Perceptual Learning via Modification of Cortical Top-Down Signals

The primary visual cortex (V1) is pre-wired to facilitate the extraction of behaviorally important visual features. Collinear edge detectors in V1, for instance, mutually enhance each other to improve the perception of lines against a noisy background. The same pre-wiring that facilitates line extraction, however, is detrimental when subjects have to discriminate the brightness of different line segments. How is it possible to improve in one task by unsupervised practicing, without getting worse in the other task? The classical view of perceptual learning is that practicing modulates the feedforward input stream through synaptic modifications onto or within V1. However, any rewiring of V1 would deteriorate other perceptual abilities different from the trained one. We propose a general neuronal model showing that perceptual learning can modulate top-down input to V1 in a task-specific way while feedforward and lateral pathways remain intact. Consistent with biological data, the model explains how context-dependent brightness discrimination is improved by a top-down recruitment of recurrent inhibition and a top-down induced increase of the neuronal gain within V1. Both the top-down modulation of inhibition and of neuronal gain are suggested to be universal features of cortical microcircuits which enable perceptual learning.

Automatic Reduction of Artifacts in EEG-Signals

Electroencephalograms (EEG) are often contaminated with high amplitude artifacts limiting the usability of data. Methods that reduce these artifacts are often restricted to certain types of artifacts, require manual interaction or large training data sets. Within this paper we introduce a novel method, which is able to eliminate many different types of artifacts without manual intervention. The algorithm first decomposes the signal into different sub-band signals in order to isolate different types of artifacts into specific frequency bands. After signal decomposition with principal component analysis (PCA) an adaptive threshold is applied to eliminate components with high variance corresponding to the dominant artifact activity. Our results show that the algorithm is able to significantly reduce artifacts while preserving the EEG activity. Parameters for the algorithm do not have to be identified for every patient individually making the method a good candidate for preprocessing in automatic seizure detection and prediction algorithms.

Ultrasonic acoustic emissions in drought-stressed trees - more than signals from cavitation?

Ultrasonic acoustic emission (UAE) in trees is often related to collapsing water columns in the flow path as a result of tensions that are too strong (cavitation). However, in a decibel (dB) range below that associated with cavitation, a close relationship was found between UAE intensities and stem radius changes. • UAE was continuously recorded on the stems of mature field-grown trees of Scots pine (Pinus sylvestris) and pubescent oak (Quercus pubescens) at a dry inner-Alpine site in Switzerland over two seasons. The averaged 20-Hz records were related to microclimatic conditions in air and soil, sap-flow rates and stem-radius fluctuations de-trended for growth (ΔW). • Within a low-dB range (27 ± 1 dB), UAE regularly increased and decreased in a diurnal rhythm in parallel with ΔW on cloudy days and at night. These low-dB emissions were interrupted by UAE abruptly switching between the low-dB range and a high-dB range (36 ± 1 dB) on clear, sunny days, corresponding to the widely supported interpretation of UAE as sound from cavitations. • It is hypothesized that the low-dB signals in drought-stressed trees are caused by respiration and/or cambial growth as these physiological activities are tissue water-content dependent and have been shown to produce courses of CO2 efflux similar to our courses of ΔW and low-dB UAE.

Mechanical signals regulating extracellular matrix gene expression in fibroblasts

Mechanical forces are essential for connective tissue homeostasis. The extracellular matrix (ECM) plays a key role in the transmission of forces generated by the organism (e.g. muscle contraction) and externally applied (e.g. gravity). The expression of specific ECM proteins such as collagens and tenascin-C, as well as of matrix metalloproteinases, involved in their turnover, is influenced by mechanical stimuli. The precise mechanisms by which mechanical strains are translated into chemical signals and lead to differential gene expression are however not fully understood. Cell-matrix adhesion sites are good candidates for hosting a "mechanosensory switch", as they transmit forces from the ECM to the cytoskeleton and vice versa by physically linking the cytoskeleton to the ECM. Integrins, transmembrane proteins located to these adhesion sites, have been shown to trigger a set of internal signaling cascades after mechanical stimulation. We have shown that the expression level of tenascin-C directly correlates with externally applied mechanical stress, as well as with RhoA/RhoA-dependent kinase-mediated cytoskeletal tension. Presumably other genes are regulated in a similar manner. The changes in ECM composition and mechanical properties derived from mechanical stress are relevant in medical intervention after ligament and tendon injury.

Traffic Routes and Signals for the Tonoplast

Tonoplast, the membrane delimiting plant vacuoles, regulates ion, water and nutrient movement between the cytosol and the vacuolar lumen through the activity of its membrane proteins. Correct traffic of proteins from the endoplasmic reticulum (ER) to the tonoplast requires (i) approval by the ER quality control, (ii) motifs for exit from the ER and (iii) motifs that promote sorting to the tonoplast. Recent evidence suggests that this traffic follows different pathways that are protein-specific and could also reflect vacuole specialization for lytic or storage function. The routes can be distinguished based on their sensitivity to drugs such as brefeldin A and C834 as well as using mutant plants that are defective in adaptor proteins of vesicle coats, or dominant-negative mutants of Rab GTPases.

Regulation of visfatin by microbial and biomechanical signals in PDL cells

OBJECTIVES This in vitro study was established to examine whether visfatin thought to be a link between periodontitis and obesity is produced by periodontal ligament (PDL) cells and, if so, whether its synthesis is modulated by microbial and/or biomechanical signals. MATERIALS AND METHODS PDL cells seeded on BioFlex® plates were exposed to the oral pathogen Fusobacterium nucleatum ATCC 25586 and/or subjected to biomechanical strain for up to 3 days. Gene expression of visfatin and toll-like receptors (TLR) 2 and 4 was analyzed by RT-PCR, visfatin protein synthesis by ELISA and immunocytochemistry, and NFκB nuclear translocation by immunofluorescence. RESULTS F. nucleatum upregulated the visfatin expression in a dose- and time-dependent fashion. Preincubation with neutralizing antibodies against TLR2 and TLR4 caused a significant inhibition of the F. nucleatum-upregulated visfatin expression at 1 day. F. nucleatum stimulated the NFκB nuclear translocation. Biomechanical loading reduced the stimulatory effects of F. nucleatum on visfatin expression at 1 and 3 days and also abrogated the F. nucleatum-induced NFκB nuclear translocation at 60 min. Biomechanical loading inhibited significantly the expression of TLR2 and TLR4 at 3 days. The regulatory effects of F. nucleatum and/or biomechanical loading on visfatin expression were also observed at protein level. CONCLUSIONS PDL cells produce visfatin, and this production is enhanced by F. nucleatum. Biomechanical loading seems to be protective against the effects of F. nucleatum on visfatin expression. CLINICAL RELEVANCE Visfatin produced by periodontal tissues could play a major role in the pathogenesis of periodontitis and the interactions with obesity and other systemic diseases.

Pathogenesis of AF: impact on intracardiac signals

Atrial fibrillation (AF) is the most common cardiac arrhythmia, and is responsible for the highest number of rhythm-related disorders and cardioembolic strokes worldwide. Intracardiac signal analysis during the onset of paroxysmal AF led to the discovery of pulmonary vein as a triggering source of AF, which has led to the development of pulmonary vein ablation--an established curative therapy for drug-resistant AF. Complex, multicomponent and rapid electrical activity widely involving the atrial substrate characterizes persistent/permanent AF. Widespread nature of the problem and complexity of signals in persistent AF reduce the success rate of ablation therapy. Although signal processing applied to extraction of relevant features from these complex electrograms has helped to improve the efficacy of ablation therapy in persistent/permanent AF, improved understanding of complex signals should help to identify sources of AF and further increase the success rate of ablation therapy.