Comparison between Spanish young and elderly people evaluated using Rivermead Behavioural Memory Test

The first objective of this work was to compare scores obtained in the daily memory function between young and elderly people, and to check whether there are differences between the groups for each of the profile scores obtained in the memory test. A second aim of this paper is to study the relationship between everyday memory and age, while controlling for gender and educational level. The total and profile scores obtained in the Rivermead Behavioural Memory Test were compared in a sample of 60 young and 120 elderly people from Valencia (Spain). Results showed significant differences between the two groups: those between 18 and 30 years obtained a higher average than those over 65. Once the group comparison was controlled for gender and educational level, the statistical effect of age group disappeared. The non-significant effect of group can not be explained by the introduction of gender, because both its main effect and the interaction were not statistically significant. However, educational level had a statistically significant effect which may explain the non-significant effect of group in this new analysis. The main conclusion is the need to carefully control for educational level in all studies related with everyday memory and ageing, as the differences found could be due to generational differences more than to biological deterioratio

Rare KK Decays

The rare decays of the $K$ meson have had a long tradition as a laboratory for testing the symmetry properties of the weak interactions, and the manner in which these symmetries are broken by higher order effects. Present--day interest is focussed on decays that are suppressed by $CP$--symmetry or GIM symmetry. Such decays, in the standard theory, are sensitive to effects of the virtual top quark, and could also reveal new interactions transcending the standard model. In addition, the radiative decays of the $K$ meson have become a useful testing--ground for effective Lagrangians describing the low energy interactions of pions, kaons and photons.Comment: Invited Talk at the Third Workshop on High Energy Particle Physics (WHEPP 3) Madras, 1994, LaTex, 14 pages, 3 figures available upon reques

Summary statistics in auditory perception

Sensory signals are transduced at high resolution, but their structure must be stored in a more compact format. Here we provide evidence that the auditory system summarizes the temporal details of sounds using time-averaged statistics. We measured discrimination of 'sound textures' that were characterized by particular statistical properties, as normally result from the superposition of many acoustic features in auditory scenes. When listeners discriminated examples of different textures, performance improved with excerpt duration. In contrast, when listeners discriminated different examples of the same texture, performance declined with duration, a paradoxical result given that the information available for discrimination grows with duration. These results indicate that once these sounds are of moderate length, the brain's representation is limited to time-averaged statistics, which, for different examples of the same texture, converge to the same values with increasing duration. Such statistical representations produce good categorical discrimination, but limit the ability to discern temporal detail.Howard Hughes Medical Institut

Beyond the Libet clock: modality variants for agency measurements

The Sense of Agency (SoA) refers to our capability to control our own actions and influence the world around us. Recent research in HCI has been exploring SoA to provide users an instinctive sense of “I did that” as opposed to “the system did that”. However, current agency measurements are limited. The Intentional Binding (IB) paradigm provides an implicit measure of the SoA. However, it is constrained by requiring high visual attention to a “Libet clock” onscreen. In this paper, we extend the timing stimulus through auditory and tactile cues. Our results demonstrate that audio timing through voice commands and haptic timing through tactile cues on the hand are alternative techniques to measure the SoA using the IB paradigm. They both address limitations of the traditional method (e.g., lack of engagement and visual demand). We discuss how our results can be applied to measure SoA in tasks involving different interactive scenarios common in HCI

Variance in Centrality within Rock Hyrax Social Networks Predicts Adult Longevity

BACKGROUND: In communal mammals the levels of social interaction among group members vary considerably. In recent years, biologists have realized that within-group interactions may affect survival of the group members. Several recent studies have demonstrated that the social integration of adult females is positively associated with infant survival, and female longevity is affected by the strength and stability of the individual social bonds. Our aim was to determine the social factors that influence adult longevity in social mammals. METHODOLOGY/PRINCIPAL FINDINGS: As a model system, we studied the social rock hyrax (Procavia capensis), a plural breeder with low reproductive skew, whose groups are mainly composed of females. We applied network theory using 11 years of behavioral data to quantify the centrality of individuals within groups, and found adult longevity to be inversely correlated to the variance in centrality. In other words, animals in groups with more equal associations lived longer. Individual centrality was not correlated with longevity, implying that social tension may affect all group members and not only the weakest or less connected ones. CONCLUSIONS/SIGNIFICANCE: Our novel findings support previous studies emphasizing the adaptive value of social associations and the consequences of inequality among adults within social groups. However, contrary to previous studies, we suggest that it is not the number or strength of associations that an adult individual has (i.e. centrality) that is important, but the overall configuration of social relationships within the group (i.e. centrality SD) that is a key factor in influencing longevity

Do Fleas Affect Energy Expenditure of Their Free-Living Hosts?

Parasites can cause energetically costly behavioural and immunological responses which potentially can reduce host fitness. However, although most laboratory studies indicate that the metabolic rate of the host increases with parasite infestation, this has never been shown in free-living host populations. In fact, studies thus far have shown no effect of parasitism on field metabolic rate (FMR).We tested the effect of parasites on the energy expenditure of a host by measuring FMR using doubly-labelled water in free-living Baluchistan gerbils (Gerbillus nanus) infested by naturally occurring fleas during winter, spring and summer. We showed for the first time that FMR of free-living G. nanus was significantly and positively correlated with parasite load in spring when parasite load was highest; this relationship approached significance in summer when parasite load was lowest but was insignificant in winter. Among seasons, winter FMRs were highest and summer FMRs were lowest in G. nanus.The lack of parasite effect on FMR in winter could be related to the fact that FMR rates were highest among seasons. In this season, thermoregulatory costs are high which may indicate that less energy could be allocated to defend against parasites or to compensate for other costly activities. The question about the cost of parasitism in nature is now one of the major themes in ecological physiology. Our study supports the hypothesis that parasites can elevate FMR of their hosts, at least under certain conditions. However, the effect is complex and factors such as season and parasite load are involved

Predicting Spike Occurrence and Neuronal Responsiveness from LFPs in Primary Somatosensory Cortex

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role

Developing optimal input design strategies in cancer systems biology with applications to microfluidic device engineering

<p>Abstract</p> <p>Background</p> <p>Mechanistic models are becoming more and more popular in Systems Biology; identification and control of models underlying biochemical pathways of interest in oncology is a primary goal in this field. Unfortunately the scarce availability of data still limits our understanding of the intrinsic characteristics of complex pathologies like cancer: acquiring information for a system understanding of complex reaction networks is time consuming and expensive. Stimulus response experiments (SRE) have been used to gain a deeper insight into the details of biochemical mechanisms underlying cell life and functioning. Optimisation of the input time-profile, however, still remains a major area of research due to the complexity of the problem and its relevance for the task of information retrieval in systems biology-related experiments.</p> <p>Results</p> <p>We have addressed the problem of quantifying the information associated to an experiment using the Fisher Information Matrix and we have proposed an optimal experimental design strategy based on evolutionary algorithm to cope with the problem of information gathering in Systems Biology. On the basis of the theoretical results obtained in the field of control systems theory, we have studied the dynamical properties of the signals to be used in cell stimulation. The results of this study have been used to develop a microfluidic device for the automation of the process of cell stimulation for system identification.</p> <p>Conclusion</p> <p>We have applied the proposed approach to the Epidermal Growth Factor Receptor pathway and we observed that it minimises the amount of parametric uncertainty associated to the identified model. A statistical framework based on Monte-Carlo estimations of the uncertainty ellipsoid confirmed the superiority of optimally designed experiments over canonical inputs. The proposed approach can be easily extended to multiobjective formulations that can also take advantage of identifiability analysis. Moreover, the availability of fully automated microfluidic platforms explicitly developed for the task of biochemical model identification will hopefully reduce the effects of the 'data rich-data poor' paradox in Systems Biology.</p