Guidelines for the recording and evaluation of pharmaco-EEG data in man: the International Pharmaco-EEG Society (IPEG)

The International Pharmaco-EEG Society (IPEG) presents updated guidelines summarising the requirements for the recording and computerised evaluation of pharmaco-EEG data in man. Since the publication of the first pharmaco-EEG guidelines in 1982, technical and data processing methods have advanced steadily, thus enhancing data quality and expanding the palette of tools available to investigate the action of drugs on the central nervous system (CNS), determine the pharmacokinetic and pharmacodynamic properties of novel therapeutics and evaluate the CNS penetration or toxicity of compounds. However, a review of the literature reveals inconsistent operating procedures from one study to another. While this fact does not invalidate results per se, the lack of standardisation constitutes a regrettable shortcoming, especially in the context of drug development programmes. Moreover, this shortcoming hampers reliable comparisons between outcomes of studies from different laboratories and hence also prevents pooling of data which is a requirement for sufficiently powering the validation of novel analytical algorithms and EEG-based biomarkers. The present updated guidelines reflect the consensus of a global panel of EEG experts and are intended to assist investigators using pharmaco-EEG in clinical research, by providing clear and concise recommendations and thereby enabling standardisation of methodology and facilitating comparability of data across laboratories

Analysis of electroencephalography signals collected in a magnetic resonance environment: characterisation of the ballistocardiographic artefact

L’acquisizione simultanea di segnali elettroencefalografici (EEG) e immagini di risonanza magnetica funzionale (fMRI) permette di investigare attivazioni cerebrali in modo non invasivo. La presenza del campo magnetico altera però in modo non trascurabile la qualità dei segnali EEG acquisiti. In particolare due artefatti sono stati individuati: l’artefatto da gradiente e l’artefatto da ballistocardiogramma (BCG). L’artefatto da BCG è legato all’attività cardiaca del soggetto, ed è caratterizzato da elevata variabilità tra un’occorrenza e l’altra in termini di ampiezza, forma d’onda e durata dell’artefatto. Differenti algoritmi sono stati implementati al fine di rimuoverlo, ma la rimozione completa rimane ancora un difficile obiettivo da raggiungere a causa della sua complessa natura. L’argomento della tesi riguarda l’analisi di segnali EEG acquisiti in ambiente di risonanza magnetica e la caratterizzazione dell’artefatto BCG. L’obiettivo è individuare ulteriori caratteristiche dell’artefatto che possano condurre al miglioramento dei precedenti metodi, o all’implementazione di nuovi. Con questa tesi abbiamo mostrato quali sono i motivi che causano la presenza di residui artefattuali nei segnali EEG processati con i metodi presenti in letteratura. Attraverso analisi statistica abbiamo riscontrato che occorrenze dell’artefatto BCG sono caratterizzate da un ritardo variabile rispetto al picco R sull’ECG, che nella nostra analisi rappresenta l’evento di riferimento nell’attività cardiaca. Abbiamo inoltre trovato che il ritardo R-BCG varia con la frequenza cardiaca. Le successive valutazioni riguardano i maggiori contributi all’artefatto BCG. Attraverso l’analisi alle componenti principali, sono stati individuati due contributi legati al fluire del sangue dal cuore verso il cervello e alla sua pulsatilità nei vasi principali dello scalpo

EEG-fMRI Based Information Theoretic Characterization of the Human Perceptual Decision System

The modern metaphor of the brain is that of a dynamic information processing device. In the current study we investigate how a core cognitive network of the human brain, the perceptual decision system, can be characterized regarding its spatiotemporal representation of task-relevant information. We capitalize on a recently developed information theoretic framework for the analysis of simultaneously acquired electroencephalography (EEG) and functional magnetic resonance imaging data (fMRI) (Ostwald et al. (2010), NeuroImage 49: 498–516). We show how this framework naturally extends from previous validations in the sensory to the cognitive domain and how it enables the economic description of neural spatiotemporal information encoding. Specifically, based on simultaneous EEG-fMRI data features from n = 13 observers performing a visual perceptual decision task, we demonstrate how the information theoretic framework is able to reproduce earlier findings on the neurobiological underpinnings of perceptual decisions from the response signal features' marginal distributions. Furthermore, using the joint EEG-fMRI feature distribution, we provide novel evidence for a highly distributed and dynamic encoding of task-relevant information in the human brain

Dynamic glucose enhanced chemical exchange saturation transfer MRI : Optimization of methodology and characterization of cerebral transport kinetics

Dynamic glucose enhanced (DGE) chemical exchange saturation transfer (CEST) MRI is an emerging imaging technique that provides a molecular-specific type of image contrast, based on magnetic labelling of exchangeable protons. The technique enables the use of biodegradable sugars as contrast agents, and such compounds are believed to have less side effects than conventional MRI contrast agents. However, as with most novel techniques, DGE MRI is associated with technical challenges, including small contrast enhancement compared to conventional techniques, sensitivity to motion and long scan durations. Therefore, DGE MRI is not yet ready for clinical implementation, and further evaluation and methodological development are required. The focus of the work presented in this thesis has been on the optimization and development of DGE MRI in humans. We first implemented the DGE MRI technique at 7 T for evaluation in healthy volunteers, and subsequently optimized and applied the DGE imaging protocol at 3 T. We demonstrated that it is possible to measure arterial input functions using DGE MRI data, and that the arterial DGE MRI signal is correlated to the venous blood glucose level. Our experiments also showed that the glucose infusion duration should preferably be prolonged to minimize the sensory side effects of the injection. We also evaluated and compared DGE MRI tissue response curves in healthy tissue and in brain tumours and confirmed that DGE MRI enables differentiation of tumour from normal tissue, but that motion-related artefacts may complicate the interpretation. We developed a post-processing method for DGE MRI based on visualization of tissue response curve types with different characteristic temporal enhancement patterns. Finally, we developed a model for kinetic analysis of DGE MRI, accounting for the different signal origin and uptake kinetics of normal D-glucose. In summary, DGE MRI has potential for tumour detection in humans and can provide information on glucose delivery, transport, and metabolism. However, further optimization of imaging and post-processing techniques is necessary, especially at lower field strengths

Roadmap on signal processing for next generation measurement systems

Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shifting the research attention towards intelligent, data-driven, signal processing. This roadmap presents a critical overview of the state-of-the-art methods and applications aiming to highlight future challenges and research opportunities towards next generation measurement systems. It covers a broad spectrum of topics ranging from basic to industrial research, organized in concise thematic sections that reflect the trends and the impacts of current and future developments per research field. Furthermore, it offers guidance to researchers and funding agencies in identifying new prospects.AerodynamicsMicrowave Sensing, Signals & System

The NIRS Cap: Key Part of Emerging Wearable Brain-Device Interfaces

Nowadays, near‐infrared spectroscopy (NIRS) fills a niche in medical imaging due to various reasons including non‐invasiveness and portability. The special characteristics of NIRS imaging make it suitable to handle topics that were only approachable using electroencephalography (EEG) such as imaging infants and children; or studying the human brain activity during actions, like walking and drawing that require a certain amount of freedom that non‐portable devices such as magnetic resonance imaging (MRI) cannot permit. This chapter discusses the unique advantages of NIRS as a functional imaging method and the main obstacles that still prevent this technology from becoming a prominent medical imaging tool. In particular, in this chapter we focus on the design of the brain‐device interface: the NIRS cap and its important role in the imaging process

Safety of Simultaneous Scalp and Intracranial Electroencephalography Functional Magnetic Resonance Imaging

Understanding the brain and its activity is one of the great challenges of modern science. Normal brain activity (cognitive processes, etc.) has been extensively studied using electroencephalography (EEG) since the 1930’s, in the form of spontaneous fluctuations in rhythms, and patterns, and in a more experimentally-driven approach in the form of event-related potentials allowing us to relate scalp voltage waveforms to brain states and behaviour. The use of EEG recorded during functional magnetic resonance imaging (EEG-fMRI) is a more recent development that has become an important tool in clinical neuroscience, for example, for the study of epileptic activity. The primary aim of this thesis is to devise a protocol in order to minimise the health risks that are associated with simultaneous scalp and intracranial EEG during fMRI (S- icEEG-fMRI). The advances in this technique will be helpful in presenting a new imaging method that will allow the measurement of brain activity with unprecedented sensitivity and coverage. However, this cannot be achieved without assessing the safety implications of such a technique. Therefore, five experiments were performed to fulfil the primary aim. First, the safety of icEEG- fMRI using body transmit RF coil was investigated to improve the results of previous attempts using a head transmit coil at 1.5T. The results of heating increases during a high-SAR sequence were in the range of 0.2-2.4 °C at the contacts with leads positioned along the central axis inside the MRI bore. These findings suggest the need for careful lead placement. Second, also for the body transmit coil we compared the heating in the vicinity of icEEG electrodes placed inside a realistically-shaped head phantom following the addition of scalp EEG electrodes. The peak temperature change was +2.7 °C at the most superior icEEG electrode contact without scalp electrodes, and +2.1 °C at the same contact and the peak increase in the vicinity of a scalp electrode contact was +0.6 °C (location FP2). These findings show that the S-icEEG-fMRI technique is feasible if our protocol is followed carefully. Third, the heating of a realistic 3D model of icEEG electrode during MRI using EM computational simulation was investigated. The resulting peak 10 g averaged SAR was 20% higher than without icEEG. Moreover, the superior icEEG placed perpendicular to B0 showed significant local SAR increase. These results were in line with previous studies. Fourth, the possibility of simplifying a complete 8-contact with 8 wires depth icEEG electrode model into an electrode with 1-contact and 1 wire using EM simulations was addressed. The results showed similar patterns of averaged SAR values around the electrode tip during phantom and electrode position along Z for the Complete and Simplified models, except an average maximum at Z = ~2.5 W/kg for the former. The SAR values during insertion depth for the Simplified model were double those for the Complete model. The effect of extension cable length is in agreement with previous experiments. Fifth, further simulations were implemented using two more simplified models: 8-contact with 1 wire shared with all contact and 8-contact 1 wire connected to each contact at a time as well as the previously modelled simplified 1-contact 1 wire. Two sets of simulations were performed: with a single electrode and with multiple electrodes. For the single electrode, three scenarios were tested: the first simplified model used only, the second simplified models used only and the third model positioned in different 13 locations. The results of these simulations showed about 11.4-20.5-fold lower SAR for the first model than the second and 0.29-5.82-fold lower SAR for the first model than the complete model. The results also showed increased SAR for the electrode close to the head coil than the ones away from it. For the multiple electrodes, three scenarios were tested: two 1-contact and wire electrodes in different separations, multiple electrodes with their wires separated and multiple electrodes with their wires shorted. The results showed interaction between the two tested electrodes. The results of the multiple electrodes presented 2 to ~10 times higher SAR for the separated setup than the shorted. The comparison between the 1-contact with 1 wire model and the complete model is still unknown and more tests are required to show it. From the findings of this PhD research, we conclude that a body RF coil can be utilized for icEEG-fMRI at 1.5 T; however, the safety protocol has to be implemented. In addition, scalp EEG can be used in conjunction with icEEG electrodes inside the body RF coil at 1.5 T and the safety protocol has to be followed. Finally, it is feasible to perform EM computational simulations using realistic icEEG electrodes on a human model. However, simplifying the realistic icEEG electrode model might result in overestimations of the heating, although it is possible that the simplification of the model can help to simulate more complex implantations such as the implantation of multiple electrodes with their leads open circuited or short circuited, which can provide more information about the safety of implanted patients inside the MRI

Sensor Approach for Brain Pathophysiology of Freezing of Gait in Parkinson\u27s Disease Patients

Parkinson\u27s Disease (PD) affects over 1% of the population over 60 years of age and is expected to reach 1 million in the USA by the year 2020, growing by 60 thousand each year. It is well understood that PD is characterized by dopaminergic loss, leading to decreased executive function causing motor symptoms such as tremors, bradykinesia, dyskinesia, and freezing of gait (FoG) as well as non-motor symptoms such as loss of smell, depression, and sleep abnormalities. A PD diagnosis is difficult to make since there is no worldwide approved test and difficult to manage since its manifestations are widely heterogeneous among subjects. Thus, understanding the patient subsets and the neural biomarkers that set them apart will lead to improved personalized care. To explore the physiological alternations caused by PD on neurological pathways and their effect on motor control, it is necessary to detect the neural activity and its dissociation with healthy physiological function. To this effect, this study presents a custom ultra-wearable sensor solution, consisting of electroencephalograph, electromyograph, ground reaction force, and symptom measurement sensors for the exploration of neural biomarkers during active gait paradigms. Additionally, this study employed novel de-noising techniques for dealing with the motion artifacts associated with active gait EEG recordings and compared time-frequency features between a group of PD with FoG and a group of age-matched controls and found significant differences between several EEG frequency bands during start and end of normal walking (with a p\u3c0.05)