Search results for " EEG"
showing 10 items of 78 documents
The Method of Fundamental Solutions in Solving Coupled Boundary Value Problems for M/EEG
2015
The estimation of neuronal activity in the human brain from electroencephalography (EEG) and magnetoencephalography (MEG) signals is a typical inverse problem whose solution pro- cess requires an accurate and fast forward solver. In this paper the method of fundamental solutions is, for the first time, proposed as a meshfree, boundary-type, and easy-to-implement alternative to the boundary element method (BEM) for solving the M/EEG forward problem. The solution of the forward problem is obtained by numerically solving a set of coupled boundary value problems for the three-dimensional Laplace equation. Numerical accuracy, convergence, and computational load are investigated. The proposed met…
Electrocortical networks in Parkinson's disease patients with Mild Cognitive Impairment. The PaCoS study
2019
Abstract Introduction Parkinson's Disease (PD) is frequently associated with cognitive dysfunction ranging from Mild Cognitive Impairment (PD-MCI) to dementia. Few electrophysiological studies are available evaluating potential pathogenetic mechanisms linked to cognitive impairment in PD since its initial phases. The objective of the study is to analyze electrocortical networks related with cognitive decline in PD-MCI for identifying possible early electrophysiological markers of cognitive impairment in PD. Methods From the PaCoS (Parkinson's disease Cognitive impairment Study) cohort, a sample of 102 subjects including 46 PD-MCI and 56 PD with normal cognition (PD-NC) was selected based on…
Time-resolved classification of dog brain signals reveals early processing of faces, species and emotion
2020
Dogs process faces and emotional expressions much like humans, but the time windows important for face processing in dogs are largely unknown. By combining our non-invasive electroencephalography (EEG) protocol on dogs with machine-learning algorithms, we show category-specific dog brain responses to pictures of human and dog facial expressions, objects, and phase-scrambled faces. We trained a support vector machine classifier with spatiotemporal EEG data to discriminate between responses to pairs of images. The classification accuracy was highest for humans or dogs vs. scrambled images, with most informative time intervals of 100–140 ms and 240–280 ms. We also detected a response sensitive…
Understanding developmental language disorder-The Helsinki longitudinal SLI study (HelSLI): A study protocol
2018
Background Developmental language disorder (DLD, also called specific language impairment, SLI) is a common developmental disorder comprising the largest disability group in pre-school-aged children. Approximately 7% of the population is expected to have developmental language difficulties. However, the specific etiological factors leading to DLD are not yet known and even the typical linguistic features appear to vary by language. We present here a project that investigates DLD at multiple levels of analysis and aims to make the reliable prediction and early identification of the difficulties possible. Following the multiple deficit model of developmental disorders, we investigate the DLD …
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…
Psychogenic nonepileptic seizures in pediatric population: A review
2019
Abstract Introduction Psychogenic nonepileptic seizures (PNES) are observable abrupt paroxysmal changes in behavior or consciousness that resemble epileptic seizures, but without concurrent electroencephalographic abnormalities. Methods In this manuscript, we reviewed literature concerning pediatric PNES and focused on those articles published in the last 10 years, in order to try to understand what the state of the art is at the moment, particularly as regards relationship and differential diagnosis with epilepsy. Results Psychogenic nonepileptic seizures have been extensively described in literature mainly in adults and less frequently in children. Despite the potential negative impact of…
The hairy elbows syndrome: clinical and neuroradiological findings.
2009
The hairy elbows syndrome (HES) is a rare congenital phenotype characterized by an abnormal increase in long hairs localized on the upper limbs extensor surfaces. This feature is often associated with short stature, facial asymmetry, dysmorphisms, intrauterine growth retardation (IUGR), and mental and speech delay. We report a case with hypertricosis cubiti associated with infantile spasms, behaviour disorders and cerebral hemisphere asymmetry. Although these findings have not been previously described we are uncertain whether they are unusual or underestimated. However, it is likely that these neurological findings are strongly interrelated leading to a more severe phenotype of the syndrom…
TMS-evoked long-lasting artefacts: A new adaptive algorithm for EEG signal correction
2017
Abstract Objective During EEG the discharge of TMS generates a long-lasting decay artefact (DA) that makes the analysis of TMS-evoked potentials (TEPs) difficult. Our aim was twofold: (1) to describe how the DA affects the recorded EEG and (2) to develop a new adaptive detrend algorithm (ADA) able to correct the DA. Methods We performed two experiments testing 50 healthy volunteers. In experiment 1, we tested the efficacy of ADA by comparing it with two commonly-used independent component analysis (ICA) algorithms. In experiment 2, we further investigated the efficiency of ADA and the impact of the DA evoked from TMS over frontal, motor and parietal areas. Results Our results demonstrated t…
The angelman syndrome: A brief review
2017
Angelman's Syndrome (AS) was described for the first time by Harry Angelman in the 1960s, based on obervation of three child patients with similar physical and behavioral features such as severe intellectual impairment, lack of language, motor disorders and happy behaviour. Many years later the typical patients' features were identified as linked to genetic abnormalities mainly characterized by neurological symptoms. Life expectancy is good although the symptoms tend to be stable and severe.
Multivariate correlation measures reveal structure and strength of brain–body physiological networks at rest and during mental stress
2021
In this work, we extend to the multivariate case the classical correlation analysis used in the field of network physiology to probe dynamic interactions between organ systems in the human body. To this end, we define different correlation-based measures of the multivariate interaction (MI) within and between the brain and body subnetworks of the human physiological network, represented, respectively, by the time series of delta, theta, alpha, and beta electroencephalographic (EEG) wave amplitudes, and of heart rate, respiration amplitude, and pulse arrival time (PAT) variability. MI is computed: (i) considering all variables in the two subnetworks to evaluate overall brain–body interaction…