Monkeys and humans share a common computation for face/voice integration

Speech production involves the movement of the mouth and other regions of the face resulting in visual motion cues. These visual cues enhance intelligibility and detection of auditory speech. As such, face-to-face speech is fundamentally a multisensory phenomenon. If speech is fundamentally multisensory, it should be reflected in the evolution of vocal communication: similar behavioral effects should be observed in other primates. Old World monkeys share with humans vocal production biomechanics and communicate face-to-face with vocalizations. It is unknown, however, if they, too, combine faces and voices to enhance their perception of vocalizations. We show that they do: monkeys combine faces and voices in noisy environments to enhance their detection of vocalizations. Their behavior parallels that of humans performing an identical task. We explored what common computational mechanism(s) could explain the pattern of results we observed across species. Standard explanations or models such as the principle of inverse effectiveness and a "race" model failed to account for their behavior patterns. Conversely, a "superposition model", positing the linear summation of activity patterns in response to visual and auditory components of vocalizations, served as a straightforward but powerful explanatory mechanism for the observed behaviors in both species. As such, it represents a putative homologous mechanism for integrating faces and voices across primates.     

Analysis of physiological signals for recognition of boredom,pain, and surprise emotions

Background

The aim of the study was to examine the differences of boredom, pain, and surprise. In addition to that, it was conducted to propose approaches for emotion recognition based on physiological signals.

Methods

Three emotions, boredom, pain, and surprise, are induced through the presentation of emotional stimuli and electrocardiography (ECG), electrodermal activity (EDA), skin temperature (SKT), and photoplethysmography (PPG) as physiological signals are measured to collect a dataset from 217 participants when experiencing the emotions. Twenty-seven physiological features are extracted from the signals to classify the three emotions. The discriminant function analysis (DFA) as a statistical method, and five machine learning algorithms (linear discriminant analysis (LDA), classification and regression trees (CART), self-organizing map (SOM), Naïve Bayes algorithm, and support vector machine (SVM)) are used for classifying the emotions.

Results

The result shows that the difference of physiological responses among emotions is significant in heart rate (HR), skin conductance level (SCL), skin conductance response (SCR), mean skin temperature (meanSKT), blood volume pulse (BVP), and pulse transit time (PTT), and the highest recognition accuracy of 84.7 % is obtained by using DFA.

Conclusions

This study demonstrates the differences of boredom, pain, and surprise and the best emotion recognizer for the classification of the three emotions by using physiological signals.     

Cross-sectional growth standards for captive baboons: II. Organ weight by body weight

We present the first cross-sectional organ weight by body weight reference standards for captive baboons (Papio hamadryas). Organ weight data were obtained from necropsy reports for 634 healthy, pedigreed, captive female and male baboons. From summary statistics we calculated and fit cross-sectional sex-specific percentile curves for: adrenals, brain, eyes, heart, kidneys, liver plus gall bladder, lungs, pancreas, pituitary gland, spleen, and thyroid gland in three kilogram body weight intervals and cross-sectional summary statistics by sex for each organ in one kilogram body weight intervals.     

Cross-sectional growth standards for captive baboons: I. Organ weight by chronological age

We present the first cross-sectional organ weight reference standards for captive baboons (Papio hamadryas). Organ weight data were obtained from necropsy reports for 634 healthy, pedigreed, captive female and male baboons. From summary statistics we calculated and fit cross-sectional, sex-specific percentile curves for: adrenals, brain, eyes, heart, kidneys, liver plus gall bladder, lungs, pancreas, pituitary gland, spleen, and thyroid gland in two year age class intervals and summary statistics by sex for each organ in one year age classes.     

Mechanical computation in neurons

Growth cones are the main motile structures located at the tip of neurites and are composed of a lamellipodium from which thin filopodia emerge. In this article, we analyzed the kinetics and dynamics of growth cones with the aim to understand two major issues: first, the strategy used by filopodia and lamellipodia during their exploration and navigation; second, what kind of mechanical problems neurons need to solve during their operation. In the developing nervous system and in the adult brain, neurons constantly need to solve mechanical problems. Growth cones must decide how to explore the environment and in which direction to grow; they also need to establish the appropriate contacts, to avoid obstacles and to determine how much force to exert. Here, we show that in sparse cultures, filopodia grow and retract following statistical patterns, nearly optimal for an efficient exploration of the environment. In a dense culture, filopodia exploration is still present although significantly reduced. Analysis on 1271, 6432, and 185 pairs of filopodia of DRG, PC12 and Hippocampal neurons respectively showed that the correlation coefficient |ρ| of the growth of more than 50% of filopodia pairs was >0.15. From a computational point of view, filopodia and lamellipodia motion can be described by a random process in which errors are corrected by efficient feedback loops. This article argues that neurons not only process sensory signals, but also solve mechanical problems throughout their entire lifespan, from the early stages of embryogenesis to adulthood. © 2009 Wiley Periodicals, Inc. Develop Neurobiol, 2009     

Spike-timing-based computation in sound localization

Spike timing is precise in the auditory system and it has been argued that it conveys information about auditory stimuli, in particular about the location of a sound source. However, beyond simple time differences, the way in which neurons might extract this information is unclear and the potential computational advantages are unknown. The computational difficulty of this task for an animal is to locate the source of an unexpected sound from two monaural signals that are highly dependent on the unknown source signal. In neuron models consisting of spectro-temporal filtering and spiking nonlinearity, we found that the binaural structure induced by spatialized sounds is mapped to synchrony patterns that depend on source location rather than on source signal. Location-specific synchrony patterns would then result in the activation of location-specific assemblies of postsynaptic neurons. We designed a spiking neuron model which exploited this principle to locate a variety of sound sources in a virtual acoustic environment using measured human head-related transfer functions. The model was able to accurately estimate the location of previously unknown sounds in both azimuth and elevation (including front/back discrimination) in a known acoustic environment. We found that multiple representations of different acoustic environments could coexist as sets of overlapping neural assemblies which could be associated with spatial locations by Hebbian learning. The model demonstrates the computational relevance of relative spike timing to extract spatial information about sources independently of the source signal.     

Continuous computation in engineered gene circuits

In this paper we consider the problem of representation and measurement in genetic circuits, and investigate how they can affect the reliability of engineered systems. We propose a design scheme, based on the notion of continuous computation, which addresses these issues. We illustrate the methodology by showing how a concept from computer architecture (namely, branch prediction) may be implemented in vivo, using a distributed approach. Simulation results confirm the in-principle feasibility of our method, and offer valuable insights into its future laboratory validation.     

Kinins in humans

The kinin peptide system in humans is complex. Whereas plasma kallikrein generates bradykinin peptides, glandular kallikrein generates kallidin peptides. Moreover, a proportion of kinin peptides is hydroxylated on proline(3) of the bradykinin sequence. We established HPLC-based radioimmunoassays for nonhydroxylated and hydroxylated bradykinin and kallidin peptides and their metabolites in blood and urine. Both nonhydroxylated and hydroxylated bradykinin and kallidin peptides were identified in human blood and urine, although the levels in blood were often below the assay detection limit. Whereas kallidin peptides were more abundant than bradykinin peptides in urine, bradykinin peptides were more abundant in blood. Bradykinin and kallidin peptide levels were higher in venous than arterial blood. Angiotensin-converting enzyme inhibition increased blood levels of bradykinin, but not kallidin, peptides. Reactive hyperemia had no effect on antecubital venous levels of bradykinin or kallidin peptide levels. These studies demonstrate differential regulation of the bradykinin and kallidin peptide systems, and indicate that blood levels of bradykinin peptides are more responsive to angiotensin-converting enzyme inhibition than blood levels of kallidin peptides.     

Pattern computation in neural communication systems

Biological data suggests that activity patterns emerging in small- and large-scale neural systems may play an important role in performing the functions of the neural system, and in particular, neural computations. It is proposed in this paper that neural systems can be understood in terms of pattern computation and abstract communication systems theory. It is shown that analysing high-resolution surface EEG data, it is possible to determine abstract probabilistic rules that describe how emerging activity patterns follow earlier activity patterns. The results indicate the applicability of the proposed approach for understanding the working of complex neural systems.     

Approximate Bayesian computation in population genetics

We propose a new method for approximate Bayesian statistical inference on the basis of summary statistics. The method is suited to complex problems that arise in population genetics, extending ideas developed in this setting by earlier authors. Properties of the posterior distribution of a parameter, such as its mean or density curve, are approximated without explicit likelihood calculations. This is achieved by fitting a local-linear regression of simulated parameter values on simulated summary statistics, and then substituting the observed summary statistics into the regression equation. The method combines many of the advantages of Bayesian statistical inference with the computational efficiency of methods based on summary statistics. A key advantage of the method is that the nuisance parameters are automatically integrated out in the simulation step, so that the large numbers of nuisance parameters that arise in population genetics problems can be handled without difficulty. Simulation results indicate computational and statistical efficiency that compares favorably with those of alternative methods previously proposed in the literature. We also compare the relative efficiency of inferences obtained using methods based on summary statistics with those obtained directly from the data using MCMC.     

Efficient computation in the IM model

In this paper we analyze the isolation-with-migration model in a continuous-time Markov chain framework, and derive analytical expressions for the probability densities of gene tree topologies with an arbitrary number of lineages. We combine these densities with both nucleotide-substitution and infinite sites mutation models and derive probabilities for use in maximum likelihood estimation. We demonstrate how to apply lumpability of continuous-time Markov chains to achieve a significant reduction in the size of the state-space under consideration. We use matrix exponentiation and spectral decomposition to derive explicit expressions for the case of two diploid individuals in two populations, when the data is given as alignment columns. We implement these expressions in order to carry out a maximum likelihood analysis and provide a simulation study to examine the performance of our method in terms of our ability to recover true parameters. Finally, we show how the performance depends on the parameters in the model.     

Coherent information structure in complex computation

We have recently presented a framework for the information dynamics of distributed computation that locally identifies the component operations of information storage, transfer, and modification. We have observed that while these component operations exist to some extent in all types of computation, complex computation is distinguished in having coherent structure in its local information dynamics profiles. In this article, we conjecture that coherent information structure is a defining feature of complex computation, particularly in biological systems or artificially evolved computation that solves human-understandable tasks. We present a methodology for studying coherent information structure, consisting of state-space diagrams of the local information dynamics and a measure of structure in these diagrams. The methodology identifies both clear and "hidden" coherent structure in complex computation, most notably reconciling conflicting interpretations of the complexity of the Elementary Cellular Automata rule 22.     

Estrogen facilitates fear conditioning and increases corticotropin-releasing hormone mRNA expression in the central amygdala in female mice

Estrogens exert important actions on fear and anxiety-like behavior both in humans and non-human animals. Currently, the mechanisms underlying estrogenic modulation of fear are not known. However, evidence suggests that estrogens may exert their influence on fear within the amygdala. The purpose of the present study was to examine effects of estrogen on fear conditioning. Specifically, the present study examined whether long-term estrogen treatment in ovariectomized female mice via Silastic capsule implantation would facilitate both contextual and cued fear conditioning. In a separate set of experiments, we then examined whether estrogen treatment in ovariectomized female mice would modulate corticotropin-releasing hormone (CRH) gene expression within the amygdala. Long-term estrogen treatment facilitated both contextual and cued fear. Ovariectomized mice treated with estrogen froze significantly more to a context as well as to a discrete auditory cue. In addition, estrogen treatment significantly increased CRH mRNA expression within the central nucleus of the amygdala as measured by in situ hybridization and quantitative PCR. These data raise the possibility that estrogens could influence fear responses in females through their actions in the amygdala.     

Mechanography in children: pediatric references in postural control

Objective:To establish pediatric age- and sex-specific references for measuring postural control with a mechanography plate in a single centre, prospective, normative data study.Methods:739 children and adolescents (396 male/343 female) aged 4 to 17 years were studied. Each participant completed the following test sequence three times: Romberg, semi-tandem, tandem, each with eyes open and closed, and a one-leg stand with eyes open, and a single two-legged jump. Normal ranges were determined based on percentile calculations using the LMS method. Results from the two-legged jump were compared to a reference population the single two-legged jump (s2LJ) assessment in 2013.Results:38 different equilibrium parameters calculated were analysed. Of all parameters Path Length, vCoFmean, Equilibrium Score and Sway Angle showed a low variation within the same age group but high dependency on age and were thus chosen for automated balance assessment.Conclusion:Standard values of postural control in healthy children derived from automated balance testing using a mechanography plate were successfully acquired and a subset of parameters for automated balance assessment identified.     

No emotional fever in toads

Four Bufo marinus toads and one Bombina bombina toad were placed individually along a temperature gradient where they could regulate their body temperature through behavioral means. When injected intraperitoneally with killed Pseudomonas aeruginosa bacteria, the toads sought heat and raised their body core temperature. Gentle handling by the experimenter, however, was not followed by heat-seeking behavior and rising core temperature. These findings confirm the existence of behavioral fever, but not emotional fever, in the species studied.