Brain-Computer Interfaces

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• Publisher: Elsevier
• Year: 2020
• Print ISBN: 9780444639349
• eBook ISBN: 9780444639332
• Topic: Medicine
• Subtopic: Neurology

Brain-Computer Interfacing, Volume 168, not only gives readers a clear understanding of what BCI science is currently offering, but also describes future expectations for restoring lost brain function in patients. In-depth technological chapters are aimed at those interested in BCI technologies and the nature of brain signals, while more comprehensive summaries are provided in the more applied chapters. Readers will be able to grasp BCI concepts, understand what needs the technologies can meet, and provide an informed opinion on BCI science. - Explores how many different causes of disability have similar functional consequences (loss of mobility, communication etc.) - Addresses how BCI can be of use - Presents a multidisciplinary review of BCI technologies and the opportunities they provide for people in need of a new kind of prosthetic - Offers a comprehensive, multidisciplinary review of BCI for researchers in neuroscience and traumatic brain injury that is also ideal for clinicians in neurology and neurosurgery

Chapter 1

Human brain function and brain-computer interfaces

Nick F. Ramsey^* Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
^* Correspondence to: N.F. Ramsey, PhD, Heidelberglaan 100, Room G.03.130, Utrecht, 3584CX, The Netherlands. Tel: + 31-88-755-6863 email address: [email protected]

Abstract

Human brain function research has evolved dramatically in the last decades. In this chapter the role of modern methods of recording brain activity in understanding human brain function is explained. Current knowledge of brain function relevant to brain-computer interface (BCI) research is detailed, with an emphasis on the motor system which provides an exceptional level of detail to decoding of intended or attempted movements in paralyzed beneficiaries of BCI technology and translation to computer-mediated actions. BCI technologies that stand to benefit the most of the detailed organization of the human cortex are, and for the foreseeable future are likely to be, reliant on intracranial electrodes. These evolving technologies are expected to enable severely paralyzed people to regain the faculty of movement and speech in the coming decades.

Keywords

Human brain; Brain function; Electrophysiology; Functional MRI; Intracranial

Introduction

With the advent of techniques to record and image human brain function, huge strides have been made in locating function-specific brain regions and interpreting their activity. Functional magnetic resonance imaging (fMRI) in particular has led to increasingly detailed maps of functions, with the latest scanners operating at a magnetic field of 7 T and making submillimeter imaging possible (Fracasso et al., 2018). In this chapter I address the various techniques used currently, and in the past, to relate brain regions to specific functions and better understand the human brain. Our understanding of human brain function is of particular interest for brain-computer interface (BCI) research, which stands to benefit from using this knowledge for optimal decoding of neural activity.

BCIs stand to benefit from the accrued knowledge of functional topography, and in particular implantable BCIs that are starting to meet the daily needs of severely paralyzed people (Vansteensel et al., 2016). Electroencephalography (EEG) (Chapter 18) and functional near infrared spectroscopy (fNIRS) (Chapter 21) carry promise as noninvasive techniques, but their inherent low spatial resolution prevents them from capitalizing on the detailed topographical organization of the cortex. Given that the detailed organization provides opportunities to discriminate detailed actions and perceptions, such as movement of individual fingers or perception of different auditory inputs, intracranial BCI solutions carry the most significant promise for translating intended limb movements and speech to actuators such as robotic limbs and synthetic speech, respectively. People who may benefit the most from current developments in this area are primarily people with locked-in syndrome (LIS) due to brainstem stroke or a degenerative motor neuron disease such as amyotrophic lateral sclerosis (ALS) (Chapter 4), but with maturation of the technology, intracranial BCIs may well become attractive for people with spinal cord lesion (Chapter 6) or cerebral palsy.

An important limitation to the development of fully implantable intracranial BCIs for humans is the hardware. Currently, systems that may be used for BCI (e.g., Vansteensel et al., 2016) are designed for the purpose of closed-loop brain stimulation for movement disorders (e.g., Parkinson's disease) (Swann et al., 2018) or epilepsy (Skarpaas et al., 2019) and contain only a few channels (amplifiers). For full exploitation of the detailed brain topography, many more channels are required, but in the absence of other clinical applications that would justify the cost of hardware development, these devices need to be designed for BCI specifically. Since the BCI field is in its infancy, the market size is unknown, which places high commercial risks with potential manufacturers. As a result, such devices are not yet available. Nevertheless, research on translating brain activity to specific actions with multiple channels is ongoing, providing a basis for (near)-future multichannel intracranial BCI systems.

History of Linking Brain to Behavior

The notion that the human brain exhibits a modular organization was put forward as early as the 17th century, when Willis claimed that functions originated from the brain (Finger, 2005). It was not until the early 19th century that research into topography of brain functions took hold in the research arena, when physicians tried to link specific functions to locations on the skull. Although this art of phrenology (Combe, 1851) lacked the systematic ordering and definition of brain functions that is, in modern day, firmly embedded in related disciplines, it did arguably herald the beginning of brain function research. The early 20th century witnessed the beginning of neuropsychology, when it became possible to study people with specific brain lesions due in part to advanced weaponry in war. The investigation into the relationship between such lesions and behavior led to increasingly refined methods for measuring behavior. Examples of pioneers include Broca and Wernicke (Broca, 1865; Wernicke, 1974). In the 1930s, Penfield and colleagues initiated the field of human brain mapping with direct electrical stimulation (ESM) of the cortex during surgery, a development that made progress in the area of understanding brain function no longer dependent on brain lesions (Penfield and Boldrey, 1937). Much of their work has been the basis of our understanding of language and motor function. ESM in awake patients is even today used widely in neurosurgery to determine where important functions, notably movement and language, that need to be spared during brain tissue removal for the treatment of patients with brain tumors or epilepsy are located. ESM causes a brief sensation or disruption of function in sensory and associative cortex, a virtual lesion as it were, and a slow muscle contraction in motor cortex. With the advent of computers, in the 1960s, combined with EEG which was discovered in the 1920s (Berger, 1931), functional mapping no longer depended on real or virtual lesions. Yet the deeper brain structures resisted detection of neural electrical signals. This was no longer a limitation when methods such as positron emission tomography (PET) in the early 1980s, and fMRI in 1992 became available to image blood flow, and in particular, changes in blood flow following execution of specific tasks (Ogawa et al., 1992). The latter rapidly became a preferred instrument for mapping brain functions, in part because MRI scanners proved to be very useful in radiology and, as a result, became widely available. Two more techniques found their way to human research: single-cell recordings with microelectrodes and electrocorticography (ECoG) with disc electrodes embedded in a silicon sheet for cortical surface recordings.

In this chapter, an overview is given of how the described techniques improved our understanding of the cortical substrate of human behavior. What we now know about the organization of brain functions directly affects BCI research not only in understanding mechanisms but also in the design of a BCI system.

Measurement of Brain Functions

Brain function experiments can be divided into (virtual) lesion studies and imaging studies. For lesion studies, emphasis lies on describing the direct behavioral consequence in detail so as to distinguish from indirect consequences. One example is inability to speak, which could result from inability to activate muscles, to comprehend, or to formulate words, each of which involves a different, albeit mutually connected, brain region. The challenge in lesion studies is to narrow down the behavioral measure and thereby reduce the number of indirectly related brain regions in order to map function to anatomy. Imaging studies require a high degree of selectivity in the function that is evoked, and they do so by designing tasks (called “paradigms”) for participants. Most often, paradigms consist of two tasks that are administered in an alternating scheme. One task is designed to activate brain regions that are directly related to the function of interest but will inevitably also activate regions that are not, such as those involved in seeing the instructions or pressing a response button. To distinguish direct from indirect regions, a second task is designed to engage only the latter regions. The participant performs the paradigm while image data are acquired continuously, generating a series of data frames. In subsequent analyses, each part of the brain (channels or brain tissue volume elements called “voxels”) is tested for its responsiveness to the alternating task. Only those regions that respond differently to the tasks are conceptually related to the function of interest since all other regions either do not respond at all or respond to both tasks in the same way.

Several difficult challenges in linking brain regions to specific functions limit the strength of evidence of brain function experiments. For one, the classical view of the brain as being organized modularly, with specific regions being responsible for specific functions and thereby allowing for mapping one onto the other, is flawed. It is now recognized that networks underlie functions, with feedforward, feedback, and modulating connections. Accordingly, it is not possible to identify all the network nodes (regions) because levels of detectable activity are continuous rather than discrete (on vs off). Moreover, ...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Handbook of Clinical Neurology 3rd Series
• Foreword
• Preface
• Contributors
• Chapter 1: Human brain function and brain-computer interfaces
• Chapter 2: Brain-computer interfaces: Definitions and principles
• Chapter 3: Stroke and potential benefits of brain-computer interface
• Chapter 4: Brain-computer interfaces for people with amyotrophic lateral sclerosis
• Chapter 5: Brain damage by trauma
• Chapter 6: Spinal cord lesions
• Chapter 7: Brain-computer interfaces for communication
• Chapter 8: Applications of brain-computer interfaces to the control of robotic and prosthetic arms
• Chapter 9: Brain-computer interfaces in neurologic rehabilitation practice
• Chapter 10: Video games as rich environments to foster brain plasticity
• Chapter 11: Brain-computer interfaces for consciousness assessment and communication in severely brain-injured patients
• Chapter 12: Smart neuromodulation in movement disorders
• Chapter 13: Bidirectional brain-computer interfaces
• Chapter 14: Brain-computer interfaces and virtual reality for neurorehabilitation
• Chapter 15: Monitoring performance of professional and occupational operators
• Chapter 16: Self-health monitoring and wearable neurotechnologies
• Chapter 17: Brain-computer interfaces for basic neuroscience
• Chapter 18: Electroencephalography
• Chapter 19: iEEG: Dura-lining electrodes
• Chapter 20: Local field potentials for BCI control
• Chapter 21: Real-time fMRI for brain-computer interfacing
• Chapter 22: Merging brain-computer interface and functional electrical stimulation technologies for movement restoration
• Chapter 23: General principles of machine learning for brain-computer interfacing
• Chapter 24: Ethics and the emergence of brain-computer interface medicine
• Chapter 25: Industrial perspectives on brain-computer interface technology
• Chapter 26: Hearing the needs of clinical users
• Index