The brain as image processor and generator:towards function-restoring brain-computer-interfaces

As neuroscientists are slowly unraveling the mysteries of the brain, neurotechnology like brain-computer-interfaces (BCIs) might become a new standard for medical applications in those with brain injuries. BCIs allow for direct communication between the brain and a device, and could potentially restore links that are broken due to brain damage. In addition, a better understanding of the human mind and its mechanisms could greatly boost the success of these devices. This dissertation features (high-field) functional magnetic resonance imaging (fMRI) to study human cognitive functioning, as fMRI allows for studying the brain of living humans in great spatial detail. Firstly, the dissertation describes how well brain regions that are important for visual perception can be located between individuals. Some of these regions are in part responsible for recognizing objects like faces, bodies, places and motion. Secondly, differences in functional organization of the brain were explored between individuals by simulating the placement of a visual cortical prosthesis. Such a prosthesis can bypass the (broken) connections between the eye and brain in blind people, and potentially restore a rudimentary form of vision. Finally, new techniques were presented that show that visual perception and mental imagery are closely related, and allow for reading letter shapes directly from the mind. Together, this dissertation adds new foundations for the development of neurotechnological applications

Expanding the role of functional mri in rehabilitation research

Functional magnetic resonance imaging (fMRI) based on blood oxygenation level dependent (BOLD) contrast has become a universal methodology in functional neuroimaging. However, the BOLD signal consists of a mix of physiological parameters and has relatively poor reproducibility. As fMRI becomes a prominent research tool for rehabilitation studies involving repeated measures of the human brain, more quantitative and stable fMRI contrasts are needed. This dissertation enhances quantitative measures to complement BOLD fMRI. These additional markers, cerebral blood flow (CBF) and cerebral blood volume (CBV) (and hence cerebral metabolic rate of oxygen (CMRO₂) modeling) are more specific imaging markers of neuronal activity than BOLD. The first aim of this dissertation assesses feasibility of complementing BOLD with quantitative fMRI measures in subjects with central visual impairment. Second, image acquisition and analysis are developed to enhance quantitative fMRI by quantifying CBV while simultaneously acquiring CBF and BOLD images. This aim seeks to relax assumptions related to existing methods that are not suitable for patient populations. Finally, CBF acquisition using a low-cost local labeling coil, which improves image quality, is combined with simultaneous acquisition of two types of traditional BOLD contrast. The demonstrated enhancement of CBF, CBV and CMRO₂measures can lead to better characterization of pathophysiology and treatment effects.Ph.D.Committee Chair: Hu, Xiaoping; Committee Member: Benkeser, Paul; Committee Member: Keilholz, Shella; Committee Member: Sathian, Krish; Committee Member: Schuchard, Ronal

MEG cortical microstates: Spatiotemporal characteristics, dynamic functional connectivity and stimulus-evoked responses

EEG microstate analysis is an approach to study brain states and their fast transitions in healthy cognition and disease. A key limitation of conventional microstate analysis is that it must be performed at the sensor level, and therefore gives limited anatomical insight. Here, we generalise the microstate methodology to be applicable to source-reconstructed electrophysiological data. Using simulations of a neural-mass network model, we first established the validity and robustness of the proposed method. Using MEG resting-state data, we uncovered ten microstates with distinct spatial distributions of cortical activation. Multivariate pattern analysis demonstrated that source-level microstates were associated with distinct functional connectivity patterns. We further demonstrated that the occurrence probability of MEG microstates were altered by auditory stimuli, exhibiting a hyperactivity of the microstate including the auditory cortex. Our results support the use of source-level microstates as a method for investigating brain dynamic activity and connectivity at the millisecond scale

Time-resolved laser speckle contrast imaging (TR-LSCI) of cerebral blood flow

To address many of the deficiencies in optical neuroimaging technologies such as poor spatial resolution, time-consuming reconstruction, low penetration depth, and contact-based measurement, a novel, noncontact, time-resolved laser speckle contrast imaging (TR-LSCI) technique has been developed for continuous, fast, and high-resolution 2D mapping of cerebral blood flow (CBF) at different depths of the head. TR-LSCI illuminates the head with picosecond-pulsed, coherent, widefield near-infrared light and synchronizes a newly developed, high-resolution, gated single-photon avalanche diode camera (SwissSPAD2) to capture CBF maps at different depths. By selectively collecting diffuse photons with longer pathlengths through the head, TR-LSCI reduces partial volume artifacts from the overlying tissues, thus improving the accuracy of CBF measurement in the deep brain. CBF map reconstruction was dramatically expedited by incorporating highly parallelized computation. The performance of TR-LSCI was evaluated using head-simulating phantoms with known properties and in-vivo rodents with varied hemodynamic challenges to the brain. Results from these pilot studies demonstrated that TR-LSCI enabled mapping CBF variations at different depths with a sampling rate of up to 1 Hz and spatial resolutions ranging from tens of micrometers on the head surface to 1-2 millimeters in the deep brain. With additional improvements and validation in larger populations against established methods, we anticipate offering a noncontact, fast, high-resolution, portable, and affordable brain imager for fundamental neuroscience research in animals and for translational studies in humans.Comment: 22 pages, 7 figures, 4 table

Feasibility of functional MRI on point-of-care MR platforms

Magnetic resonance imaging (MRI) has proven to be a clinically valuable tool that can produce anatomical and functional images with improved soft tissue contrast compared to other imaging modalities. There has recently been a surge in low- and mid-field scanners due to hardware developments and innovative acquisition techniques. These compact scanners are accessible, offer reduced siting requirements and can be made operational at a reduced cost. This thesis aims to implement blood-oxygen-level-dependent (BOLD) resting-state functional MRI (fMRI) at such a mid-field point-of-care scanner. The availability of this technique can be beneficial to get neurological information in cases of traumatic brain injury, stroke, epilepsy, and dementia. This technique was previously not implemented at low- and mid-field since signal-to-noise ratio and the contrast scale with field strength. Studies were conducted to gauge the performance of an independent component analysis (ICA) based platform (GraphICA) to analyze artificially added noisy resting state functional data previously collected with a 3T scanner. This platform was used in later chapters to preprocess and perform functional connectivity studies with data from a mid-field scanner. A single echo gradient echo echoplanar imaging (GE-EPI) sequence is typically used for BOLD-based fMRI. Task-based fMRI experiments were performed with this sequence to gauge the feasibility of this technique on a mid-field scanner. Once the feasibility was established, the sequence was further optimized to suit mid-field scanners by considering all the imaging parameters. Resting-state experiments were conducted with an optimized single echo GE-EPI sequence with reduced dead time on a mid-field scanner. Temporal and image signal-to-noise ratio were calculated for different cortical regions. Along with that, functional connectivity studies and identification of resting-state networks were performed with GraphICA which demonstrated the feasibility of this resting-state fMRI at mid-field. The reliability and repeatability of the identified networks were assessed by comparing the networks identified with 3T data. Resting-state experiments were conducted with a multi-echo GE-EPI sequence to use the dead time due to long T2* at mid-field effectively. Temporal signal-to-noise was calculated for different cortical regions. Along with that, functional connectivity studies and identification of resting-state networks were performed with GraphICA which demonstrated the feasibility of this resting-state fMRI at mid-field

LayNii: a software suite for layer-fMRI

High-resolution fMRI in the sub-millimeter regime allows researchers to resolve brain activity across cortical layers and columns non-invasively. While these high-resolution data make it possible to address novel questions of directional information flow within and across brain circuits, the corresponding data analyses are challenged by MRI artifacts, including image blurring, image distortions, low SNR, and restricted coverage. These challenges often result in insufficient spatial accuracy of conventional analysis pipelines. Here we introduce a new software suite that is specifically designed for layer-specific functional MRI: LayNii. This toolbox is a collection of command-line executable programs written in C/C++ and is distributed opensource and as pre-compiled binaries for Linux, Windows, and macOS. LayNii is designed for layer-fMRI data that suffer from SNR and coverage constraints and thus cannot be straightforwardly analyzed in alternative software packages. Some of the most popular programs of LayNii contain ‘layerification’ and columnarization in the native voxel space of functional data as well as many other layer-fMRI specific analysis tasks: layer-specific smoothing, model-based vein mitigation of GE-BOLD data, quality assessment of artifact dominated sub-millimeter fMRI, as well as analyses of VASO data

Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain

Magnetoencephalography (MEG) is a noninvasive technique for investigating neuronal activity in the living human brain. The time resolution of the method is better than 1 ms and the spatial discrimination is, under favorable circumstances, 2-3 mm for sources in the cerebral cortex. In MEG studies, the weak 10 fT-1 pT magnetic fields produced by electric currents flowing in neurons are measured with multichannel SQUID (superconducting quantum interference device) gradiometers. The sites in the cerebral cortex that are activated by a stimulus can be found from the detected magnetic-field distribution, provided that appropriate assumptions about the source render the solution of the inverse problem unique. Many interesting properties of the working human brain can be studied, including spontaneous activity and signal processing following external stimuli. For clinical purposes, determination of the locations of epileptic foci is of interest. The authors begin with a general introduction and a short discussion of the neural basis of MEG. The mathematical theory of the method is then explained in detail, followed by a thorough description of MEG instrumentation, data analysis, and practical construction of multi-SQUID devices. Finally, several MEG experiments performed in the authors' laboratory are described, covering studies of evoked responses and of spontaneous activity in both healthy and diseased brains. Many MEG studies by other groups are discussed briefly as well.Peer reviewe

Social and Affective Neuroscience of Everyday Human Interaction

This Open Access book presents the current state of the art knowledge on social and affective neuroscience based on empirical findings. This volume is divided into several sections first guiding the reader through important theoretical topics within affective neuroscience, social neuroscience and moral emotions, and clinical neuroscience. Each chapter addresses everyday social interactions and various aspects of social interactions from a different angle taking the reader on a diverse journey. The last section of the book is of methodological nature. Basic information is presented for the reader to learn about common methodologies used in neuroscience alongside advanced input to deepen the understanding and usability of these methods in social and affective neuroscience for more experienced readers

+microstate: A MATLAB toolbox for brain microstate analysis in sensor and cortical EEG/MEG

+microstate is a MATLAB toolbox for brain functional microstate analysis. It builds upon previous EEG microstate literature and toolboxes by including algorithms for source-space microstate analysis. +microstate includes codes for performing individual- and group-level brain microstate analysis in resting-state and task-based data including event-related potentials/fields. Functions are included to visualise and perform statistical analysis of microstate sequences, including novel advanced statistical approaches such as statistical testing for associated functional connectivity patterns, cluster-permutation topographic ANOVAs, and analysis of microstate probabilities in response to stimuli. Additionally, codes for simulating microstate sequences and their associated M/EEG data are included in the toolbox, which can be used to generate artificial data with ground truth microstates and to validate the methodology. +microstate integrates with widely used toolboxes for M/EEG processing including Fieldtrip, SPM, LORETA/sLORETA, EEGLAB, and Brainstorm to aid with accessibility, and includes wrappers for pre-existing toolboxes for brain-state estimation such as Hidden Markov modelling (HMM-MAR) and independent component analysis (FastICA) to aid with direct comparison with these techniques. In this paper, we first introduce +microstate before subsequently performing example analyses using open access datasets to demonstrate and validate the methodology. MATLAB live scripts for each of these analyses are included in +microstate, to act as a tutorial and to aid with reproduction of the results presented in this manuscript

Social and Affective Neuroscience of Everyday Human Interaction

This Open Access book presents the current state of the art knowledge on social and affective neuroscience based on empirical findings. This volume is divided into several sections first guiding the reader through important theoretical topics within affective neuroscience, social neuroscience and moral emotions, and clinical neuroscience. Each chapter addresses everyday social interactions and various aspects of social interactions from a different angle taking the reader on a diverse journey. The last section of the book is of methodological nature. Basic information is presented for the reader to learn about common methodologies used in neuroscience alongside advanced input to deepen the understanding and usability of these methods in social and affective neuroscience for more experienced readers