Reduced foveal vision enhances peripheral monitoring and peripheral event detection

Introduction: Although it seems plausible that sports performance relies on high-acuity foveal vision, it could be empirically shown that myoptic blur (up to +2 diopters) does not harm performance in sport tasks that require foveal information pick-up like golf putting (Bulson, Ciuffreda, & Hung, 2008). How myoptic blur affects peripheral performance is yet unknown. Attention might be less needed for processing visual cues foveally and lead to better performance because peripheral cues are better processed as a function of reduced foveal vision, which will be tested in the current experiment. Methods: 18 sport science students with self-reported myopia volunteered as participants, all of them regularly wearing contact lenses. Exclusion criteria comprised visual correction other than myopic, correction of astigmatism and use of contact lenses out of Swiss delivery area. For each of the participants, three pairs of additional contact lenses (besides their regular lenses; used in the “plano” condition) were manufactured with an individual overcorrection to a retinal defocus of +1 to +3 diopters (referred to as “+1.00 D”, “+2.00 D”, and “+3.00 D” condition, respectively). Gaze data were acquired while participants had to perform a multiple object tracking (MOT) task that required to track 4 out of 10 moving stimuli. In addition, in 66.7 % of all trials, one of the 4 targets suddenly stopped during the motion phase for a period of 0.5 s. Stimuli moved in front of a picture of a sports hall to allow for foveal processing. Due to the directional hypotheses, the level of significance for one-tailed tests on differences was set at α = .05 and posteriori effect sizes were computed as partial eta squares (ηρ2). Results: Due to problems with the gaze-data collection, 3 participants had to be excluded from further analyses. The expectation of a centroid strategy was confirmed because gaze was closer to the centroid than the target (all p < .01). In comparison to the plano baseline, participants more often recalled all 4 targets under defocus conditions, F(1,14) = 26.13, p < .01, ηρ2 = .65. The three defocus conditions differed significantly, F(2,28) = 2.56, p = .05, ηρ2 = .16, with a higher accuracy as a function of a defocus increase and significant contrasts between conditions +1.00 D and +2.00 D (p = .03) and +1.00 D and +3.00 D (p = .03). For stop trials, significant differences could neither be found between plano baseline and defocus conditions, F(1,14) = .19, p = .67, ηρ2 = .01, nor between the three defocus conditions, F(2,28) = 1.09, p = .18, ηρ2 = .07. Participants reacted faster in “4 correct+button” trials under defocus than under plano-baseline conditions, F(1,14) = 10.77, p < .01, ηρ2 = .44. The defocus conditions differed significantly, F(2,28) = 6.16, p < .01, ηρ2 = .31, with shorter response times as a function of a defocus increase and significant contrasts between +1.00 D and +2.00 D (p = .01) and +1.00 D and +3.00 D (p < .01). Discussion: The results show that gaze behaviour in MOT is not affected to a relevant degree by a visual overcorrection up to +3 diopters. Hence, it can be taken for granted that peripheral event detection was investigated in the present study. This overcorrection, however, does not harm the capability to peripherally track objects. Moreover, if an event has to be detected peripherally, neither response accuracy nor response time is negatively affected. Findings could claim considerable relevance for all sport situations in which peripheral vision is required which now needs applied studies on this topic. References: Bulson, R. C., Ciuffreda, K. J., & Hung, G. K. (2008). The effect of retinal defocus on golf putting. Ophthalmic and Physiological Optics, 28, 334-344.

Applied Graph Theory in Computer Vision and Pattern Recognition

This book will serve as a foundation for a variety of useful applications of graph theory to computer vision, pattern recognition, and related areas. It covers a representative set of novel graph-theoretic methods for complex computer vision and pattern recognition tasks. The first part of the book presents the application of graph theory to low-level processing of digital images such as a new method for partitioning a given image into a hierarchy of homogeneous areas using graph pyramids, or a study of the relationship between graph theory and digital topology. Part II presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, including a survey of graph based methodologies for pattern recognition and computer vision, a presentation of a series of computationally efficient algorithms for testing graph isomorphism and related graph matching tasks in pattern recognition and a new graph distance measure to be used for solving graph matching problems. Finally, Part III provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks. It includes a critical review of the main graph-based and structural methods for fingerprint classification, a new method to visualize time series of graphs, and potential applications in computer network monitoring and abnormal event detection.

Energy-Efficient Management Of Heterogeneous Wireless Sensor Networks

Various applications for the purposes of event detection, localization, and monitoring can benefit from the use of wireless sensor networks (WSNs). Wireless sensor networks are generally easy to deploy, with flexible topology and can support diversity of tasks thanks to the large variety of sensors that can be attached to the wireless sensor nodes. To guarantee the efficient operation of such a heterogeneous wireless sensor networks during its lifetime an appropriate management is necessary. Typically, there are three management tasks, namely monitoring, (re) configuration, and code updating. On the one hand, status information, such as battery state and node connectivity, of both the wireless sensor network and the sensor nodes has to be monitored. And on the other hand, sensor nodes have to be (re)configured, e.g., setting the sensing interval. Most importantly, new applications have to be deployed as well as bug fixes have to be applied during the network lifetime. All management tasks have to be performed in a reliable, time- and energy-efficient manner. The ability to disseminate data from one sender to multiple receivers in a reliable, time- and energy-efficient manner is critical for the execution of the management tasks, especially for code updating. Using multicast communication in wireless sensor networks is an efficient way to handle such traffic pattern. Due to the nature of code updates a multicast protocol has to support bulky traffic and endto-end reliability. Further, the limited resources of wireless sensor nodes demand an energy-efficient operation of the multicast protocol. Current data dissemination schemes do not fulfil all of the above requirements. In order to close the gap, we designed the Sensor Node Overlay Multicast (SNOMC) protocol such that to support a reliable, time-efficient and energy-efficient dissemination of data from one sender node to multiple receivers. In contrast to other multicast transport protocols, which do not support reliability mechanisms, SNOMC supports end-to-end reliability using a NACK-based reliability mechanism. The mechanism is simple and easy to implement and can significantly reduce the number of transmissions. It is complemented by a data acknowledgement after successful reception of all data fragments by the receiver nodes. In SNOMC three different caching strategies are integrated for an efficient handling of necessary retransmissions, namely, caching on each intermediate node, caching on branching nodes, or caching only on the sender node. Moreover, an option was included to pro-actively request missing fragments. SNOMC was evaluated both in the OMNeT++ simulator and in our in-house real-world testbed and compared to a number of common data dissemination protocols, such as Flooding, MPR, TinyCubus, PSFQ, and both UDP and TCP. The results showed that SNOMC outperforms the selected protocols in terms of transmission time, number of transmitted packets, and energy-consumption. Moreover, we showed that SNOMC performs well with different underlying MAC protocols, which support different levels of reliability and energy-efficiency. Thus, SNOMC can offer a robust, high-performing solution for the efficient distribution of code updates and management information in a wireless sensor network. To address the three management tasks, in this thesis we developed the Management Architecture for Wireless Sensor Networks (MARWIS). MARWIS is specifically designed for the management of heterogeneous wireless sensor networks. A distinguished feature of its design is the use of wireless mesh nodes as backbone, which enables diverse communication platforms and offloading functionality from the sensor nodes to the mesh nodes. This hierarchical architecture allows for efficient operation of the management tasks, due to the organisation of the sensor nodes into small sub-networks each managed by a mesh node. Furthermore, we developed a intuitive -based graphical user interface, which allows non-expert users to easily perform management tasks in the network. In contrast to other management frameworks, such as Mate, MANNA, TinyCubus, or code dissemination protocols, such as Impala, Trickle, and Deluge, MARWIS offers an integrated solution monitoring, configuration and code updating of sensor nodes. Integration of SNOMC into MARWIS further increases performance efficiency of the management tasks. To our knowledge, our approach is the first one, which offers a combination of a management architecture with an efficient overlay multicast transport protocol. This combination of SNOMC and MARWIS supports reliably, time- and energy-efficient operation of a heterogeneous wireless sensor network.

Influence of polyvascular disease on cardiovascular event rates. Insights from the REACH Registry

Cardiovascular event rates have been shown to increase substantially with the number of symptomatic disease locations. We sought to assess the risk profile, management and subsequent event rates of polyvascular disease patients. Consecutive outpatients were assessed for atherosclerotic risk factors and medications in the REACH Registry. A total of 19,117 symptomatic patients in Europe completed a 2-year follow-up: 77.2% with single arterial bed disease (coronary artery or cerebrovascular or peripheral arterial disease) and 22.8% with polyvascular disease (>/= 1 disease location). Polyvascular disease patients were older (68.5 +/- 9.4 vs 66.3 +/- 9.9 years, p < 0.0001), more often current or former smokers (64.9% vs 58.7%, p < 0.0001), and more often suffered from hypertension (59.5% vs 46.6%, p < 0.0001) and diabetes (34.5% vs 25.9%, p < 0.0001) than single arterial bed disease patients. Despite more intense medical therapy, risk factors (smoking, hypertension, low fasting glucose, and low fasting total cholesterol) were less often controlled in polyvascular disease patients. This was associated with substantially more events over 2 years compared with single arterial bed disease patients (cMACCE [cardiovascular death/non-fatal stroke/non-fatal MI] odds ratio, 1.63 [95% CI, 1.45-1.83], p < 0.0001). In conclusion, polyvascular disease patients have more cardiovascular risk factors, and the prognosis for these patients is significantly worse than for patients with single arterial bed disease. This suggests a need to improve detection and consequent medical treatment of polyvascular disease.

Modulation of NF-kappaB activation in Theileria annulata-infected cloned cell lines is associated with detection of parasite-dependent IKK signalosomes and disruption of the actin cytoskeleton

Summary Apicomplexan parasites within the genus Theileria have the ability to induce continuous proliferation and prevent apoptosis of the infected bovine leukocyte. Protection against apoptosis involves constitutive activation of the bovine transcription factor NF-kappaB in a parasite-dependent manner. Activation of NF-kappaB is thought to involve recruitment of IKK signalosomes at the surface of the macroschizont stage of the parasite, and it has been postulated that additional host proteins with adaptor or scaffolding function may be involved in signalosome formation. In this study two clonal cell lines were identified that show marked differences in the level of activated NF-kappaB. Further characterization of these lines demonstrated that elevated levels of activated NF-kappaB correlated with increased resistance to cell death and detection of parasite-associated IKK signalosomes, supporting results of our previous studies. Evidence was also provided for the existence of host- and parasite-dependent NF-kappaB activation pathways that are influenced by the architecture of the actin cytoskeleton. Despite this influence, it appears that the primary event required for formation of the parasite-dependent IKK signalosome is likely to be an interaction between a signalosome component and a parasite-encoded surface ligand.

Improved detection of amnestic MCI by means of discriminative vector quantization of single-trial cognitive ERP responses

Cognitive event-related potentials (ERPs) are widely employed in the study of dementive disorders. The morphology of averaged response is known to be under the influence of neurodegenerative processes and exploited for diagnostic purposes. This work is built over the idea that there is additional information in the dynamics of single-trial responses. We introduce a novel way to detect mild cognitive impairment (MCI) from the recordings of auditory ERP responses. Using single trial responses from a cohort of 25 amnestic MCI patients and a group of age-matched controls, we suggest a descriptor capable of encapsulating single-trial (ST) response dynamics for the benefit of early diagnosis. A customized vector quantization (VQ) scheme is first employed to summarize the overall set of ST-responses by means of a small-sized codebook of brain waves that is semantically organized. Each ST-response is then treated as a trajectory that can be encoded as a sequence of code vectors. A subject's set of responses is consequently represented as a histogram of activated code vectors. Discriminating MCI patients from healthy controls is based on the deduced response profiles and carried out by means of a standard machine learning procedure. The novel response representation was found to improve significantly MCI detection with respect to the standard alternative representation obtained via ensemble averaging (13% in terms of sensitivity and 6% in terms of specificity). Hence, the role of cognitive ERPs as biomarker for MCI can be enhanced by adopting the delicate description of our VQ scheme.

On the comparison of VR-responses, as performance measures in prospective memory, with auditory P300 responses in MCI detection

Patients with amnestic mild cognitive impairment are at high risk for developing Alzheimer's disease. Besides episodic memory dysfunction they show deficits in accessing contextual knowledge that further specifies a general spatial navigation task or an executive function (EF) virtual action planning. There has been only one previous work with virtual reality and the use of a virtual action planning supermarket for the diagnosis of mild cognitive impairment. The authors of that study examined the feasibility and the validity of the virtual action planning supermarket (VAP-S) for the diagnosis of patients with mild cognitive impairment (MCI) and found that the VAP-S is a viable tool to assess EF deficits. In our study we employed the in-house platform of virtual action planning museum (VAP-M) and a sample of 25 MCI and 25 controls, in order to investigate deficits in spatial navigation, prospective memory and executive function. In addition, we used the morphology of late components in event-related potential (ERP) responses, as a marker for cognitive dysfunction. The related measurements were fed to a common classification scheme facilitating the direct comparison of both approaches. Our results indicate that both the VAP-M and ERP averages were able to differentiate between healthy elders and patients with amnestic mild cognitive impairment and agree with the findings of the virtual action planning supermarket (VAP-S). The sensitivity (specificity) was 100% (98%) for the VAP-M data and 87%(90%) for the ERP responses. Considering that ERPs have proven to advance the early detection and diagnosis of "presymptomatic AD", the suggested VAP-M platform appears as an appealing alternative.

Can a novel computerized cognitive screening test provide additional information for early detection of Alzheimer's disease?

BACKGROUND: Virtual reality testing of everyday activities is a novel type of computerized assessment that measures cognitive, executive, and motor performance as a screening tool for early dementia. This study used a virtual reality day-out task (VR-DOT) environment to evaluate its predictive value in patients with mild cognitive impairment (MCI). METHODS: One hundred thirty-four patients with MCI were selected and compared with 75 healthy control subjects. Participants received an initial assessment that included VR-DOT, a neuropsychological evaluation, magnetic resonance imaging (MRI) scan, and event-related potentials (ERPs). After 12 months, participants were assessed again with MRI, ERP, VR-DOT, and neuropsychological tests. RESULTS: At the end of the study, we differentiated two subgroups of patients with MCI according to their clinical evolution from baseline to follow-up: 56 MCI progressors and 78 MCI nonprogressors. VR-DOT performance profiles correlated strongly with existing predictive biomarkers, especially the ERP and MRI biomarkers of cortical thickness. CONCLUSIONS: Compared with ERP, MRI, or neuropsychological tests alone, the VR-DOT could provide additional predictive information in a low-cost, computerized, and noninvasive way.

Extraversion and short-term memory for chromatic stimuli: an event-related potential analysis.

The present study investigated extraversion-related individual differences in visual short-term memory (VSTM) functioning. Event related potentials were recorded from 50 introverts and 50 extraverts while they performed a VSTM task based on a color-change detection paradigm with three different set sizes. Although introverts and extraverts showed almost identical hit rates and reaction times, introverts displayed larger N1 amplitudes than extraverts independent of color change or set size. Extraverts also showed larger P3 amplitudes compared to introverts when there was a color change, whereas no extraversion-related difference in P3 amplitude was found in the no-change condition. Our findings provided the first experimental evidence that introverts' greater reactivity to punctuate physical stimulation, as indicated by larger N1 amplitude, also holds for complex visual stimulus patterns. Furthermore, P3 amplitude in the change condition was larger for extraverts than introverts suggesting higher sensitivity to context change. Finally, there were no extraversion-related differences in P3 amplitude dependent on set size. This latter finding does not support the resource allocation explanation as a source of differences between introverts and extraverts.