Subthreshold oscillations in a map-based neuron model

Self-sustained subthreshold oscillations in a discrete-time model of neuronal behavior are considered. We discuss bifurcation scenarios explaining the birth of these oscillations and their transformation into tonic spikes. Specific features of these transitions caused by the discrete-time dynamics of the model and the influence of external noise are discussed.Comment: To be published in Physics Letters

Surface currents in the macaronesian region, thirteen years of drifting data

Peer Reviewe

Comparative whole genome transcriptome analysis of three Plasmodium falciparum strains

Gene expression patterns have been demonstrated to be highly variable between similar cell types, for example lab strains and wild strains of Saccharomyces cerevisiae cultured under identical growth conditions exhibit a wide range of expression differences. We have used a genome-wide approach to characterize transcriptional differences between strains of Plasmodium falciparum by characterizing the transcriptome of the 48 h intraerythrocytic developmental cycle (IDC) for two strains, 3D7 and Dd2 and compared these results to our prior work using the HB3 strain. These three strains originate from geographically diverse locations and possess distinct drug sensitivity phenotypes. Our goal was to identify transcriptional differences related to phenotypic properties of these strains including immune evasion and drug sensitivity. We find that the highly streamlined transcriptome is remarkably well conserved among all three strains, and differences in gene expression occur mainly in genes coding for surface antigens involved in parasite–host interactions. Our analysis also detects several transcripts that are unique to individual strains as well as identifying large chromosomal deletions and highly polymorphic regions across strains. The majority of these genes are uncharacterized and have no homology to other species. These tractable transcriptional differences provide important phenotypes for these otherwise highly related strains of Plasmodium

Introduction

Abstract not availabl

Transmission of Information in Active Networks

Shannon's Capacity Theorem is the main concept behind the Theory of Communication. It says that if the amount of information contained in a signal is smaller than the channel capacity of a physical media of communication, it can be transmitted with arbitrarily small probability of error. This theorem is usually applicable to ideal channels of communication in which the information to be transmitted does not alter the passive characteristics of the channel that basically tries to reproduce the source of information. For an {\it active channel}, a network formed by elements that are dynamical systems (such as neurons, chaotic or periodic oscillators), it is unclear if such theorem is applicable, once an active channel can adapt to the input of a signal, altering its capacity. To shed light into this matter, we show, among other results, how to calculate the information capacity of an active channel of communication. Then, we show that the {\it channel capacity} depends on whether the active channel is self-excitable or not and that, contrary to a current belief, desynchronization can provide an environment in which large amounts of information can be transmitted in a channel that is self-excitable. An interesting case of a self-excitable active channel is a network of electrically connected Hindmarsh-Rose chaotic neurons.Comment: 15 pages, 5 figures. submitted for publication. to appear in Phys. Rev.

Reconstruction and flux-balance analysis of the Plasmodium falciparum metabolic network

In the paper we present a metabolic reconstruction and flux-balance analysis (FBA) of Plasmodium falciparum, the primary agent of malaria. The compartmentalized metabolic network of the parasite accounts for 1001 reactions and 616 metabolites. Enzyme–gene associations were established for 366 genes and 75% of all enzymatic reactions.The model was able to reproduce phenotypes of experimental gene knockout and drug inhibition assays with up to 90% accuracy. The model also can be used to efficiently integrate mRNA-expression data to improve the accuracy of metabolic predictions.Using FBA of the reconstructed metabolic network, we identified 40 enzymatic drug targets (i.e. in silico essential genes) with no or very low sequence identity to human proteins.We experimentally tested one of the identified drug targets, nicotinate mononucleotide adenylyltransferase, using a recently discovered small-molecule inhibitor

Electrophysiological Characterization of The Cerebellum in the Arterially Perfused Hindbrain and Upper Body of The Rat

In the present study, a non-pulsatile arterially perfused hindbrain and upper body rat preparation is described which is an extension of the brainstem preparation reported by Potts et al., (Brain Res Bull 53(1):59–67), 1. The modified in situ preparation allows study of cerebellar function whilst preserving the integrity of many of its interconnections with the brainstem, upper spinal cord and the peripheral nervous system of the head and forelimbs. Evoked mossy fibre, climbing fibre and parallel fibre field potentials and EMG activity elicited in forelimb biceps muscle by interpositus stimulation provided evidence that both cerebellar inputs and outputs remain operational in this preparation. Similarly, the spontaneous and evoked single unit activity of Purkinje cells, putative Golgi cells, molecular interneurones and cerebellar nuclear neurones was similar to activity patterns reported in vivo. The advantages of the preparation include the ability to record, without the complications of anaesthesia, stabile single unit activity for extended periods (3 h or more), from regions of the rat cerebellum that are difficult to access in vivo. The preparation should therefore be a useful adjunct to in vitro and in vivo studies of neural circuits underlying cerebellar contributions to movement control and motor learning

Coherence Resonance and Noise-Induced Synchronization in Globally Coupled Hodgkin-Huxley Neurons

The coherence resonance (CR) of globally coupled Hodgkin-Huxley neurons is studied. When the neurons are set in the subthreshold regime near the firing threshold, the additive noise induces limit cycles. The coherence of the system is optimized by the noise. A bell-shaped curve is found for the peak height of power spectra of the spike train, being significantly different from a monotonic behavior for the single neuron. The coupling of the network can enhance CR in two different ways. In particular, when the coupling is strong enough, the synchronization of the system is induced and optimized by the noise. This synchronization leads to a high and wide plateau in the local measure of coherence curve. The local-noise-induced limit cycle can evolve to a refined spatiotemporal order through the dynamical optimization among the autonomous oscillation of an individual neuron, the coupling of the network, and the local noise.Comment: five pages, five figure