Search

Brain state in the time preceding the task affects motor performance at single trial level. Aim of the study was to investigate, through a single trial analysis of the Power Spectral Density (PSD) of the cortical sources of EEG rhythms, whether there are EEG markers, which can predict trial-by-trial the subject's performance as measured by the reaction time (RT). 20 healthy adult volunteers performed a specific visuomotor task while continuously recorded with a 64 electrodes EEG. For each single trial, the PSD of the cortical sources of EEG rhythms was obtained from EEG data to cortical current density time series in 12 regions of interest at Brodmann areas level. Results showed a statistically significant increase of posterior and limbic alpha 1 and of frontal beta 2 power, and a reduction of frontal and limbic delta and of temporal alpha 1 power, during triggering stimulus presentation for better performance, namely faster responses. At single trial level, correlation analyses between RTs and significant PSD, revealed positive correlations in frontal delta, temporal alpha 1, and limbic delta bands, and negative ones in frontal beta 2, parietal alpha 1, and occipital alpha 1 bands. Furthermore, the subject’s faster responses have been found as correlated with the similarity between the PSD values in parietal and occipital alpha 1. Predicting individual's performance at single trial level, might be extremely useful in the clinical context, since it could allow to launch rehabilitative therapies in the most efficient brain state, avoiding useless interventions.

At the Fermilab Tevatron proton-antiproton (pp¯) collider, high-mass electron-neutrino (eν) pairs are produced predominantly in the process pp¯→W(→eν)+X. The asymmetry of the electron and positron yield as a function of their pseudorapidity constrain the slope of the ratio of the u- to d-quark parton distributions versus the fraction of the proton momentum carried by the quarks. This paper reports on the measurement of the electron-charge asymmetry using the full data set recorded by the Collider Detector at Fermilab in 2001-2011 and corresponding to 9.1 fb-1 of integrated luminosity. The measurement significantly improves the precision of the Tevatron constraints on the parton-distribution functions of the proton. Numerical tables of the measurement are provided. © 2021 authors. Published by the American Physical Society.

BackgroundDecision scores and ethically mindful algorithms are being established to adjudicate mechanical ventilation in the context of potential resources shortage due to the current onslaught of COVID-19 cases. There is a need for a reproducible and objective method to provide quantitative information for those scores.PurposeTowards this goal, we present a retrospective study testing the ability of a deep learning algorithm at extracting features from chest x-rays (CXR) to track and predict radiological evolution.Materials and MethodsWe trained a repurposed deep learning algorithm on the CheXnet open dataset (224,316 chest X-ray images of 65,240 unique patients) to extract features that mapped to radiological labels. We collected CXRs of COVID-19-positive patients from two open-source datasets (last accessed on April 9, 2020)(Italian Society for Medical and Interventional Radiology and MILA). Data collected form 60 pairs of sequential CXRs from 40 COVID patients (mean age ± standard deviation: 56 ± 13 years; 23 men, 10 women, seven not reported) and were categorized in three categories: “Worse”, “Stable”, or “Improved” on the basis of radiological evolution ascertained from images and reports. Receiver operating characteristic analyses, Mann-Whitney tests were performed.ResultsOn patients from the CheXnet dataset, the area under ROC curves ranged from 0.71 to 0.93 for seven imaging features and one diagnosis. Deep learning features between “Worse” and “Improved” outcome categories were significantly different for three radiological signs and one diagnostic (“Consolidation”, “Lung Lesion”, “Pleural effusion” and “Pneumonia”; all P < 0.05). Features from the first CXR of each pair could correctly predict the outcome category between “Worse” and “Improved” cases with 82.7% accuracy.ConclusionCXR deep learning features show promise for classifying the disease trajectory. Once validated in studies incorporating clinical data and with larger sample sizes, this information may be considered to inform triage decisions.

Alzheimer's disease (AD) is the most common neurodegenerative disease among the elderly with a progressive decline in cognitive function significantly affecting quality of life. Both the prevalence and emotional and financial burdens of AD on patients, their families, and society are predicted to grow significantly in the near future, due to a prolongation of the lifespan. Several lines of evidence suggest that modifications of risk-enhancing life styles and initiation of pharmacological and non-pharmacological treatments in the early stage of disease, although not able to modify its course, helps to maintain personal autonomy in daily activities and significantly reduces the total costs of disease management. Moreover, many clinical trials with potentially disease-modifying drugs are devoted to prodromal stages of AD. Thus, the identification of markers of conversion from prodromal form to clinically AD may be crucial for developing strategies of early interventions. The current available markers, including volumetric magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebral spinal fluid (CSF) analysis are expensive, poorly available in community health facilities, and relatively invasive. Taking into account its low cost, widespread availability and non-invasiveness, electroencephalography (EEG) would represent a candidate for tracking the prodromal phases of cognitive decline in routine clinical settings eventually in combination with other markers. In this scenario, the present paper provides an overview of epidemiology, genetic risk factors, neuropsychological, fluid and neuroimaging biomarkers in AD and describes the potential role of EEG in AD investigation, trying in particular to point out whether advanced analysis of EEG rhythms exploring brain function has sufficient specificity/sensitivity/accuracy for the early diagnosis of AD.

The goal of this paper is to examine existing methods to study the "Human Brain Connectome" with a specific focus on the neurophysiological ones. In recent years, a new approach has been developed to evaluate the anatomical and functional organization of the human brain: the aim of this promising multimodality effort is to identify and classify neuronal networks with a number of neurobiologically meaningful and easily computable measures to create its connectome. By defining anatomical and functional connections of brain regions on the same map through an integrated approach, comprising both modern neurophysiological and neuroimaging (i.e. flow/metabolic) brain-mapping techniques, network analysis becomes a powerful tool for exploring structural-functional connectivity mechanisms and for revealing etiological relationships that link connectivity abnormalities to neuropsychiatric disorders. Following a recent IFCN-endorsed meeting, a panel of international experts was selected to produce this current state-of-art document, which covers the available knowledge on anatomical and functional connectivity, including the most commonly used structural and functional MRI, EEG, MEG and non-invasive brain stimulation techniques and measures of local and global brain connectivity.

Introduction Transcranial direct current stimulation (tDCS) is well establishedamong the non-invasive brain stimulation techniques as a method to modulate brain excitability. Polarity-dependent modulations of membrane potentials are detected after the application of anodal and cathodal stimulation, leading to changes in the electrical activity of the neurons. Objective The main aim of the present study was to test the hypothesis that tDCS can affect in a polarityspecific manner the functional coupling of the sensorimotor areas during the eyes-open resting condition as revealed by total EEG coherence (i.e., coherence across the average of all combinations of the electrode pairs placed around the stimulation electrode). Material & methods The changes in the total EEG coherence were evaluated pre-, during, and post-anodal and cathodal tDCS. Results While no differences were observed in the connectivity characteristics of the two pre-stimulation periods, a connectivity increase was observed in the alpha 2 band in the post-anodal tDCS with respect to pre-anodal and post-cathodal tDCS. Conclusions The present study suggests that a specific approach based on the analyses of the functional coupling of EEG rhythms might enhance understanding of tDCS-induced effects on cortical connectivity. Moreover, this result suggests that anodal tDCS could possibly modify cortical connectivity more effectively with respect to cathodal tDCS. Download : Download high-res image (279KB) Download : Download full-size image Download : Download high-res image (160KB) Download : Download full-size image

Introduction The cortical representation of a muscle can be significantly modified by plastic reorganization following a limb amputation. These plastic changes are not immutable and can be further modified restoring by the use of prosthesis like new bionic anthropomorphic prosthesis connected to the peripheral nervous system via bidirectional neural interfaces. Transcranial magnetic stimulation (TMS) is a non-invasive technique commonly used to assess topographical reorganization of motor brain areas. Objective The aim of this study is to evaluate the motor cortical reorganization of primary motor cortex with the TMS mapping technique in a left trans-radial amputee patient following the use of a novel prosthetic system able to provide somatosensory feed-back from the lost hand of the user. Materials and methods Cortical motor output was mapped via TMS (intensity 10% above standardized excitability motor Threshold) for each hemisphere at the beginning, after 1 month and 2 month of training with the new prosthetic system. Peripheral responses were recorded from forearm flexor and extensor carpi ulnaris muscles of both limbs. Resting and Active motor threshold were also collected during separate mapping of right and left hemispheres. Results No significant differences were found in the motor thresholds between the two hemispheres before and after implantation. Pre-surgical TMS motor maps showed a slight abnormal interhemispheric asymmetry of motor cortex topography, resulted in a smaller area of representation of muscles governing the stump compared to the area for the intact limb. Following training, post-surgical maps, showed a reduction and a partial reversal of this asymmetry because of an enlargement of the excitable area on the right hemisphere contralateral to the stump, leading towards a more symmetrical muscle representation in the two hemispheres, as in control subjects. Conclusions Our experiment provides a direct and unique evidence of brain plasticity changes occurring in the motor cortex following the use of a prosthetic system able to restore a somatosensory feedback from the missing limb after amputation. Figure options Download full-size image Download high-quality image (378 K) Download as PowerPoint slide Figure options Download full-size image Download high-quality image (399 K) Download as PowerPoint slide

Introduction Transcranial direct current stimulation (tDCS) is a non-invasive method modulating cortical excitability in a polarity-dependent way. At present, only few studies investigated the effects of tDCS on the modulation of functional connectivity between remote cortical areas. Objective In the present study we aimed to investigate the impact of bipolar tDCS on cortical networks connectivity through graph theoretical analysis. Materials & methods High-density EEG recordings were acquired before and after bipolar anodal, cathodal and sham tDCS applied over the primary motor cortex of the dominant hemisphere in 14 healthy subjects. Results Results showed that, after bipolar anodal tDCS stimulation over the dominant primary motor cortex the related brain network presented a more small-worldnessy, meaning a global tendency to be more random in its functional connections respect to prestimulus condition in both hemispheres. Conclusions Our results suggest that tDCS is able to modulate globally the cortical connectivity of the brain, modifying the underlying functional organization via complex pattern of direct and indirect cortical activations or inhibitions of the stimulated networks, which might be related to changes in synaptic efficiency of the motor network and related brain areas.

Sleep onset is characterized by specific and orchestrated patterns of frequency and topographical EEG changes. Power analyses and computational assessments of network dynamics have described an earlier synchronization of the centrofrontal areas rhythms and a spread of synchronizing signals from associative prefrontal to posterior areas. We assess how “small world” characteristics of brain networks, as reflected in EEG rhythms, are modified in the wakefulness-sleep transition comparing pre- and post-sleep onset epochs. 40 healthy subjects (20 males;age range 18–29 years) were analyzed. EEG functional connectivity was evaluated in the cortical sources’ networks during the wake-to-sleep transition by graph theory application for the evaluation of small-world characteristics. Sleep onset is characterized by a less ordered brain network (as reflected by small world higher values) in sigma band for the frontal lobes indicating stronger connectivity, and a more ordered brain network in low frequency delta and theta bands indicating disconnection on the remaining brain areas. Results depict the timing and topography of the specific mechanisms for the maintenance of functional connectivity of frontal brain regions at the sleep onset, also providing a possible explanation for the prevalence of the frontal-to-posterior information flow directionality previously observed after sleep onset.

Aim of this study was to verify whether the topological organization of human brain functional networks is different for males and females in resting state EEGs. Undirected and weighted brain networks were computed by eLORETA lagged linear connectivity in 130 subjects (59 males and 71 females) within each hemisphere and in four resting state networks (Attentional Network (AN), Frontal Network (FN), Sensorimotor Network (SN), Default Mode Network (DMN)). We found that small-world (SW) architecture in the left hemisphere Frontal network presented differences in both delta and alpha band, in particular lower values in delta and higher in alpha 2 in males respect to females while in the right hemisphere differences were found in lower values of SW in males respect to females in gamma Attentional, delta Sensorimotor and delta and gamma DMNs. Gender small-worldness differences in some of resting state networks indicated that there are specific brain differences in the EEG rhythms when the brain is in the resting-state condition. These specific regions could be considered related to the functions of behavior and cognition and should be taken into account both for research on healthy and brain diseased subjects.

Introduction Motor evoked potentials (MEPs) elicited by a train of consecutive, individual transcranial magnetic stimuli demonstrate fluctuations in amplitude with respect to time when recorded from a relaxed muscle. The influence of time-varying, instantaneous modifications of the electroencephalography (EEG) properties immediately preceding the transcranial magnetic stimulation (TMS) has rarely been explored. Objective The aim of this study was to investigate the influence of the pre-TMS motor cortex and related areas EEG profile on time variants of the MEPs amplitude. Materials & methods MRI-navigated TMS and multichannel TMS-compatible EEG devices were used. For each experimental subject, posthoc analysis of the MEPs amplitude that was based on the 50th percentile of the MEPs amplitude distribution provided two subgroups corresponding to “high” (large amplitude) and “low” (small amplitude). The pre-stimulus EEG characteristics (coherence and spectral profile) from the motor cortex and related areas were analyzed separately for the “high” and “low” MEPs and were then compared. Results On the stimulated hemisphere, EEG coupling was observed more often in the high compared to the low MEP trials. Moreover, a paradigmatic pattern in which TMS was able to lead to significantly larger MEPs was found when the EEG of the stimulated motor cortex was coupled in the beta 2 band with the ipsilateral prefrontal cortex and in the delta band with the bilateral centro-parietal-occipital cortices. Conclusions This data provide evidence for a statistically significant influence of time-varying and spatially patterned synchronization of EEG rhythms in determining cortical excitability, namely motor cortex excitability in response to TMS.

HLA-DRB4 gene is associated with Churg-Strauss syndrome (CSS), a systemic eosinophilic vasculitis with a prodromal phase characterized by severe asthma, eosinophilia, nasal polyposis, and sinusitis. Aim of this study was to evaluate if the presence of HLA-DRB4 in asthmatic patients is associated with a clinical picture resembling that of the prodromal phase of CSS. HLA-DRB1 was determined in a cohort of 159 asthmatic patients and its frequency was compared with that of 1808 blood donors. HLA-DRB4 presence/absence was correlated with clinical features, including sinusitis, nasal polyposis, eosinophils, antiasthmatic drugs, asthma severity, and pulmonary function tests. HLA-DRB4 gene was associated with severe persistent asthma before treatment (P<0.02), near fatal or severe hypoxemic asthma (P<0.01), sinusitis (P<0.01), nasal polyposis (P<0.01), number of patients with eosinophils >1000/μl: (P<0.05), need of beclomethasone >1000–2000 μg/daily (P<0.001), use of a third controller (P<0.05), and oral prednisone (P<0.02). HLA-DRB4 gene is associated in asthmatic patients with a clinical picture characterized by asthma severity, sinusitis, nasal polyposis, and eosinophilia closely resembling that of the prodromal phase of CSS and might be useful to suspect corticosteroids-masked cases of CSS.

In a previous study, we found that patients who were offered the possibility of participation in a clinical trial had unexpressed concerns and fears that prevented them from making free or fully knowledgeable choices about their trial participation. In a selected population of patients who were offered participation in a phase I trial, we prospectively investigated whether a face-to-face discussion about their unexpressed fears might lead to a more conscious decision about whether to accept/refuse participation in the trial.After the presentation of the trial, a questionnaire was administered to assess the presence of specific fears. Before the patients decided whether to participate in the trial, they discussed any fears that they had; finally, the impact of the discussion on the patients' choice to participate was evaluated.The majority (86%) of the patients thought that physicians conduct clinical trials for scientific interest, 13% felt exploited as 'guinea pigs' and 20% believed they were offered participation because they had no further hope for improvement. These existing fears were not elicited during the trial interview because the patients were themselves unaware of having them (28%) and because of fear of the doctors (3%). The possibility of discussing these fears was felt as an opportunity and made patients feel more conscious (92%) and freer (97%) when making their choice.Recognising and discussing misconceptions and fears, often unexpressed, make patients freer and more aware when facing the choice of whether or not \to participate in a phase I clinical trial.

Functional connectivity, revealed by EEG, evaluates time synchronization in anatomically distinct but functionally collaborating brain regions. Structural connection, revealed by diffusion tensor imaging (DTI), detects fractional anisotropy (FA). FA decreases in pathological aging corpus callosum (CC) and could reflect functional disconnections. We investigated correlations between structural damage of CC (MRI-DTI) and functional abnormalities of brain integration (cortical Characteristic Path Length of EEG). Resting state EEG and MRI were evaluated in 9 healthy controls-Nold, 10 Mild Cognitive Impairment – MCI, 10 mild Alzheimer Disease – AD, 11 moderate AD. Undirected and weighted brain network was built to evaluate graph Path Length weighting network edges by eLORETA lagged connectivity. Callosal FA reduction was associated to a loss of brain interhemispheric functional connectivity characterized by increased delta and decreased alpha Path Length. Global (path length as index of how efficient is the information transfer inside network) functional measure can reflect the reduction of fibers connecting the hemispheres as revealed by DTI. Functional and structural disconnections do not share the same timing (functional coming first) in the prodromal stage of disease, but in disease evolution (from healthy to dementia) it is possible to obtain statistical correlations between connectivity’s indexes.

The large majority (80%) of people with multiple sclerosis (MS) complain of fatigue, which is the most disabling symptom in half of them. While the few drugs used to treat MS fatigue are limitedly useful, it was recently observed the efficacy of a personalized neuromodulation treatment, supporting the concept that interventions modifying the sensorimotor network activity balances could be suitable non-pharmacological treatments for MS fatigue. Aim of the present study is to strengthen knowledge of the brain unbalances, which proper neuromodulations should target to compensate. We collected electroencephalographic (EEG) data in 18 people with mild MS, while they were in resting state with open eyes. To ensure a wide range of fatigue, we enrolled patients to have Higher- or Lower-Fatigue based on scores of the modified Fatigue Impact Scale (mFIS). We selected the graph theory small-world index, calculated on networks of cortical nodes estimated by eLORETA, to evaluate the characteristics of left and right frontal (Motor) and parieto-occipital-temporal (Sensory) brain networks separately. Fatigue symptoms increased together with the small-world index in the Sensory network of the left dominant hemisphere. This finding hones understanding of the targets of neuromodulation interventions, indicating the sensory network of the dominant left hemisphere as a specific target.

Several experimental studies have shown that, nevertheless motor symptoms are late events in the natural history of Alzheimer’s disease (AD), neuropathological progression in the motor cortex parallels that in other brain cortices generally considered more specific targets of the aggression. In the last years we have clearly demonstrated that motor cortex excitability is enhanced in AD since the early stages of the disease and this is probably related to its severity and progression. To further investigate, for the first time without peripheral or attentional confounding effects, the neurophysiological hallmarks of motor cortex functionality in AD we used here transcranial magnetic stimulation (TMS) combined with electroencephalography (EEG). We then demonstrated that in mild AD, despite the lack of clinical manifestations, the sensorimotor system is strongly hyper-excitable and its connectivity is deeply rearranged with the recruitment of additional neural sources, the activation of reverberant circuits and their integration in the distributed excitatory network subtending sensorimotor functions.

Phantom limb pain (PLP) is a frequent consequence of amputation and the challenge remains to find a long-lasting treatment. Recent evidence suggests that PLP is likely correlated to aberrant plastic changes in the cortex. We aimed to counteract these changes through sensory feedback generated by intraneural electrical stimulation and thereby control and alleviate pain. A 34-year-old male with a left hand/forearm amputation had four intraneural electrode arrays implanted in the median and ulnar nerves for 30 days. We developed and tested a prototype system to drive sensory feedback through intraneural electrical stimulation. Functional testing was first carried out to map the type, strength, and location of the sensations generated by electrical stimulation. We then selected specific stimulation sequences that were applied in repeated sessions. The pain perception and cortical neurophysiological maps were measured before and after these sessions. The participant experienced a decrease in the pain perception (rated from 8 to 4–5 at VAS) during and up to a few hours after the stimulation sessions. We also found a change in the somatosensory map of the right cortical hemisphere. Intraneural electrical stimulation was able to reliably generate sensory feedback, modulate cortical organization, and temporarily relieve PLP.

Objective After cerebral ischemia, disruption and subsequent reorganization of functional connections occur both locally and remote to the lesion. Recently, brain complexity has been described using the graph theory, an elegant approach which depicts important properties of complex systems by quantifying topologies of network representations. We tested whether ischemic stroke may determine changes in smallworldness of cortical networks as measured by cortical sources of EEG. Methods Graph characteristics of EEG of 30 consecutive stroke patients in acute stage (no more than 5 days after the event) were examined. Connectivity analysis was performed using eLORETA in both hemispheres. Results Network rearrangements are mainly detected in delta, theta and alpha bands. Similar findings were observed in both hemispheres regardless the side of ischemic lesion: bilaterally decreased smallworldness in the delta band; similar modification observed in the theta band, but statistically significant only in left hemisphere stroke patients. Conclusions After an acute stroke, brain cortex rearranges its network connections diffusely, in a frequency-dependent modality in order to face the new anatomical and functional condition. Modifications in distinct frequencies suggests that the network remodelling occurs with different modalities. Key message Stroke-related brain network reorganization could reflect a not negligible adaptive process.

Human actions are characterized by time-varying engagement of functional distributed networks within the brain. We investigated whether specific pre-stimulus interhemispheric connectivity, as a measure of synchronized network between the two brain hemispheres, could lead to a better performance (as revealed by reaction-time) in a simple visuomotor task. Eighteen healthy adults underwent electroencephalographic recording during a visual go/no-go task. In the go/no go task, were presented random visual stimulus (50% green or red). Subjects had to press the mouse button after the green stimuli. Interhemispheric coupling was evaluated by the spectral coherence among all the electrodes covering one hemisphere and matched with those on the other. The task-related results showed that interhemispheric connectivity decreased in delta and increased in alpha band. Furthermore, were observed positive delta and negative alpha correlations with the reaction time. The best performance is anticipated by the better functional coupling of cortical circuits involved during the processing of the sensorimotor information, occurring between the two hemispheres pending cognitive go/no-go task. The present study provides direct confirmation for a stochastic linking of cortical areas, as revealed by oscillatory synchronization of the two hemispheres in selected EEG rhythms, in determining behaviour performance in a cognitive-motor task.

It has been shown that elite pistol shooters are characterized by a power increase of wide cortical electroencephalographic (EEG) alpha (about 8-12 Hz) and beta (about 14-35 Hz) rhythms during the preparation of air pistol shots, possibly related to selective attentional and "neural efficiency" processes [Del Percio C, Babiloni C, Bertollo M, Marzano N, Iacoboni M, Infarinato F, Lizio R, Stocchi M, Robazza C, Cibelli G, Comani S, Eusebi F (2009a) Hum Brain Mapp 30(11):3527-3540; Del Percio C, Babiloni C, Marzano N, Iacoboni M, Infarinato F, Vecchio F, Lizio R, Aschieri P, Fiore A, Toran G, Gallamini M, Baratto M, Eusebi F (2009b) Brain Res Bull 79(3-4):193-200]. Here, we tested the hypothesis that such processes are associated with an enhanced functional coupling of posterior cortical regions involved in task-relevant attentional processes and visuo-motor transformations. To this aim, between-electrodes spectral coherence was computed from spatially enhanced EEG data collected during a previous study (i.e. right handed 18 elite air pistol shooters and 10 matched non-athletes; augmented 10-20 system; surface Laplacian estimation). Theta (about 4-6 Hz), low-frequency alpha (about 8-10 Hz), high-frequency alpha (about 10-12 Hz), low-frequency beta (14-22 Hz), high-frequency beta (23-35 Hz), and gamma (36-44 Hz) bands were considered. Statistical results showed that intra-hemispheric low-frequency alpha (parietal-temporal and parietal-occipital regions), high-frequency alpha (parietal-temporal and parietal-occipital regions), high-frequency beta, and gamma (parietal-temporal regions) coherence values were stable in amplitude in the elite athletes but not in the non-athletes during the preparation of pistol shots. The same applies to inter-hemispheric low-frequency alpha (parietal regions), high-frequency alpha (parietal regions), high-frequency beta and gamma coherence values. These findings suggest that under the present experimental conditions, elite athletes are characterized by the stabilization of functional coupling of preparatory EEG rhythms between "visuo-spatial" parietal area and other posterior cortical areas.

Burning fossil fuel in the North American continent contributes more to the CO2 global warming problem than in any other continent. The resulting climate changes are expected to alter food production. The overall changes in temperature, moisture, carbon dioxide, insect pests, plant pathogens, and weeds associated with global warming are projected to reduce food production in North America. However, in Africa, the projected slight rise in rainfall is encouraging, especially since Africa already suffers from severe shortages of rainfall. For all regions, a reduction in fossil fuel burning is vital. Adoption of sound ecological resource management, especially soil and water conservation and the prevention of deforestation, is important. Together, these steps will benefit agriculture, the environment, farmers, and society as a whole.

Background: The asthmatic-prodromal phase of Churg–Strauss syndrome (CSS) is usually considered allergic, but data about the involved allergens are scarce. The aim of our work was to examine the prevalence of allergy in a group of CSS patients and in two control groups of persistent asthmatic subjects selected for eosinophilia >10% [first control group patients (CGP1)] and eosinophils

The authors report on the case of a low-grade fibromyxoid sarcoma (LGFMS) with giant rosettes in a 4-year-old boy. The tumor arose in the paravertebral region and had infiltrated the vertebral canal between L2 and S1. A review of the literature indicates that this is one of the youngest patients diagnosed with a tumor of this type, and spinal involvement had never been reported with LGFMS.

Occipital sources of resting state alpha rhythms are abnormal in patients with amnesic mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Here we hypnotized whether the activity of these sources is related to neurodegeneration in occipital lobe as measured by magnetic resonance imaging (MRI). Resting-state eyes-closed EEG rhythms were recorded in 30 healthy elderly (Nold), 37 MCI, and 40 AD subjects. Neurodegeneration of the occipital lobe was indexed by weighted averages of gray matter density (GMD). EEG rhythms of interest were alpha 1 (8–10.5 Hz) and alpha 2 (10.5–13 Hz). EEG cortical sources were estimated by LORETA. Results showed a positive correlation between GMD in the occipital lobe and the magnitude of occipital alpha sources in the MCI and AD subjects. Furthermore, there was a positive correlation between the magnitude of alpha sources and the cognitive status as revealed by Mini Mental State Evaluation score all subjects. These results suggest that in amnesic MCI and AD subjects, occipital sources of resting state alpha rhythms reflect AD neurodegeneration in the occipital lobe. Cortical sources of resting state EEG rhythms in AD patients are promising for preliminary screening of elderly subjects at risk for AD.

Alzheimer’s disease (AD) patients show abnormal cortical sources of resting state EEG rhythms, especially at delta (1–4 Hz) and alpha (8–13 Hz) bands. Here we hypothesized that this abnormality is correlated to impaired structural brain connectivity. Eyes closed resting state EEG and structural MRI-DTI (diffusion tensor imaging) data were acquired in 21 AD and in 9 mild cognitive impairment (MCI) patients. LORETA and FSL were used for data analysis. Compared to MCI subjects, AD patients showed a reduction of DTI fractional anisotropy (FA) in several white matter brain bundles ( p p p