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ObjectiveTo assess the role of jejunum in insulin resistance in humans and in experimental animals.DesignTwenty-four subjects undergoing biliopancreatic diversion (BPD) or Roux-en-Y gastric bypass (RYGB) were enrolled. Insulin sensitivity was measured at baseline and at 1 week after surgery using oral glucose minimal model.We excluded the jejunum from intestinal continuity in pigs and created a jejunal loop with its vascular and nerve supply intact accessible from two cutaneous stomas, and reconnected the bowel with an end-to-end anastomosis. Glucose stable isotopes were given in the stomach or in the jejunal loop.In vitro studies using primary porcine and human hepatocytes or myoblasts tested the effects of plasma on gluconeogenesis or glucose uptake and insulin signalling.ResultsWhole-body insulin sensitivity (SI∙104: 0.54±0.12 before vs 0.82±0.11 after BPD, p=0.024 and 0.41±0.09 before vs 0.65±0.09/pM/min after RYGB, p=not significant) and Glucose Disposition Index increased only after BPD. In pigs, insulin sensitivity was significantly lower when glucose was administered in the jejunal loop than in the stomach (glucose rate of disappearance (Rd) area under the curve (AUC)/insulin AUC∙10: 1.82±0.31 vs 2.96±0.33 mmol/pM/min, p=0.0017).Metabolomics showed a similar pattern before surgery and during jejunal-loop stimulation, pointing to a higher expression of gluconeogenetic substrates, a metabolic signature of impaired insulin sensitivity.A greater hepatocyte phosphoenolpyruvate-carboxykinase and glucose-6-phosphatase gene expression was elicited with plasma from porcine jejunal loop or before surgery compared with plasma from jejunectomy in pigs or jejunal bypass in humans.Stimulation of myoblasts with plasma from porcine jejunal loop or before surgery reduced glucose uptake, Ser473-Akt phosphorylation and GLUT4 expression compared with plasma obtained during gastric glucose administration after jejunectomy in pigs or after jejunal bypass in humans.ConclusionProximal gut plays a crucial role in controlling insulin sensitivity through a distinctive metabolic signature involving hepatic gluconeogenesis and muscle insulin resistance. Bypassing the jejunum is beneficial in terms of insulin-mediated glucose disposal in obesity.Trial registration numberNCT03111953.

Metabolic surgery improves insulin resistance and is associated with the remission of type 2 diabetes, but the mechanisms involved remain unknown. We find that human jejunal mucosa secretes heat shock proteins (HSPs) in vitro, in particular HSP70 and GRP78. Circulating levels of HSP70 are higher in people resistant to insulin, compared to the healthy and normalize after duodenal–jejunal bypass. Insulin sensitivity negatively correlates with the plasma level of HSP70, while body mass index does not. A high-energy diet increases the circulating levels of HSP70 and insulin resistance. HSP70 stimulates the accumulation of lipid droplets and inhibits Ser473 phosphorylation of Akt and glucose uptake in immortalized liver cells and peripheral blood cells. Serum depleted of HSPs, as well as the serum from the insulin-resistant people subjected to a duodenal–jejunal bypass, reverse these features, identifying gut-secreted HSPs as possible causes of insulin resistance. Duodenal–jejunal bypass might reduce the secretion of HSPs either by shortening the food transit or by decreasing the fat stimulation of endocrine cells.

Generally, the training evaluation methods consist in experts supervision and qualitative check of the operator's skills improvement by asking them to perform specific tasks and by verifying the final performance. The aim of this work is to find out if it is possible to obtain quantitative information about the degree of the learning process throughout the training period by analyzing neuro-physiological signals, such as the electroencephalogram, the electrocardiogram and the electrooculogram. In fact, it is well known that such signals correlate with a variety of cognitive processes, e.g. attention, information processing, and working memory. A group of 10 subjects have been asked to train daily with the NASA multi-attribute-task-battery. During such training period the neuro-physiological, behavioral and subjective data have been collected. In particular, the neuro-physiological signals have been recorded on the first (T1), on the third (T3) and on the last training day (T5), while the behavioral and subjective data have been collected every day. Finally, all these data have been compared for a complete overview of the learning process and its relations with the neuro-physiological parameters. It has been shown how the integration of brain activity, in the theta and alpha frequency bands, with the autonomic parameters of heart rate and eyeblink rate could be used as metric for the evaluation of the learning progress, as well as the final training level reached by the subjects, in terms of request of cognitive resources.

The purpose of this study was to examine the contribution of nonesterified fatty acids (NEFA) and incretin to insulin resistance and diabetes amelioration after malabsorptive metabolic surgery that induces steatorrhea. In fact, NEFA infusion reduces glucose-stimulated insulin secretion, and high-fat diets predict diabetes development. Six healthy controls, 11 obese subjects, and 10 type 2 diabetic (T2D) subjects were studied before and 1 mo after biliopancreatic diversion (BPD). Twenty-four-hour plasma glucose, NEFA, insulin, C-peptide, glucagon-like peptide-1 (GLP-1), and gastric inhibitory polypeptide (GIP) time courses were obtained and analyzed by Granger causality and graph analyses. Insulin sensitivity and secretion were computed by the oral glucose minimal model. Before metabolic surgery, NEFA levels had the strongest influence on the other variables in both obese and T2D subjects. After surgery, GLP-1 and C-peptide levels controlled the system in obese and T2D subjects. Twenty-four-hour GIP levels were markedly reduced after BPD. Finally, not only did GLP-1 levels play a central role, but also insulin and C-peptide levels had a comparable relevance in the network of healthy controls. After BPD, insulin sensitivity was completely normalized in both obese and T2D individuals. Increased 24-h GLP-1 circulating levels positively influenced glucose homeostasis in both obese and T2D subjects who underwent a malabsorptive bariatric operation. In the latter, the reduction of plasma GIP levels also contributed to the improvement of glucose metabolism. It is possible that the combination of a pharmaceutical treatment reducing GIP and increasing GLP-1 plasma levels will contribute to better glycemic control in T2D. The application of Granger causality and graph analyses sheds new light on the pathophysiology of metabolic surgery.

Intestinal nutrients stimulate insulin secretion more potently than intravenous (IV) glucose administration under similar plasma glucose levels (incretin effect). According to the anti-incretin theory, intestinal nutrients should also cause a reduction of insulin sensitivity and/or secretion (anti-incretin effect) to defend against hyperinsulinemia-hypoglycemia. An exaggerated anti-incretin effect could contribute to insulin resistance/type 2 diabetes, whereas reduction of anti-incretin signals might explain diabetes improvement after bariatric surgery. In this study, we tested some of the predictions made by the anti-incretin theory. Eight healthy volunteers and eight severely obese subjects with insulin resistance were studied. Insulin secretion, insulin sensitivity, Ra, and disposition index were measured after oral glucose tolerance test and isoglycemic IV glucose injection (IGIV). Obese subjects were studied before and after intestinal bypass surgery (biliopancreatic diversion [BPD]). The d-xylose test and lactulose-to-rhamnose ratio were used to test for possible malabsorption of glucose after surgery. Monte Carlo mathematical simulations were used to test whether insulin secretion induced by oral glucose could cause hypoglycemia when coupled with the levels of insulin sensitivity measured during IGIV. Despite isoglycemic conditions, insulin sensitivity was lower during oral than during IV glucose administration. This difference was amplified in obese subjects and reduced to normal after BPD. No evidence of glucose malabsorption was found. Mathematical simulations showed that hypoglycemia would occur if insulin sensitivity were not reduced by oral glucose stimulation. This study demonstrates an anti-incretin effect of intestinal glucose stimulation, which downregulates insulin sensitivity. The findings support a new model for how foodborne factors can induce insulin-resistance and provide a possible explanation for the improvement of insulin resistance/diabetes after gastrointestinal bypass surgery.

Gastric bypass surgery can dramatically improve type 2 diabetes. It has been hypothesized that by excluding duodenum and jejunum from nutrient transit, this procedure may reduce putative signals from the proximal intestine that negatively influence insulin sensitivity (SI). To test this hypothesis, resection or bypass of different intestinal segments were performed in diabetic Goto-Kakizaki and Wistar rats. Rats were randomly assigned to five groups: duodenal-jejunal bypass (DJB), jejunal resection (jejunectomy), ileal resection (ileectomy), pair-fed sham-operated, and nonoperated controls. Oral glucose tolerance test was performed within 2 weeks after surgery. Baseline and poststimulation levels of glucose, insulin, glucagon-like peptide 1 (GLP-1), and glucose-dependent insulinotropic polypeptide (GIP) were measured. Minimal model analysis was used to assess SI. SI improved after DJB (SI = 1.14 ± 0.32 × 10(-4) min(-1) ⋅ pM(-1)) and jejunectomy (SI = 0.80 ± 0.14 × 10(-4) min(-1) ⋅ pM(-1)), but not after ileectomy or sham operation/pair feeding in diabetic rats. Both DJB and jejunal resection normalized SI in diabetic rats as shown by SI levels equivalent to those of Wistar rats (SI = 1.01 ± 0.06 × 10(-4) min(-1) ⋅ pM(-1); P = NS). Glucose effectiveness did not change after operations in any group. While ileectomy increased plasma GIP levels, no changes in GIP or GLP-1 were observed after DJB and jejunectomy. These findings support the hypothesis that anatomic alterations of the proximal small bowel may reduce factors associated with negative influence on SI, therefore contributing to the control of diabetes after gastric bypass surgery.

ObjectiveIn this study a gaze independent event related potential (ERP)-based brain computer interface (BCI) for communication purpose was combined with an asynchronous classifier endowed with dynamical stopping feature. The aim was to evaluate if and how the performance of such asynchronous system could be negatively affected in terms of communication efficiency and robustness to false positives during the intentional no-control state. Material and methodsThe proposed system was validated with the participation of 9 healthy subjects. A comparison was performed between asynchronous and synchronous classification technique outputs while users were controlling the same gaze independent BCI interface. The performance of both classification techniques were assessed both off-line and on-line by means of the efficiency metric introduced by Bianchi et al. (2007). This latter metric allows to set a different misclassification cost for wrong classifications and abstentions. Robustness was evaluated as the rate of false positives occurring during voluntary no-control states. ResultsThe asynchronous classifier did not exhibited significantly higher accuracy or lower error rate with respect to the synchronous classifier (accuracy: 74.66% versus 87.96%, error rate: 7.11% versus 12.04% respectively). However, the on-line and off-line analysis revealed that the communication efficiency was significantly improved (p

Insulin resistance is the common denominator of several diseases including type 2 diabetes and cancer, and investigating the mechanisms responsible for insulin signaling impairment is of primary importance. A mathematical model of the insulin signaling network (ISN) is proposed and used to investigate the dose-response curves of components of this network. Experimental data of C2C12 myoblasts with phosphatase and tensin homologue (PTEN) suppressed and data of L6 myotubes with induced insulin resistance have been analyzed by the model. We focused particularly on single and double Akt phosphorylation and pointed out insulin signaling changes related to insulin resistance. Moreover, a new characterization of the upstream signaling of the mammalian target of rapamycin complex 2 (mTORC2) is presented. As it is widely recognized that ISN proteins have a crucial role also in cell proliferation and death, the ISN model was linked to a cell population model and applied to data of a cell line of acute myeloid leukemia treated with a mammalian target of rapamycin inhibitor with antitumor activity. The analysis revealed simple relationships among the concentrations of ISN proteins and the parameters of the cell population model that characterize cell cycle progression and cell death.

The Farwell and Donchin P300 speller interface is one of the most widely used brain-computer interface (BCI) paradigms for writing text. Recent studies have shown that the recognition accuracy of the P300 speller decreases significantly when eye movement is impaired. This report introduces the GeoSpell interface (Geometric Speller), which implements a stimulation framework for a P300-based BCI that has been optimised for operation in covert visual attention. We compared the Geospell with the P300 speller interface under overt attention conditions with regard to effectiveness, efficiency and user satisfaction. Ten healthy subjects participated in the study. The performance of the GeoSpell interface in covert attention was comparable with that of the P300 speller in overt attention. As expected, the effectiveness of the spelling decreased with the new interface in covert attention. The NASA task load index (TLX) for workload assessment did not differ significantly between the two modalities.This study introduces and evaluates a gaze-independent, P300-based brain-computer interface, the efficacy and user satisfaction of which were comparable with those off the classical P300 speller. Despite a decrease in effectiveness due to the use of covert attention, the performance of the GeoSpell far exceeded the threshold of accuracy with regard to effective spelling.

In this study we illustrate a methodology able to follow and study concurrent and simultaneous brain processes during cooperation between individuals, with non invasive EEG methodologies. We collected data from fourteen pairs of subjects while they were playing a card game with EEG. Data collection was made simultaneously on all the subjects during the card game. An extension of the Granger-causality approach allows us to estimate the functional connection between signals estimated from different Regions of Interest (ROIs) in different brains during the analyzed task. Finally, with the use of graph theory, we contrast the functional connectivity patterns of the two players belonging to the same team. Statistically significant functional connectivities were obtained from signals estimated in the ROIs modeling the anterior cingulate cortex (ACC) and the prefrontal areas described by the Brodmann areas 8 with the signals estimated in all the other modelled cortical areas. Results presented suggested the existence of Granger-sense causal relations between the EEG activity estimated in the prefrontal areas 8 and 9/46 of one player with the EEG activity estimated in the ACC of their companion. We illustrated the feasibility of functional connectivity methodology on the EEG hyperscannings performed on a group of subjects. These functional connectivity estimated from the couple of brains could suggest, in statistical and mathematical terms, the modelled cortical areas that are correlated in Granger-sense during the solution of a particular task. EEG hyperscannings could be used to investigate experimental paradigms where the knowledge of the simultaneous interactions between the subjects have a value.

OBJECTIVE—The purpose of this study was to elucidate the mechanisms of diabetes reversibility after malabsorptive bariatric surgery. RESEARCH DESIGN AND METHODS—Peripheral insulin sensitivity and β-cell function after either intravenous (IVGTT) or oral glucose tolerance (OGTT) tests and minimal model analysis were assessed in nine obese, type 2 diabetic subjects before and 1 month after biliopancreatic diversion and compared with those in six normal-weight control subjects. Insulin-dependent whole-body glucose disposal was measured by the euglycemic clamp, and glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) were also measured. RESULTS—The first phase of insulin secretion after the IVGTT was fully normalized after the operation. The disposition index from OGTT data was increased about 10-fold and became similar to the values found in control subjects, and the disposition index from IVGTT data increased about 3.5-fold, similarly to what happened after the euglycemic clamp. The area under the curve (AUC) for GIP decreased about four times (from 3,000 ± 816 to 577 ± 155 pmol · l−1 · min, P < 0.05). On the contrary, the AUC for GLP1 almost tripled (from 150.4 ± 24.4 to 424.4 ± 64.3 pmol · l−1 · min, P < 0.001). No significant correlation was found between GIP or GLP1 percent changes and modification of the sensitivity indexes independently of the route of glucose administration. CONCLUSIONS—Restoration of the first-phase insulin secretion and normalization of insulin sensitivity in type 2 diabetic subjects after malabsorptive bariatric surgery seem to be related to the reduction of the effect of some intestinal factor(s) resulting from intestinal bypass.

The present work intends to evaluate the dynamics of the cerebral networks during the preparation and the execution of the foot movement. In order to achieve this objective, we have used mathematical tools capable of estimating the cortical activity via high-resolution EEG techniques. Afterwards we estimated, the instantaneous relationships occurring among the time-series of sixteen regions of interest (ROIs) in the Alpha (7-12 Hz) and Beta (13-29 Hz) band through the adaptive multivariate autoregressive models. Eventually, we evaluated the weighted-topology of the cerebral networks by calculating some theoretical graph indexes. The results show that the main structural changes are encoded in the highest spectral contents (Beta band). In particular, during the execution of the foot movement the cingulate motor areas (CM) work as network "hubs" presenting a large amount of outgoing links to the other ROIs. Moreover, the connectivity pattern changes its structure according to the different temporal stages of the task. In particular, the communication between the ROIs reaches its highest level of efficiency during the preparation of the foot movement, as revealed by the "small-world" property of the network, which is characterized by the presence of abundant clustering connections combined with short average distances between the cortical areas.

We describe a set of computational tools able to estimate cortical activity and connectivity from high-resolution EEG and fMRI recordings in humans. These methods comprise the estimation of cortical activity using realistic geometry head volume conductor models and distributed cortical source models, followed by the evaluation of cortical connectivity between regions of interest coincident with the Brodmann areas via the use of Partial Directed Coherence. Connectivity patterns estimated on the cortical surface in different frequency bands are then imaged and interpreted with measures based on graph theory. These computational tools were applied on a set of EEG and fMRI data from a Stroop task to demonstrate the potential of the proposed approach. The present findings suggest that the methodology is able to identify differences in functional connectivity patterns elicited by different experimental tasks or conditions.

Static hemodynamic or neuroelectric images of brain regions activated during particular tasks do not convey the information of how these regions communicate to each other. Cortical connectivity estimation aims at describing these interactions as connectivity patterns which hold the direction and strength of the information flow between cortical areas. In this study, we attempted to estimate the causality between distributed cortical systems during a movement volition task in preparation for execution of simple movements by a group of normal healthy subjects and by a group of Spinal Cord Injured (SCI) patients. To estimate the causality between the spatial distributed patterns of cortical activity in the frequency domain, we applied a series of processing steps on the recorded EEG data. From the high-resolution EEG recordings we estimated the cortical waveforms for the regions of interest (ROIs), each representing a selected sensor group population. The solutions of the linear inverse problem returned a series of cortical waveforms for each ROI considered and for each trial analyzed. For each subject, the cortical waveforms were then subjected to Independent Component Analysis (ICA) pre-processing. The independent components obtained by the application of the ThinICA algorithm were further processed by a Partial Directed Coherence algorithm, in order to extract the causality between spatial cortical patterns of the estimated data. The source-target cortical dependencies found in the group of normal subjects were relatively similar in all frequency bands analyzed. For the normal subjects we observed a common source pattern in an ensemble of cortical areas including the right parietal and right lip primary motor areas and bilaterally the primary foot and posterior SMA areas. The target of this cortical network, in the Granger-sense of causality, was shown to be a smaller network composed mostly by the primary foot motor areas and the posterior SMA bilaterally. In the case of the SCI population, both the source and the target cortical patterns had larger sizes than in the normal population. The source cortical areas included always the primary foot and lip motor areas, often bilaterally. In addition, the right parietal area and the bilateral premotor area 6 were also involved. Again, the patterns remained substantially stable across the different frequency bands analyzed. The target cortical patterns observed in the SCI population had larger extensions when compared to the normal ones, since in most cases they involved the bilateral activation of the primary foot movement areas as well as the SMA, the primary lip areas and the parietal cortical areas.

Methods based on the multivariate autoregressive (MVAR) approach are commonly used for effective connectivity estimation as they allow to include all available sources into a unique model. To ensure high levels of accuracy for high model dimensions, all the observations are used to provide a unique estimation of the model, and thus of the network and its properties. The unavailability of a distribution of connectivity values for a single experimental condition prevents to perform statistical comparisons between different conditions at a single subject level. This is a major limitation, especially when dealing with the heterogeneity of clinical conditions presented by patients. In the present paper we proposed a novel approach to the construction of a distribution of connectivity in a single subject case. The proposed approach is based on small perturbations of the networks properties and allows to assess significant changes in brain connectivity indexes derived from graph theory. Its feasibility and applicability were investigated by means of a simulation study and an application to real EEG data.

Occipital sources of resting-state electroencephalographic (EEG) alpha rhythms are abnormal, at the group level, in patients with amnesic mild cognitive impairment (MCI) and Alzheimer's disease (AD). Here, we evaluated the hypothesis that amplitude of these occipital sources is related to neuro-degeneration in occipital lobe as measured by magnetic resonance imaging. Resting-state eyes-closed EEG rhythms were recorded in 45 healthy elderly (Nold), 100 MCI, and 90 AD subjects. Neuro-degeneration of occipital lobe was indexed by weighted averages of gray matter density, estimated from structural MRIs. EEG rhythms of interest were alpha 1 (8-10.5 Hz) and alpha 2 (10.5-13 Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography. Results showed a positive correlation between occipital gray matter density and amplitude of occipital alpha 1 sources in Nold, MCI, and AD subjects as a whole group (r = 0.3, p = 0.000004, N = 235). Furthermore, there was a positive correlation between the amplitude of occipital alpha 1 sources and cognitive status as revealed by Mini Mental State Examination score across all subjects (r = 0.38, p = 0.000001, N = 235). Finally, amplitude of occipital alpha 1 sources allowed a moderate classification of individual Nold and AD subjects (sensitivity: 87.8%; specificity: 66.7%; area under the receiver operating characteristic curve: 0.81). These results suggest that the amplitude of occipital sources of resting- state alpha rhythms is related to AD neurodegeneration in occipital lobe along pathologic aging. (C) 2015 Elsevier Inc. All rights reserved.

In this study, we investigated the possibility to evaluate the impact of different avionic technologies on the mental workload of helicopter's pilots by measuring their brain activity with the EEG during a series of simulated missions carried out at AgustaWestland facilities in Yeovil (UK). The tested avionic technologies were: i) Head-Up Display (HUD); ii) Head-Mounted Display (HMD); iii) Full Conformal symbology (FC); iv) Flight Guidance (FG) symbology; v) Synthetic Vision System (SVS); and vi) Radar Obstacles (RO) detection system. It has been already demonstrated that in cognitive tasks, when the cerebral workload increases the EEG power spectral density (PSD) in theta band over frontal areas increases, and the EEG PSD in alpha band decreases over parietal areas. A mental workload index (MWL) has been here defined as the ratio between the frontal theta and parietal alpha EEG PSD values. Such index has been used for testing and comparing the different avionic technologies. Results suggested that the HUD provided a significant (p;.05) workload reduction across all the flight scenarios with respect to the other technologies. In addition, the simultaneous use of FC and FG technologies (FC+FG) produced a significant decrement of the workload (p;.01) with respect to the use of only the FC. Moreover, the use of the SVS technology provided on Head Down Display (HDD) with the simultaneous use of FC+FG and the RO seemed to produce a lower cerebral workload when compared with the use of only the FC. Interestingly, the workload estimation by means of subjective measures, provided by pilots through a NASA-TLX questionnaire, did not provide any significant differences among the different flight scenarios. These results suggested that the proposed MWL cognitive neurometrics could be used as a reliable measure of the user's mental workload, being a valid indicator for the comparison and the test of different avionic technologies.

Metabolically healthy skeletal muscle possesses the ability to switch easily between glucose and fat oxidation in response to homeostatic signals. In type 2 diabetes mellitus and obesity, the skeletal muscle shows a great reduction in this metabolic flexibility. A substrate like dodecanedioic acid (C-12), able to increase skeletal muscle glycogen stores via succinyl-CoA formation, might both postpone the fatigue and increase fatty acid utilization, since it does not affect insulin secretion. In healthy volunteers and in type 2 diabetic subjects, the effect of an oral C-12 load was compared with a glucose or water load during prolonged, moderate-intensity, physical exercise. C-12 metabolism was analyzed by a mathematical model. After C-12, diabetics were able to complete the 2 h of exercise. Nonesterified fatty acids increased both during and after the exercise in the C-12 session. C-12 oxidation provided 14% of total energy expenditure, and the sum of C-12 plus lipids oxidized after the C-12 meal was significantly greater than lipids oxidized after the glucose meal ( P < 0.025). The fraction of C-12 that entered the central compartment was 47% of that ingested. During the first phase of the exercise (∼60 min), the mean C-12 clearance from the central compartment toward tissues was 2.57 and 1.30 l/min during the second phase of the exercise. In conclusion, C-12 seems to be a suitable energy substrate during exercise, since it reduces muscle fatigue, is rapidly oxidized, and does not stimulate insulin secretion, which implies that lipolysis is not inhibited as reported after glucose ingestion.

The problem of the definition and evaluation of brain connectivity has become a central one in neuroscience during recent years as a way to understand the organization and interaction of cortical areas during the execution of cognitive or motor tasks. In this article, we propose the use of the directed transfer function (DTF) method on cortical signals estimated from high-resolution electroencephalography (EEG) recordings. An application of the proposed technique to the estimation of the cortical connectivity pattern in normal subjects and in one spinal-cord-injured patient is also provided

Today, the concept of brain connectivity plays a central role in the neuroscience. While functional connectivity is defined as the temporal coherence between the activities of different brain areas, the effective connectivity is defined as the simplest brain circuit that would produce the same temporal relationship as observed experimentally between cortical sites. The most used method to estimate effective connectivity in neuroscience is the structural equation modeling (SEM), typically used on data related to the brain hemodynamic behavior. However, the use of hemodynamic measures limits the temporal resolution on which the brain process can be followed. The present research proposes the use of the SEM approach on the cortical waveforms estimated from the high-resolution EEG data, which exhibits a good spatial resolution and a higher temporal resolution than hemodynamic measures. We performed a simulation study, in which different main factors were systematically manipulated in the generation of test signals, and the errors in the estimated connectivity were evaluated by the analysis of variance (ANOVA). Such factors were the signal-to-noise ratio and the duration of the simulated cortical activity. Since SEM technique is based on the use of a model formulated on the basis of anatomical and physiological constraints, different experimental conditions were analyzed, in order to evaluate the effect of errors made in the a priori model formulation on its performances. The feasibility of the proposed approach has been shown in a human study using high-resolution EEG recordings related to finger tapping movements.

Objective To test a technique called Directed Transfer Function (DTF) for the estimation of human cortical connectivity, by means of simulation study and human study, using high resolution EEG recordings related to finger movements. Methods The method of the Directed Transfer Function (DTF) is a frequency-domain approach, based on a multivariate autoregressive modeling of time series and on the concept of Granger causality. Since the spreading of the potential from the cortex to the sensors makes it difficult to infer the relation between the spatial patterns on the sensor space and those on the cortical sites, we propose the use of the DTF method on cortical signals estimated from high resolution EEG recordings, which exhibit a higher spatial resolution than conventional cerebral electromagnetic measures. The simulation study was followed by an analysis of variance (ANOVA) of the results obtained for different levels of Signal to Noise Ratio (SNR) and temporal length, as they have been systematically imposed on simulated signals. The whole methodology was then applied to high resolution EEG data recorded during a visually paced finger movement. Results The statistical analysis performed returns that during simulations, DTF is able to estimate correctly the imposed connectivity patterns under reasonable operative conditions, i.e. when data exhibit a SNR of at least 3 and a length of at least 75 s of non-consecutive recordings at 64 Hz of sampling rate, equivalent, more generally, to 4800 data samples. Conclusions Functional connectivity patterns of cortical activity can be effectively estimated under general conditions met in any practical EEG recordings, by combining high resolution EEG techniques, linear inverse estimation and the DTF method. Significance The estimation of cortical connectivity can be performed not only with hemodynamic measurements, by using functional MRI recordings, but also with modern EEG recordings treated with advanced computational techniques.

The study aimed at mapping (i) the distributed alpha (8–13 Hz) electroencephalography (EEG) sources specific for mild Alzheimer's disease (AD) compared with vascular dementia (VaD) in normal, elderly people (Nold) and (ii) the distributed alpha EEG sources sensitive to mild AD at different stages of severity. Resting EEG (10–20 electrode montage) was recorded from 48 mild AD, 20 VaD and 38 Nold subjects. Both AD and VaD patients had 24–17 on their mini mental state examinations (MMSE). Alpha bands were subdivided in alpha 1 (8–10.5 Hz) and alpha 2 (10.5–13 Hz) subbands. Cortical alpha EEG sources were modeled by “low resolution brain electromagnetic tomography” (LORETA). Regarding issue (i), there was a decline of central, parietal, temporal and limbic alpha 1 sources specific to the mild AD group with respect to Nold and VaD groups. On the other hand, occipital alpha 1 sources showed a strong decline in mild AD compared with the VaD group. However, this finding was “unspecific” because a certain decline of these sources was also recognized in VaD compared with Nold. Regarding issue (ii), there was a lower power of occipital alpha 1 sources in the mild AD more severely diseased subgroup. On the whole, these findings stress the reliability of modern technologies for EEG analysis as the LORETA approach to the study of cortical rhythmicity in resting mild AD.

The aim of this paper is to analyze whether the use of the cortical activity estimated from noninvasive EEG recordings could be useful to detect mental states related to the imagination of limb movements. Estimation of cortical activity was performed on high-resolution EEG data related to the imagination of limb movements gathered in five normal, healthy subjects by using realistic head models. Cortical activity was estimated in region of interest (ROI) associated with the subject's Brodmann areas (BAs) by using depth-weighted minimum norm solutions. Comparisons between surface recorded EEG and the estimated cortical activity were performed. The estimated cortical activity related to the mental imagery of limbs in the five subjects is located mainly over the contralateral primary motor area. The unbalance between brain activity estimated in contralateral and ipsilateral motor cortical areas relative to the finger movement imagination is greater than those obtained in the scalp EEG recordings. Results suggest that the use of the estimated cortical activity for the motor imagery of upper limbs could be potentially superior with respect to the use of surface EEG recordings. This is due to a greater statistically significant unbalance between the activity estimated in the contralateral and ipsilateral hemisphere with respect to those observed with surface EEG. These results are useful in the context of the development of a noninvasive Brain Computer Interface.

The aim of this study is to present a package including standard software for the electroencephalographic (EEG), electro-oculographic (EOG) and electromyographic (EMG) preliminary data analysis, which may be suitable to standardize the results of many EEG research centers studies (i.e. multi-centric studies) especially focused on event-related potentials. In particular, our software package includes (semi)automatic procedures for (i) EOG artifact detection and correction, (ii) EMG analysis, (iii) EEG artifact analysis, (iv) optimization of the ratio between artifact-free EEG channels and trials to be rejected. The performances of the software package on EOG-EEG-EMG data related to cognitive-motor tasks were evaluated with respect to the preliminary data analysis performed by two expert electroencephalographists (gold standard). Due to its extreme importance for multi-centric EEG studies, we compared the performances of two representative "regression" methods for the EOG correction in time and frequency domains. The aim was the selection of the most suitable method in the perspective of a multi-centric EEG study. The results showed an acceptable agreement of approximately 95% between the human and software behaviors, for the detection of vertical and horizontal EOG artifacts, the measurement of hand EMG responses for a cognitive-motor paradigm, the detection of involuntary mirror movements, and the detection of EEG artifacts. Furthermore, our results indicated a particular reliability of a 'regression' EOG correction method operating in time domain (i.e. ordinary least squares). These results suggest that such a software package could be used for multi-centric EEG studies.

Background Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory, that is a mathematical representation of a network, which is essentially reduced to nodes and connections between them. Methods We used high-resolution EEG technology to enhance the poor spatial information of the EEG activity on the scalp and it gives a measure of the electrical activity on the cortical surface. Afterwards, we used the Directed Transfer Function (DTF) that is a multivariate spectral measure for the estimation of the directional influences between any given pair of channels in a multivariate dataset. Finally, a graph theoretical approach was used to model the brain networks as graphs. These methods were used to analyze the structure of cortical connectivity during the attempt to move a paralyzed limb in a group (N=5) of spinal cord injured patients and during the movement execution in a group (N=5) of healthy subjects. Results Analysis performed on the cortical networks estimated from the group of normal and SCI patients revealed that both groups present few nodes with a high out-degree value (i.e. outgoing links). This property is valid in the networks estimated for all the frequency bands investigated. In particular, cingulate motor areas (CMAs) ROIs act as ‘‘hubs’’ for the outflow of information in both groups, SCI and healthy. Results also suggest that spinal cord injuries affect the functional architecture of the cortical network sub-serving the volition of motor acts mainly in its local feature property. In particular, a higher local efficiency El can be observed in the SCI patients for three frequency bands, theta (3-6 Hz), alpha (7-12 Hz) and beta (13-29 Hz). By taking into account all the possible pathways between different ROI couples, we were able to separate clearly the network properties of the SCI group from the CTRL group. In particular, we report a sort of compensatory mechanism in the SCI patients for the Theta (3-6 Hz) frequency band, indicating a higher level of “activation” Ω within the cortical network during the motor task. The activation index is directly related to diffusion, a type of dynamics that underlies several biological systems including possible spreading of neuronal activation across several cortical regions. Conclusions The present study aims at demonstrating the possible applications of graph theoretical approaches in the analyses of brain functional connectivity from EEG signals. In particular, the methodological aspects of the i) cortical activity from scalp EEG signals, ii) functional connectivity estimations iii) graph theoretical indexes are emphasized in the present paper to show their impact in a real application.