This paper investigates the performance of calibration techniques on synthetic Electroencephalography (EEG) data. Brain source localization was performed using an iterative algorithm. A transfer-function-based calibration technique was developed. This technique can be applied in two forms: external calibration and autocalibration. For a low density EEG array system, it was shown that the propos...

ABSTRACT: A statistical mechanics of neuronal interactions (SMNI) is explored as providing some a basis for correlating EEG evoked potentials to reaction times. Some specific elements of SMNI, previously used to develop a theory of short-term memory (STM) and a model of electroencephalography (EEG) are key to providing this basis. Hick’s Law, an observed linear relationship between reaction tim...

The goal of the inverse problem in electroencephalography is to determine electrical activity within the cranial volume based on potential measurements taken from the scalp. In this paper we discuss the modeling components of our software system for solving the inverse EEG problem. Our implementation is constructed within the BioPSE problem solving environment, a flexible framework for implemen...

Brainstorm is a collaborative open-source application dedicated to magnetoencephalography (MEG) and electroencephalography (EEG) data visualization and processing, with an emphasis on cortical source estimation techniques and their integration with anatomical magnetic resonance imaging (MRI) data. The primary objective of the software is to connect MEG/EEG neuroscience investigators with both t...

A plausible model of the statistical mechanics of neocortical interactions (SMNI), spans several important neuroscientific phenomena including phenomena measured by electroencephalography (EEG) (Ingber, 1982; Ingber, 1983; Ingber, 1984; Ingber, 1985a; Ingber, 1985b; Ingber, 1991; Ingber, 1992; Ingber, 1994; Ingber, 1995a; Ingber and Nunez, 1990). Fitted SMNI functional forms to EEG data may hel...

Sensed signals from the human body provide information about the health status. The basic clinical methods used for the diagnosis of neural disorders include electroencephalography (EEG). There are a number of algorithms for automatic localization of epileptic graphoelements. Currently, the most widespread disease of the brain is epilepsy which can be diagnosed by using EEG. We will further dea...

Nowadays, electroencephalography signals can be acquired from a patient lying in a magnetic resonance imaging system. It is even possible to acquire EEG signals during an MR imaging sequence. However, such EEG signals are severely distorted by artifacts originating from various effects (e.g., MR gradients, ECG). In this paper, a simple method is presented to reduce such artifacts. Thereby, spec...

Responsive neurostimulation (RNS) is rapidly gaining traction as a therapy for medically refractory epilepsy. Depth electrode placement for stimulation of a deep seizure focus may be indicated after the focus has been electrophysiologically localized using depth electroencephalography (depth EEG). We describe a simple technique whereby the bony trajectories created during initial stereotactic p...

Traumatic brain injury (TBI) is a silent epidemic. Mild traumatic brain injury (mTBI) causes brain injury that results in electrophysiologic abnormalities visible on electroencephalography (EEG) recordings. The purpose of this brief review was to discuss the importance of EEG findings in traumatic brain injury. Relevant articles published during the 1996-2016 period were retrieved from Medline ...

Introduction: Both functional magnetic resonance imaging (FMRI) and electroencephalography (EEG) show interesting and structured phenomena during rest; i.e. Resting State Networks (RSNs) in FMRI and rhythmic oscillations in EEG. In addition, many studies have now shown FMRI activation maps derived from EEG rhythms. Mantini el al. [1] have demonstrated that some temporal correlation exists betwe...