Sub-cortical sources of the somatosensory pathway are hypoactive in migraine interictally:a Functional Source Separation analysis

Background: Recent morpho-functional evidence pointed out that abnormalities in the thalamus could play a major role in the expression of migraine neurophysiological and clinical correlates. Whether this phenomenon is primary or secondary to its functional disconnection from the brainstem remains to be determined. We used a Functional Source Separation algorithm of EEG signal to extract the activity of the different neuronal pools recruited at different latencies along the somatosensory pathway in interictal migraine without aura (MO) patients. Methods: Twenty MO patients and 20 healthy volunteers (HV) underwent EEG recording. Four ad-hoc functional constraints, two sub-cortical (FS14 at brainstem and FS16 at thalamic level) and two cortical (FS20 radial and FS22 tangential parietal sources), were used to extract the activity of successive stages of somatosensory information processing in response to the separate left and right median nerve electric stimulation. A band-pass digital filter (450-750 Hz) was applied offline in order to extract high-frequency oscillatory (HFO) activity from the broadband EEG signal. Results: In both stimulated sides, significant reduced sub-cortical brainstem (FS14) and thalamic (FS16) HFO activations characterized MO patients when compared with HV. No difference emerged in the two cortical HFO activations between the two groups. Conclusions: Present results are the first neurophysiological evidence supporting the hypothesis that a functional disconnection of the thalamus from the subcortical monoaminergic system may underline the interictal cortical abnormal information processing in migraine. Further studies are needed to investigate the precise directional connectivity across the entire primary subcortical and cortical somatosensory pathway in interictal MO. Written informed consent to publication was obtained from the patient(s).

The effect of nutritional supplementation on the multifocal electroretinogram in healthy eyes

BACKGROUND: Previous studies have demonstrated an increase in macular pigment optical density (MPOD) with lutein (L)-based supplementation in healthy eyes. However, not all studies have assessed whether this increase in MPOD is associated with changes to other measures of retinal function such as the multifocal ERG (mfERG). Some studies also fail to report dietary levels of L and zeaxanthin (Z). Because of the associations between increased levels of L and Z, and reduced risk of AMD, this study was designed to assess the effects of L-based supplementation on mfERG amplitudes and latencies in healthy eyes. METHODS: Multifocal ERG amplitudes, visual acuity, contrast sensitivity, MPOD and dietary levels of L and Z were assessed in this longitudinal, randomized clinical trial. Fifty-two healthy eyes from 52 participants were randomly allocated to receive a L-based supplement (treated group), or no supplement (non-treated group). RESULTS: There were 25 subjects aged 18-77 (mean age ± SD; 48 ± 17) in the treated group and 27 subjects aged 21-69 (mean age ± SD; 43 ± 16) in the non-treated group. All participants attended for three visits: visit one at baseline, visit two at 20 weeks and visit three at 40 weeks. A statistically significant increase in MPOD (F = 17.0, p ≤ 0.001) and shortening of mfERG ring 2 P1 latency (F = 3.69, p = 0.04) was seen in the treated group. CONCLUSIONS: Although the results were not clinically significant, the reported trend for improvement in MPOD and mfERG outcomes warrants further investigation.

Deconvolution of magnetic acoustic change complex (mACC)

Objective: The aim of this study was to design a novel experimental approach to investigate the morphological characteristics of auditory cortical responses elicited by rapidly changing synthesized speech sounds. Methods: Six sound-evoked magnetoencephalographic (MEG) responses were measured to a synthesized train of speech sounds using the vowels /e/ and /u/ in 17 normal hearing young adults. Responses were measured to: (i) the onset of the speech train, (ii) an F0 increment; (iii) an F0 decrement; (iv) an F2 decrement; (v) an F2 increment; and (vi) the offset of the speech train using short (jittered around 135. ms) and long (1500. ms) stimulus onset asynchronies (SOAs). The least squares (LS) deconvolution technique was used to disentangle the overlapping MEG responses in the short SOA condition only. Results: Comparison between the morphology of the recovered cortical responses in the short and long SOAs conditions showed high similarity, suggesting that the LS deconvolution technique was successful in disentangling the MEG waveforms. Waveform latencies and amplitudes were different for the two SOAs conditions and were influenced by the spectro-temporal properties of the sound sequence. The magnetic acoustic change complex (mACC) for the short SOA condition showed significantly lower amplitudes and shorter latencies compared to the long SOA condition. The F0 transition showed a larger reduction in amplitude from long to short SOA compared to the F2 transition. Lateralization of the cortical responses were observed under some stimulus conditions and appeared to be associated with the spectro-temporal properties of the acoustic stimulus. Conclusions: The LS deconvolution technique provides a new tool to study the properties of the auditory cortical response to rapidly changing sound stimuli. The presence of the cortical auditory evoked responses for rapid transition of synthesized speech stimuli suggests that the temporal code is preserved at the level of the auditory cortex. Further, the reduced amplitudes and shorter latencies might reflect intrinsic properties of the cortical neurons to rapidly presented sounds. Significance: This is the first demonstration of the separation of overlapping cortical responses to rapidly changing speech sounds and offers a potential new biomarker of discrimination of rapid transition of sound.

Improving storage performance through layout optimizations

Disk drives are the bottleneck in the processing of large amounts of data used in almost all common applications. File systems attempt to reduce this by storing data sequentially on the disk drives, thereby reducing the access latencies. Although this strategy is useful when data is retrieved sequentially, the access patterns in real world workloads is not necessarily sequential and this mismatch results in storage I/O performance degradation. This thesis demonstrates that one way to improve the storage performance is to reorganize data on disk drives in the same way in which it is mostly accessed. We identify two classes of accesses: static, where access patterns do not change over the lifetime of the data and dynamic, where access patterns frequently change over short durations of time, and propose, implement and evaluate layout strategies for each of these. Our strategies are implemented in a way that they can be seamlessly integrated or removed from the system as desired. We evaluate our layout strategies for static policies using tree-structured XML data where accesses to the storage device are mostly of two kinds—parent-to-child or child-to-sibling. Our results show that for a specific class of deep-focused queries, the existing file system layout policy performs better by 5–54X. For the non-deep-focused queries, our native layout mechanism shows an improvement of 3–127X. To improve performance of the dynamic access patterns, we implement a self-optimizing storage system that performs rearranges popular block accesses on a dedicated partition based on the observed workload characteristics. Our evaluation shows an improvement of over 80% in the disk busy times over a range of workloads. These results show that applying the knowledge of data access patterns for allocation decisions can substantially improve the I/O performance.

Optimizing storage and memory systems for energy and performance

Electrical energy is an essential resource for the modern world. Unfortunately, its price has almost doubled in the last decade. Furthermore, energy production is also currently one of the primary sources of pollution. These concerns are becoming more important in data-centers. As more computational power is required to serve hundreds of millions of users, bigger data-centers are becoming necessary. This results in higher electrical energy consumption. Of all the energy used in data-centers, including power distribution units, lights, and cooling, computer hardware consumes as much as 80%. Consequently, there is opportunity to make data-centers more energy efficient by designing systems with lower energy footprint. Consuming less energy is critical not only in data-centers. It is also important in mobile devices where battery-based energy is a scarce resource. Reducing the energy consumption of these devices will allow them to last longer and re-charge less frequently. Saving energy in computer systems is a challenging problem. Improving a system's energy efficiency usually comes at the cost of compromises in other areas such as performance or reliability. In the case of secondary storage, for example, spinning-down the disks to save energy can incur high latencies if they are accessed while in this state. The challenge is to be able to increase the energy efficiency while keeping the system as reliable and responsive as before. This thesis tackles the problem of improving energy efficiency in existing systems while reducing the impact on performance. First, we propose a new technique to achieve fine grained energy proportionality in multi-disk systems; Second, we design and implement an energy-efficient cache system using flash memory that increases disk idleness to save energy; Finally, we identify and explore solutions for the page fetch-before-update problem in caching systems that can: (a) control better I/O traffic to secondary storage and (b) provide critical performance improvement for energy efficient systems.

Improving Storage Performance Through Layout Optimizations

Disk drives are the bottleneck in the processing of large amounts of data used in almost all common applications. File systems attempt to reduce this by storing data sequentially on the disk drives, thereby reducing the access latencies. Although this strategy is useful when data is retrieved sequentially, the access patterns in real world workloads is not necessarily sequential and this mismatch results in storage I/O performance degradation. This thesis demonstrates that one way to improve the storage performance is to reorganize data on disk drives in the same way in which it is mostly accessed. We identify two classes of accesses: static, where access patterns do not change over the lifetime of the data and dynamic, where access patterns frequently change over short durations of time, and propose, implement and evaluate layout strategies for each of these. Our strategies are implemented in a way that they can be seamlessly integrated or removed from the system as desired. We evaluate our layout strategies for static policies using tree-structured XML data where accesses to the storage device are mostly of two kinds - parent-tochild or child-to-sibling. Our results show that for a specific class of deep-focused queries, the existing file system layout policy performs better by 5-54X. For the non-deep-focused queries, our native layout mechanism shows an improvement of 3-127X. To improve performance of the dynamic access patterns, we implement a self-optimizing storage system that performs rearranges popular block accesses on a dedicated partition based on the observed workload characteristics. Our evaluation shows an improvement of over 80% in the disk busy times over a range of workloads. These results show that applying the knowledge of data access patterns for allocation decisions can substantially improve the I/O performance.

Fitting model-based psychometric functions to simultaneity and temporal-order judgment data: MATLAB and R routines

Research on temporal-order perception uses temporal-order judgment (TOJ) tasks or synchrony judgment (SJ) tasks in their binary SJ2 or ternary SJ3 variants. In all cases, two stimuli are presented with some temporal delay, and observers judge the order of presentation. Arbitrary psychometric functions are typically fitted to obtain performance measures such as sensitivity or the point of subjective simultaneity, but the parameters of these functions are uninterpretable. We describe routines in MATLAB and R that fit model-based functions whose parameters are interpretable in terms of the processes underlying temporal-order and simultaneity judgments and responses. These functions arise from an independent-channels model assuming arrival latencies with exponential distributions and a trichotomous decision space. Different routines fit data separately for SJ2, SJ3, and TOJ tasks, jointly for any two tasks, or also jointly for the three tasks (for common cases in which two or even the three tasks were used with the same stimuli and participants). Additional routines provide bootstrap p-values and confidence intervals for estimated parameters. A further routine is included that obtains performance measures from the fitted functions. An R package for Windows and source code of the MATLAB and R routines are available as Supplementary Files.

Hand somatosensory sub-cortical sources arehypoactive in migraine interictally: a functionalsource separation analysis

Background: Recent morpho-functional evidences pointed out that abnormalities in the thalamus could play a major role in the expression of migraine neurophysiological and clinical correlates. Whether this phenomenon is primary or secondary to its functional disconnection from the brain stem remains to be determined.Aim: We used a Functional Source Separation algorithmof EEG signal to extract the activity of the different neuronal pools recruited at different latencies along the somatosensory pathway in interictal migraine without aura(MO) patients. Method: Twenty MO patients and 20 healthy volunteers(HV) underwent EEG recording. Four ad-hoc functional constraints, two sub-cortical (FS14 at brain stem andFS16 at thalamic level) and two cortical (FS20 radial andFS22 tangential parietal sources), were used to extract the activity of successive stages of somatosensory information processing in response to the separate left and right median nerve electric stimulation. A band-pass digital filter (450–750 Hz) was applied offline in order to extract high-frequency oscillatory (HFO) activity from the broadband EEG signal. Results: In both stimulated sides, significant reduced subcortical brain stem (FS14) and thalamic (FS16) HFO activations characterized MO patients when compared with HV. No difference emerged in the two cortical HFO activations between two groups. Conclusion: Present results are the first neurophysiological evidence supporting the hypothesis that a functional disconnection of the thalamus from the subcortical monoaminergicsystem may underline the interictal cortical abnormal information processing in migraine. Further studiesare needed to investigate the precise directional connectivity across the entire primary subcortical and cortical somatosensory pathway in interictal MO.

Rôle de DSCAM dans le développement normal du cortex moteur et de la voie corticospinale

DSCAM est exprimé dans le cortex lors du développement et sa mutation altère l’arborisation dendritique des neurones pyramidaux du cortex moteur. Considérant que les souris DSCAM2J possèdent des problèmes posturaux et locomoteurs, nous émettons l’hypothèse que DSCAM est impliqué dans le fonctionnement normal du cortex moteur et de la voie corticospinale. Comparées aux souris contrôles, les souris DSCAM2J vont présenter des problèmes moteurs à basse vitesse et enjamber un obstacle presque normalement à vitesse intermédiaire. Le traçage antérograde de la voie corticospinale révèle un patron d’innervation normal dans le tronc cérébrale et la moelle épinière. Des microstimulations intracorticale du cortex moteur évoque des réponses électromyographiques dans les membres à un seuil et une latence plus élevé. Par contre, une stimulation de la voie corticospinale dans la médulla évoque des réponses électromyographies à un seuil et une latence similaire entre les deux groupes, suggérant une réduction de l’excitabilité du cortex moteur.

Real-time analytics on large dynamic graphs

In today's fast-paced and interconnected digital world, the data generated by an increasing number of applications is being modeled as dynamic graphs. The graph structure encodes relationships among data items, while the structural changes to the graphs as well as the continuous stream of information produced by the entities in these graphs make them dynamic in nature. Examples include social networks where users post status updates, images, videos, etc.; phone call networks where nodes may send text messages or place phone calls; road traffic networks where the traffic behavior of the road segments changes constantly, and so on. There is a tremendous value in storing, managing, and analyzing such dynamic graphs and deriving meaningful insights in real-time. However, a majority of the work in graph analytics assumes a static setting, and there is a lack of systematic study of the various dynamic scenarios, the complexity they impose on the analysis tasks, and the challenges in building efficient systems that can support such tasks at a large scale. In this dissertation, I design a unified streaming graph data management framework, and develop prototype systems to support increasingly complex tasks on dynamic graphs. In the first part, I focus on the management and querying of distributed graph data. I develop a hybrid replication policy that monitors the read-write frequencies of the nodes to decide dynamically what data to replicate, and whether to do eager or lazy replication in order to minimize network communication and support low-latency querying. In the second part, I study parallel execution of continuous neighborhood-driven aggregates, where each node aggregates the information generated in its neighborhoods. I build my system around the notion of an aggregation overlay graph, a pre-compiled data structure that enables sharing of partial aggregates across different queries, and also allows partial pre-computation of the aggregates to minimize the query latencies and increase throughput. Finally, I extend the framework to support continuous detection and analysis of activity-based subgraphs, where subgraphs could be specified using both graph structure as well as activity conditions on the nodes. The query specification tasks in my system are expressed using a set of active structural primitives, which allows the query evaluator to use a set of novel optimization techniques, thereby achieving high throughput. Overall, in this dissertation, I define and investigate a set of novel tasks on dynamic graphs, design scalable optimization techniques, build prototype systems, and show the effectiveness of the proposed techniques through extensive evaluation using large-scale real and synthetic datasets.

Is Experts' Knowledge Modular?

This paper explores, both with empirical data and with computer simulations, the extent to which modularity characterises experts' knowledge. We discuss a replication of Chase and Simon's (1973) classic method of identifying 'chunks', i.e., perceptual patterns stored in memory and used as units. This method uses data about the placement of pairs of items in a memory task and consists of comparing latencies between these items and the number and type of relations they share. We then compare the human data with simulations carried out with CHREST, a computer model of perception and memory. We show that the model, based upon the acquisition of a large number of chunks, accounts for the human data well. This is taken as evidence that human knowledge is organised in a modular fashion.

Low spatial frequency filtering modulates early brain processing of affective complex pictures

Recent research on affective processing has suggested that low spatial frequency information of fearful faces provide rapid emotional cues to the amygdala, whereas high spatial frequencies convey fine-grained information to the fusiform gyrus, regardless of emotional expression. In the present experiment, we examined the effects of low (LSF, <15 cycles/image width) and high spatial frequency filtering (HSF, >25 cycles/image width) on brain processing of complex pictures depicting pleasant, unpleasant, and neutral scenes. Event-related potentials (ERP), percentage of recognized stimuli and response times were recorded in 19 healthy volunteers. Behavioral results indicated faster reaction times in response to unpleasant LSF than to unpleasant HSF pictures. Unpleasant LSF pictures and pleasant unfiltered pictures also elicited significant enhancements of P1 amplitudes at occipital electrodes as compared to neutral LSF and unfiltered pictures, respectively; whereas no significant effects of affective modulation were found for HSF pictures. Moreover, mean ERP amplitudes in the time between 200 and 500ms post-stimulus were significantly greater for affective (pleasant and unpleasant) than for neutral unfiltered pictures; whereas no significant affective modulation was found for HSF or LSF pictures at those latencies. The fact that affective LSF pictures elicited an enhancement of brain responses at early, but not at later latencies, suggests the existence of a rapid and preattentive neural mechanism for the processing of motivationally relevant stimuli, which could be driven by LSF cues. Our findings confirm thus previous results showing differences on brain processing of affective LSF and HSF faces, and extend these results to more complex and social affective pictures.

Cyber foraging for green computing, improving performance and prolonging battery life of mobile devices

The increasing dependency of everyday life on mobile devices also increases the number and complexity of computing tasks to be supported by these devices. However, the inherent requirement of mobility restricts them from being resources rich both in terms of energy (battery capacity) and other computing resources such as processing capacity, memory and other resources. This thesis looks into cyber foraging technique of offloading computing tasks. Various experiments on android mobile devices are carried out to evaluate offloading benefits in terms of sustainability advantage, prolonging battery life and augmenting the performance of mobile devices. This thesis considers two scenarios of cyber foraging namely opportunistic offloading and competitive offloading. These results show that the offloading scenarios are important for both green computing and resource augmentation of mobile devices. A significant advantage in battery life gain and performance enhancement is obtained. Moreover, cyber foraging is proved to be efficient in minimizing energy consumption per computing tasks. The work is based on scavenger cyber foraging system. In addition, the work can be used as a basis for studying cyber foraging and other similar approaches such as mobile cloud/edge computing for internet of things devices and improving the user experiences of applications by minimizing latencies through the use of potential nearby surrogates.

Raciocínio contrafactual e modelos mentais

A ideia central deste estudo é de que «... raciocinar sobre factos e raciocinar sobre possibilidades e impossibilidades, baseia-se nos mesmos tipos de representações mentais e processos cognitivos» (Byrne, 1997, p. 107). Quer dizer que as pessoas raciocinam através da construção e revisão de modelos mentais (e.g., Johnson-Laird, Byrne, 1991). As condicionais contrafactuais requerem que os raciocinadores tenham em mente não apenas o que é suposto ser verdadeiro, mas também o que é supostamente verdadeiro mas factualmente falso (Byrne, 1997, p. 117; cf. Johnson-Laird, Byrne, 1991, pp. 72- -73). E a hipótese de que a representação inicial de uma condicional contrafactual é mais explícita do que a de uma condicional factual, permite prever que as inferências Modus Tollens e Negação do Antecedente deverão ser feitas com maior frequência a partir das condicionais contrafactuais do que das factuais. Byrne e Tasso (in press) encontraram evidência para esta hipótese. No estudo que apresentamos, também procuramos replicar esses resultados encontrados por Byrne e Tasso, e acrescentamos algumas hipóteses relacionadas com as latências para compreender os dois tipos de condicionais, e para escolher a conclusão. Utilizamos condicionais neutras do tipo «Se houve um círculo, então houve um triângulo», e apresentamos aos participantes os quatro silogismos condicionais no programa SUPERLAB.

A Hardware Task-Graph Scheduler for Reconfigurable Multi-tasking Systems

Reconfigurable hardware can be used to build a multitasking system where tasks are assigned to HW resources at run-time according to the requirements of the running applications. These tasks are frequently represented as direct acyclic graphs and their execution is typically controlled by an embedded processor that schedules the graph execution. In order to improve the efficiency of the system, the scheduler can apply prefetch and reuse techniques that can greatly reduce the reconfiguration latencies. For an embedded processor all these computations represent a heavy computational load that can significantly reduce the system performance. To overcome this problem we have implemented a HW scheduler using reconfigurable resources. In addition we have implemented both prefetch and replacement techniques that obtain as good results as previous complex SW approaches, while demanding just a few clock cycles to carry out the computations. We consider that the HW cost of the system (in our experiments 3% of a Virtex-II PRO xc2vp30 FPGA) is affordable taking into account the great efficiency of the techniques applied to hide the reconfiguration latency and the negligible run-time penalty introduced by the scheduler computations.