Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

Neuromotor prostheses (NMPs) aim to replace or restore lost motor functions in paralysed humans by routeing movement-related signals from the brain, around damaged parts of the nervous system, to external effectors. To translate preclinical results from intact animals to a clinically useful NMP, movement signals must persist in cortex after spinal cord injury and be engaged by movement intent when sensory inputs and limb movement are long absent. Furthermore, NMPs would require that intention-driven neuronal activity be converted into a control signal that enables useful tasks. Here we show initial results for a tetraplegic human (MN) using a pilot NMP. Neuronal ensemble activity recorded through a 96-microelectrode array implanted in primary motor cortex demonstrated that intended hand motion modulates cortical spiking patterns three years after spinal cord injury. Decoders were created, providing a ‘neural cursor’ with which MN opened simulated e-mail and operated devices such as a television, even while conversing. Furthermore, MN used neural control to open and close a prosthetic hand, and perform rudimentary actions with a multi-jointed robotic arm. These early results suggest that NMPs based upon intracortical neuronal ensemble spiking activity could provide a valuable new neurotechnology to restore independence for humans with paralysis. The cover shows Matt Nagle, first participant in the BrainGate pilot clinical trial. He is unable to move his arms or legs following cervical spinal cord injury. Researchers at the Department of Neuroscience at Brown University, working with biotech company Cyberkinetics and 3 other institutions, demonstrate that movement-related signals can be relayed from the brain via an implanted BrainGate chip, allowing the patient to drive a computer screen cursor and activate simple robotic devices. Such neuromotor prostheses could pave the way towards systems to replace or restore lost motor function in paralysed humans. Prior to this advance, this type of work has been performed chiefly in monkeys. The latest example of such research has achieved a large increase in speed over current devices, enhancing the prospects for clinically viable brain-machine interfaces.

Neuronal ensemble control of prosthetic devices by a human with tetraplegia

Over the past 20 years, neuroimaging has become a predominant technique in systems neuroscience. One might envisage that over the next 20 years the neuroimaging of distributed processing and connectivity will play a major role in disclosing the brain's functional architecture and operational principles. The inception of this journal has been foreshadowed by an ever-increasing number of publications on functional connectivity, causal modeling, connectomics, and multivariate analyses of distributed patterns of brain responses. I accepted the invitation to write this review with great pleasure and hope to celebrate and critique the achievements to date, while addressing the challenges ahead.

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Functional and effective connectivity: a review.

Brain-computer interface (BCI) systems can be used to control limb neuroprostheses in order to restore limb functionality of paralyzed persons. Traditionally, only invasive BMI (brain machine interfaces) are thought to provide an adequate signal-to-noise ratio and bandwidth to control an upper limb neuroprosthesis accurately in a continuous manner with sufficient degrees-of-freedom. This paper supports work which already showed that it is possible to decode the velocity of executed arm/hand movements from electroencephalographic signals but using a different movement paradigm and suppressing eye movements. It was possible to decode movement velocities with a high correlation with actual executed movements. This could pave the way to a new type of prostheses control using a direct link betweeen natural hand movement imagination and prostheses movement.

Decoding of hand movement velocities in three dimensions from the EEG during continuous movement of the arm

It is well-known that human neural representations of grasping movement observation and execution share similarities. However, it remains unclear to what extent neural patterns of movement observation relate with behavioral covariates of the movement, such as muscle or kinematic activity, or with categorical models that describe hand posture or object properties. In this study, we explored the relation between EEG neural representation of observing a large variety of hand-object interaction images and two representations of the observed movement’s execution: the behavioral covariates and categorical models. We found that the EEG representation of the observation phase was correlated with the muscle representation during the execution most strongly in the movement holding phase. Furthermore, we found similarities with the categorical model that reflects the shape and the size of the object. With these findings we gain a joint understanding of the relation between movement observation and execution and a mean to facilitate an intuitive control of neuroprostheses in motor impaired individuals.

How similar are the neural patterns when observing grasping hand postures to the behavioral patterns when executing the grasp

This chapter gives an overview on the foundation of the electroencephalogram (EEG), describes its phenomena, and explains how EEG recordings can be performed. This includes types of electrodes, amplifiers, and known artifacts. Further on, the term brain–computer interface (BCI) is introduced and its components and useful experimental paradigms get explained. With an outlook of application scenarios we build the basis for further chapters in this book.

Gernot Müller-Putz

Papers

Decoding of hand movement velocities in three dimensions from the EEG during continuous movement of the arm

How similar are the neural patterns when observing grasping hand postures to the behavioral patterns when executing the grasp

Electroencephalography and Brain–Computer Interfaces

Proceedings of the Sixth International Brain-Computer Interface Meeting: BCI Past, Present, and Future

Self-paced control of an hand orthosis using SSVEP-based BCI.