Electrophysiological and behavioral correlates of stable automatic semantic retrieval in aging

Previous studies have shown both declining and stable semantic-memory abilities during healthy aging. There is consistent evidence that semantic processes involving controlled mechanisms weaken with age. In contrast, results of aging studies on automatic semantic retrieval are often inconsistent, probably due to methodological limitations and differences. The present study therefore examines age-related alterations in automatic semantic retrieval and memory structure with a novel combination of critical methodological factors, i.e., the selection of subjects, a well-designed paradigm, and electrophysiological methods that result in unambiguous signal markers. Healthy young and elderly participants performed lexical decisions on visually presented word/non-word pairs with a stimulus onset asynchrony (SOA) of 150 ms. Behavioral and electrophysiological data were measured, and the N400-LPC complex, an event-related potential component sensitive to lexical-semantic retrieval, was analyzed by power and topographic distribution of electrical brain activity. Both age groups exhibited semantic priming (SP) and concreteness effects in behavioral reaction time and the electrophysiological N400-LPC complex. Importantly, elderly subjects did not differ significantly from the young in their lexical decision and SP performances as well as in the N400-LPC SP effect. The only difference was an age-related delay measured in the N400-LPC microstate. This could be attributed to existing age effects in controlled functions, as further supported by the replicated age difference in word fluency. The present results add new behavioral and neurophysiological evidence to earlier findings, by showing that automatic semantic retrieval remains stable in global signal strength and topographic distribution during healthy aging.

Sex Differences in Semantic Processing: Event-Related Brain Potentials Distinguish between Lower and Higher Order Semantic Analysis during Word Reading

Behavioral studies suggest that women and men differ in the strategic elaboration of verbally encoded information especially in the absence of external task demand. However, measuring such covert processing requires other than behavioral data. The present study used event-related potentials to compare sexes in lower and higher order semantic processing during the passive reading of semantically related and unrelated word pairs. Women and men showed the same early context effect in the P1-N1 transition period. This finding indicates that the initial lexical-semantic access is similar in men and women. In contrast, sexes differed in higher order semantic processing. Women showed an earlier and longer lasting context effect in the N400 accompanied by larger signal strength in temporal networks similarly recruited by men and women. The results suggest that women spontaneously conduct a deeper semantic analysis. This leads to faster processing of related words in the active neural networks as reflected in a shorter stability of the N400 map in women. Taken together, the findings demonstrate that there is a selective sex difference in the controlled semantic analysis during passive word reading that is not reflected in different functional organization but in the depth of processing.

Multi-antenna non-line-of-sight identification techniques for target localization in mobile ad-hoc networks

Target localization has a wide range of military and civilian applications in wireless mobile networks. Examples include battle-field surveillance, emergency 911 (E911), traffc alert, habitat monitoring, resource allocation, routing, and disaster mitigation. Basic localization techniques include time-of-arrival (TOA), direction-of-arrival (DOA) and received-signal strength (RSS) estimation. Techniques that are proposed based on TOA and DOA are very sensitive to the availability of Line-of-sight (LOS) which is the direct path between the transmitter and the receiver. If LOS is not available, TOA and DOA estimation errors create a large localization error. In order to reduce NLOS localization error, NLOS identifcation, mitigation, and localization techniques have been proposed. This research investigates NLOS identifcation for multiple antennas radio systems. The techniques proposed in the literature mainly use one antenna element to enable NLOS identifcation. When a single antenna is utilized, limited features of the wireless channel can be exploited to identify NLOS situations. However, in DOA-based wireless localization systems, multiple antenna elements are available. In addition, multiple antenna technology has been adopted in many widely used wireless systems such as wireless LAN 802.11n and WiMAX 802.16e which are good candidates for localization based services. In this work, the potential of spatial channel information for high performance NLOS identifcation is investigated. Considering narrowband multiple antenna wireless systems, two xvNLOS identifcation techniques are proposed. Here, the implementation of spatial correlation of channel coeffcients across antenna elements as a metric for NLOS identifcation is proposed. In order to obtain the spatial correlation, a new multi-input multi-output (MIMO) channel model based on rough surface theory is proposed. This model can be used to compute the spatial correlation between the antenna pair separated by any distance. In addition, a new NLOS identifcation technique that exploits the statistics of phase difference across two antenna elements is proposed. This technique assumes the phases received across two antenna elements are uncorrelated. This assumption is validated based on the well-known circular and elliptic scattering models. Next, it is proved that the channel Rician K-factor is a function of the phase difference variance. Exploiting Rician K-factor, techniques to identify NLOS scenarios are proposed. Considering wideband multiple antenna wireless systems which use MIMO-orthogonal frequency division multiplexing (OFDM) signaling, space-time-frequency channel correlation is exploited to attain NLOS identifcation in time-varying, frequency-selective and spaceselective radio channels. Novel NLOS identi?cation measures based on space, time and frequency channel correlation are proposed and their performances are evaluated. These measures represent a better NLOS identifcation performance compared to those that only use space, time or frequency.

An optimized lead system for long-term esophageal electrocardiography

Long-term electrocardiography (ECG) featuring adequate atrial and ventricular signal quality is highly desirable. Routinely used surface leads are limited in atrial signal sensitivity and recording capability impeding complete ECG delineation, i.e. in the presence of supraventricular arrhythmias. Long-term esophageal ECG might overcome these limitations but requires a dedicated lead system and recorder design. To this end, we analysed multiple-lead esophageal ECGs with respect to signal quality by describing the ECG waves as a function of the insertion level, interelectrode distance, electrode shape and amplifier's input range. The results derived from clinical data show that two bipolar esophageal leads, an atrial lead with short (15 mm) interelectrode distance and a ventricular lead with long (80 mm) interelectrode distance provide non-inferior ventricular signal strength and superior atrial signal strength compared to standard surface lead II. High atrial signal slope in particular is observed with the atrial esophageal lead. The proposed esophageal lead system in combination with an increased recorder input range of ±20 mV minimizes signal loss due to excessive electrode motion typically observed in esophageal ECGs. The design proposal might help to standardize long-term esophageal ECG registrations and facilitate novel ECG classification systems based on the independent detection of ventricular and atrial electrical activity.

SDR-based Passive Indoor Localization System for GSM

This study deals with indoor positioning using GSM radio, which has the distinct advantage of wide coverage over other wireless technologies. In particular, we focus on passive localization systems that are able to achieve high localization accuracy without any prior knowledge of the indoor environment or the tracking device radio settings. In order to overcome these challenges, newly proposed localization algorithms based on the exploitation of the received signal strength (RSS) are proposed. We explore the effects of non-line-of-sight communication links, opening and closing of doors, and human mobility on RSS measurements and localization accuracy. We have implemented the proposed algorithms on top of software defined radio systems and carried out detailed empirical indoor experiments. The performance results show that the proposed solutions are accurate with average localization errors between 2.4 and 3.2 meters.

An electrophysiological investigation of emotional change: preliminary data

Many psychotherapy researchers agree that emotional change is critical to therapeutic progress. In emotion-focused and Gestalt therapy, one technique to foster emotional change is the empty chair dialogue. Psychotherapy research has yielded ample evidence that this technique helps to alleviate longstanding interpersonal grievances (‘unfinished business’) and facilitates emotional change. Until now, little is known about the neurophysiological correlates of such emotional change. The present study thus aims at adding a further level of analysis to psychotherapy research, and may enrich knowledge about mechanisms of change. Neurophysiological correlates of emotional change were investigated using multi-channel electroencephalography. Individuals experiencing ‘unfinished business’ were guided by experienced therapists to participate in an empty chair dialogue. Event-related brain potentials were recorded before and after the intervention while participants were viewing pictures of the person central to their interpersonal grievance as well as pictures of control persons. Event related potentials are compared regarding topography and overall signal strength. Preliminary results will be discussed regarding neurophysiological mechanisms of action potentially occurring during emotional change.

Quality control for retinal OCT in multiple sclerosis: validation of the OSCAR-IB criteria.

BACKGROUND Retinal optical coherence tomography (OCT) permits quantification of retinal layer atrophy relevant to assessment of neurodegeneration in multiple sclerosis (MS). Measurement artefacts may limit the use of OCT to MS research. OBJECTIVE An expert task force convened with the aim to provide guidance on the use of validated quality control (QC) criteria for the use of OCT in MS research and clinical trials. METHODS A prospective multi-centre (n = 13) study. Peripapillary ring scan QC rating of an OCT training set (n = 50) was followed by a test set (n = 50). Inter-rater agreement was calculated using kappa statistics. Results were discussed at a round table after the assessment had taken place. RESULTS The inter-rater QC agreement was substantial (kappa = 0.7). Disagreement was found highest for judging signal strength (kappa = 0.40). Future steps to resolve these issues were discussed. CONCLUSION Substantial agreement for QC assessment was achieved with aid of the OSCAR-IB criteria. The task force has developed a website for free online training and QC certification. The criteria may prove useful for future research and trials in MS using OCT as a secondary outcome measure in a multi-centre setting.

Measurement of Higgs boson production in the diphoton decay channel in pp collisions at center-of-mass energies of 7 and 8 TeV with the ATLAS detector

A measurement of the production processes of the recently discovered Higgs boson is performed in the two-photon final state using 4.5  fb −1 of proton-proton collisions data at s √ =7  TeV and 20.3  fb −1 at s √ =8  TeV collected by the ATLAS detector at the Large Hadron Collider. The number of observed Higgs boson decays to diphotons divided by the corresponding Standard Model prediction, called the signal strength, is found to be μ=1.17±0.27 at the value of the Higgs boson mass measured by ATLAS, m H =125.4  GeV . The analysis is optimized to measure the signal strengths for individual Higgs boson production processes at this value of m H . They are found to be μ ggF =1.32±0.38 , μ VBF =0.8±0.7 , μ WH =1.0±1.6 , μ ZH =0.1 +3.7 −0.1 , and μ tt ¯ H =1.6 +2.7 −1.8 , for Higgs boson production through gluon fusion, vector-boson fusion, and in association with a W or Z boson or a top-quark pair, respectively. Compared with the previously published ATLAS analysis, the results reported here also benefit from a new energy calibration procedure for photons and the subsequent reduction of the systematic uncertainty on the diphoton mass resolution. No significant deviations from the predictions of the Standard Model are found.

Range-based Weighted-likelihood Particle Filter for RSS-based Indoor Tracking

Attractive business cases in various application fields contribute to the sustained long-term interest in indoor localization and tracking by the research community. Location tracking is generally treated as a dynamic state estimation problem, consisting of two steps: (i) location estimation through measurement, and (ii) location prediction. For the estimation step, one of the most efficient and low-cost solutions is Received Signal Strength (RSS)-based ranging. However, various challenges - unrealistic propagation model, non-line of sight (NLOS), and multipath propagation - are yet to be addressed. Particle filters are a popular choice for dealing with the inherent non-linearities in both location measurements and motion dynamics. While such filters have been successfully applied to accurate, time-based ranging measurements, dealing with the more error-prone RSS based ranging is still challenging. In this work, we address the above issues with a novel, weighted likelihood, bootstrap particle filter for tracking via RSS-based ranging. Our filter weights the individual likelihoods from different anchor nodes exponentially, according to the ranging estimation. We also employ an improved propagation model for more accurate RSS-based ranging, which we suggested in recent work. We implemented and tested our algorithm in a passive localization system with IEEE 802.15.4 signals, showing that our proposed solution largely outperforms a traditional bootstrap particle filter.

Fine-grained indoor positioning and tracking systems

Indoor positioning has attracted considerable attention for decades due to the increasing demands for location based services. In the past years, although numerous methods have been proposed for indoor positioning, it is still challenging to find a convincing solution that combines high positioning accuracy and ease of deployment. Radio-based indoor positioning has emerged as a dominant method due to its ubiquitousness, especially for WiFi. RSSI (Received Signal Strength Indicator) has been investigated in the area of indoor positioning for decades. However, it is prone to multipath propagation and hence fingerprinting has become the most commonly used method for indoor positioning using RSSI. The drawback of fingerprinting is that it requires intensive labour efforts to calibrate the radio map prior to experiments, which makes the deployment of the positioning system very time consuming. Using time information as another way for radio-based indoor positioning is challenged by time synchronization among anchor nodes and timestamp accuracy. Besides radio-based positioning methods, intensive research has been conducted to make use of inertial sensors for indoor tracking due to the fast developments of smartphones. However, these methods are normally prone to accumulative errors and might not be available for some applications, such as passive positioning. This thesis focuses on network-based indoor positioning and tracking systems, mainly for passive positioning, which does not require the participation of targets in the positioning process. To achieve high positioning accuracy, we work on some information of radio signals from physical-layer processing, such as timestamps and channel information. The contributions in this thesis can be divided into two parts: time-based positioning and channel information based positioning. First, for time-based indoor positioning (especially for narrow-band signals), we address challenges for compensating synchronization offsets among anchor nodes, designing timestamps with high resolution, and developing accurate positioning methods. Second, we work on range-based positioning methods with channel information to passively locate and track WiFi targets. Targeting less efforts for deployment, we work on range-based methods, which require much less calibration efforts than fingerprinting. By designing some novel enhanced methods for both ranging and positioning (including trilateration for stationary targets and particle filter for mobile targets), we are able to locate WiFi targets with high accuracy solely relying on radio signals and our proposed enhanced particle filter significantly outperforms the other commonly used range-based positioning algorithms, e.g., a traditional particle filter, extended Kalman filter and trilateration algorithms. In addition to using radio signals for passive positioning, we propose a second enhanced particle filter for active positioning to fuse inertial sensor and channel information to track indoor targets, which achieves higher tracking accuracy than tracking methods solely relying on either radio signals or inertial sensors.

Stable carbon and oxygen isotopes in tree rings show physiological responses of Pericopsis elata to precipitation in the Congo Basin

In equatorial regions, where tree rings are less distinct or even absent, the response of forests to high-frequency climate variability is poorly understood. We measured stable carbon and oxygen isotopes in anatomically distinct, annual growth rings of four Pericopsis elata trees from a plantation in the Congo Basin, to assess their sensitivity to recorded changes in precipitation over the last 50 y. Our results suggest that oxygen isotopes have high common signal strength (EPS = 0.74), and respond to multi-annual precipitation variability at the regional scale, with low δ18O values (28–29‰) during wetter conditions (1960–1970). Conversely, δ13C are mostly related to growth variation, which in a light-demanding species are driven by competition for light. Differences in δ13C values between fast- and slow-growing trees (c. 2‰), result in low common signal strength (EPS = 0.37) and are driven by micro-site conditions rather than by climate. This study highlights the potential for understanding the causes of growth variation in P. elata as well as past hydroclimatic changes, in a climatically complex region characterized by a bimodal distribution in precipitation.

Increased geranylgeranylated K-Ras contributes to antineoplastic effects of farnesyltransferase inhibitors.

The Ras family of small GTPases (N-, H-, and K-Ras) is a group of important signaling mediators. Ras is frequently activated in some cancers, while others maintain low level activity to achieve optimal cell growth. In cells with endogenously low levels of active Ras, increasing Ras signaling through the ERK and p38 MAPK pathways can cause growth arrest or cell death. Ras requires prenylation – the addition of a 15-carbon (farnesyl) or 20-carbon (geranylgeranyl) group – to keep the protein anchored into membranes for effective signaling. N- and K-Ras can be alternatively geranylgeranylated (GG’d) if farnesylation is inhibited but are preferentially farnesylated. Small molecule inhibitors of farnesyltransferase (FTIs) have been developed as a means to alter Ras signaling. Our initial studies with FTIs in malignant and non-malignant cells revealed FTI-induced cell cycle arrest, reduced proliferation, and increased Ras signaling. These findings led us to the hypothesis that FTI induced increased GG’d Ras. We further hypothesized that the specific effects of FTI on cell cycle and growth result from increased signal strength of GG’d Ras. Our results did show that increase in GG’d K-Ras in particular results in reduced cell viability and cell cycle arrest. Genetically engineered constructs capable of only one type of prenylation confirmed that GG’d K-Ras recapitulated the effect of FTI in 293T cells. In tumor cell lines ERK and p38 MAPK pathways were both strongly activated in response to FTI, indicating the increased activity of GG’d K-Ras results in antiproliferative signals specifically through these pathways. These results collectively indicate FTI increases active GG’d K-Ras which activates ERK and p38 MAPKs to reduced cell viability and induce cell cycle arrest in malignant cells. This is the first report that identifies increased activity of GG’d K-Ras contributes to antineoplastic effects from FTI by increasing the activity of downstream MAPKs. Our observations suggest increased GG’d K-Ras activity, rather than inhibition of farnesylated Ras, is a major source of the cytostatic and cytotoxic effects of FTI. Our data may allow for determination of which patients would benefit from FTI by excluding tumors or diseases which have strong K-Ras signaling.