EEG-Biofeedback and epilepsy: concept, methodology and tools for (neuro)therapy planning and objective evaluation

EEG-Biofeedback and Epilepsy: Concept, Methodology and Tools for (Neuro)therapy Planning and Objective Evaluation ABSTRACT Objective diagnosis and therapy evaluation are still challenging tasks for many neurological disorders. This is highly related to the diversity of cases and the variety of treatment modalities available. Especially in the case of epilepsy, which is a complex disorder not well-explained at the biochemical and physiological levels, there is the need for investigations for novel features, which can be extracted and quantified from electrophysiological signals in clinical practice. Neurotherapy is a complementary treatment applied in various disorders of the central nervous system, including epilepsy. The method is subsumed under behavioral medicine and is considered an operant conditioning in psychological terms. Although the application areas of this promising unconventional approach are rapidly increasing, the method is strongly debated, since the neurophysiological underpinnings of the process are not yet well understood. Therefore, verification of the efficacy of the treatment is one of the core issues in this field of research. Considering the diversity in epilepsy and its various treatment modalities, a concept and a methodology were developed in this work for increasing objectivity in diagnosis and therapy evaluation. The approach can also fulfill the requirement of patient-specific neurotherapy planning. Neuroprofile is introduced as a tool for defining a structured set of quantifiable measures which can be extracted from electrophysiological signals. A set of novel quantitative features (i.e., percentage epileptic pattern occurrence, contingent negative variation level difference measure, direct current recovery index, heart rate recovery ratio, and hyperventilation heart rate index) were defined, and the methods were introduced for extracting them. A software concept and the corresponding tools (i.e., the neuroprofile extraction module and a database) were developed as a basis for automation to support the methodology. The features introduced were investigated through real data, which were acquired both in laboratory studies with voluntary control subjects and in clinical applications with epilepsy patients. The results indicate the usefulness of the introduced measures and possible benefits of integrating the indices obtained from electroencephalogram (EEG) and electrocardiogram for diagnosis and therapy evaluation. The applicability of the methodology was demonstrated on sample cases for therapy evaluation. Based on the insights gained through the work, synergetics was proposed as a theoretical framework for comprehending neurotherapy as a complex process of learning. Furthermore, direct current (DC)-level in EEG was hypothesized to be an order parameter of the brain complex open system. For future research in this field, investigation of the interactions between higher cognitive functions and the autonomous nervous system was proposed. Keywords: EEG-biofeedback, epilepsy, neurotherapy, slow cortical potentials, objective diagnosis, therapy evaluation, epileptic pattern quantification, fractal dimension, contingent negative variation, hyperventilation, DC-shifts, instantaneous heart rate, neuroprofile, database system, synergetics.Die Epilepsie ist eine komplexe neurologische Erkrankung, die auf biochemischer und physiologischer Ebene nicht ausreichend geklärt ist. Die Vielfalt der epileptischen Krankheitsbilder und der Behandlungsmodalitäten verursacht ein Defizit an quantitativen Kenngrößen auf elektrophysiologischer Basis, die die Objektivität und die Effizienz der Diagnose und der Therapieevaluierung signifikant erhöhen können. Die Neurotherapie (bzw. EEG-Biofeedback) ist eine komplementäre Behandlung, die bei Erkrankungen, welche in Zusammenhang mit Regulationsproblemen des Zentralnervensystems stehen, angewandt wird. Obwohl sich die Applikationen dieser unkonventionellen Methode erweitern, wird sie nach wie vor stark diskutiert, da deren neuro- und psychophysiologischen Mechanismen wenig erforscht sind. Aus diesem Grund ist die Ermittlung von Kenngrößen als elektrophysiologische Korrelaten der ablaufenden Prozesse zur objektiven Einstellung und Therapievalidierung eines der Kernprobleme des Forschungsgebietes und auch der vorliegenden Arbeit. Unter Berücksichtigung der aktuellen neurologischen Erkenntnisse und der durch Untersuchungen an Probanden, sowie an Epilepsie-Patienten gewonnenen Ergebnisse, wurden ein Konzept und eine Methodologie entwickelt, um die Objektivität in der Diagnose und Therapieevaluierung zu erhöhen. Die Methodologie basiert auf einem Neuroprofil, welches als ein signalanalytisches mehrdimensionales Modell eingeführt wurde. Es beschreibt einen strukturierten Satz quantifizierbarer Kenngrößen, die aus dem Elektroenzephalogramm (EEG), den ereignisbezogenen Potentialen und dem Elektrokardiogramm extrahiert werden können. Als Komponenten des Neuroprofils wurden neuartige quantitative Kenngrößen (percentage epileptic pattern occurrence, contingent negative variation level difference measure, direct current recovery index, heart rate recovery ratio, hyperventilation heart rate index) definiert und die Methoden zu deren Berechnung algorithmisiert. Die Anwendbarkeit der Methodologie wurde beispielhaft für die Evaluierung von Neurotherapien an Epilepsie-Patienten demonstriert. Als Basis für eine zukünftige Automatisierung wurden ein Softwarekonzept und entsprechende Tools (neuroprofile extraction module und die Datenbank ?NeuroBase?) entwickelt. Der Ansatz erfüllt auch die Anforderungen der patientenspezifischen Therapieplanung und kann auf andere Krankheitsbilder übertragen werden. Durch die neu gewonnenen Erkenntnisse wurde die Synergetik als ein theoretischer Rahmen für die Analyse der Neurotherapie als komplexer Lernprozess vorgeschlagen. Es wurde die Hypothese aufgestellt, dass das Gleichspannungsniveau im EEG ein Ordnungsparameter des Gehirn ist, wobei das Gehirn als ein komplexes offenes System betrachtet wird. Für zukünftige Forschungen auf dem Gebiet wird empfohlen, die Wechselwirkungen zwischen den höheren kognitiven Funktionen und dem autonomen Nervensystem in diesem Kontext zu untersuchen

Simultaneous measurement of DC-EEG and transcutaneous pCO2

DC potential shifts are the shifts observed in the EEG baseline which can last from seconds to minutes. The significance of these low-frequency components in healthy as well as pathological states of human physiology is getting more and more attention not only in scientific research but also in clinical applications. In this paper, we present our novel multimodal measurement setup for simultaneously investigating DC potential shifts in EEG (DC-EEG) and the changes in noninvasive transcutaneous pCO2 measurements. We present preliminary results of our measurements during hyperventilation and apnea, which are two commonly used activation methods for changes in pCO2

Neurotherapy: More than an Extra Feedback Loop to the Pathological Brain

Neurotherapy is a complementary treatment used in various disorders of the central nervous system (CNS), such as epilepsy and attention deficit hyperactivity. The method is subsumed under the behavioral medicine, and is considered to be an operand conditioning in psychological terms. However, its mechanisms are not well understood yet. In this article, we discuss the drawbacks of a conventional control engineering approach to analyze such a complex process (i.e. EEGbiofeedback) which elicits alterations on a complex system (i.e. CNS). Based on the results and observations we gained on the course of our clinical studies with epilepsy patients, we discuss the plausibility of a general systems theoretical approach to the neurotherapy process. Using the concepts of complexity, open systems, selforganization, and self-regulation, we underline the necessity of a systems theoretical framework. We show the analogies of the EEG-biofeedback process to other operand conditioning experiments explained via the methods of the synergetics

A Matlab toolbox for analyzing repetitive movements: application in gait and tapping experiments

Coordination and timing in repetitive movements have been intensively investigated in diverse experimental settings for understanding the underlying basic mechanisms in healthy controls. On this basic research side, there are mainly two theoretical models: the Wing-Kristofferson (WK) model and the Haken-Kelso-Bunz (HKB) model. On the clinical side of the research, several efforts have been spent on quantitatively assessing gait and other repetitive movements such as tapping, especially as an outcome measure of clinical trials in diverse neurological disorders. Nevertheless, Parkinson's disease (PD) remains the predominant disorder in the clinical literature in this context, as the tremor activity and the changes in the gait are both common symptoms in PD. Although there are motion recording systems for data acquisition in clinical settings, the tools for analysis and quantification of the extracted time-series offered by these systems are severely restricted. Therefore, we introduce a toolbox which enables the analysis of repetitive movements within the framework of the two main theoretical models of motor coordination, which explicitly focuses on varying clinical and experimental settings such as self-paced vs. cued or uni-manual vs. bi-manual measurements. The toolbox contains particular pipelines for digital signal processing. Licensed under the GNU General Public License (GNU-GPL), the open source toolbox is freely available and can be downloaded from the Github link: https://github.com/MehmetEylemKirlangic/RepetitiveMovementAnalysis . We illustrate the application of the toolbox on sample experiments of gait and tapping with a control subject, as well as with a Parkinson's patient. The patient has gone through a brain surgery for deep brain stimulation (DBS); hence, we present the results for both stimulation ON and stimulation OFF modes. Sample data are freely accessible at: https:// github.com/MehmetEylemKirlangic/DATA

3D Reconstructed cyto- muscarinic M2 receptor, and fiber archtiecture of the rat brain registered to the Waxholm Space Atlas

High-resolution multiscale and multimodal 3D models of the brain are essential tools to understand its complex structural and functional organization. Neuroimaging techniques addressing different aspects of brain organization should be integrated in a reference space to enable topographically correct alignment and subsequent analysis of the various datasets and their modalities. The Waxholm Space (http://software.incf.org/software/waxholm-space) is a publicly available 3D coordinate-based standard reference space for the mapping and registration of neuroanatomical data in rodent brains. This paper provides a newly developed pipeline combining imaging and reconstruction steps with a novel registration strategy to integrate new neuroimaging modalities into the Waxholm Space atlas. As a proof of principle, we incorporated large scale high-resolution cyto-, muscarinic M2 receptor, and fiber architectonic images of rat brains into the 3D digital MRI based atlas of the Sprague Dawley rat in Waxholm Space. We describe the whole workflow, from image acquisition to reconstruction and registration of these three modalities into the Waxholm Space rat atlas. The registration of the brain sections into the atlas is performed by using both linear and non-linear transformations. The validity of the procedure is qualitatively demonstrated by visual inspection, and a quantitative evaluation is performed by measurement of the concordance between representative atlas-delineated regions and the same regions based on receptor or fiber architectonic data. This novel approach enables for the first time the generation of 3D reconstructed volumes of nerve fibers and fiber tracts, or of muscarinic M2 receptor density distributions, in an entire rat brain. Additionally, our pipeline facilitates the inclusion of further neuroimaging datasets, e.g., 3D reconstructed volumes of histochemical stainings or of the regional distributions of multiple other receptor types, into the Waxholm Space. Thereby, a multiscale and multimodal rat brain model was created in the Waxholm Space atlas of the rat brain. Since the registration of these multimodal high-resolution datasets into the same coordinate system is an indispensable requisite for multi-parameter analyses, this approach enables combined studies on receptor and cell distributions as well as fiber densities in the same anatomical structures at microscopic scales for the first time

Wistar rat brain fibre orientation model

The 3D fibre orientation model of a male Wistar rat brain was derived from 3D-PLI as described in Axer et al. 2011a [1]. The brain was immersion fixed in 4% paraformaldehyde. After cryoprotection (10% glycerin for 3 days, followed by 20% glycerin for 14 days at +4°C), the brain was deep frozen at -50°C and stored till further processing. The brain was serially sectioned in the coronal plane (section thickness 60 μm) using a large-scale cryostat microtome (Polycut CM 3500, Leica, Germany) and coverslipped with glycerin. Immediately after coverslipping, the sections were measured using the large-area polarimeter (LAP, pixel size: 64 μm x 64 μm, cf. [1]). During sectioning, each blockface was digitized using a CCD camera mounted above the brain in order to obtain an undistorted reference image of each section. Spatial resolution in the z-direction was 60 μm. No staining was applied. This procedure resulted in an uninterrupted series of 446 sections through the entire brain, which ultimately enabled the 3D reconstruction. The application of the Jones calculus [2] describes the light transmittance through the LAP and enables the calculation of the individual spatial fiber orientation in each voxel (defined by pixel size and section thickness). The fiber orientation is defined by the pair of angles (α, φ) = (inclination, direction) indicating the fiber axis orientation out of and within the section plane, respectively. Inclination and direction angles are encoded in RGB or HSV color space to provide one fiber orientation map (FOM) per section. The entire data set of aligned FOMs (i.e. the fibre orientation model) is assembled in a single NIfTI file (http://nifti.nimh.nih.gov). FOMs are the fundamental data structure provided by 3D-PLI and have an in-plane resolution of 64 μm×64 μm, and, since each section was 60 μm thick, a spatial resolution in the z-direction of 60 μm. They contain a single 3D fiber orientation vector per voxel that is interpreted as the spatial orientation of the fibers in this voxel. Non-linear deformations introduced by brain sectioning and mounting were corrected using blockface images as undistorted references for the spatial alignment of 3D-PLI FOMs. Hence, in a first step the blockface images had to be 3D reconstructed. The reconstruction method consisted of a two-phase registration: a marker-based alignment of the blockface images and a refinement of the pre-reconstructed volume using 3D information [3]. The 3D reconstruction of the FOMs was done in two steps: (i) a 3D affine registration ensured the correct spatial alignment of the brains and (ii) a subsequent 3D non-linear registration compensated non-linear distortions of the brain sections. Using segmented images the centers of gravity of the corresponding brain masks were calculated and aligned. Based on this initial transformation, an intensity based rigid registration was performed using mutual information as metric. The second step, the refinement, was done by means of a slice-by-slice B-Spline registration with sum of squared differences as metric and a grid size of 5 × 6 [4]. Afterwards the fibre orientation model was transferred into the common rodent reference space, the Waxholm Space atlas [5]. The transformation of the brains into the same space was also done in the two step strategy described above. **References** [1] Axer, M., Amunts, K., Gräßel, D., Palm, C., Dammers, J., Axer, H., et al. (2011a). A novel approach to the human connectome: ultra-high resolution mapping of fiber tracts in the brain. NeuroImage 54, 1091–1101. doi: 10.1016/j.neuroimage.2010.08.075 [2] Jones, RC. (1941) A new calculus for the treatment of optical systems. J. Opt. Soc. Am. 31, 488–503. doi:10.1364/JOSA.31.000488 [3] Schober, M., Schlömer, P., Cremer, M., Mohlberg, H., Huynh, A.-M., Schubert, N., et al. (2015). “Reference volume generation for subsequent 3D reconstruction of histological sections,” in Proceedings of Bildverarbeitung für die Medizin, (Lübeck), 143–148. [4] Schubert, N., Kirlangic, M. E., Schober, M., Huynh, A.-M., Amunts, K., Zilles, K., et al. (2016). 3D Reconstructed Cyto-, Muscarinic M2 Receptor, and Fiber Architecture of the Rat Brain Registered to the Waxholm Space Atlas. Frontiers Neuroanatomy 10, 1-13. doi: 10.3389/fnana.2016.00051 [5] Papp, E. A., Leergaard, T. B., Calabrese, E., Johnson, G. A., and Bjaalie, J. G. (2014). Waxholm space atlas of the Spraque Dawley rat brain. NeuroImage 97, 374–386. doi: 10.1016/j.neuroimage.2014.04.00