Auditory motion direction encoding in auditory cortex and high-level visual cortex

The aim of this functional magnetic resonance imaging (fMRI) study was to identify human brain areas that are sensitive to the direction of auditory motion. Such directional sensitivity was assessed in a hypothesis-free manner by analyzing fMRI response patterns across the entire brain volume using a spherical-searchlight approach. In addition, we assessed directional sensitivity in three predefined brain areas that have been associated with auditory motion perception in previous neuroimaging studies. These were the primary auditory cortex, the planum temporale and the visual motion complex (hMT/V5+). Our whole-brain analysis revealed that the direction of sound-source movement could be decoded from fMRI response patterns in the right auditory cortex and in a high-level visual area located in the right lateral occipital cortex. Our region-of-interest-based analysis showed that the decoding of the direction of auditory motion was most reliable with activation patterns of the left and right planum temporale. Auditory motion direction could not be decoded from activation patterns in hMT/V5+. These findings provide further evidence for the planum temporale playing a central role in supporting auditory motion perception. In addition, our findings suggest a cross-modal transfer of directional information to high-level visual cortex in healthy humans.

[A database of available DNA tests in the dog]

For genetic counseling this report presents a database of canine hereditary diseases and coat color characteristics, which have been solved on the molecular level.The database facilitates access to appropriate diagnostic laboratories for specific phenotypes. The recent decoding of the dog genome provides ideal conditions for the molecular genetic analysis of hereditary traits and diseases. Therefore the authors would like to encourage veterinary surgeons in particular to report cases to assist the molecular analysis of further phenotypes in future.

Affective and linguistic processing of speech prosody: DC potential studies

Speech melody or prosody subserves linguistic, emotional, and pragmatic functions in speech communication. Prosodic perception is based on the decoding of acoustic cues with a predominant function of frequency-related information perceived as speaker's pitch. Evaluation of prosodic meaning is a cognitive function implemented in cortical and subcortical networks that generate continuously updated affective or linguistic speaker impressions. Various brain-imaging methods allow delineation of neural structures involved in prosody processing. In contrast to functional magnetic resonance imaging techniques, DC (direct current, slow) components of the EEG directly measure cortical activation without temporal delay. Activation patterns obtained with this method are highly task specific and intraindividually reproducible. Studies presented here investigated the topography of prosodic stimulus processing in dependence on acoustic stimulus structure and linguistic or affective task demands, respectively. Data obtained from measuring DC potentials demonstrated that the right hemisphere has a predominant role in processing emotions from the tone of voice, irrespective of emotional valence. However, right hemisphere involvement is modulated by diverse speech and language-related conditions that are associated with a left hemisphere participation in prosody processing. The degree of left hemisphere involvement depends on several factors such as (i) articulatory demands on the perceiver of prosody (possibly, also the poser), (ii) a relative left hemisphere specialization in processing temporal cues mediating prosodic meaning, and (iii) the propensity of prosody to act on the segment level in order to modulate word or sentence meaning. The specific role of top-down effects in terms of either linguistically or affectively oriented attention on lateralization of stimulus processing is not clear and requires further investigations.

Soft-decision equalization techniques for frequency selective MIMO channels

Multi-input multi-output (MIMO) technology is an emerging solution for high data rate wireless communications. We develop soft-decision based equalization techniques for frequency selective MIMO channels in the quest for low-complexity equalizers with BER performance competitive to that of ML sequence detection. We first propose soft decision equalization (SDE), and demonstrate that decision feedback equalization (DFE) based on soft-decisions, expressed via the posterior probabilities associated with feedback symbols, is able to outperform hard-decision DFE, with a low computational cost that is polynomial in the number of symbols to be recovered, and linear in the signal constellation size. Building upon the probabilistic data association (PDA) multiuser detector, we present two new MIMO equalization solutions to handle the distinctive channel memory. With their low complexity, simple implementations, and impressive near-optimum performance offered by iterative soft-decision processing, the proposed SDE methods are attractive candidates to deliver efficient reception solutions to practical high-capacity MIMO systems. Motivated by the need for low-complexity receiver processing, we further present an alternative low-complexity soft-decision equalization approach for frequency selective MIMO communication systems. With the help of iterative processing, two detection and estimation schemes based on second-order statistics are harmoniously put together to yield a two-part receiver structure: local multiuser detection (MUD) using soft-decision Probabilistic Data Association (PDA) detection, and dynamic noise-interference tracking using Kalman filtering. The proposed Kalman-PDA detector performs local MUD within a sub-block of the received data instead of over the entire data set, to reduce the computational load. At the same time, all the inter-ference affecting the local sub-block, including both multiple access and inter-symbol interference, is properly modeled as the state vector of a linear system, and dynamically tracked by Kalman filtering. Two types of Kalman filters are designed, both of which are able to track an finite impulse response (FIR) MIMO channel of any memory length. The overall algorithms enjoy low complexity that is only polynomial in the number of information-bearing bits to be detected, regardless of the data block size. Furthermore, we introduce two optional performance-enhancing techniques: cross- layer automatic repeat request (ARQ) for uncoded systems and code-aided method for coded systems. We take Kalman-PDA as an example, and show via simulations that both techniques can render error performance that is better than Kalman-PDA alone and competitive to sphere decoding. At last, we consider the case that channel state information (CSI) is not perfectly known to the receiver, and present an iterative channel estimation algorithm. Simulations show that the performance of SDE with channel estimation approaches that of SDE with perfect CSI.

Applications of finite geometries to designs and codes

This dissertation concerns the intersection of three areas of discrete mathematics: finite geometries, design theory, and coding theory. The central theme is the power of finite geometry designs, which are constructed from the points and t-dimensional subspaces of a projective or affine geometry. We use these designs to construct and analyze combinatorial objects which inherit their best properties from these geometric structures. A central question in the study of finite geometry designs is Hamada’s conjecture, which proposes that finite geometry designs are the unique designs with minimum p-rank among all designs with the same parameters. In this dissertation, we will examine several questions related to Hamada’s conjecture, including the existence of counterexamples. We will also study the applicability of certain decoding methods to known counterexamples. We begin by constructing an infinite family of counterexamples to Hamada’s conjecture. These designs are the first infinite class of counterexamples for the affine case of Hamada’s conjecture. We further demonstrate how these designs, along with the projective polarity designs of Jungnickel and Tonchev, admit majority-logic decoding schemes. The codes obtained from these polarity designs attain error-correcting performance which is, in certain cases, equal to that of the finite geometry designs from which they are derived. This further demonstrates the highly geometric structure maintained by these designs. Finite geometries also help us construct several types of quantum error-correcting codes. We use relatives of finite geometry designs to construct infinite families of q-ary quantum stabilizer codes. We also construct entanglement-assisted quantum error-correcting codes (EAQECCs) which admit a particularly efficient and effective error-correcting scheme, while also providing the first general method for constructing these quantum codes with known parameters and desirable properties. Finite geometry designs are used to give exceptional examples of these codes.

MAXIMAL ARCS, ABOVE AND BEYOND

This report explores combinatorial structures in Finite Geometries by giving known constructions of maximal arcs; using maximal arcs to construct two-weight codes, partial geometries, strongly regular graphs and LDPC codes; a review on how to generalize maximal arcs to higher dimensions through Perp-Systems; and an effort in finding constructions of new Perp-Systems.

Real-Time Passive Capturing of the GSM Radio

This paper addresses the problem of service development based on GSM handset signaling. The aim is to achieve this goal without the participation of the users, which requires the use of a passive GSM receiver on the uplink. Since no tool for GSM uplink capturing was available, we developed a new method that can synchronize to multiple mobile devices by simply overhearing traffic between them and the network. Our work includes the implementation of modules for signal recovery, message reconstruction and parsing. The method has been validated against a benchmark solution on GSM downlink and independently evaluated on uplink channels. Initial evaluations show up to 99% success rate in message decoding, which is a very promising result. Moreover, we conducted measurements that reveal insights on the impact of signal power on the capturing performance and investigate possible reactive measures.

An OMNeT++ Framework to Evaluate Video Transmission in Mobile Wireless Multimedia Sensor Networks

The development and evaluation of new algorithms and protocols for Wireless Multimedia Sensor Networks (WMSNs) are usually supported by means of a discrete event network simulator, where OMNeT++ is one of the most important ones. However, experiments involving multimedia transmission, video flows with different characteristics, genres, group of pictures lengths, and coding techniques must be evaluated based also on Quality of Experience (QoE) metrics to reflect the user's perception. Such experiments require the evaluation of video-related information, i.e., frame type, received/lost, delay, jitter, decoding errors, as well as inter and intra-frame dependency of received/distorted videos. However, existing OMNeT++ frameworks for WMSNs do not support video transmissions with QoE-awareness, neither a large set of mobility traces to enable evaluations under different multimedia/mobile situations. In this paper, we propose a Mobile MultiMedia Wireless Sensor Network OMNeT++ framework (M3WSN) to support transmission, control and evaluation of real video sequences in mobile WMSNs.

Distributed sensor failure detection in sensor networks

We investigate the problem of distributed sensors' failure detection in networks with a small number of defective sensors, whose measurements differ significantly from the neighbor measurements. We build on the sparse nature of the binary sensor failure signals to propose a novel distributed detection algorithm based on gossip mechanisms and on Group Testing (GT), where the latter has been used so far in centralized detection problems. The new distributed GT algorithm estimates the set of scattered defective sensors with a low complexity distance decoder from a small number of linearly independent binary messages exchanged by the sensors. We first consider networks with one defective sensor and determine the minimal number of linearly independent messages needed for its detection with high probability. We then extend our study to the multiple defective sensors detection by modifying appropriately the message exchange protocol and the decoding procedure. We show that, for small and medium sized networks, the number of messages required for successful detection is actually smaller than the minimal number computed theoretically. Finally, simulations demonstrate that the proposed method outperforms methods based on random walks in terms of both detection performance and convergence rate.

Scp160p is required for translational efficiency of codon-optimized mRNAs in yeast

The budding yeast multi-K homology domain RNA-binding protein Scp160p binds to > 1000 messenger RNAs (mRNAs) and polyribosomes, and its mammalian homolog vigilin binds transfer RNAs (tRNAs) and translation elongation factor EF1alpha. Despite its implication in translation, studies on Scp160p's molecular function are lacking to date. We applied translational profiling approaches and demonstrate that the association of a specific subset of mRNAs with ribosomes or heavy polysomes depends on Scp160p. Interaction of Scp160p with these mRNAs requires the conserved K homology domains 13 and 14. Transfer RNA pairing index analysis of Scp160p target mRNAs indicates a high degree of consecutive use of iso-decoding codons. As shown for one target mRNA encoding the glycoprotein Pry3p, Scp160p depletion results in translational downregulation but increased association with polysomes, suggesting that it is required for efficient translation elongation. Depletion of Scp160p also decreased the relative abundance of ribosome-associated tRNAs whose codons show low potential for autocorrelation on mRNAs. Conversely, tRNAs with highly autocorrelated codons in mRNAs are less impaired. Our data indicate that Scp160p might increase the efficiency of tRNA recharge, or prevent diffusion of discharged tRNAs, both of which were also proposed to be the likely basis for the translational fitness effect of tRNA pairing.

Distributed Rate Allocation in Inter-Session Network Coding

In this work, we propose a distributed rate allocation algorithm that minimizes the average decoding delay for multimedia clients in inter-session network coding systems. We consider a scenario where the users are organized in a mesh network and each user requests the content of one of the available sources. We propose a novel distributed algorithm where network users determine the coding operations and the packet rates to be requested from the parent nodes, such that the decoding delay is minimized for all clients. A rate allocation problem is solved by every user, which seeks the rates that minimize the average decoding delay for its children and for itself. Since this optimization problem is a priori non-convex, we introduce the concept of equivalent packet flows, which permits to estimate the expected number of packets that every user needs to collect for decoding. We then decompose our original rate allocation problem into a set of convex subproblems, which are eventually combined to obtain an effective approximate solution to the delay minimization problem. The results demonstrate that the proposed scheme eliminates the bottlenecks and reduces the decoding delay experienced by users with limited bandwidth resources. We validate the performance of our distributed rate allocation algorithm in different video streaming scenarios using the NS-3 network simulator. We show that our system is able to take benefit of inter-session network coding for simultaneous delivery of video sessions in networks with path diversity.

When small non-coding RNAs meet the ribosome: Tuning the translational machinery

The functions of ribosomes in translation are complex and involve different types of activities critical for decoding the genetic code, linkage of amino acids via amide bonds to form polypeptide chains, as well as the release and proper targeting of the synthesized protein. Non-protein-coding RNAs (ncRNAs) have been recognized to be crucial in establishing regulatory networks.1 However all of the recently discovered ncRNAs involved in translation regulation target the mRNA rather than the ribosome. The main goal of this project is to identify potential novel ncRNAs that directly bind and possibly regulate the ribosome during protein biosynthesis. To address this question we applied various stress conditions to the archaeal model organism Haloferax volcanii and deep-sequenced the ribosome-associated small ncRNA interactome. In total we identified 6.250 ncRNA candidates. Significantly, we observed the emersed presence of tRNA-derived fragments (tRFs). These tRFs have been identified in all domains of life and represent a growing, yet functionally poorly understood, class of ncRNAs. Here we present evidence that tRFs from H. volcanii directly bind to ribosomes. In the presented genomic screen of the ribosome-associated RNome a 26 residue long fragment originating from the 5’ part of valine tRNA was by far the most abundant tRF. The Val-tRF is processed in a stress- dependent manner and was found to primarily target the small ribosomal subunit in vitro and in vivo. As a consequence of ribosome binding, Val-tRF reduces protein synthesis by interfering with peptidyl transferase activity. Therefore this tRF functions as ribosome-bound small ncRNA capable of regulating gene expression in H. volcanii under environmental stress conditions probably by fine-tuning the rate of protein production.2 Currently we are investigating the binding site of this tRF on the 30S subunit in more detail.

Impacts of a word-picture training on reading in youth with mixed intellectual disabilities. A waiting-list control group comparison

Individuals with intellectual disabilities (ID) often struggle with learning how to read. Reading difficulties seem to be the most common secondary condition of ID. Only one in five children with mild or moderate ID achieves even minimal literacy skills. However, literacy education for children and adolescents with ID has been largely overlooked by researchers and educators. While there is little research on reading of children with ID, many training studies have been conducted with other populations with reading difficulties. The most common approach of acquiring literacy skills consists of sophisticated programs that train phonological skills and auditory perception. Only few studies investigated the influence of implicit learning on literacy skills. Implicit learning processes seem to be largely independent of age and IQ. Children are sensitive to the statistics of their learning environment. By frequent word reading they acquire implicit knowledge about the frequency of single letters and letter patterns in written words. Additionally, semantic connections not only improve the word understanding, but also facilitate storage of words in memory. Advances in communication technology have introduced new possibilities for remediating literacy skills. Computers can provide training material in attractive ways, for example through animations and immediate feedback .These opportunities can scaffold and support attention processes central to learning. Thus, the aim of this intervention study was to develop and implement a computer based word-picture training, which is based on statistical and semantic learning, and to examine the training effects on reading, spelling and attention in children and adolescents (9-16 years) diagnosed with mental retardation (general IQ  74). Fifty children participated in four to five weekly training sessions of 15-20 minutes over 4 weeks, and completed assessments of attention, reading, spelling, short-term memory and fluid intelligence before and after training. After a first assessment (T1), the entire sample was divided in a training group (group A) and a waiting control group (group B). After 4 weeks of training with group A, a second assessment (T2) was administered with both training groups. Afterwards, group B was trained for 4 weeks, before a last assessment (T3) was carried out in both groups. Overall, the results showed that the word-picture training led to substantial gains on word decoding and attention for both training groups. These effects were preserved six weeks later (group A). There was also a clear tendency of improvement in spelling after training for both groups, although the effect did not reach significance. These findings highlight the fact that an implicit statistical learning training in a playful way by motivating computer programs can not only promote reading development, but also attention in children with intellectual disabilities.

Religious Identity and Consumption

Consumption choices assist in solving the problem of how to convey and recognize religious identities. In the communication of an identity, individuals use the knowledge embedded in consumption norms, which restrict the range of choices to a smaller set and abbreviate the required knowledge for encoding and decoding messages. Using this knowledge as a shared framework for understanding, individuals with religious beliefs can choose consumption items that would not only strengthen their beliefs but also help them express the intensity of their commitments to these beliefs. Because individuals and societies have different beliefs, norms, commitments, and expressive needs, consumption choice can help to express these differences. Our explanation contrasts with incentive-based approaches that view religious consumption norms as solutions to free-rider problem inherent in clubs.