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 interfaces (BCIs) provide more independence to people with severe motor disabilities but current BCIs’ performance is still not optimal and often the user’s intentions are misinterpreted. Error-related potentials (ErrPs) are the neurophysiological signature of error processing and their detection can help improving a BCI’s performance.A major inconvenience of BCIs is that they commonly require a long calibration period, before the user can receive feedback of their own brain signals. Here, we use the data of 15 participants and compare the performance of a personalized ErrP classifier with a generic ErrP classifier. We concluded that there was no significant difference in classification performance between the generic and the personalized classifiers (Wilcoxon signed rank tests, two-sided and one-sided left and right). This results indicate that the use of a generic ErrP classifier is a good strategy to remove the calibration period of a ErrP classifier, allowing participants to receive immediate feedback of the ErrP detections.

A Generic Error-related Potential Classifier Offers a Comparable Performance to a Personalized Classifier

We developed a framework for systematic evaluation of BCI systems. This framework is intended to compare features extracted from a variety of spectral measures related to functional connectivity, effective connectivity, or instantaneous power. Different measures are treated in a consistent manner, allowing fair comparison within a repeated measures design. We applied the framework to BCI data from 14 subjects recorded on two days each, and demonstrated the framework's feasibility by confirming results from the literature. Furthermore, we could show that electrode selection becomes more focal in the second BCI session, but classification accuracy stays unchanged.

Towards a framework based on single trial connectivity for enhancing knowledge discovery in BCI

The past four years have seen major advances in the field of brain–computer interfaces (BCIs) (also known as brain–machine interfaces or BMIs). The journal Brain–Computer Interfaces published its f...

The Sixth International Brain-Computer Interface Meeting: Advances in Basic and Clinical Research.

A corrigendum on EEG beta suppression and low gamma modulationare different elements of human upright walking by Seeber,M.,Scherer,R.,Wagner,J.,Solis-Escalante,T.,andMuller-Putz,G.R.(2014)Front.Hum. Neurosci.8:485.doi:10.3389/fnhum.2014.00485

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Corrigendum: EEG beta suppression and low gamma modulation are different elements of human upright walking

This work was supported by the FP7 EU Research Project BETTER (247935). The authors are thankful to Silvia Mena del Horno and Javier Bonilla for assistance during the experiments.

/pdf/cortical-activation-patterns-of-cue-paced-foot-movement-in-4co9xjv5tt.pdf

Gernot Müller-Putz

Papers

A Generic Error-related Potential Classifier Offers a Comparable Performance to a Personalized Classifier

Towards a framework based on single trial connectivity for enhancing knowledge discovery in BCI

The Sixth International Brain-Computer Interface Meeting: Advances in Basic and Clinical Research.

Corrigendum: EEG beta suppression and low gamma modulation are different elements of human upright walking

Cortical Activation Patterns of Cue-Paced Foot Movement in Subacute Stroke Patients.