Impact of skull sutures, spongiform bone distribution, and aging skull conductivities on the EEG forward and inverse problems.

. Source imaging is a principal objective for electroencephalography (EEG), the solutions of which require forward problem (FP) computations characterising the electric potential distribution on the scalp due to known sources. Additionally, the EEG-FP is dependent upon realistic, anatomically correct volume conductors and accurate tissue conductivities, where the skull is particularly important.

Optimal design of on-scalp electromagnetic sensor arrays for brain source localisation.

Optically pumped magnetometers (OPMs) are quickly widening the scopes of noninvasive neurophysiological imaging. The possibility of placing these magnetic field sensors on the scalp allows not only to acquire signals from people in movement, but also to reduce the distance between the sensors and the brain, with a consequent gain in the signal-to-noise ratio. These advantages make the technique particularly attractive to characterise sources of brain activity in demanding populations, such as children and patients with epilepsy.

Does participant's age impact on tDCS induced fields? Insights from computational simulations.

: Understanding the induced current flow from transcranial direct current stimulation (tDCS) is essential for determining the optimal dose and treatment. Head tissue conductivities play a key role in the resulting electromagnetic fields. However, there exists a complicated relationship between skull conductivity and participant age, that remains unclear.

The analytical subtraction approach for solving the forward problem in EEG.

Objective: The subtraction approach is known for being a theoretically-rigorous and accurate technique for solving the forward problem in electroencephalography by means of the finite element method. One key aspect of this approach consists of computing integrals of singular kernels over the discretised domain, usually referred to as potential integrals. Several techniques have been proposed for dealing with such integrals, all of them approximating the results at the expense of reducing the accuracy of the solution.

Variation in Reported Human Head Tissue Electrical Conductivity Values.

Electromagnetic source characterisation requires accurate volume conductor models representing head geometry and the electrical conductivity field. Head tissue conductivity is often assumed from previous literature, however, despite extensive research, measurements are inconsistent. A meta-analysis of reported human head electrical conductivity values was therefore conducted to determine significant variation and subsequent influential factors.

Beyond episodic memory: Semantic processing as independent predictor of hippocampal/perirhinal volume in aging and mild cognitive impairment due to Alzheimer's disease.

Objective: Given that lexical-semantic decline precedes episodic memory deficits in the Alzheimer's disease (AD) timeline, it is expected that performance on a lexical-semantic task would be associated with mediotemporal volumes independently of the association this region has with episodic memory in the early stage of AD.

Method: Fifty patients with mild cognitive impairment due to AD and 50 healthy adults completed tests of lexical-semantic skills (category fluency test), episodic memory for semantically relevant material (prose memory test), episodic memory for non semantically relevant material (Rey-Osterrieth Figure test), lexical-executive abilities (letter fluency test), and a neurostructural MRI. Hippocampal, perirhinal, entorhinal, temporopolar, and orbitofrontal volumes were extracted.

Generalised coherent point drift for group-wise multi-dimensional analysis of diffusion brain MRI data.

A probabilistic framework for registering generalised point sets comprising multiple voxel-wise data features such as positions, orientations and scalar-valued quantities, is proposed. It is employed for the analysis of magnetic resonance diffusion tensor image (DTI)-derived quantities, such as fractional anisotropy (FA) and fibre orientation, across multiple subjects. A hybrid Student's t-Watson-Gaussian mixture model-based non-rigid registration framework is formulated for the joint registration and clustering of voxel-wise DTI-derived data, acquired from multiple subjects.

Sensitivity of the Projected Subtraction Approach to Mesh Degeneracies and Its Impact on the Forward Problem in EEG.

Objective: Subtraction-based techniques are known for being theoretically rigorous and accurate methods for solving the forward problem in electroencephalography (EEG-FP) by means of the finite-element method. Within them, the projected subtraction (PS) approach is generally adopted because of its computational efficiency. Although this technique received the attention of the community, its sensitivity to degenerated elements is still poorly understood.

Machine-learning Support to Individual Diagnosis of Mild Cognitive Impairment Using Multimodal MRI and Cognitive Assessments.

Background: Understanding whether the cognitive profile of a patient indicates mild cognitive impairment (MCI) or performance levels within normality is often a clinical challenge. The use of resting-state functional magnetic resonance imaging (RS-fMRI) and machine learning may represent valid aids in clinical settings for the identification of MCI patients.

Methods: Machine-learning models were computed to test the classificatory accuracy of cognitive, volumetric [structural magnetic resonance imaging (sMRI)] and blood oxygen level dependent-connectivity (extracted from RS-fMRI) features, in single-modality and mixed classifiers.

Simultaneous magnetic resonance diffusion and pseudo-diffusion tensor imaging.

Purpose: An emerging topic in diffusion magnetic resonance is imaging blood microcirculation alongside water diffusion using the intravoxel incoherent motion (IVIM) model. Recently, a combined IVIM diffusion tensor imaging (IVIM-DTI) model was proposed, which accounts for both anisotropic pseudo-diffusion due to blood microcirculation and anisotropic diffusion due to tissue microstructures. In this article, we propose a robust IVIM-DTI approach for simultaneous diffusion and pseudo-diffusion tensor imaging.

Evaluation of wave delivery methodology for brain MRE: Insights from computational simulations.

Purpose: MR elastography (MRE) of the brain is being explored as a biomarker of neurodegenerative disease such as dementia. However, MRE measures for healthy brain have varied widely. Differing wave delivery methodologies may have influenced this, hence finite element-based simulations were performed to explore this possibility.

A parametric finite element solution of the generalised Bloch-Torrey equation for arbitrary domains.

Nuclear magnetic resonance (NMR) has proven of enormous value in the investigation of porous media. Its use allows to study pore size distributions, tortuosity, and permeability as a function of the relaxation time, diffusivity, and flow. This information plays an important role in plenty of applications, ranging from oil industry to medical diagnosis.

Integration of Cognitive Tests and Resting State fMRI for the Individual Identification of Mild Cognitive Impairment.

Background: Resting-state functional magnetic resonance imaging (RS-fMRI) appears as a promising imaging technique to identify early biomarkers of Alzheimer type neurodegeneration, which can be more sensitive to detect the earliest stages of this disease than structural alterations. Recent findings have highlighted interesting patterns of alteration in resting-state activity at the mild cognitive impairment (MCI) prodromal stage of Alzheimer's disease. However, it has not been established whether RS-fMRI alterations may be of any diagnostic use at the individual patient level and whether parameters derived from RS-fMRI images add any quantitative predictive/classificatory value to standard cognitive tests (CTs).

Extent of cortical generators visible on the scalp: effect of a subdural grid.

The effect of the non-conducting substrate of a subdural grid on the scalp electric potential distribution is studied through simulations. Using a detailed head model and the finite element method we show that the governing physics equations predict an important attenuation in the scalp potential for generators located under the grid, and an amplification for generators located under holes in the skull filled with conductive media. These effects are spatially localized and do not cancel each other.

Size of cortical generators of epileptic interictal events and visibility on scalp EEG.

Growing evidence indicates that fast oscillations (>80 Hz) can be recorded interictally in the scalp EEG of patients with epilepsy, and that they may point to the seizure-onset zone. However, mechanisms underpinning the emergence of scalp fast oscillations, and whether they differ from those of interictal epileptic discharges (IEDs), are yet to be understood. The visibility of cortical electric activity on scalp EEG recordings is dependent on two factors: the characteristics of the cortical generator and the background level.

Error bounds in diffusion tensor estimation using multiple-coil acquisition systems.

We extend the diffusion tensor (DT) signal model for multiple-coil acquisition systems. Considering the sum-of-squares reconstruction method, we compute the Cramér-Rao bound (CRB) assuming the widely accepted noncentral chi distribution. Within this framework, we assess the effect of noise in DT estimation and other measures derived from it, as a function of the number of acquisition coils, as well as other system parameters.

Neural processing of emotional facial and semantic expressions in euthymic bipolar disorder (BD) and its association with theory of mind (ToM).

Background: Adults with bipolar disorder (BD) have cognitive impairments that affect face processing and social cognition. However, it remains unknown whether these deficits in euthymic BD have impaired brain markers of emotional processing.

Methodology/principal Findings: We recruited twenty six participants, 13 controls subjects with an equal number of euthymic BD participants.

Electrode and brain modeling in stereo-EEG.

Objective: To quantify the perturbation due to the presence of a measuring depth electrode on the intracranial electric potential distribution, and to study the effect of the heterogeneity and anisotropy of the brain tissues' electric conductivity.

Methods: The governing differential equations are solved with the Boundary Elements Method to compute the perturbation on the electric potential distribution caused by the presence of the measuring electrode, and with the Finite Elements Method to simulate measurements in an heterogeneous anisotropic brain model.

Results: The perturbation on the measured electric potential is negligible if the source of electric activity is located more than approximately 1mm away from the electrode.

Cortical deficits of emotional face processing in adults with ADHD: its relation to social cognition and executive function.

Although it has been shown that adults with attention-deficit hyperactivity disorder (ADHD) have impaired social cognition, no previous study has reported the brain correlates of face valence processing. This study looked for behavioral, neuropsychological, and electrophysiological markers of emotion processing for faces (N170) in adult ADHD compared to controls matched by age, gender, educational level, and handedness. We designed an event-related potential (ERP) study based on a dual valence task (DVT), in which faces and words were presented to test the effects of stimulus type (faces, words, or face-word stimuli) and valence (positive versus negative).

Shrinkage approach for EEG covariance matrix estimation.

We present a shrinkage estimator for the EEG spatial covariance matrix of the background activity. We show that such an estimator has some advantages over the maximum likelihood and sample covariance estimators when the number of available data to carry out the estimation is low. We find sufficient conditions for the consistency of the shrinkage estimators and results concerning their numerical stability.