Convolutional neural network propagation on electroencephalographic scalograms for detection of schizophrenia.

Objective: Electroencephalographic analysis (EEG) has emerged as a powerful tool for brain state interpretation. Studies have shown distinct deviances of patients with schizophrenia in EEG activation at specific frequency bands.

Methods: Evidence is presented for the validation of a Convolutional Neural Network (CNN) model using transfer learning for scalp EEGs of patients and controls during the performance of a speeded sensorimotor task and a working memory task.

A condition-independent framework for the classification of error-related brain activity.

The cognitive processing and detection of errors is important in the adaptation of the behavioral and learning processes. This brain activity is often reflected as distinct patterns of event-related potentials (ERPs) that can be employed in the detection and interpretation of the cerebral responses to erroneous stimuli. However, high-accuracy cross-condition classification is challenging due to the significant variations of the error-related ERP components (ErrPs) between complexity conditions, thus hindering the development of error recognition systems.

Discrete states of attention during active visual fixation revealed by Markovian analysis of the time series of intrusive saccades.

The frequency of intrusive saccades during maintenance of active visual fixation has been used as a measure of sustained visual attention in studies of healthy subjects as well as of neuropsychiatric patient populations. In this study, the mechanism that generates intrusive saccades during active visual fixation was investigated in a population of young healthy men performing three sustained fixation tasks (fixation to a visual target, fixation to a visual target with visual distracters, and fixation straight ahead in the dark). Markov Chain modeling of inter-saccade intervals (ISIs) was utilized.

EEG-based investigation of brain connectivity changes in psychotic patients undergoing the primitive expression form of dance therapy: a methodological pilot study.

Primitive expression (PE) is a form of dance therapy (DT) that involves an interaction of ethologically and socially based forms which are supplied for re-enactment. There exist very few studies of DT applications including in their protocol the measurement of neurophysiological parameters. The present pilot study investigates the use of the correlation coefficient (ρ) and mutual information (MI), and of novel measures extracted from ρ and MI, on electroencephalographic (EEG) data recorded in patients with schizophrenia while they undergo PE DT, in order to expand the set of neurophysiology-based approaches for quantifying possible DT effects, using parameters that might provide insights about any potential brain connectivity changes in these patients during the PE DT process.

Automatic identification of oculomotor behavior using pattern recognition techniques.

In this paper, a methodological scheme for identifying distinct patterns of oculomotor behavior such as saccades, microsaccades, blinks and fixations from time series of eye's angular displacement is presented. The first step of the proposed methodology involves signal detrending for artifacts removal and estimation of eye's angular velocity. Then, feature vectors from fourteen first-order statistical features are formed from each angular displacement and velocity signal using sliding, fixed-length time windows.

Amplitude normalization applied to an artificial neural network-based automatic sleep spindle detection system.

Sleep spindles are significant rhythmic transients present in the sleep electroencephalogram (EEG) of non-rapid eye movement (NREM) sleep. Automatic sleep spindle detection techniques are sought for the automation of sleep staging and the detailed study of sleep spindle patterns, of possible physiological significance. A deficiency of many of the available automatic detection techniques is their reliance on the amplitude level of the recorded EEG voltage values.

Dynamics of regional brain activity in epilepsy: a cross-disciplinary study on both intracranial and scalp-recorded epileptic seizures.

Objective: Recent cross-disciplinary literature suggests a dynamical analogy between earthquakes and epileptic seizures. This study extends the focus of inquiry for the applicability of models for earthquake dynamics to examine both scalp-recorded and intracranial electroencephalogram recordings related to epileptic seizures.

Approach: First, we provide an updated definition of the electric event in terms of magnitude and we focus on the applicability of (i) a model for earthquake dynamics, rooted in a nonextensive Tsallis framework, (ii) the traditional Gutenberg and Richter law and (iii) an alternative method for the magnitude-frequency relation for earthquakes.

Performance evaluation of an Artificial Neural Network automatic spindle detection system.

Sleep spindles are transient waveforms found in the electroencephalogram (EEG) of non-rapid eye movement (NREM) sleep. Sleep spindles are used for the classification of sleep stages and have been studied in the context of various psychiatric and neurological disorders, such as Alzheimer's disease (AD) and the so-called Mild Cognitive Impairment (MCI), which is considered to be a transitional stage between normal aging and dementia. The visual processing of whole-night sleep EEG recordings is tedious.

Effect of frequency deviance direction on performance and mismatch negativity.

The mismatch negativity (MMN) component of the auditory event-related potential is associated with automatic perceptual inference concerning changes in auditory stimulation. Recent studies have addressed the question whether performance and MMN is affected by the direction of frequency deviance. In the present study, the frequency MMN and performance is investigated during an auditory identification task.

Single-trial magnetoencephalography signals encoded as an unfolding decision process.

The model of a stochastic decision process unfolding in motor and premotor regions of the brain was encoded in single-trial magnetoencephalographic (MEG) recordings while ten healthy subjects performed a sensorimotor Reaction Time (RT) task. The duration of single-trial MEG signals preceding the motor response, recorded over the motor cortex contralateral to the responding hand, co-varied with RT across trials according to the model's prediction. Furthermore, these signals displayed the same properties of a "rising-to-a-fixed-threshold" decision process as posited by the model and observed in the activity of single neurons in the primate cortex.

Classification of Error-Related Negativity (ERN) and Positivity (Pe) potentials using kNN and Support Vector Machines.

Error processing in subjects performing actions has been associated with the Event-Related Potential (ERP) components called Error-Related Negativity (ERN) and Error Positivity (Pe). In this paper, features based on statistical measures of the sample of averaged ERP recordings are used for classifying correct from incorrect actions. Three feature selection techniques were used and compared.

Independent component analysis for source localization of EEG sleep spindle components.

Sleep spindles are bursts of sleep electroencephalogram (EEG) quasirhythmic activity within the frequency band of 11-16 Hz, characterized by progressively increasing, then gradually decreasing amplitude. The purpose of the present study was to process sleep spindles with Independent Component Analysis (ICA) in order to investigate the possibility of extracting, through visual analysis of the spindle EEG and visual selection of Independent Components (ICs), spindle "components" (SCs) corresponding to separate EEG activity patterns during a spindle, and to investigate the intracranial current sources underlying these SCs. Current source analysis using Low-Resolution Brain Electromagnetic Tomography (LORETA) was applied to the original and the ICA-reconstructed EEGs.

Mismatch task conditions and error related ERPs.

Background: The N200 component of event related potentials (ERPs) is considered an index of monitoring error related responses. The aim of the present work was to study the effect of mismatch conditions on the subjects' responses in an auditory identification task and their relation to the N200 of stimulus-locked ERPs.

Methods: An auditory identification task required to correctly map a horizontal slider onto an active frequency range by selecting a slider position that matched the stimulus tone in each trial.

Classification of event-related potentials associated with response errors in actors and observers based on autoregressive modeling.

Event-Related Potentials (ERPs) provide non-invasive measurements of the electrical activity on the scalp related to the processing of stimuli and preparation of responses by the brain. In this paper an ERP-signal classification method is proposed for discriminating between ERPs of correct and incorrect responses of actors and of observers seeing an actor making such responses. The classification method targeted signals containing error-related negativity (ERN) and error positivity (Pe) components, which are typically associated with error processing in the human brain.

Behavioral and brain pattern differences between acting and observing in an auditory task.

Background: Recent research has shown that errors seem to influence the patterns of brain activity. Additionally current notions support the idea that similar brain mechanisms are activated during acting and observing. The aim of the present study was to examine the patterns of brain activity of actors and observers elicited upon receiving feedback information of the actor's response.

Independent components of sleep spindles.

Sleep spindles are considered a hallmark of stage 2 of the sleep electroencephalogram (EEG) and are used both for sleep staging and for clinical studies of pharmacological agents. Analyses of sleep spindle topography, as well as intracranial source investigations provided evidence for the existence of two distinct sleep spindle types, "slow" and "fast" spindles at approximately 12 and 14 Hz, respectively. The aim of the present study was to apply Independent Component Analysis (ICA) to sleep spindles, for examining the possibility of extracting, through visual analysis of the spindle EEG and selection of Independent Components (ICs), spindle "components" corresponding to separate EEG activity patterns, and to investigate the sources underlying these spindle components.

Upgrading undergraduate biomedical engineering laboratory training.

This paper presents the upgrading of biomedical engineering laboratory training at the Department of Medical Instrumentation Technology of the Technological Educational Institution of Athens (TEI-A), taking place in the framework of the "Upgrading of Undergraduate Curricula of TEI-A" project. The educational material of selected specialized laboratory sectors is totally renewed, and new sectors are introduced, so that student-centered learning is promoted utilizing advanced computer-enhanced educational environments. The current implementation status is presented for the laboratories dealing with biosignal acquisition, medical data digital processing and, more extensively, computer networks applications in medicine, where a training application simulating a Radiology Department computer network was developed.

Identifying Differences in the P600 Component of ERP-Signals between OCD Patients and Controls Employing a PNN-based Majority Vote Classification Scheme.

In the present study an attempt was made to focus in the differences between Obsessive-Compulsive Disorder (OCD) patients and healthy controls, as reflected by the P600 component of event-related potential (ERP) signals, to locate brain areas that may be related to Working Memory (WM) deficits. Neuropsychological research has yielded contradicting results regarding WM in OCD. Eighteen patients with OCD symptomatology and 20 normal controls (age and sex matched) were subjected to a computerized version of the digit span Wechsler test.

Independent component analysis applied to the P600 component of event-related potentials.

The analysis of the P600 component of Event-related Potentials (ERPs) has attracted attention due to its relation to covert cognitive mechanisms, in connection to memory processes. The component may often be low-amplitude, compared to other components such as the P300. Independent component analysis (ICA) techniques have been successfully applied in ERP processing, in the framework of blind source separation (BSS) for unmixing recorded potentials into a sum of temporally independent and spatially fixed components.

Upgrading the biomedical engineering undergraduate curriculum based on current trends in higher education.

This paper presents the reforming of the curriculum of the Department of Medical Instrumentation Technology at the Technological Educational Institution of Athens (TEI-A), as inspired by current trends in higher education. The reforming is taking place in the framework of the "Upgrading of Undergraduate Curricula of TEI-A" project The project-funded upgrading focuses on a core of eight laboratory sectors, with particular emphasis placed on student-centered learning, taking advantage of computer-enhanced educational environment. The existing and proposed curricula are compared.

Sleep spindle detection using artificial neural networks trained with filtered time-domain EEG: a feasibility study.

An artificial neural network (ANN) based on the Multi-Layer Perceptron (MLP) architecture is used for detecting sleep spindles in band-pass filtered electroencephalograms (EEG), without feature extraction. Following optimum classification schemes, the sensitivity of the network ranges from 79.2% to 87.

Psychophysiological differences in schizophrenics with and without delusional misidentification syndromes: a P300 study.

There is a debate on whether delusional misidentification syndromes (DMSs) and schizophrenia are distinct disorders. Information-processing deficits have been found in both. Since the P300 component of event-related potentials (ERPs) reflects attention and working memory (WM) mechanisms, the P300 elicited during a WM test was studied in schizophrenic patients with DMS in comparison to schizophrenic patients without DMS and controls.

Long-term abstinence syndrome in heroin addicts: indices of P300 alterations associated with a short memory task.

Attentional deficits have been implicated in the pathophysiology of opioid addicts. The P300 component of event-related potentials (ERPs) is considered as a manifestation of attentional operations. The authors' goal was the comparison of P300 elicited during a short memory test between subjects with prolonged heroin abstinence and current heroin users as well as healthy controls.

Psychophysiological correlates of patients with delusional misidentification syndromes and psychotic major depression.

Background: Psychotic major depression (PMD) and delusional misidentification syndromes (DMS) exhibit cognitive deficits. Since the P300 component of event-related potentials (ERPs) provides valuable information concerning cognition, we studied this component of ERPs in DMS and PMD patients.

Methods: Nine patients with DMS, 15 patients with PMD, and 11 healthy controls, matched for age, sex and educational level, were tested using the auditory P300 component of ERPs.