993 resultados para Electric activity


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The present study shows that different neural activity during mental imagery and abstract mentation can be assigned to well-defined steps of the brain's information-processing. During randomized visual presentation of single, imagery-type and abstract-type words, 27 channel event-related potential (ERP) field maps were obtained from 25 subjects (sequence-divided into a first and second group for statistics). The brain field map series showed a sequence of typical map configurations that were quasi-stable for brief time periods (microstates). The microstates were concatenated by rapid map changes. As different map configurations must result from different spatial patterns of neural activity, each microstate represents different active neural networks. Accordingly, microstates are assumed to correspond to discrete steps of information-processing. Comparing microstate topographies (using centroids) between imagery- and abstract-type words, significantly different microstates were found in both subject groups at 286–354 ms where imagery-type words were more right-lateralized than abstract-type words, and at 550–606 ms and 606–666 ms where anterior-posterior differences occurred. We conclude that language-processing consists of several, well-defined steps and that the brain-states incorporating those steps are altered by the stimuli's capacities to generate mental imagery or abstract mentation in a state-dependent manner.

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Covert brain activity related to task-free, spontaneous (i.e. unrequested), emotional evaluation of human face images was analysed in 27-channel averaged event-related potential (ERP) map series recorded from 18 healthy subjects while observing random sequences of face images without further instructions. After recording, subjects self-rated each face image on a scale from “liked” to “disliked”. These ratings were used to dichotomize the face images into the affective evaluation categories of “liked” and “disliked” for each subject and the subjects into the affective attitudes of “philanthropists” and “misanthropists” (depending on their mean rating across images). Event-related map series were averaged for “liked” and “disliked” face images and for “philanthropists” and “misanthropists”. The spatial configuration (landscape) of the electric field maps was assessed numerically by the electric gravity center, a conservative estimate of the mean location of all intracerebral, active, electric sources. Differences in electric gravity center location indicate activity of different neuronal populations. The electric gravity center locations of all event-related maps were averaged over the entire stimulus-on time (450 ms). The mean electric gravity center for disliked faces was located (significant across subjects) more to the right and somewhat more posterior than for liked faces. Similar differences were found between the mean electric gravity centers of misanthropists (more right and posterior) and philanthropists. Our neurophysiological findings are in line with neuropsychological findings, revealing visual emotional processing to depend on affective evaluation category and affective attitude, and extending the conclusions to a paradigm without directed task.

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The neurocognitive processes underlying the formation and maintenance of paranormal beliefs are important for understanding schizotypal ideation. Behavioral studies indicated that both schizotypal and paranormal ideation are based on an overreliance on the right hemisphere, whose coarse rather than focussed semantic processing may favor the emergence of 'loose' and 'uncommon' associations. To elucidate the electrophysiological basis of these behavioral observations, 35-channel resting EEG was recorded in pre-screened female strong believers and disbelievers during resting baseline. EEG data were subjected to FFT-Dipole-Approximation analysis, a reference-free frequency-domain dipole source modeling, and Regional (hemispheric) Omega Complexity analysis, a linear approach estimating the complexity of the trajectories of momentary EEG map series in state space. Compared to disbelievers, believers showed: more right-located sources of the beta2 band (18.5-21 Hz, excitatory activity); reduced interhemispheric differences in Omega complexity values; higher scores on the Magical Ideation scale; more general negative affect; and more hypnagogic-like reveries after a 4-min eyes-closed resting period. Thus, subjects differing in their declared paranormal belief displayed different active, cerebral neural populations during resting, task-free conditions. As hypothesized, believers showed relatively higher right hemispheric activation and reduced hemispheric asymmetry of functional complexity. These markers may constitute the neurophysiological basis for paranormal and schizotypal ideation.

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Objectives: Although behavioral studies have demonstrated that normative affective traits modulate the processing of facial and emotionally charged stimuli, direct electrophysiological evidence for this modulation is still lacking. Methods: Event-related potential (ERP) data associated with personal, traitlike approach- or withdrawal-related attitude (assessed post-recording and 14 months later) were investigated in 18 subjects during task-free (i.e. unrequested, spontaneous) emotional evaluation of faces. Temporal and spatial aspects of 27 channel ERP were analyzed with microstate analysis and low resolution electromagnetic tomography (LORETA), a new method to compute 3 dimensional cortical current density implemented in the Talairach brain atlas. Results: Microstate analysis showed group differences 132-196 and 196-272 ms poststimulus, with right-shifted electric gravity centers for subjects with negative affective attitude. During these (over subjects reliably identifiable) personality-modulated, face-elicited microstates, LORETA revealed activation of bilateral occipito-temporal regions, reportedly associated with facial configuration extraction processes. Negative compared to positive affective attitude showed higher activity right temporal; positive compared to negative attitude showed higher activity left temporo-parieto-occipital. Conclusions: These temporal and spatial aspects suggest that the subject groups differed in brain activity at early, automatic, stimulus-related face processing steps when structural face encoding (configuration extraction) occurs. In sum, the brain functional microstates associated with affect-related personality features modulate brain mechanisms during face processing already at early information processing stages.

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OBJECTIVE To compare EEG power spectra and LORETA-computed intracortical activity between Alzheimer's disease (AD) patients and healthy controls, and to correlate the results with cognitive performance in the AD group. METHODS Nineteen channel resting EEG was recorded in 21 mild to moderate AD patients and in 23 controls. Power spectra and intracortical LORETA tomography were computed in seven frequency bands and compared between groups. In the AD patients, the EEG results were correlated with cognitive performance (Mini Mental State Examination, MMSE). RESULTS AD patients showed increased power in EEG delta and theta frequency bands, and decreased power in alpha2, beta1, beta2 and beta3. LORETA specified that increases and decreases of power affected different cortical areas while largely sparing prefrontal cortex. Delta power correlated negatively and alpha1 power positively with the AD patients' MMSE scores; LORETA tomography localized these correlations in left temporo-parietal cortex. CONCLUSIONS The non-invasive EEG method of LORETA localized pathological cortical activity in our mild to moderate AD patients in agreement with the literature, and yielded striking correlations between EEG delta and alpha1 activity and MMSE scores in left temporo-parietal cortex. SIGNIFICANCE The present data support the hypothesis of an asymmetrical progression of the Alzheimer's disease.

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In this paper the daily temporal and spatial behavior of electric vehicles (EVs) is modelled using an activity-based (ActBM) microsimulation model for Flanders region (Belgium). Assuming that all EVs are completely charged at the beginning of the day, this mobility model is used to determine the percentage of Flemish vehicles that cannot cover their programmed daily trips and need to be recharged during the day. Assuming a variable electricity price, an optimization algorithm determines when and where EVs can be recharged at minimum cost for their owners. This optimization takes into account the individual mobility constraint for each vehicle, as they can only be charged when the car is stopped and the owner is performing an activity. From this information, the aggregated electric demand for Flanders is obtained, identifying the most overloaded areas at the critical hours. Finally it is also analyzed what activities EV owners are underway during their recharging period. From this analysis, different actions for public charging point deployment in different areas and for different activities are proposed.

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One of the main objectives of European Commission related to climate and energy is the well-known 20-20-20 targets to be achieved in 2020: Europe has to reduce greenhouse gas emissions of at least 20% below 1990 levels, 20% of EU energy consumption has to come from renewable resources and, finally, a 20% reduction in primary energy use compared with projected levels, has to be achieved by improving energy efficiency. In order to reach these objectives, it is necessary to reduce the overall emissions, mainly in transport (reducing CO2, NOx and other pollutants), and to increase the penetration of the intermittent renewable energy. A high deployment of battery electric (BEVs) and plug-in hybrid electric vehicles (PHEVs), with a low-cost source of energy storage, could help to achieve both targets. Hybrid electric vehicles (HEVs) use a combination of a conventional internal combustion engine (ICE) with one (or more) electric motor. There are different grades of hybridation from micro-hybrids with start-stop capability, mild hybrids (with kinetic energy recovery), medium hybrids (mild hybrids plus energy assist) and full hybrids (medium hybrids plus electric launch capability). These last types of vehicles use a typical battery capacity around 1-2 kWh. Plug in hybrid electric vehicles (PHEVs) use larger battery capacities to achieve limited electric-only driving range. These vehicles are charged by on-board electricity generation or either plugging into electric outlets. Typical battery capacity is around 10 kWh. Battery Electric Vehicles (BEVs) are only driven by electric power and their typical battery capacity is around 15-20 kWh. One type of PHEV, the Extended Range Electric Vehicle (EREV), operates as a BEV until its plug-in battery capacity is depleted; at which point its gasoline engine powers an electric generator to extend the vehicle's range. The charging of PHEVs (including EREVs) and BEVs will have different impacts to the electric grid, depending on the number of vehicles and the start time for charging. Initially, the lecture will start analyzing the electrical power requirements for charging PHEVs-BEVs in Flanders region (Belgium) under different charging scenarios. Secondly and based on an activity-based microsimulation mobility model, an efficient method to reduce this impact will be presented.

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Oscillating electric fields can be rectified by proteins in cell membranes to give rise to a dc transport of a substance across the membrane or a net conversion of a substrate to a product. This provides a basis for signal averaging and may be important for understanding the effects of weak extremely low frequency (ELF) electric fields on cellular systems. We consider the limits imposed by thermal and "excess" biological noise on the magnitude and exposure duration of such electric field-induced membrane activity. Under certain circumstances, the excess noise leads to an increase in the signal-to-noise ratio in a manner similar to processes labeled "stochastic resonance." Numerical results indicate that it is difficult to reconcile biological effects with low field strengths.

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Joint thesis (M. E. in E. E.: Diemer; M. E.: Cooper)--Cornell University, June 1903.

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In this report, the Commission examines developments relevant to the competitiveness of the retail and wholesale markets. In the retail market, two key indicators of activity are examined: The first indicator is the rate of customer switching from bundled services to "delivery services." Customers taking delivery services are either purchasing power and energy from ARES or are purchasing power and energy from the host utility on an "unbundled" basis under the utility's delivery services tariffs. Currently, bundled power sales mainly consist of sales to customers under the Sec. 16-110 "Power Purchase Option" (PPO). The second indicator of retail activity presented in this report is the number of suppliers active in the State's nine service territories.

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Mode of access: Internet.

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This paper for the first time discusses a computational study of using magneto-electric (ME) nanoparticles to artificially stimulate the neural activity deep in the brain. The new technology provides a unique way to couple electric signals in the neural network to the magnetic dipoles in the nanoparticles with the purpose to enable a non-invasive approach. Simulations of the effect of ME nanoparticles for non-invasively stimulating the brain of a patient with Parkinson’s Disease to bring the pulsed sequences of the electric field to the levels comparable to those of healthy people show that the optimized values for the concentration of the 20-nm nanoparticles (with the magneto-electric (ME) coefficient of 100 V cm21 Oe21 in the aqueous solution) is 36106 particles/cc, and the frequency of the externally applied 300-Oe magnetic field is 80 Hz.

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Nanoparticles are often considered as efficient drug delivery vehicles for precisely dispensing the therapeutic payloads specifically to the diseased sites in the patient’s body, thereby minimizing the toxic side effects of the payloads on the healthy tissue. However, the fundamental physics that underlies the nanoparticles’ intrinsic interaction with the surrounding cells is inadequately elucidated. The ability of the nanoparticles to precisely control the release of its payloads externally (on-demand) without depending on the physiological conditions of the target sites has the potential to enable patient- and disease-specific nanomedicine, also known as Personalized NanoMedicine (PNM). In this dissertation, magneto-electric nanoparticles (MENs) were utilized for the first time to enable important functions, such as (i) field-controlled high-efficacy dissipation-free targeted drug delivery system and on-demand release at the sub-cellular level, (ii) non-invasive energy-efficient stimulation of deep brain tissue at body temperature, and (iii) a high-sensitivity contrasting agent to map the neuronal activity in the brain non-invasively. First, this dissertation specifically focuses on using MENs as energy-efficient and dissipation-free field-controlled nano-vehicle for targeted delivery and on-demand release of a anti-cancer Paclitaxel (Taxol) drug and a anti-HIV AZT 5’-triphosphate (AZTTP) drug from 30-nm MENs (CoFe2O4-BaTiO3) by applying low-energy DC and low-frequency (below 1000 Hz) AC fields to separate the functions of delivery and release, respectively. Second, this dissertation focuses on the use of MENs to non-invasively stimulate the deep brain neuronal activity via application of a low energy and low frequency external magnetic field to activate intrinsic electric dipoles at the cellular level through numerical simulations. Third, this dissertation describes the use of MENs to track the neuronal activities in the brain (non-invasively) using a magnetic resonance and a magnetic nanoparticle imaging by monitoring the changes in the magnetization of the MENs surrounding the neuronal tissue under different states. The potential therapeutic and diagnostic impact of this innovative and novel study is highly significant not only in HIV-AIDS, Cancer, Parkinson’s and Alzheimer’s disease but also in many CNS and other diseases, where the ability to remotely control targeted drug delivery/release, and diagnostics is the key.