To eat or not to eat? Kinematics and muscle activity of reach-to-grasp movements are influenced by the action goal, but observers do not detect these differences

Recent evidence suggests that the mirror neuron system responds to the goals of actions, even when the end of the movement is hidden from view. To investigate whether this predictive ability might be based on the detection of early differences between actions with different outcomes, we used electromyography (EMG) and motion tracking to assess whether two actions with different goals (grasp to eat and grasp to place) differed from each other in their initial reaching phases. In a second experiment, we then tested whether observers could detect early differences and predict the outcome of these movements, based on seeing only part of the actions. Experiment 1 revealed early kinematic differences between the two movements, with grasp-to-eat movements characterised by an earlier peak acceleration, and different grasp position, compared to grasp-to-place movements. There were also significant differences in forearm muscle activity in the reaching phase of the two actions. The behavioural data arising from Experiments 2a and 2b indicated that observers are not able to predict whether an object is going to be brought to the mouth or placed until after the grasp has been completed. This suggests that the early kinematic differences are either not visible to observers, or that they are not used to predict the end-goals of actions. These data are discussed in the context of the mirror neuron system

Photosynthetic activity and early growth of four Cacao genotypes as influenced by different shade regimes under West African dry and wet season conditions

The physiological performance of four cacao clones was examined under three artificial shade regimes over the course of a year in Ghana. Plants under light shade had significantly higher photosynthetic rates in the rainy seasons whereas in the dry season there was a trend of higher photosynthetic rates under heavy shade. The results imply that during the wet seasons light was the main limiting factor to photosynthesis whereas in the dry season vapour pressure deficit was the major factor limiting photosynthesis through stomatal regulation. Leaf area was generally lower under heavier shade but the difference between shade treatments varied between clones. Such differences in leaf area allocation appeared to underlie genotypic differences in final biomass production in response to shade. The results suggest that shade for young cacao should be provided based on the current ambient environment and genotype.

Connecting mean field models of neural activity to EEG and fMRI data

Progress in functional neuroimaging of the brain increasingly relies on the integration of data from complementary imaging modalities in order to improve spatiotemporal resolution and interpretability. However, the usefulness of merely statistical combinations is limited, since neural signal sources differ between modalities and are related non-trivially. We demonstrate here that a mean field model of brain activity can simultaneously predict EEG and fMRI BOLD with proper signal generation and expression. Simulations are shown using a realistic head model based on structural MRI, which includes both dense short-range background connectivity and long-range specific connectivity between brain regions. The distribution of modeled neural masses is comparable to the spatial resolution of fMRI BOLD, and the temporal resolution of the modeled dynamics, importantly including activity conduction, matches the fastest known EEG phenomena. The creation of a cortical mean field model with anatomically sound geometry, extensive connectivity, and proper signal expression is an important first step towards the model-based integration of multimodal neuroimages.

Wave-activity conservation laws for the three-dimensional anelastic and Boussinesq equations with a horizontally homogeneous background flow

Wave-activity conservation laws are key to understanding wave propagation in inhomogeneous environments. Their most general formulation follows from the Hamiltonian structure of geophysical fluid dynamics. For large-scale atmospheric dynamics, the Eliassen–Palm wave activity is a well-known example and is central to theoretical analysis. On the mesoscale, while such conservation laws have been worked out in two dimensions, their application to a horizontally homogeneous background flow in three dimensions fails because of a degeneracy created by the absence of a background potential vorticity gradient. Earlier three-dimensional results based on linear WKB theory considered only Doppler-shifted gravity waves, not waves in a stratified shear flow. Consideration of a background flow depending only on altitude is motivated by the parameterization of subgrid-scales in climate models where there is an imposed separation of horizontal length and time scales, but vertical coupling within each column. Here we show how this degeneracy can be overcome and wave-activity conservation laws derived for three-dimensional disturbances to a horizontally homogeneous background flow. Explicit expressions for pseudoenergy and pseudomomentum in the anelastic and Boussinesq models are derived, and it is shown how the previously derived relations for the two-dimensional problem can be treated as a limiting case of the three-dimensional problem. The results also generalize earlier three-dimensional results in that there is no slowly varying WKB-type requirement on the background flow, and the results are extendable to finite amplitude. The relationship A E =cA P between pseudoenergy A E and pseudomomentum A P, where c is the horizontal phase speed in the direction of symmetry associated with A P, has important applications to gravity-wave parameterization and provides a generalized statement of the first Eliassen–Palm theorem.

Towards a model-based integration of co-registered electroencephalography/functional magnetic resonance imaging data with realistic neural population meshes

Brain activity can be measured with several non-invasive neuroimaging modalities, but each modality has inherent limitations with respect to resolution, contrast and interpretability. It is hoped that multimodal integration will address these limitations by using the complementary features of already available data. However, purely statistical integration can prove problematic owing to the disparate signal sources. As an alternative, we propose here an advanced neural population model implemented on an anatomically sound cortical mesh with freely adjustable connectivity, which features proper signal expression through a realistic head model for the electroencephalogram (EEG), as well as a haemodynamic model for functional magnetic resonance imaging based on blood oxygen level dependent contrast (fMRI BOLD). It hence allows simultaneous and realistic predictions of EEG and fMRI BOLD from the same underlying model of neural activity. As proof of principle, we investigate here the influence on simulated brain activity of strengthening visual connectivity. In the future we plan to fit multimodal data with this neural population model. This promises novel, model-based insights into the brain's activity in sleep, rest and task conditions.

Classification of cortical microcircuits based on micro-electrode-array data from slices of rat barrel cortex

The bewildering complexity of cortical microcircuits at the single cell level gives rise to surprisingly robust emergent activity patterns at the level of laminar and columnar local field potentials (LFPs) in response to targeted local stimuli. Here we report the results of our multivariate data-analytic approach based on simultaneous multi-site recordings using micro-electrode-array chips for investigation of the microcircuitary of rat somatosensory (barrel) cortex. We find high repeatability of stimulus-induced responses, and typical spatial distributions of LFP responses to stimuli in supragranular, granular, and infragranular layers, where the last form a particularly distinct class. Population spikes appear to travel with about 33 cm/s from granular to infragranular layers. Responses within barrel related columns have different profiles than those in neighbouring columns to the left or interchangeably to the right. Variations between slices occur, but can be minimized by strictly obeying controlled experimental protocols. Cluster analysis on normalized recordings indicates specific spatial distributions of time series reflecting the location of sources and sinks independent of the stimulus layer. Although the precise correspondences between single cell activity and LFPs are still far from clear, a sophisticated neuroinformatics approach in combination with multi-site LFP recordings in the standardized slice preparation is suitable for comparing normal conditions to genetically or pharmacologically altered situations based on real cortical microcircuitry.

Population based models of cortical drug response: insights from anaesthesia

A great explanatory gap lies between the molecular pharmacology of psychoactive agents and the neurophysiological changes they induce, as recorded by neuroimaging modalities. Causally relating the cellular actions of psychoactive compounds to their influence on population activity is experimentally challenging. Recent developments in the dynamical modelling of neural tissue have attempted to span this explanatory gap between microscopic targets and their macroscopic neurophysiological effects via a range of biologically plausible dynamical models of cortical tissue. Such theoretical models allow exploration of neural dynamics, in particular their modification by drug action. The ability to theoretically bridge scales is due to a biologically plausible averaging of cortical tissue properties. In the resulting macroscopic neural field, individual neurons need not be explicitly represented (as in neural networks). The following paper aims to provide a non-technical introduction to the mean field population modelling of drug action and its recent successes in modelling anaesthesia.

An exploratory study into the putative prebiotic activity of fructans isolated from Agave angustifolia and the associated anticancer activity

Linear Inulin type fructan (ITF) prebiotics have a putative role in the prevention of colorectal cancer, whereas relatively little is known about branched fructans. This study aims to investigate the fermentation properties and potential prebiotic activity of branched fructans derived from Agave angustifolia Haw, using the Simulator of Human Intestinal Microbial Ecosystem (SHIME) model. The proximal, transverse and distal vessels were used to investigate fructan fermentation throughout the colon and to assess the alterations of the microbial composition and fermentation metabolites (short chain fatty acids and ammonia). The influence on bioactivity of the fermentation supernatant was assessed by MTT, Comet and transepithelial electrical resistance (TER), respectively. Addition of Agave fructan to the SHIME model significantly increased (P<0.05), bifidobacteria populations (proximal and transverse), SCFA concentrations (proximal, transverse and distal) and decreased ammonia concentrations in the distal vessel. Furthermore, the fermentation supernatant significantly (P<0.05) increased the TER of a Caco-2 cell monolayer (%) and decreased fluorescein-based paracellular flux, suggesting enhanced barrier function and reduced epithelial barrier permeability (proximal and distal vessel). While cytotoxicity and genotoxicity remained unaltered in response to the presence of Agave fructans. To conclude, branched Agave fructans show indications of prebiotic activity, particularly in relation to colon health by exerting a positive influence on gut barrier function, an important aspect of colon carcinogenesis.

Assessment of winter cyclone activity in a transient ECHAM4-OPYC3 GHG experiment

Winter cyclone activity over the Northern Hemisphere is investigated in an ECHAM4/OPYC3 greenhouse gas scenario simulation. The goal of this investigation is to identify changes in cyclone activity associated with increasing concentrations. To this aim, two 50-year time periods are analysed, one representing present day climate conditions and the other a perturbed climate when CO2 concentrations exceed twice the present concentrations. Cyclone activity is assessed using an automatic algorithm, which identifies and tracks cyclones based on sea level pressure fields. The algorithm detects not only large and long living cyclones over the main ocean basins, but also their smaller counterparts in secondary storm track regions like the Mediterranean Basin. For the present climate, results show a good agreement with NCEP-reanalysis, provided that the spectral and time resolutions of the reanalysis are reduced to those available for the model. Several prominent changes in cyclone activity are observed for the scenario period in comparison to the present day climate, especially over the main ocean basins. A significant decrease of overall cyclone track density is found between 35 and 55 degrees North, together with a small increase polewards. These changes result from two different signals for deep and medium cyclones: for deep cyclones (core pressure below 990 hPa) there is a poleward shift in the greenhouse gas scenario, while for medium cyclones (core pressure between 990 and 1010 hPa) a general decrease in cyclone counts is found. The same kind of changes (a shift for intense cyclones and an overall decrease for the weaker ones) are detected when distinguishing cyclones from their intensity, quantified in terms of ∇2p. Thus, the simulated changes can not solely be attributed to alterations in mean sea level pressure. Instead, corresponding increases in upper-tropospheric baroclinicity suggest more favourable conditions for the development of stronger systems at higher latitudes, especially at the delta regions of the North Atlantic and the North Pacific storm tracks.

On the group-velocity property for wave-activity conservation laws

The density and the flux of wave-activity conservation laws are generally required to satisfy the group-velocity property: under the WKB approximation (i.e., for nearly monochromatic small-amplitude waves in a slowly varying medium), the flux divided by the density equals the group velocity. It is shown that this property is automatically satisfied if, under the WKB approximation, the only source of rapid variations in the density and the flux lies in the wave phase. A particular form of the density, based on a self-adjoint operator, is proposed as a systematic choice for a density verifying this condition.

Lateral boundary contributions to wave-activity invariants and nonlinear stability theorems for balanced dynamics

The slow advective-timescale dynamics of the atmosphere and oceans is referred to as balanced dynamics. An extensive body of theory for disturbances to basic flows exists for the quasi-geostrophic (QG) model of balanced dynamics, based on wave-activity invariants and nonlinear stability theorems associated with exact symmetry-based conservation laws. In attempting to extend this theory to the semi-geostrophic (SG) model of balanced dynamics, Kushner & Shepherd discovered lateral boundary contributions to the SG wave-activity invariants which are not present in the QG theory, and which affect the stability theorems. However, because of technical difficulties associated with the SG model, the analysis of Kushner & Shepherd was not fully nonlinear. This paper examines the issue of lateral boundary contributions to wave-activity invariants for balanced dynamics in the context of Salmon's nearly geostrophic model of rotating shallow-water flow. Salmon's model has certain similarities with the SG model, but also has important differences that allow the present analysis to be carried to finite amplitude. In the process, the way in which constraints produce boundary contributions to wave-activity invariants, and additional conditions in the associated stability theorems, is clarified. It is shown that Salmon's model possesses two kinds of stability theorems: an analogue of Ripa's small-amplitude stability theorem for shallow-water flow, and a finite-amplitude analogue of Kushner & Shepherd's SG stability theorem in which the ‘subsonic’ condition of Ripa's theorem is replaced by a condition that the flow be cyclonic along lateral boundaries. As with the SG theorem, this last condition has a simple physical interpretation involving the coastal Kelvin waves that exist in both models. Salmon's model has recently emerged as an important prototype for constrained Hamiltonian balanced models. The extent to which the present analysis applies to this general class of models is discussed.

Genetic evidence for a predominant role of PI3Kβ catalytic activity in ITAM- and integrin-mediated signaling in platelets.

Phosphatidylinositol 3-kinase (PI3K) isoforms PI3Kbeta and PI3Kgamma are implicated in platelet adhesion, activation, and aggregation, but their relative contribution is still unclear or controversial. Here, we report the first comparative functional analysis of platelets from mice expressing a catalytically inactive form of PI3Kbeta or PI3Kgamma. We demonstrate that both isoforms were similarly required for maximal activation of the small GTPase Rap1b and for complete platelet aggregation upon stimulation of G protein-coupled receptors for adenosine 5'-diphosphate (ADP) or U46619. Their contribution to these events, however, was largely redundant and dispensable. However, PI3Kbeta, but not PI3Kgamma, enzymatic activity was absolutely required for Akt phosphorylation, Rap1 activation, and platelet aggregation downstream of the immunoreceptor tyrosine-based activation motif (ITAM)-bearing receptor glycoprotein VI (GPVI). Moreover, PI3Kbeta was a major essential regulator of platelet adhesion to fibrinogen and of integrin alpha(IIb)beta(3)-mediated spreading. These results provide genetic evidence for a crucial and selective role of PI3Kbeta in signaling through GPVI and integrin alpha(IIb)beta(3).

Balanced excitation and inhibition: Model based analysis of local field potentials

We have developed a model of the local field potential (LFP) based on the conservation of charge, the independence principle of ionic flows and the classical Hodgkin–Huxley (HH) type intracellular model of synaptic activity. Insights were gained through the simulation of the HH intracellular model on the nonlinear relationship between the balance of synaptic conductances and that of post-synaptic currents. The latter is dependent not only on the former, but also on the temporal lag between the excitatory and inhibitory conductances, as well as the strength of the afferent signal. The proposed LFP model provides a method for decomposing the LFP recordings near the soma of layer IV pyramidal neurons in the barrel cortex of anaesthetised rats into two highly correlated components with opposite polarity. The temporal dynamics and the proportional balance of the two components are comparable to the excitatory and inhibitory post-synaptic currents computed from the HH model. This suggests that the two components of the LFP reflect the underlying excitatory and inhibitory post-synaptic currents of the local neural population. We further used the model to decompose a sequence of evoked LFP responses under repetitive electrical stimulation (5 Hz) of the whisker pad. We found that as neural responses adapted, the excitatory and inhibitory components also adapted proportionately, while the temporal lag between the onsets of the two components increased during frequency adaptation. Our results demonstrated that the balance between neural excitation and inhibition can be investigated using extracellular recordings. Extension of the model to incorporate multiple compartments should allow more quantitative interpretations of surface Electroencephalography (EEG) recordings into components reflecting the excitatory, inhibitory and passive ionic current flows generated by local neural populations.

A dynamic causal model of the coupling between pulse stimulation and neural activity

We present a dynamic causal model that can explain context-dependent changes in neural responses, in the rat barrel cortex, to an electrical whisker stimulation at different frequencies. Neural responses were measured in terms of local field potentials. These were converted into current source density (CSD) data, and the time series of the CSD sink was extracted to provide a time series response train. The model structure consists of three layers (approximating the responses from the brain stem to the thalamus and then the barrel cortex), and the latter two layers contain nonlinearly coupled modules of linear second-order dynamic systems. The interaction of these modules forms a nonlinear regulatory system that determines the temporal structure of the neural response amplitude for the thalamic and cortical layers. The model is based on the measured population dynamics of neurons rather than the dynamics of a single neuron and was evaluated against CSD data from experiments with varying stimulation frequency (1–40 Hz), random pulse trains, and awake and anesthetized animals. The model parameters obtained by optimization for different physiological conditions (anesthetized or awake) were significantly different. Following Friston, Mechelli, Turner, and Price (2000), this work is part of a formal mathematical system currently being developed (Zheng et al., 2005) that links stimulation to the blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal through neural activity and hemodynamic variables. The importance of the model described here is that it can be used to invert the hemodynamic measurements of changes in blood flow to estimate the underlying neural activity.

Lack of association between PCK1 polymorphisms and obesity, physical activity, and fitness in European Youth Heart Study (EYHS)

Phosphoenolpyruvate carboxykinase-1 (PCK1) is the rate-limiting enzyme in the hepatic gluconeogenic pathway. Studies have shown that overexpression of Pck1 in mice results in obesity-related traits and higher levels of physical activity (PA). Therefore, our aims were to investigate whether common genetic variation in the PCK1 gene influences obesity-related traits, PA, and fitness, and to examine whether PA and fitness attenuate the influence of the PCK1 polymorphisms on obesity in children. Analyses were undertaken on data from Danish and Estonian children (958 boys and 1,104 girls) from the European Youth Heart Study (EYHS), a school-based, cross-sectional study of children (mean ± s.d. age: 9.6 ± 0.4 years) and adolescents (15.5 ± 0.5 years). We genotyped eight polymorphisms that captured the common genetic variations in the PCK1 gene. The association between the PCK1 polymorphisms and BMI, waist circumference (WC), sum of four skinfolds, PA, and fitness was tested using an additive model adjusted for age, age-group, gender, maturity, and country. Interactions were tested by including interaction terms in the model. None of the polymorphisms were significantly associated with BMI, WC, sum of four skinfolds, PA, and fitness, and also with the risk of being overweight or obese (P > 0.05). The interactions between the polymorphisms and age-group, gender, PA, and fitness were not statistically significant. This is the first study to comprehensively examine the association of PCK1 polymorphisms with obesity, PA, and fitness. Despite strong evidence from animal studies, our study in the EYHS cohort failed to identify an association of PCK1 polymorphisms with obesity, PA, and fitness.