences, and weighting each one by its prior probability. The genealogies vary in tree topology and in branch lengths. Although the likelihood and the prior are straightforward to compute, the summation over all genealogies seems at first sight hopelessly difficult. This paper reports that it is possible to carry out a Monte Carlo integration to evaluate the likelihoods approximately. The method uses bootstrap sampling of sites to create data sets for each of which a maximum likelihood tree is estimated. The resulting trees are assumed to be sampled from a distribution whose height is proportional to the likelihood surface for the full data. That it will be so is dependent on a theorem which is not proven, but seems likely to be true if the sequences are not short. One can use the resulting estimated likelihood curve to make a maximum likelihood estimate of the parameter of interest, N(e) or of 4N(e) mu. The method requires at least 100 times the computational effort required for estimation of a phylogeny by maximum likelihood, but is practical on today's work stations. The method does not at present have any way of dealing with recombination.     

Dynamics of betting behavior under flat reward condition

One of the missions of the cognitive process of animals, including humans, is to make reasonable judgments and decisions in the presence of uncertainty. The balance between exploration and exploitation investigated in the reinforcement-learning paradigm is one of the key factors in this process. Recently, following the pioneering work in behavioral economics, growing attention has been directed to human behaviors exhibiting deviations from the simple maximization of external reward. Here we study the dynamics of betting behavior in a simple game, where the probability of reward and the magnitude of reward are designed to give a "zero" expected net reward ("flat reward condition"). No matter how the subject behaves, there is on average no change in one's resources, and therefore every possible sequence of action has the same value. Even in such a situation, the subjects are found to behave not in a random manner, but in ways showing characteristic tendencies, reflecting the dynamics of brain's reward system. Our results suggest that brain's reward system is characterized by a rich and complex dynamics only loosely coupled with external reward structure.     

A flashing line can warp your mind

Keeping pace with a constantly changing world requires the ability to make predictions about the future on a variety of timescales. A very basic example of this is the ability to predict the future location of a moving object in the brief time that it takes to perceive and respond to that object. In this issue of Neuron, experiments by Sundberg, Fallah, and Reynolds reveal a potential neural substrate for making short-range predictions about motion in visual area V4.     

An unexpected sequence of events: mismatch detection in the human hippocampus

The ability to identify and react to novelty within the environment is fundamental to survival. Computational models emphasize the potential role of the hippocampus in novelty detection, its unique anatomical circuitry making it ideally suited to act as a comparator between past and present experience. The hippocampus, therefore, is viewed to detect associative mismatches between what is expected based on retrieval of past experience and current sensory input. However, direct evidence that the human hippocampus performs such operations is lacking. We explored brain responses to novel sequences of objects using functional magnetic resonance imaging (fMRI), while subjects performed an incidental target detection task. Our results demonstrate that hippocampal activation was maximal when prior predictions concerning which object would appear next in a sequence were violated by sensory reality. In so doing, we establish the biological reality of associative match-mismatch computations within the human hippocampus, a process widely held to play a cardinal role in novelty detection. Our results also suggest that the hippocampus may generate predictions about how future events will unfold, and critically detect when these expectancies are violated, even when task demands do not require it. The present study also offers broader insights into the nature of essential computations carried out by the hippocampus, which may also underpin its unique contribution to episodic memory.     

Fast,easy measurements for assessing vital signs of tall grassland

We present a small set of measurements for monitoring the recovery of tallgrass ecosystems. The measures incorporate indices of water retention, nutrient cycling, primary production, and the condition of the plant community. Careful novices can make the measurements in a few minutes per sample with simple tools. Our measurements are intended for tallgrass restorations on degraded pastures or former croplands in situations where budgets are tight and neither experienced botanists nor skilled specialists are available for data collection (e.g. restorations that rely on volunteers for data collection, grazing lands whose managers seek improved ecological condition, or sites monitored by novice students). We searched the literature for grassland condition measures that did not require substantial time per measurement, specialized equipment or expert judgments, field tested candidate measurements at six sites that spanned an extreme range of ecological condition, and eliminated those that did not correspond to expert assessments of site condition, that suffered from technical problems, or that depended on recent weather or subtle judgments. We then tested whether different workers could confidently apply the remaining measurements, and used them to assess the condition of 11 fields involved in a prairie restoration experiment. The recommended measurements are presence of bare ground, abundance of five important native perennial grass species, and abundance of two invasive species. These measurements are analogous to vital signs. They provide basic information on the condition of a site rapidly and inexpensively, and can alert analysts to situations that warrant more detailed evaluation.     

A Simple Numerical Procedure for Estimating the Prior Probability in the Biomathematical Proof of Paternity

This note gives a simple procedure for finding the maximum likelihood estimate of the prior probabilities in paternity cases. The procedure is based on a fixed point principle.     

TASTE DISCRIMINATION BY THE 3-AFC METHOD: TESTING SENSITIVITY PREDICTIONS REGARDING PARTICULAR TASTING SEQUENCES BASED ON THE SEQUENTIAL SENSITIVITY ANALYSIS MODEL

3-AFC discrimination tests between'threshold'concentration NaCl solutions and purified water stimuli were performed using a variety of interstimulus rinsing regimes to test predictions of test sensitivity based on the Sequential Sensitivity Analysis model. Superior performance on triads with NaCl as the'odd'stimulus, over triads with water as the'odd'stimulus, confirmed earlier research. It was possible, using SSA predictions, to find the right combination of rinses, to arrange for either set of triads to elicit strongly superior performance from judges. This manipulation was predicted by SSA but not by an unequal variance Thurstonian model. Failure of some SSA predictions highlighted the notion of stimulus enhancement by adaptation, leading to a modification of the model. Such manipulation of interstimulus rinses could form the basis for increasing or decreasing test sensitivity.     

Do Young Children Understand Relative Value Comparisons?

Many forms of judgments, such as those used in economic games or measures of social comparison, require understanding relative value, as well as the more complex ability to make comparisons between relative values. To examine whether young children can accurately compare relative values, we presented children 4 to 7 years with simple judgments of relative value in two scenarios. Children then were asked to compare the relative values in the two scenarios. Results show that even the youngest children downgraded evaluations of a reward when another has a larger amount, indicating the ability to make relative value judgments. When asked to compare relative values however, only the oldest children were able to make these comparisons consistently. We then extended this analysis to economic game performance. Specifically, previous results using economic games suggest that younger children are more generous than older ones. We replicate this result, and then show that a simple change in procedure, based on the initial study, is sufficient to change young children’s choices. Our results strongly suggest that conclusions regarding young children’s pro-social motives based on relative value comparisons should be viewed cautiously.     

Estimating Effective Population Size and Mutation Rate from Sequence Data Using Metropolis-Hastings Sampling

We present a new way to make a maximum likelihood estimate of the parameter 4N(e)μ (effective population size times mutation rate per site, or θ) based on a population sample of molecular sequences. We use a Metropolis-Hastings Markov chain Monte Carlo method to sample genealogies in proportion to the product of their likelihood with respect to the data and their prior probability with respect to a coalescent distribution. A specific value of θ must be chosen to generate the coalescent distribution, but the resulting trees can be used to evaluate the likelihood at other values of θ, generating a likelihood curve. This procedure concentrates sampling on those genealogies that contribute most of the likelihood, allowing estimation of meaningful likelihood curves based on relatively small samples. The method can potentially be extended to cases involving varying population size, recombination, and migration.     

The Presence of a Therapy Dog Results in Improved Object Recognition Performance in Preschool Children

ABSTRACT

The purpose of this study was to determine whether the presence of a dog would have an impact on object recognition memory performance of preschool children. This work represents an extension of previous research which found that preschoolers require fewer instructional prompts to complete this type of memory task when in the presence of a dog. If children require fewer instructional prompts it is possible that they are better able to focus on the task itself and as a result, improved memory performance is likely. Because the earlier experiment utilized a very simple version of the task that was readily completed by the preschool children, the overall performance data were at ceiling. The current study, involving 20 preschool children, included a manipulation of task difficulty through varying the number of distracters (one versus four) present at test. Increasing the number of distractors in a simple recognition task is known to make that task more challenging, and thus performance was expected to be slower and less accurate in the four distracter conditions relative to the one-distracter conditions. The collaborators in the study were either a therapy dog or a human. A two-way repeated measures design was used such that each child served as his/her own control and was tested in each of four separate conditions: dog present (one and four distracters) and human present (one and four distracters). The results showed that the preschool children performed the object recognition task faster and more accurately in the presence of the therapy dog relative to a human and also in the one-distracter versus four-distracter condition. The authors conclude that these effects result from increased focus and/or motivation resulting from the presence of the dog.     

Identifying protein-protein interfacial residues in heterocomplexes using residue conservation scores

Identifying protein–protein interfaces is crucial for structural biology. Because of the constraints in wet experiments, many computational methods have been proposed. Without knowing any information about the partner chains, a new method of predicting protein–protein interaction interface residues purely based on evolutionary information in heterocomplexes is proposed here. Unlike traditional approaches using multiple sequence alignment profiles to represent the conservation level for each residue, we make predictions based on the concept of residue conservation scores so that the dimension of the feature vector for each residue can be drastically reduced, at least 20 times less than conventional methods. Based on the representation approach, a simple linear discriminant function is used to make predictions, so the computational complexity of the whole prediction procedure can also be greatly decreased. By testing our approach on 69 heterocomplex chains, experimental results demonstrate the performance of our approach is indeed superior to current existing methods.     

Nesting habitat preference of the African White-backed Vulture Gyps africanus and the effects of anthropogenic disturbance

The African White-backed Vulture Gyps africanus is widely distributed across sub-Saharan Africa but populations are in decline. Loss of suitable habitat for foraging and breeding are among the most important causes, and future conservation will require identification of suitable remaining habitat and the threats to it and to the vultures in it. Like many large raptors, African White-backed Vultures have a long breeding cycle and thus spend much of each year near their nest site, but ecological correlates of nest sites have not been quantified for any African vulture species. We use nest-site data for African White-backed Vultures collected during aerial and ground surveys and habitat data derived from a GIS to develop statistical models that estimate the probability of nest presence in relation to habitat characteristics, and test these models against an independent dataset. The models predicted that both direct and indirect disturbance by humans limit the potential distribution. Suitable habitat needs to be identified and receive adequate protection from poaching. Poaching of vultures is thought to be mainly for use in traditional medicine and does not target any particular species, so all vulture species can be considered equally at risk. We predict the likelihood of individuals nesting in currently unprotected areas should they become protected. These predictions show that readily available GIS data combined with relatively simple statistical modelling can provide meaningful large-scale predictions of habitat availability.     

MEASUREMENT OF PHOTOGRAPHIC QUALITY AND INDIVIDUAL DISTINCTIVENESS FOR THE PHOTOGRAPHIC IDENTIFICATION OF HUMPBACK WHALES, MEGAPTERA NOVAEANGLIAE

Accurate identification of humpback whales from photographic identification data depends on the quality of the photographs and the distinctiveness of the flukes. Criteria for evaluating photographic quality and individual distinctiveness were developed involving judgments about overall quality or distinctiveness and about specific aspects of each. These criteria were tested for the level of agreement among judges. The distinctiveness scheme was tested for the independence of distinctiveness judgments and photographic quality. Our results show that judges could agree when evaluating specific and overall aspects of photographic quality and individual distinctiveness. The level of agreement varied for different pairs of judges, and less adept judges were identified. Ability to agree on evaluations of photographic quality was independent of the experience of the judges. Overall photographic quality and overall distinctiveness were successfully predicted from more specific variables, but the agreement between judges for these was not significantly greater than the agreement for the overall measures judged directly. There was no correlation between individual distinctiveness and photographic quality for four of the five judges, but the power of this rest may be low. Analyses of photographic identification data frequently require evaluations of photographic quality and individual distinctiveness. To obtain reliable results from such analyses, evaluation schemes and judges should be tested to ensure reliable and consistent evaluations.     

A Simple Method for Estimating Informative Node Age Priors for the Fossil Calibration of Molecular Divergence Time Analyses

Molecular divergence time analyses often rely on the age of fossil lineages to calibrate node age estimates. Most divergence time analyses are now performed in a Bayesian framework, where fossil calibrations are incorporated as parametric prior probabilities on node ages. It is widely accepted that an ideal parameterization of such node age prior probabilities should be based on a comprehensive analysis of the fossil record of the clade of interest, but there is currently no generally applicable approach for calculating such informative priors. We provide here a simple and easily implemented method that employs fossil data to estimate the likely amount of missing history prior to the oldest fossil occurrence of a clade, which can be used to fit an informative parametric prior probability distribution on a node age. Specifically, our method uses the extant diversity and the stratigraphic distribution of fossil lineages confidently assigned to a clade to fit a branching model of lineage diversification. Conditioning this on a simple model of fossil preservation, we estimate the likely amount of missing history prior to the oldest fossil occurrence of a clade. The likelihood surface of missing history can then be translated into a parametric prior probability distribution on the age of the clade of interest. We show that the method performs well with simulated fossil distribution data, but that the likelihood surface of missing history can at times be too complex for the distribution-fitting algorithm employed by our software tool. An empirical example of the application of our method is performed to estimate echinoid node ages. A simulation-based sensitivity analysis using the echinoid data set shows that node age prior distributions estimated under poor preservation rates are significantly less informative than those estimated under high preservation rates.     

Relative Changes from Prior Reward Contingencies Can Constrain Brain Correlates of Outcome Monitoring

It is well-known that the affective value of an environment can be relative to whether it reflects an improvement or a worsening from a previous state. A potential explanation for this phenomenon suggests that relative changes from previous reward contingencies can constrain how brain monitoring systems form predictions about future events. In support of this idea, we found that changes per se relative to previous states of learned reward contingencies modulated the Feedback-Related Negativity (FRN), a human brain potential known to index discrepancies between predictions and affective outcomes. Specifically, we observed that environments with a 50% reward probability yielded different FRN patterns according to whether they reflected an improvement or a worsening from a previous environment. Further, we also found that this pattern of results was driven mainly by variations in the amplitude of ERPs to positive outcomes. Overall, these results suggest that relative changes in reward probability from previous learned environments can constrain how neural systems of outcome monitoring formulate predictions about the likelihood of future rewards and nonrewards.     

On hierarchical Bayes procedures for predicting simple exponential survival

The situation considered is the prediction of a future observation from a simple exponential survival distribution in a hierarchical Bayes context. It is shown that when the hyperparameters need to be estimated from the data, a sample reuse approach is superior to maximum likelihood and method of moments estimation procedures.     

How haptic size sensations improve distance perception

Determining distances to objects is one of the most ubiquitous perceptual tasks in everyday life. Nevertheless, it is challenging because the information from a single image confounds object size and distance. Though our brains frequently judge distances accurately, the underlying computations employed by the brain are not well understood. Our work illuminates these computions by formulating a family of probabilistic models that encompass a variety of distinct hypotheses about distance and size perception. We compare these models' predictions to a set of human distance judgments in an interception experiment and use Bayesian analysis tools to quantitatively select the best hypothesis on the basis of its explanatory power and robustness over experimental data. The central question is: whether, and how, human distance perception incorporates size cues to improve accuracy. Our conclusions are: 1) humans incorporate haptic object size sensations for distance perception, 2) the incorporation of haptic sensations is suboptimal given their reliability, 3) humans use environmentally accurate size and distance priors, 4) distance judgments are produced by perceptual "posterior sampling". In addition, we compared our model's estimated sensory and motor noise parameters with previously reported measurements in the perceptual literature and found good correspondence between them. Taken together, these results represent a major step forward in establishing the computational underpinnings of human distance perception and the role of size information.     

A Bayesian perspective on a non-parsimonious parsimony model

Several stochastic models of character change, when implemented in a maximum likelihood framework, are known to give a correspondence between the maximum parsimony method and the method of maximum likelihood. One such model has an independently estimated branch-length parameter for each site and each branch of the phylogenetic tree. This model--the no-common-mechanism model--has many parameters, and, in fact, the number of parameters increases as fast as the alignment is extended. We take a Bayesian approach to the no-common-mechanism model and place independent gamma prior probability distributions on the branch-length parameters. We are able to analytically integrate over the branch lengths, and this allowed us to implement an efficient Markov chain Monte Carlo method for exploring the space of phylogenetic trees. We were able to reliably estimate the posterior probabilities of clades for phylogenetic trees of up to 500 sequences. However, the Bayesian approach to the problem, at least as implemented here with an independent prior on the length of each branch, does not tame the behavior of the branch-length parameters. The integrated likelihood appears to be a simple rescaling of the parsimony score for a tree, and the marginal posterior probability distribution of the length of a branch is dependent upon how the maximum parsimony method reconstructs the characters at the interior nodes of the tree. The method we describe, however, is of potential importance in the analysis of morphological character data and also for improving the behavior of Markov chain Monte Carlo methods implemented for models in which sites share a common branch-length parameter.