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Serenella Salinari

Publications and source records attributed to Serenella Salinari.

16 recordsLinked to original sources
PubMed2007

Comparison of different cortical connectivity estimators for high-resolution EEG recordings.

The aim of this work is to characterize quantitatively the performance of a body of techniques in the frequency domain for the estimation of cortical connectivity from high-resolution EEG recordings in different operative conditions commonly encountered in practice. Connectivity pattern estimators investigated are the Directed Transfer Function (DTF), its modification known as direct DTF (dDTF) and the Partial Directed Coherence (PDC). Predefined patterns of cortical connectivity were simulated and then retrieved by the application of the DTF, dDTF, and PDC methods. Signal-to-noise ratio (SNR) and length (LENGTH) of EEG epochs were studied as factors affecting the reconstruction of the imposed connectivity patterns. Reconstruction quality and error rate in estimated connectivity patterns were evaluated by means of some indexes of quality for the reconstructed connectivity pattern. The error functions were statistically analyzed with analysis of variance (ANOVA). The whole methodology was then applied to high-resolution EEG data recorded during the well-known Stroop paradigm. Simulations indicated that all three methods correctly estimated the simulated connectivity patterns under reasonable conditions. However, performance of the methods differed somewhat as a function of SNR and LENGTH factors. The methods were generally equivalent when applied to the Stroop data. In general, the amount of available EEG affected the accuracy of connectivity pattern estimations. Analysis of 27 s of nonconsecutive recordings with an SNR of 3 or more ensured that the connectivity pattern could be accurately recovered with an error below 7% for the PDC and 5% for the DTF. In conclusion, functional connectivity patterns of cortical activity can be effectively estimated under general conditions met in most EEG recordings by combining high-resolution EEG techniques, linear inverse estimation of the cortical activity, and frequency domain multivariate methods such as PDC, DTF, and dDTF.

Analysis of Variance↗
PubMed2006

Dodecanedioic acid overcomes metabolic inflexibility in type 2 diabetic subjects.

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 ( approximately 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.

Administration, Oral↗
PubMed2006

Donepezil effects on sources of cortical rhythms in mild Alzheimer's disease: Responders vs. Non-Responders.

Acetylcholinesterase inhibitors (AChEI) such as donepezil act in mild Alzheimer's disease (AD) by increasing cholinergic tone. Differences in the clinical response in patients who do or do not benefit from therapy may be due to different functional features of the central neural systems. We tested this hypothesis using cortical electroencephalographic (EEG) rhythmicity. Resting eyes-closed EEG data were recorded in 58 mild AD patients (Mini Mental State Examination [MMSE] range 17-24) before and approximately 1 year after standard donepezil treatment. Based on changes of MMSE scores between baseline and follow-up, 28 patients were classified as "Responders" (MMSEvar >or=0) and 30 patients as "Non-Responders" (MMSEvar <0). EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). Cortical EEG sources were studied with low-resolution brain electromagnetic tomography (LORETA). Before treatment, posterior sources of delta, alpha 1 and alpha 2 frequencies were greater in amplitude in Non-Responders. After treatment, a lesser magnitude reduction of occipital and temporal alpha 1 sources characterized Responders. These results suggest that Responders and Non-Responders had different EEG cortical rhythms. Donepezil could act by reactivating existing yet functionally silent cortical synapses in Responders, restoring temporal and occipital alpha rhythms.

Aged↗
PubMed2006

Assessing cortical functional connectivity by partial directed coherence: simulations and application to real data.

The aim of this paper is to test a technique called partial directed coherence (PDC) and its modification (squared PDC; sPDC) for the estimation of human cortical connectivity by means of simulation study, in which both PDC and sPDC were studied by analysis of variance. The statistical analysis performed returned that both PDC and sPDC are able to estimate correctly the imposed connectivity patterns when data exhibit a signal-to-noise ratio of at least 3 and a length of at least 27 s of nonconsecutive recordings at 250 Hz of sampling rate, equivalent, more generally, to 6750 data samples.

Algorithms↗
PubMed2005

Sources of cortical rhythms change as a function of cognitive impairment in pathological aging: a multicenter study.

OBJECTIVE: The present study tested the hypothesis that cortical electroencephalographic (EEG) rhythms. change across normal elderly (Nold), mild cognitive impairment (MCI), and Alzheimer's disease (AD) subjects as a function of the global cognitive level. METHODS: Resting eyes-closed EEG data were recorded in 155 MCI, 193 mild AD, and 126 age-matched Nold subjects. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). EEG cortical sources were estimated by LORETA. RESULTS: Occipital delta and alpha 1 sources in parietal, occipital, temporal, and 'limbic' areas had an intermediate magnitude in MCI subjects compared to mild AD and Nold subjects. These five EEG sources presented both linear and nonlinear (linear, exponential, logarithmic, and power) correlations with the global cognitive level (as revealed by mini mental state examination score) across all subjects. CONCLUSIONS: Cortical EEG rhythms change in pathological aging as a function of the global cognitive level. SIGNIFICANCE: The present functional data on large populations support the 'transitional hypothesis' of a shadow zone across normality, pre-clinical stage of dementia (MCI), and AD.

Aged↗
PubMed2005

Estimation of the cortical connectivity by high-resolution EEG and structural equation modeling: simulations and application to finger tapping data.

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.

Algorithms↗
PubMed2004

Estimation of the effective and functional human cortical connectivity with structural equation modeling and directed transfer function applied to high-resolution EEG.

Different brain imaging devices are presently available to provide images of the human functional cortical activity, based on hemodynamic, metabolic or electromagnetic measurements. However, static images of brain regions activated during particular tasks do not convey the information of how these regions are interconnected. The concept of brain connectivity plays a central role in the neuroscience, and different definitions of connectivity, functional and effective, have been adopted in literature. While the functional connectivity is defined as the temporal coherence among 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 among cortical sites. The structural equation modeling (SEM) is the most used method to estimate effective connectivity in neuroscience, and its typical application is on data related to brain hemodynamic behavior tested by functional magnetic resonance imaging (fMRI), whereas the directed transfer function (DTF) method is a frequency-domain approach based on both a multivariate autoregressive (MVAR) modeling of time series and on the concept of Granger causality. This study presents advanced methods for the estimation of cortical connectivity by applying SEM and DTF on the cortical signals estimated from high-resolution electroencephalography (EEG) recordings, since these signals exhibit a higher spatial resolution than conventional cerebral electromagnetic measures. To estimate correctly the cortical signals, we used a subject's multicompartment head model (scalp, skull, dura mater, cortex) constructed from individual MRI, a distributed source model and a regularized linear inverse source estimates of cortical current density. Before the application of SEM and DTF methodology to the cortical waveforms estimated from high-resolution EEG data, we performed a simulation study, in which different main factors (signal-to-noise ratio, SNR, and simulated cortical activity duration, LENGTH) were systematically manipulated in the generation of test signals, and the errors in the estimated connectivity were evaluated by the analysis of variance (ANOVA). The statistical analysis returned that during simulations, both SEM and DTF estimators were able to correctly estimate the imposed connectivity patterns under reasonable operative conditions, that is, when data exhibit an SNR of at least 3 and a LENGTH of at least 75 s of nonconsecutive EEG recordings at 64 Hz of sampling rate. Hence, effective and 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 and linear inverse estimation with SEM or DTF methods. We conclude that the estimation of cortical connectivity can be performed not only with hemodynamic measurements, but also with EEG signals treated with advanced computational techniques.

Adult↗
PubMed2004

Multimodal integration of EEG, MEG and fMRI data for the solution of the neuroimage puzzle.

In this paper, advanced methods for the modeling of human cortical activity from combined high-resolution electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) data are presented. These methods include a subject's multicompartment head model (scalp, skull, dura mater, cortex) constructed from magnetic resonance images, multidipole source model and regularized linear inverse source estimates of cortical current density. Determination of the priors in the resolution of the linear inverse problem was performed with the use of information from the hemodynamic responses of the cortical areas as revealed by block-designed (strength of activated voxels) fMRI. Examples of the application of these methods to the estimation of the time varying cortical current density activity in selected region of interest (ROI) are presented for movement-related high-resolution EEG data.

Algorithms↗
PubMed2004

Mapping distributed sources of cortical rhythms in mild Alzheimer's disease. A multicentric EEG study.

The study aimed at mapping (i) the distributed electroencephalographic (EEG) sources specific for mild Alzheimer's disease (AD) compared to vascular dementia (VaD) or normal elderly people (Nold) and (ii) the distributed EEG sources sensitive to the 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 of mini mental state examination (MMSE). EEG rhythms were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). Cortical 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 (low alpha) sources specific for mild AD group with respect to Nold and VaD groups. Furthermore, occipital alpha 1 sources showed a strong decline in mild AD compared to VaD group. Finally, distributed theta sources were largely abnormal in VaD but not in mild AD group. Regarding issue ii, there was a lower power of occipital alpha 1 sources in mild AD subgroup having more severe disease. Compared to previous field studies, this was the first investigation that illustrated the power spectrum profiles at the level of cortical (macroregions) EEG sources in mild AD patients having different severity of the disease with respect to VaD and normal subjects. Future studies should evaluate the clinical usefulness of this approach in early differential diagnosis, disease staging, and therapy monitoring.

Aged↗
PubMed2004

Individual analysis of EEG frequency and band power in mild Alzheimer's disease.

OBJECTIVE: This EEG study investigates the role of the cholinergic system, cortico-cortical connections, and sub-cortical white matter on the relationship between individual EEG frequencies and their relative power bands. METHODS: EEGs were recorded at rest in 30 normal elderly subjects (Nold), 60 mild Alzheimer disease (AD) and 20 vascular dementia (VaD) patients, comparable for Mini Mental State Evaluation scores (MMSE 17-24). Individual EEG frequencies were indexed by the theta/alpha transition frequency (TF) and by the individual alpha frequency (IAF) with power peak in the extended alpha range (5-14 Hz). Relative power was separately computed for delta, theta, alpha1, alpha2, and alpha3 bands, on the basis of the TF and IAF. RESULTS: Using normal subjects as a reference, VaD patients showed 'slowing' of alpha frequency (TF-IAF) and lower alpha2 power; Mild AD patients showed lower alpha2 and alpha3 power; delta power was higher in both AD and VaD patients; Theta power was higher only in VaD patients. CONCLUSIONS: Individual analysis of the alpha frequency and power can discriminate mild AD from VaD and normal elderly subjects. SIGNIFICANCE: This analysis may probe pathophysiological mechanisms causing AD and VaD.

Aged↗
PubMed2004

Cortical networks generating movement-related EEG rhythms in Alzheimer's disease: an EEG coherence study.

Patients with mild Alzheimer's disease (AD) present with abnormally strong values of frontal and ipsilateral central sensorimotor rhythms. The authors tested 2 working hypotheses of the related electroencephalographic (EEG) coherence: disconnection, defined as a sign of a reduced coordination within the frontoparietal and interhemispheric networks, and cooperation, defined as a reflection of the reorganization of the brain sensorimotor networks. Results showed that, compared with healthy controls, patients with mild AD had an unreactive and abnormally low interhemispheric EEG coherence and an unreactive and abnormally high frontoparietal EEG coherence. These findings support the hypothesis of an impaired mechanism of sensorimotor cortical coupling (disconnection) in mild AD.

Aged↗
PubMed2004

The ingestion of saturated fatty acid triacylglycerols acutely affects insulin secretion and insulin sensitivity in human subjects.

To assess the effects of acute dietary saturated fat intake on glucose-induced insulin secretion rate (ISR), measured by the C-peptide deconvolution method, and on insulin clearance and sensitivity, five obese and five normal-weight women (controls) were studied after either a 100 g oral butter load or a 100 ml water load. At 120 min after the oral load a hyperglycaemic clamp was performed over 180 min. A dramatic increase of ISR occurred after butter compared with the water challenge in the controls (1305.6 (SE 124.1) v. 616.1 (SE 52.5) pmol/min; P<0.01) and to a lesser degree in the obese subjects (1975.0 (SE 44.1) v. 1417.5 (se 56.0) pmol/min; P<0.05). Insulin sensitivity was impaired after butter (0.60 x 10(-2) (SE 0.11 x 10(-2)) v. 2.26 x 10(-2) (SE 0.32 x 10(-2)) ml/min per kg FFM per (pmol/l); P<0.01) in the controls but not in the obese group. Insulin clearance during the clamp was reduced after butter compared with after the water load only in the controls (0.89 (SE 0.22) v. 1.70 (SE 0.15) litres/min; P<0.01). The data are consistent with the hypothesis that acute excess lipid availability may lead to a compensatory elevation in glucose-induced insulin secretion as a result of the decline in insulin sensitivity and a reduced insulin clearance.

Administration, Oral↗
PubMed2004

Abnormal fronto-parietal coupling of brain rhythms in mild Alzheimer's disease: a multicentric EEG study.

Cholinergic deafferentation/recovery in rats mainly impinges on the fronto-parietal coupling of brain rhythms [D. P. Holschneider et al. (1999) Exp. Brain Res., 126, 270-280]. Is this reflected by the functional coupling of fronto-parietal cortical rhythms at an early stage of Alzheimer's disease (mild AD)? Resting electroencephalographic (EEG) rhythms were studied in 82 patients with mild AD and in control subjects, such as 41 normal elderly (Nold) subjects and 25 patients with vascular dementia (VaD). Patients with AD and VaD had similar mini-mental state evaluation scores of 17-24. The functional coupling was estimated by means of the synchronization likelihood (SL) of the EEG data at electrode pairs, accounting for linear and non-linear components of that coupling. Cortical rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha (1 8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz) and gamma (30-40 Hz). A preliminary data analysis (Nold) showed that surface Laplacian transformation of the EEG data reduced the values of SL, possibly because of the reduction of influences due to head volume conduction. Therefore, the final analysis was performed on Laplacian-transformed EEG data. The SL was dominant at alpha 1 band in all groups. Compared with the Nold subjects, patients with VaD and mild AD presented a marked reduction of SL at both fronto-parietal (delta-alpha) and inter-hemispherical (delta-beta) electrode pairs. The feature distinguishing the patients with mild AD with respect to patients with VaD groups was a more prominent reduction of fronto-parietal alpha 1 SL. These results suggest that mild AD is characterized by an abnormal fronto-parietal coupling of the dominant human cortical rhythm at 8-10.5 Hz.

Aged↗
PubMed2003

The use of EEG modifications due to motor imagery for brain-computer interfaces.

The opening of a communication channel between brain and computer [brain-computer interface (BCI)] is possible by using changes in electroencephalogram (EEG) power spectra related to the imagination of movements. In this paper, we present results obtained by recording EEG during an upper limb motor imagery task in a total of 18 subjects by using low-resolution surface Laplacian, different linear and quadratic classifiers, as well as a variable number of scalp electrodes, from 2 to 26. The results (variable correct classification rate of mental imagery between 75% and 95%) suggest that it is possible to recognize quite reliably ongoing mental movement imagery for BCI applications.

Algorithms↗
PubMed2003

Bioimpedance analysis: a useful technique for assessing appendicular lean soft tissue mass and distribution.

The present study was aimed at evaluating the feasibility and reliability of lower limb skeletal muscle (SM) mass estimates obtained by bioimpedance analysis (BIA). BIA estimates were compared with the estimates obtained by dual-energy X-ray absorptiometry (DXA). Ten normal weight and 10 obese women had BIA and DXA evaluations. Lower limb SM mass was then derived from DXA appendicular lean soft tissue estimates. Lower limb SM mass and SM distribution were also estimated from BIA modeling that fits measured resistance values along the leg. SM mass (mean +/- SD) was 5.8 +/- 1.0 kg by BIA vs. 5.8 +/- 1.1 kg by DXA in normal weight subjects and 7.2 +/- 1.4 kg by BIA vs. 7.2 +/- 1.2 kg by DXA in obese subjects. Mean +/- SD of the absolute value of the relative error was 7.0 +/- 3.4 and 5.9 +/- 3.4% in the two groups, respectively. Similar results were obtained by using five resistance values for the analysis. In conclusion, the proposed BIA model provides an adequate means of evaluating appendicular SM mass.

Absorptiometry, Photon↗