MRI-based brain volumetry in chronic whiplash patients: no evidence for traumatic brain injury

INTRODUCTION: Cognitive complaints, such as poor concentration and memory deficits, are frequent after whiplash injury and play an important role in disability. The origin of these complaints is discussed controversially. Some authors postulate brain lesions as a consequence of whiplash injuries. Potential diffuse axonal injury (DAI) with subsequent atrophy of the brain and ventricular expansion is of particular interest as focal brain lesions have not been documented so far in whiplash injury. OBJECTIVE: To investigate whether traumatic brain injury can be identified using a magnetic resonance (MR)-based quantitative analysis of normalized ventricle-brain ratios (VBR) in chronic whiplash patients with subjective cognitive impairment that cannot be objectively confirmed by neuropsychological testing. MATERIALS AND METHODS: MR examination was performed in 21 patients with whiplash injury and symptom persistence for 9 months on average and in 18 matched healthy controls. Conventional MR imaging (MRI) was used to assess the volumes of grey and white matter and of ventricles. The normalized VBR was calculated. RESULTS: The values of normalized VBR did not differ in whiplash patients when compared with that in healthy controls (F = 0.216, P = 0.645). CONCLUSIONS: This study does not support loss of brain tissue following whiplash injury as measured by VBR. On this basis, traumatic brain injury with subsequent DAI does not seem to be the underlying mechanism for persistent concentration and memory deficits that are subjectively reported but not objectively verifiable as neuropsychological deficits.

Reducing main memory access latency through SDRAM address mapping techniques and access reordering mechanisms

As the performance gap between microprocessors and memory continues to increase, main memory accesses result in long latencies which become a factor limiting system performance. Previous studies show that main memory access streams contain significant localities and SDRAM devices provide parallelism through multiple banks and channels. These locality and parallelism have not been exploited thoroughly by conventional memory controllers. In this thesis, SDRAM address mapping techniques and memory access reordering mechanisms are studied and applied to memory controller design with the goal of reducing observed main memory access latency. The proposed bit-reversal address mapping attempts to distribute main memory accesses evenly in the SDRAM address space to enable bank parallelism. As memory accesses to unique banks are interleaved, the access latencies are partially hidden and therefore reduced. With the consideration of cache conflict misses, bit-reversal address mapping is able to direct potential row conflicts to different banks, further improving the performance. The proposed burst scheduling is a novel access reordering mechanism, which creates bursts by clustering accesses directed to the same rows of the same banks. Subjected to a threshold, reads are allowed to preempt writes and qualified writes are piggybacked at the end of the bursts. A sophisticated access scheduler selects accesses based on priorities and interleaves accesses to maximize the SDRAM data bus utilization. Consequentially burst scheduling reduces row conflict rate, increasing and exploiting the available row locality. Using a revised SimpleScalar and M5 simulator, both techniques are evaluated and compared with existing academic and industrial solutions. With SPEC CPU2000 benchmarks, bit-reversal reduces the execution time by 14% on average over traditional page interleaving address mapping. Burst scheduling also achieves a 15% reduction in execution time over conventional bank in order scheduling. Working constructively together, bit-reversal and burst scheduling successfully achieve a 19% speedup across simulated benchmarks.

Memory resource balancing for virtualized computing

Virtualization has become a common abstraction layer in modern data centers. By multiplexing hardware resources into multiple virtual machines (VMs) and thus enabling several operating systems to run on the same physical platform simultaneously, it can effectively reduce power consumption and building size or improve security by isolating VMs. In a virtualized system, memory resource management plays a critical role in achieving high resource utilization and performance. Insufficient memory allocation to a VM will degrade its performance dramatically. On the contrary, over-allocation causes waste of memory resources. Meanwhile, a VM’s memory demand may vary significantly. As a result, effective memory resource management calls for a dynamic memory balancer, which, ideally, can adjust memory allocation in a timely manner for each VM based on their current memory demand and thus achieve the best memory utilization and the optimal overall performance. In order to estimate the memory demand of each VM and to arbitrate possible memory resource contention, a widely proposed approach is to construct an LRU-based miss ratio curve (MRC), which provides not only the current working set size (WSS) but also the correlation between performance and the target memory allocation size. Unfortunately, the cost of constructing an MRC is nontrivial. In this dissertation, we first present a low overhead LRU-based memory demand tracking scheme, which includes three orthogonal optimizations: AVL-based LRU organization, dynamic hot set sizing and intermittent memory tracking. Our evaluation results show that, for the whole SPEC CPU 2006 benchmark suite, after applying the three optimizing techniques, the mean overhead of MRC construction is lowered from 173% to only 2%. Based on current WSS, we then predict its trend in the near future and take different strategies for different prediction results. When there is a sufficient amount of physical memory on the host, it locally balances its memory resource for the VMs. Once the local memory resource is insufficient and the memory pressure is predicted to sustain for a sufficiently long time, a relatively expensive solution, VM live migration, is used to move one or more VMs from the hot host to other host(s). Finally, for transient memory pressure, a remote cache is used to alleviate the temporary performance penalty. Our experimental results show that this design achieves 49% center-wide speedup.

Potential for hardware-based techniques for reuse distance analysis

Reuse distance analysis, the prediction of how many distinct memory addresses will be accessed between two accesses to a given address, has been established as a useful technique in profile-based compiler optimization, but the cost of collecting the memory reuse profile has been prohibitive for some applications. In this report, we propose using the hardware monitoring facilities available in existing CPUs to gather an approximate reuse distance profile. The difficulties associated with this monitoring technique are discussed, most importantly that there is no obvious link between the reuse profile produced by hardware monitoring and the actual reuse behavior. Potential applications which would be made viable by a reliable hardware-based reuse distance analysis are identified.

Visual vector inversion during memory antisaccades--a TMS study

In the memory antisaccade task, subjects are instructed to look at an imaginary point precisely at the opposite side of a peripheral visual stimulus presented short time previously. To perform this task accurately, the visual vector, i.e., the distance between a central fixation point and the peripheral stimulus, must be inverted from one visual hemifield to the other. Recent data in humans and monkeys suggest that the posterior parietal cortex (PPC) might be critically involved in the process of visual vector inversion. In the present study, we investigated the temporal dynamics of visual vector inversion in the human PPC by using transcranial magnetic stimulation (TMS). In six healthy subjects, single pulse TMS was applied over the right PPC during a memory antisaccade task at four different time intervals: 100 ms, 217 ms, 333 ms, or 450 ms after target onset. The results indicate that for rightward antisaccades, i.e., when the visual target was presented in the left screen-half, TMS had a significant effect on saccade gain when applied 100 ms after target onset, but not later. For leftward antisaccades, i.e., when the visual target was presented in the right screen-half, a significant TMS effect on gain was found for the 333 ms and 450 ms conditions, but not for the earlier ones. This double dissociation of saccade gain suggests that the initial process of vector inversion can be disrupted 100 ms after onset of the visual stimulus and that TMS interfered with motor saccade planning based on an inversed vector signal at 333 ms and 450 ms after stimulus onset.

LOCAL DIGITAL CONTROL OF POWER ELECTRONIC CONVERTERS IN A DC MICROGRID BASED ON A-PRIORI DERIVATION OF SWITCHING SURFACES

In power electronic basedmicrogrids, the computational requirements needed to implement an optimized online control strategy can be prohibitive. The work presented in this dissertation proposes a generalized method of derivation of geometric manifolds in a dc microgrid that is based on the a-priori computation of the optimal reactions and trajectories for classes of events in a dc microgrid. The proposed states are the stored energies in all the energy storage elements of the dc microgrid and power flowing into them. It is anticipated that calculating a large enough set of dissimilar transient scenarios will also span many scenarios not specifically used to develop the surface. These geometric manifolds will then be used as reference surfaces in any type of controller, such as a sliding mode hysteretic controller. The presence of switched power converters in microgrids involve different control actions for different system events. The control of the switch states of the converters is essential for steady state and transient operations. A digital memory look-up based controller that uses a hysteretic sliding mode control strategy is an effective technique to generate the proper switch states for the converters. An example dcmicrogrid with three dc-dc boost converters and resistive loads is considered for this work. The geometric manifolds are successfully generated for transient events, such as step changes in the loads and the sources. The surfaces corresponding to a specific case of step change in the loads are then used as reference surfaces in an EEPROM for experimentally validating the control strategy. The required switch states corresponding to this specific transient scenario are programmed in the EEPROM as a memory table. This controls the switching of the dc-dc boost converters and drives the system states to the reference manifold. In this work, it is shown that this strategy effectively controls the system for a transient condition such as step changes in the loads for the example case.

Transactional Memory in a Dynamic Language

Concurrency control is mostly based on locks and is therefore notoriously difficult to use. Even though some programming languages provide high-level constructs, these add complexity and potentially hard-to-detect bugs to the application. Transactional memory is an attractive mechanism that does not have the drawbacks of locks, however the underlying implementation is often difficult to integrate into an existing language. In this paper we show how we have introduced transactional semantics into Smalltalk by using the reflective facilities of the language. Our approach is based on method annotations, incremental parse tree transformations and an optimistic commit protocol. The implementation does not depend on modifications to the virtual machine and therefore can be changed at the language level. We report on a practical case study, benchmarks and further and on-going work.

The Role of Consciousness in Memory

Conscious events interact with memory systems in learning, rehearsal and retrieval (Ebbinghaus 1885/1964; Tulving 1985). Here we present hypotheses that arise from the IDA computional model (Franklin, Kelemen and McCauley 1998; Franklin 2001b) of global workspace theory (Baars 1988, 2002). Our primary tool for this exploration is a flexible cognitive cycle employed by the IDA computational model and hypothesized to be a basic element of human cognitive processing. Since cognitive cycles are hypothesized to occur five to ten times a second and include interaction between conscious contents and several of the memory systems, they provide the means for an exceptionally fine-grained analysis of various cognitive tasks. We apply this tool to the small effect size of subliminal learning compared to supraliminal learning, to process dissociation, to implicit learning, to recognition vs. recall, and to the availability heuristic in recall. The IDA model elucidates the role of consciousness in the updating of perceptual memory, transient episodic memory, and procedural memory. In most cases, memory is hypothesized to interact with conscious events for its normal functioning. The methodology of the paper is unusual in that the hypotheses and explanations presented are derived from an empirically based, but broad and qualitative computational model of human cognition.

Plasmodium berghei sporozoite challenge of vaccinated BALB/c mice leads to the induction of humoral immunity and improved function of CD8(+) memory T cells.

Protection against malaria can be achieved by induction of a strong CD8(+) T-cell response against the Plasmodium circumsporozoite protein (CSP), but most subunit vaccines suffer from insufficient memory responses. In the present study, we analyzed the impact of postimmunization sporozoite challenge on the development of long-lasting immunity. BALB/c mice were immunized by a heterologous prime/boost regimen against Plasmodium berghei CSP that induces a strong CD8(+) T-cell response and sterile protection, which is short-lived. Here, we show that protective immunity is prolonged by a sporozoite challenge after immunization. Repeated challenges induced sporozoite-specific antibodies that showed protective capacity. The numbers of CSP-specific CD8(+) T cells were not substantially enhanced by sporozoite infections; however, CSP-specific memory CD8(+) T cells of challenged mice displayed a higher cytotoxic activity than memory T cells of immunized-only mice. CD4(+) T cells contributed to protection as well; but CD8(+) memory T cells were found to be the central mediator of sterile protection. Based on these data, we suggest that prolonged protective immunity observed after immunization and infection is composed of different antiparasitic mechanisms including CD8(+) effector-memory T cells with increased cytotoxic activity as well as CD4(+) memory T cells and neutralizing antibodies.

A Routing Protocol Based on Energy and Link Quality for Internet of Things Applications

The Internet of Things (IoT) is attracting considerable attention from the universities, industries, citizens and governments for applications, such as healthcare, environmental monitoring and smart buildings. IoT enables network connectivity between smart devices at all times, everywhere, and about everything. In this context, Wireless Sensor Networks (WSNs) play an important role in increasing the ubiquity of networks with smart devices that are low-cost and easy to deploy. However, sensor nodes are restricted in terms of energy, processing and memory. Additionally, low-power radios are very sensitive to noise, interference and multipath distortions. In this context, this article proposes a routing protocol based on Routing by Energy and Link quality (REL) for IoT applications. To increase reliability and energy-efficiency, REL selects routes on the basis of a proposed end-to-end link quality estimator mechanism, residual energy and hop count. Furthermore, REL proposes an event-driven mechanism to provide load balancing and avoid the premature energy depletion of nodes/networks. Performance evaluations were carried out using simulation and testbed experiments to show the impact and benefits of REL in small and large-scale networks. The results show that REL increases the network lifetime and services availability, as well as the quality of service of IoT applications. It also provides an even distribution of scarce network resources and reduces the packet loss rate, compared with the performance of well-known protocols.

Recognition memory across the lifespan: the impact of word frequency and study-test interval on estimates of familiarity and recollection

The goal of this study was to investigate recognition memory performance across the lifespan and to determine how estimates of recollection and familiarity contribute to performance. In each of three experiments, participants from five groups from 14 up to 85 years of age (children, young adults, middle-aged adults, young-old adults, and old-old adults) were presented with high- and low-frequency words in a study phase and were tested immediately afterwards and/or after a one day retention interval. The results showed that word frequency and retention interval affected recognition memory performance as well as estimates of recollection and familiarity. Across the lifespan, the trajectory of recognition memory followed an inverse u-shape function that was neither affected by word frequency nor by retention interval. The trajectory of estimates of recollection also followed an inverse u-shape function, and was especially pronounced for low-frequency words. In contrast, estimates of familiarity did not differ across the lifespan. The results indicate that age differences in recognition memory are mainly due to differences in processes related to recollection while the contribution of familiarity-based processes seems to be age-invariant.

Prospective memory, executive functions and metacognitive control: An empirical approach to their structural interrelations in young elementary school children

Introduction Prospective memory (PM), the ability to remember to perform intended activities in the future (Kliegel & Jäger, 2007), is crucial to succeed in everyday life. PM seems to improve gradually over the childhood years (Zimmermann & Meier, 2006), but yet little is known about PM competences in young school children in general, and even less is known about factors influencing its development. Currently, a number of studies suggest that executive functions (EF) are potentially influencing processes (Ford, Driscoll, Shum & Macaulay, 2012; Mahy & Moses, 2011). Additionally, metacognitive processes (MC: monitoring and control) are assumed to be involved while optimizing one’s performance (Krebs & Roebers, 2010; 2012; Roebers, Schmid, & Roderer, 2009). Yet, the relations between PM, EF and MC remain relatively unspecified. We intend to empirically examine the structural relations between these constructs. Method A cross-sectional study including 119 2nd graders (mage = 95.03, sdage = 4.82) will be presented. Participants (n = 68 girls) completed three EF tasks (stroop, updating, shifting), a computerised event-based PM task and a MC spelling task. The latent variables PM, EF and MC that were represented by manifest variables deriving from the conducted tasks, were interrelated by structural equation modelling. Results Analyses revealed clear associations between the three cognitive constructs PM, EF and MC (rpm-EF = .45, rpm-MC = .23, ref-MC = .20). A three factor model, as opposed to one or two factor models, appeared to fit excellently to the data (chi2(17, 119) = 18.86, p = .34, remsea = .030, cfi = .990, tli = .978). Discussion The results indicate that already in young elementary school children, PM, EF and MC are empirically well distinguishable, but nevertheless substantially interrelated. PM and EF seem to share a substantial amount of variance while for MC, more unique processes may be assumed.

The human vestibular cortex revealed by coordinate-based activation likelihood estimation meta-analysis.

The vestibular system contributes to the control of posture and eye movements and is also involved in various cognitive functions including spatial navigation and memory. These functions are subtended by projections to a vestibular cortex, whose exact location in the human brain is still a matter of debate (Lopez and Blanke, 2011). The vestibular cortex can be defined as the network of all cortical areas receiving inputs from the vestibular system, including areas where vestibular signals influence the processing of other sensory (e.g. somatosensory and visual) and motor signals. Previous neuroimaging studies used caloric vestibular stimulation (CVS), galvanic vestibular stimulation (GVS), and auditory stimulation (clicks and short-tone bursts) to activate the vestibular receptors and localize the vestibular cortex. However, these three methods differ regarding the receptors stimulated (otoliths, semicircular canals) and the concurrent activation of the tactile, thermal, nociceptive and auditory systems. To evaluate the convergence between these methods and provide a statistical analysis of the localization of the human vestibular cortex, we performed an activation likelihood estimation (ALE) meta-analysis of neuroimaging studies using CVS, GVS, and auditory stimuli. We analyzed a total of 352 activation foci reported in 16 studies carried out in a total of 192 healthy participants. The results reveal that the main regions activated by CVS, GVS, or auditory stimuli were located in the Sylvian fissure, insula, retroinsular cortex, fronto-parietal operculum, superior temporal gyrus, and cingulate cortex. Conjunction analysis indicated that regions showing convergence between two stimulation methods were located in the median (short gyrus III) and posterior (long gyrus IV) insula, parietal operculum and retroinsular cortex (Ri). The only area of convergence between all three methods of stimulation was located in Ri. The data indicate that Ri, parietal operculum and posterior insula are vestibular regions where afferents converge from otoliths and semicircular canals, and may thus be involved in the processing of signals informing about body rotations, translations and tilts. Results from the meta-analysis are in agreement with electrophysiological recordings in monkeys showing main vestibular projections in the transitional zone between Ri, the insular granular field (Ig), and SII.

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.

How important is importance for prospective memory?

Forgetting to carry out an intention as planned can have serious consequences in everyday life. People sometimes even forget intentions that they consider as very important. Here, we review the literature on the impact of importance on prospective memory performance. We highlight different methods used to manipulate the importance of a prospective memory task such as providing rewards, importance relative to other ongoing activities, absolute importance, and providing social motives. Moreover, we address the relationship between importance and other factors known to affect prospective memory and ongoing task performance such as type of prospective memory task (time-, event-, or activity-based), cognitive loads, and processing overlaps. Finally, we provide a connection to motivation, we summarize the effects of task importance and we identify important venues for future research.