Search results for " Electroencephalography"
showing 10 items of 15 documents
Quantification of cortical proprioceptive processing through a wireless and miniaturized EEG amplifier.
2022
Corticokinematic coherence (CKC) is computed between limb kinematics and cortical activity (e.g. MEG, EEG), and it can be used to detect, quantify and localize the cortical processing of proprioceptive afference arising from the body. EEG-based studies on CKC have been limited to lab environments due to bulky, non-portable instrumentations. We recently proposed a wireless and miniaturized EEG acquisition system aimed at enabling EEG studies outside the laboratory. The purpose of this work is to compare the EEG-based CKC values obtained with this device with a conventional wired-EEG acquisition system to validate its use in the quantification of cortical proprioceptive processing. Eleven hea…
Zonisamide in children and young adults with refractory epilepsy: an open label, multicenter Italian study
2009
Summary Purpose To report on the first multicenter Italian experience with zonisamide as an add-on drug for refractory generalised or partial epilepsy in children, adolescents and young adults. Methods The patients were enrolled in a prospective, add-on, open-label treatment study from eight Italian centres for children and adolescent epilepsy care. Eighty-two young patients (45 males, 37 females), aged between 3 and 34 years (mean 13.1 years), all affected by partial (47) or generalised (35) refractory epilepsy, were enrolled in the study. ZNS was added to the baseline therapy at a starting dose of 1 mg/kg/day twice daily. This dose was increased by 2 mg/kg every 1–2 weeks over a period of…
Design and validation of a wireless Body Sensor Network for integrated EEG and HD-sEMG acquisitions
2022
Sensorimotor integration is the process through which the human brain plans the motor program execution according to external sources. Within this context, corticomuscular and corticokinematic coherence analyses are common methods to investigate the mechanism underlying the central control of muscle activation. This requires the synchronous acquisition of several physiological signals, including EEG and sEMG. Nevertheless, physical constraints of the current, mostly wired, technologies limit their application in dynamic and naturalistic contexts. In fact, although many efforts were made in the development of biomedical instrumentation for EEG and High Density-surface EMG (HD-sEMG) signal ac…
Estimation of brain connectivity through Artificial Neural Networks
2019
Among different methods available for estimating brain connectivity from electroencephalographic signals (EEG), those based on MVAR models have proved to be flexible and accurate. They rely on the solution of linear equations that can be pursued through artificial neural networks (ANNs) used as MVAR model. However, when few data samples are available, there is a lack of accuracy in estimating MVAR parameters due to the collinearity between regressors. Moreover, the assessment procedure is also affected by the lack of data points. The mathematical solution to these problems is represented by penalized regression methods based on l 1 norm, that can reduce collinearity by means of variable sel…
Measuring the agreement between brain connectivity networks.
2016
Investigating the level of similarity between two brain networks, resulting from measures of effective connectivity in the brain, can be of interest from many respects. In this study, we propose and test the idea to borrow measures of association used in machine learning to provide a measure of similarity between the structure of (un-weighted) brain connectivity networks. The measures here explored are the accuracy, Cohen's Kappa (K) and Area Under Curve (AUC). We implemented two simulation studies, reproducing two contexts of application that can be particularly interesting for practical applications, namely: i) in methodological studies, performed on surrogate data, aiming at comparing th…
Distributed analysis of simultaneous EEG-fMRI time-series: modeling and interpretation issues
2009
Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) represent brain activity in terms of a reliable anatomical localization and a detailed temporal evolution of neural signals. Simultaneous EEG-fMRI recordings offer the possibility to greatly enrich the significance and the interpretation of the single modality results because the same neural processes are observed from the same brain at the same time. Nonetheless, the different physical nature of the measured signals by the two techniques renders the coupling not always straightforward, especially in cognitive experiments where spatially localized and distributed effects coexist and evolve temporally at different …
Dysfunction of attention switching networks in amyotrophic lateral sclerosis
2019
Objective To localise and characterise changes in cognitive networks in Amyotrophic Lateral Sclerosis (ALS) using source analysis of mismatch negativity (MMN) waveforms. Rationale The MMN waveform has an increased average delay in ALS. MMN has been attributed to change detection and involuntary attention switching. This therefore indicates pathological impairment of the neural network components which generate these functions. Source localisation can mitigate the poor spatial resolution of sensor-level EEG analysis by associating the sensor-level signals to the contributing brain sources. The functional activity in each generating source can therefore be individually measured and investigat…
Continuous electroencephalography in a mixed non-neurological intensive care population, an observational study.
2016
Abstract Purpose Continuous electroencephalography (cEEG) improves monitoring of the brain in unconscious patients, but implementation at ICU is difficult. The present investigation shows a way to introduce cEEG at an anesthesiological ICU and discusses the first experiences. Materials and methods The study analyzed the feasibility of cEEG, assessed the interpretable cEEG time, importance of automatic seizure detection, the incidence of seizures, the predominant background EEG activity, incidence of delirium and mortality. Results Fifty-three cEEGs of 50 patients with a median interpretable length of 24 hours [IQR 20 to 42 hours] were recorded. One patient had status epilepticus, while 5 pa…
Cerebral haemodynamic changes during propofol-remifentanil or sevoflurane anaesthesia: transcranial Doppler study under bispectral index monitoring
2006
Background. Sevoflurane or propofol–remifentanil-based anaesthetic regimens represent modern techniques for neurosurgical anaesthesia. Nevertheless, there are potential differences related to their activity on the cerebrovascular system. The magnitude of such difference is not completely known. Methods. In total 40 patients, treated for spinal or maxillo-facial disorders, were randomly allocated to either i.v. propofol–remifentanil or inhalational sevoflurane anaesthesia. Transcranial Doppler was used to assess changes in cerebral blood flow velocity, carbon dioxide reactivity, cerebral autoregulation and the bispectral index to assess the depth of anaesthesia. Results. Time-averaged mean f…
Single-trial Connectivity Estimation through the Least Absolute Shrinkage and Selection Operator.
2019
Methods based on the use of multivariate autoregressive models (MVAR) have proved to be an accurate tool for the estimation of functional links between the activity originated in different brain regions. A well-established method for the parameters estimation is the Ordinary Least Square (OLS) approach, followed by an assessment procedure that can be performed by means of Asymptotic Statistic (AS). However, the performances of both procedures are strongly influenced by the number of data samples available, thus limiting the conditions in which brain connectivity can be estimated. The aim of this paper is to introduce and test a regression method based on Least Absolute Shrinkage and Selecti…