Analysis of slow- and fast-alpha band asymmetry during performance of a saccadic eye movement task: Dissociation between memory- and attention-driven systems

This study aimed at analyzing the relationship between slow- and fast-alpha asymmetry within frontal cortex and the planning, execution and voluntary control of saccadic eye movements (SEM), and quantitative electroencephalography (qEEG) was recorded using a 20-channel EEG system in 12 healthy participants performing a fixed (i.e., memory-driven) and a random SEM (i.e., stimulus-driven) condition. We find main effects for SEM condition in slow- and fast-alpha asymmetry at electrodes F3-F4, which are located over premotor cortex, specifically a negative asymmetry between conditions. When analyzing electrodes F7-F8, which are located over prefrontal cortex, we found a main effect for condition in slow-alpha asymmetry, particularly a positive asymmetry between conditions. In conclusion, the present approach supports the association of slow- and fast-alpha bands with the planning and preparation of SEM, and the specific role of these sub-bands for both, the attention network and the coordination and integration of sensory information with a (oculo)-motor response. (C) 2011 Elsevier B.V. All rights reserved.

Alpha-band power in the left frontal cortex discriminates the execution of fixed stimulus during saccadic eye movement

Introduction: The saccadic paradigm has been used to investigate specific cortical networks involving attention. The behavioral and electrophysiological investigations of the SEM contribute significantly to the understanding of attentive patterns presented of neurological and psychiatric disorders and sports performance. Objective: The current study aimed to investigate absolute alpha power changes in sensorimotor brain regions and the frontal eye fields during the execution of a saccadic task. Methods: Twelve healthy volunteers (mean age: 26.25; SD: +/- 4.13) performed a saccadic task while the electroencephalographic signal was simultaneously recorded for the cerebral cortex electrodes. The participants were instructed to follow the LEDs with their eyes, being submitted to two different task conditions: a fixed pattern versus a random pattern. Results: We found a moment main effect for the C3, C4, F3 and F4 electrodes and a condition main effect for the F3 electrode. We also found interaction between factor conditions and frontal electrodes. Conclusions: We conclude that absolute alpha power in the left frontal cortex discriminates the execution of the two stimulus presentation patterns during SEM. (C) 2012 Elsevier Ireland Ltd. All rights reserved.

Functional coupling of sensorimotor and associative areas during a catching ball task: a qEEG coherence study

Abstract Background Catching an object is a complex movement that involves not only programming but also effective motor coordination. Such behavior is related to the activation and recruitment of cortical regions that participates in the sensorimotor integration process. This study aimed to elucidate the cortical mechanisms involved in anticipatory actions when performing a task of catching an object in free fall. Methods Quantitative electroencephalography (qEEG) was recorded using a 20-channel EEG system in 20 healthy right-handed participants performed the catching ball task. We used the EEG coherence analysis to investigate subdivisions of alpha (8-12 Hz) and beta (12-30 Hz) bands, which are related to cognitive processing and sensory-motor integration. Results Notwithstanding, we found the main effects for the factor block; for alpha-1, coherence decreased from the first to sixth block, and the opposite effect occurred for alpha-2 and beta-2, with coherence increasing along the blocks. Conclusion It was concluded that to perform successfully our task, which involved anticipatory processes (i.e. feedback mechanisms), subjects exhibited a great involvement of sensory-motor and associative areas, possibly due to organization of information to process visuospatial parameters and further catch the falling object.

Brain activity and medical diagnosis: an EEG study

Abstract Background Despite new brain imaging techniques that have improved the study of the underlying processes of human decision-making, to the best of our knowledge, there have been very few studies that have attempted to investigate brain activity during medical diagnostic processing. We investigated brain electroencephalography (EEG) activity associated with diagnostic decision-making in the realm of veterinary medicine using X-rays as a fundamental auxiliary test. EEG signals were analysed using Principal Components (PCA) and Logistic Regression Analysis Results The principal component analysis revealed three patterns that accounted for 85% of the total variance in the EEG activity recorded while veterinary doctors read a clinical history, examined an X-ray image pertinent to a medical case, and selected among alternative diagnostic hypotheses. Two of these patterns are proposed to be associated with visual processing and the executive control of the task. The other two patterns are proposed to be related to the reasoning process that occurs during diagnostic decision-making. Conclusions PCA analysis was successful in disclosing the different patterns of brain activity associated with hypothesis triggering and handling (pattern P1); identification uncertainty and prevalence assessment (pattern P3), and hypothesis plausibility calculation (pattern P2); Logistic regression analysis was successful in disclosing the brain activity associated with clinical reasoning success, and together with regression analysis showed that clinical practice reorganizes the neural circuits supporting clinical reasoning.

Parallel modeling of the electric field distribution in the brain

The term "Brain Imaging" identi�es a set of techniques to analyze the structure and/or functional behavior of the brain in normal and/or pathological situations. These techniques are largely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent �fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In this context, usage of classical solutions (e.g. f MRI, PET-CT) could be unfeasible, due to their low temporal resolution, high cost and limited portability. For these reasons alternative low cost techniques are object of research, typically based on simple recording hardware and on intensive data elaboration process. Typical examples are ElectroEncephaloGraphy (EEG) and Electrical Impedance Tomography (EIT), where electric potential at the patient's scalp is recorded by high impedance electrodes. In EEG potentials are directly generated from neuronal activity, while in EIT by the injection of small currents at the scalp. To retrieve meaningful insights on brain activity from measurements, EIT and EEG relies on detailed knowledge of the underlying electrical properties of the body. This is obtained from numerical models of the electric �field distribution therein. The inhomogeneous and anisotropic electric properties of human tissues make accurate modeling and simulation very challenging, leading to a tradeo�ff between physical accuracy and technical feasibility, which currently severely limits the capabilities of these techniques. Moreover elaboration of data recorded requires usage of regularization techniques computationally intensive, which influences the application with heavy temporal constraints (such as BCI). This work focuses on the parallel implementation of a work-flow for EEG and EIT data processing. The resulting software is accelerated using multi-core GPUs, in order to provide solution in reasonable times and address requirements of real-time BCI systems, without over-simplifying the complexity and accuracy of the head models.

Predittori precoci di outcome neurologico nei neonati affetti da Encefalopatia Ipossico-Ischemica sottoposti a trattamento ipotermico. Studio combinato Elettroencefalogramma ad integrazione di ampiezza e Spettroscopia nel vicino infrarosso

Background: Brain cooling (BC) represents the elective treatment in asphyxiated newborns. Amplitude Integrated Electroencephalography (aEEG) and Near Infrared Spectroscopy (NIRS) monitoring may help to evaluate changes in cerebral electrical activity and cerebral hemodynamics during hypothermia. Objectives: To evaluate the prognostic value of aEEG time course and NIRS data in asphyxiated cooled infants. Methods: 12 term neonates admitted to our NICU with moderate-severe Hypoxic-Ischemic Encephalopathy (HIE) underwent selective BC. aEEG and NIRS monitoring were started as soon as possible and maintained during the whole hypothermic treatment. Follow-up was scheduled at regular intervals; adverse outcome was defined as death, cerebral palsy (CP) or global quotient < 88.7 at Griffiths’ Scale. Results: 2/12 infants died, 2 developed CP, 1 was normal at 6 months of age and then lost at follow-up and 7 showed a normal outcome at least at 1 year of age. The aEEG background pattern at 24 hours of life was abnormal in 10 newborns; only 4 of them developed an adverse outcome, whereas the 2 infants with a normal aEEG developed normally. In infants with adverse outcome NIRS showed a higher Tissue Oxygenation Index (TOI) than those with normal outcome (80.0±10.5% vs 66.9±7.0%, p=0.057; 79.7±9.4% vs 67.1±7.9%, p=0.034; 80.2±8.8% vs 71.6±5.9%, p=0.069 at 6, 12 and 24 hours of life, respectively). Conclusions: The aEEG background pattern at 24 hours of life loses its positive predictive value after BC implementation; TOI could be useful to predict early on infants that may benefit from other innovative therapies.

Analog Signal Acquisition and Conditioning for Near-Field Capacitive Communication and Active Combined EEG-EIT Monitoring

The work of the present thesis is focused on the implementation of microelectronic voltage sensing devices, with the purpose of transmitting and extracting analog information between devices of different nature at short distances or upon contact. Initally, chip-to-chip communication has been studied, and circuitry for 3D capacitive coupling has been implemented. Such circuits allow the communication between dies fabricated in different technologies. Due to their novelty, they are not standardized and currently not supported by standard CAD tools. In order to overcome such burden, a novel approach for the characterization of such communicating links has been proposed. This results in shorter design times and increased accuracy. Communication between an integrated circuit (IC) and a probe card has been extensively studied as well. Today wafer probing is a costly test procedure with many drawbacks, which could be overcome by a different communication approach such as capacitive coupling. For this reason wireless wafer probing has been investigated as an alternative approach to standard on-contact wafer probing. Interfaces between integrated circuits and biological systems have also been investigated. Active electrodes for simultaneous electroencephalography (EEG) and electrical impedance tomography (EIT) have been implemented for the first time in a 0.35 um process. Number of wires has been minimized by sharing the analog outputs and supply on a single wire, thus implementing electrodes that require only 4 wires for their operation. Minimization of wires reduces the cable weight and thus limits the patient's discomfort. The physical channel for communication between an IC and a biological medium is represented by the electrode itself. As this is a very crucial point for biopotential acquisitions, large efforts have been carried in order to investigate the different electrode technologies and geometries and an electromagnetic model is presented in order to characterize the properties of the electrode to skin interface.

Innovative Man Machine Interfaces In Aeronautics

The research activity focused on the study, design and evaluation of innovative human-machine interfaces based on virtual three-dimensional environments. It is based on the brain electrical activities recorded in real time through the electrical impulses emitted by the brain waves of the user. The achieved target is to identify and sort in real time the different brain states and adapt the interface and/or stimuli to the corresponding emotional state of the user. The setup of an experimental facility based on an innovative experimental methodology for “man in the loop" simulation was established. It allowed involving during pilot training in virtually simulated flights, both pilot and flight examiner, in order to compare the subjective evaluations of this latter to the objective measurements of the brain activity of the pilot. This was done recording all the relevant information versus a time-line. Different combinations of emotional intensities obtained, led to an evaluation of the current situational awareness of the user. These results have a great implication in the current training methodology of the pilots, and its use could be extended as a tool that can improve the evaluation of a pilot/crew performance in interacting with the aircraft when performing tasks and procedures, especially in critical situations. This research also resulted in the design of an interface that adapts the control of the machine to the situation awareness of the user. The new concept worked on, aimed at improving the efficiency between a user and the interface, and gaining capacity by reducing the user’s workload and hence improving the system overall safety. This innovative research combining emotions measured through electroencephalography resulted in a human-machine interface that would have three aeronautical related applications: • An evaluation tool during the pilot training; • An input for cockpit environment; • An adaptation tool of the cockpit automation.

Fabry's disease and psychosis: causality or coincidence?

A 21-year-old female with Fabry's disease (FD) presented acute psychotic symptoms such as delusions, auditory hallucinations and formal thought disorders. Since the age of 14, she had suffered from various psychiatric symptoms increasing in frequency and intensity. We considered the differential diagnoses of prodromal symptoms of schizophrenia and organic schizophrenia-like disorder. Routine examinations including cognitive testing, electroencephalography and structural magnetic resonance imaging revealed no pathological findings. Additional structural and functional imaging demonstrated a minor CNS involvement of FD, yet without functional limitations. In summary our examination results support the thesis that in the case of our patient a mere coincidence of FD and psychotic symptoms is more likely than a causal connection.

Neuroelectromagnetic correlates of perceptual closure processes

Perceptual closure refers to the coherent perception of an object under circumstances when the visual information is incomplete. Although the perceptual closure index observed in electroencephalography reflects that an object has been recognized, the full spatiotemporal dynamics of cortical source activity underlying perceptual closure processing remain unknown so far. To address this question, we recorded magnetoencephalographic activity in 15 subjects (11 females) during a visual closure task and performed beamforming over a sequence of successive short time windows to localize high-frequency gamma-band activity (60–100 Hz). Two-tone images of human faces (Mooney faces) were used to examine perceptual closure. Event-related fields exhibited a magnetic closure index between 250 and 325 ms. Time-frequency analyses revealed sustained high-frequency gamma-band activity associated with the processing of Mooney stimuli; closure-related gamma-band activity was observed between 200 and 300 ms over occipitotemporal channels. Time-resolved source reconstruction revealed an early (0–200 ms) coactivation of caudal inferior temporal gyrus (cITG) and regions in posterior parietal cortex (PPC). At the time of perceptual closure (200–400 ms), the activation in cITG extended to the fusiform gyrus, if a face was perceived. Our data provide the first electrophysiological evidence that perceptual closure for Mooney faces starts with an interaction between areas related to processing of three-dimensional structure from shading cues (cITG) and areas associated with the activation of long-term memory templates (PPC). Later, at the moment of perceptual closure, inferior temporal cortex areas specialized for the perceived object are activated, i.e., the fusiform gyrus related to face processing for Mooney stimuli.

Forbidden ordinal patterns of periictal intracranial EEG indicate deterministic dynamics in human epileptic seizures

Epileptic seizures typically reveal a high degree of stereotypy, that is, for an individual patient they are characterized by an ordered and predictable sequence of symptoms and signs with typically little variability. Stereotypy implies that ictal neuronal dynamics might have deterministic characteristics, presumably most pronounced in the ictogenic parts of the brain, which may provide diagnostically and therapeutically important information. Therefore the goal of our study was to search for indications of determinism in periictal intracranial electroencephalography (EEG) studies recorded from patients with pharmacoresistent epilepsy.

Relationship between bispectral index values and volatile anesthetic concentrations during the maintenance phase of anesthesia in the B-Unaware trial

Hypnotic depth during anesthesia affects electroencephalography waveforms and electroencephalogram-derived indices, such as the bispectral index (BIS). Titrating anesthetic administration against the BIS assumes reliable relationships between BIS values, electroencephalogram waveforms, and effect site concentration, beyond loss of responsiveness. Associations among BIS, end-tidal anesthetic concentrations (ETAC), and patient characteristics were examined during anesthetic maintenance, using B-Unaware trial data.

Resting-state EEG in schizophrenia: auditory verbal hallucinations are related to shortening of specific microstates

Abnormal perceptions and cognitions in schizophrenia might be related to abnormal resting states of the brain. Previous research found that a specific class (class D) of sub-second electroencephalography (EEG) microstates was shortened in schizophrenia. This shortening correlated with positive symptoms. We questioned if this reflected positive psychotic traits or present psychopathology.

Artists' advance: decreased upper alpha power while drawing in artists compared with non-artists

Brain mechanisms associated with artistic talents or skills are still not well understood. This exploratory study investigated differences in brain activity of artists and non-artists while drawing previously presented perspective line-drawings from memory and completing other drawing-related tasks. Electroencephalography (EEG) data were analyzed for power in the frequency domain by means of a Fast Fourier Transform (FFT). Low Resolution Brain Electromagnetic Tomography (LORETA) was applied to localize emerging significances. During drawing and related tasks, decreased power was seen in artists compared to non-artists mainly in upper alpha frequency ranges. Decreased alpha power is often associated with an increase in cognitive functioning and may reflect enhanced semantic memory performance and object recognition processes in artists. These assumptions are supported by the behavioral data assessed in this study and complement previous findings showing increased parietal activations in non-artists compared to artists while drawing. However, due to the exploratory nature of the analysis, additional confirmatory studies will be needed.

On seeing the trees and the forest: Single-signal and multisignal analysis of periictal intracranial EEG

Epileptic seizures are associated with a dysregulation of electrical brain activity on many different spatial scales. To better understand the dynamics of epileptic seizures, that is, how the seizures initiate, propagate, and terminate, it is important to consider changes of electrical brain activity on different spatial scales. Herein we set out to analyze periictal electrical brain activity on comparatively small and large spatial scales by assessing changes in single intracranial electroencephalography (EEG) signals and of averaged interdependences of pairs of EEG signals.