Does the information in the phase of low frequency LFP reflect the low frequency envelope of local spike rates?

Recently, it has been shown that when the timing of spikes is measured relative to the phase of the cortical local field potentials (LFP), spikes can carry substantial more information about an external stimulus [1]. Experimental studies in sensory cortices of macaque have shown that the extra information obtained with such phase-of-firing codes above that in the firing rate alone ranges from 55 in primary visual cortex [1] to more than 100 in primary auditory cortex [2]. Here, we use a mathematical model that relates local spike trains and the resulting LFP, to explain the emergence of the phase-of-firing codes in cortex. The model is based on the one proposed in [3] and incorporates two types of integration over the spiking activity: i) a time convolution that results from the filtering properties of neural structures [4], which embeds history effects in LFP from past spiking activity, and ii) an integration step over the activity of neurons in the neighbourhood of the measuring electrode. When the spikes recorded from macaque primary visual cortex were used to synthesize the LFP, the model could reproduce the phase-of-firing information found using the real LFP, as shown in Figure 1. This suggests that an important component of phase-of-firing information originates from the surrounding neural population and past spiking activity. The next question that arises is what is the relative contribution of the neuron population size and the length of the firing rate history embedded in the LFP. We are currently investigating this question by parametrically varying both the population size and time integration ranges in generating the synthetic LFP

Poroelastic Modelling of CSF circulation via the incorporation of experimentally derived microscale water transport properties

We outline how multicompartmental poroelasticity is applied to the study of dementia. We utilize a 3D version of our poroelastic code to investigate the effects within parenchymal tissue. This system is coupled with multiple pipelines within the VPH-DARE@IT project which account for patient/subject-specific boundary conditions in the arterial compartment, in addition to both an image segmentation-mesh and integrated cardiovascular system model pipeline respectively. This consolidated template allows for the extraction of boundary conditions to run CFD simulations for the ventricles. Finally, we outline some experimental results that will help inform the MPET system

Inverse Current Source Density Method in Two Dimensions: Inferring Neural Activation from Multielectrode Recordings

The recent development of large multielectrode recording arrays has made it affordable for an increasing number of laboratories to record from multiple brain regions simultaneously. The development of analytical tools for array data, however, lags behind these technological advances in hardware. In this paper, we present a method based on forward modeling for estimating current source density from electrophysiological signals recorded on a two-dimensional grid using multi-electrode rectangular arrays. This new method, which we call two-dimensional inverse Current Source Density (iCSD 2D), is based upon and extends our previous one- and three-dimensional techniques. We test several variants of our method, both on surrogate data generated from a collection of Gaussian sources, and on model data from a population of layer 5 neocortical pyramidal neurons. We also apply the method to experimental data from the rat subiculum. The main advantages of the proposed method are the explicit specification of its assumptions, the possibility to include system-specific information as it becomes available, the ability to estimate CSD at the grid boundaries, and lower reconstruction errors when compared to the traditional approach. These features make iCSD 2D a substantial improvement over the approaches used so far and a powerful new tool for the analysis of multielectrode array data. We also provide a free GUI-based MATLAB toolbox to analyze and visualize our test data as well as user datasets

Multiplexed, High Density Electrophysiology with Nanofabricated Neural Probes

Extracellular electrode arrays can reveal the neuronal network correlates of behavior with single-cell, single-spike, and sub-millisecond resolution. However, implantable electrodes are inherently invasive, and efforts to scale up the number and density of recording sites must compromise on device size in order to connect the electrodes. Here, we report on silicon-based neural probes employing nanofabricated, high-density electrical leads. Furthermore, we address the challenge of reading out multichannel data with an application-specific integrated circuit (ASIC) performing signal amplification, band-pass filtering, and multiplexing functions. We demonstrate high spatial resolution extracellular measurements with a fully integrated, low noise 64-channel system weighing just 330 mg. The on-chip multiplexers make possible recordings with substantially fewer external wires than the number of input channels. By combining nanofabricated probes with ASICs we have implemented a system for performing large-scale, high-density electrophysiology in small, freely behaving animals that is both minimally invasive and highly scalable

Aerobic capacity, activity levels and daily energy expenditure in male and female adolescents of the kenyan nandi sub-group

The relative importance of genetic and socio-cultural influences contributing to the success of east Africans in endurance athletics remains unknown in part because the pre-training phenotype of this population remains incompletely assessed. Here cardiopulmonary fitness, physical activity levels, distance travelled to school and daily energy expenditure in 15 habitually active male (13.9±1.6 years) and 15 habitually active female (13.9±1.2) adolescents from a rural Nandi primary school are assessed. Aerobic capacity ([Formula: see text]) was evaluated during two maximal discontinuous incremental exercise tests; physical activity using accelerometry combined with a global positioning system; and energy expenditure using the doubly labelled water method. The [Formula: see text] of the male and female adolescents were 73.9±5.7 ml(.) kg(-1.) min(-1) and 61.5±6.3 ml(.) kg(-1.) min(-1), respectively. Total time spent in sedentary, light, moderate and vigorous physical activities per day was 406±63 min (50% of total monitored time), 244±56 min (30%), 75±18 min (9%) and 82±30 min (10%). Average total daily distance travelled to and from school was 7.5±3.0 km (0.8-13.4 km). Mean daily energy expenditure, activity-induced energy expenditure and physical activity level was 12.2±3.4 MJ(.) day(-1), 5.4±3.0 MJ(.) day(-1) and 2.2±0.6. 70.6% of the variation in [Formula: see text] was explained by sex (partial R(2) = 54.7%) and body mass index (partial R(2) = 15.9%). Energy expenditure and physical activity variables did not predict variation in [Formula: see text] once sex had been accounted for. The highly active and energy-demanding lifestyle of rural Kenyan adolescents may account for their exceptional aerobic fitness and collectively prime them for later training and athletic success

Lateral opening in the intact β-barrel assembly machinery captured by cryo-EM

The β-barrel assembly machinery (BAM) is a ~203 kDa complex of five proteins (BamA-E) which is essential for viability in E. coli. BAM promotes the folding and insertion of β-barrel proteins into the outer membrane via a poorly understood mechanism. Several current models suggest that BAM functions through a ‘lateral gating’ motion of the β-barrel of BamA. Here we present a cryo-EM structure of the BamABCDE complex, at 4.9 Å resolution. The structure is in a laterally open conformation showing that gating is independent of BamB binding. We describe conformational changes throughout the complex, and interactions between BamA, B, D, and E and the detergent micelle that suggest communication between BAM and the lipid bilayer. Finally, using an enhanced reconstitution protocol and functional assays, we show that for the outer membrane protein OmpT, efficient folding in vitro requires lateral gating in BAM

Subsampling effects in neuronal avalanche distributions recorded in vivo

Background Many systems in nature are characterized by complex behaviour where large cascades of events, or avalanches, unpredictably alternate with periods of little activity. Snow avalanches are an example. Often the size distribution f(s) of a system's avalanches follows a power law, and the branching parameter sigma, the average number of events triggered by a single preceding event, is unity. A power law for f(s), and sigma=1, are hallmark features of self-organized critical (SOC) systems, and both have been found for neuronal activity in vitro. Therefore, and since SOC systems and neuronal activity both show large variability, long-term stability and memory capabilities, SOC has been proposed to govern neuronal dynamics in vivo. Testing this hypothesis is difficult because neuronal activity is spatially or temporally subsampled, while theories of SOC systems assume full sampling. To close this gap, we investigated how subsampling affects f(s) and sigma by imposing subsampling on three different SOC models. We then compared f(s) and sigma of the subsampled models with those of multielectrode local field potential (LFP) activity recorded in three macaque monkeys performing a short term memory task. Results Neither the LFP nor the subsampled SOC models showed a power law for f(s). Both, f(s) and sigma, depended sensitively on the subsampling geometry and the dynamics of the model. Only one of the SOC models, the Abelian Sandpile Model, exhibited f(s) and sigma similar to those calculated from LFP activity. Conclusions Since subsampling can prevent the observation of the characteristic power law and sigma in SOC systems, misclassifications of critical systems as sub- or supercritical are possible. Nevertheless, the system specific scaling of f(s) and sigma under subsampling conditions may prove useful to select physiologically motivated models of brain function. Models that better reproduce f(s) and sigma calculated from the physiological recordings may be selected over alternatives

In Silico Analysis of the Apolipoprotein E and the Amyloid β Peptide Interaction: Misfolding Induced by Frustration of the Salt Bridge Network

The relationship between Apolipoprotein E (ApoE) and the aggregation processes of the amyloid β (Aβ) peptide has been shown to be crucial for Alzheimer's disease (AD). The presence of the ApoE4 isoform is considered to be a contributing risk factor for AD. However, the detailed molecular properties of ApoE4 interacting with the Aβ peptide are unknown, although various mechanisms have been proposed to explain the physiological and pathological role of this relationship. Here, computer simulations have been used to investigate the process of Aβ interaction with the N-terminal domain of the human ApoE isoforms (ApoE2, ApoE3 and ApoE4). Molecular docking combined with molecular dynamics simulations have been undertaken to determine the Aβ peptide binding sites and the relative stability of binding to each of the ApoE isoforms. Our results show that from the several ApoE isoforms investigated, only ApoE4 presents a misfolded intermediate when bound to Aβ. Moreover, the initial α-helix used as the Aβ peptide model structure also becomes unstructured due to the interaction with ApoE4. These structural changes appear to be related to a rearrangement of the salt bridge network in ApoE4, for which we propose a model. It seems plausible that ApoE4 in its partially unfolded state is incapable of performing the clearance of Aβ, thereby promoting amyloid forming processes. Hence, the proposed model can be used to identify potential drug binding sites in the ApoE4-Aβ complex, where the interaction between the two molecules can be inhibited