General principles of machine learning for brain-computer interfacing

Differences in peripheral microcirculatory blood flow regulation in chronic kidney disease based on wavelet analysis of resting near-infrared spectroscopy

Vascular impairment is closely related to increased mortality in chronic kidney disease (CKD). The objective of this study was to assess impairments in the regulation of peripheral microvascular perfusion in patients with CKD based on time-frequency spectral analysis of resting near-infrared spectroscopy (NIRS) signals. Total hemoglobin (tHb) concentration and tissue saturation index (TSI) signals were collected using NIRS for a continuous 5 mins at 10 Hz from the forearm of 55 participants (34 CKD including 5 with end-stage renal disease, and 21 age-matched control). Continuous wavelet transform-based spectral analysis was used to quantify the spectral amplitude within five pre-defined frequency intervals (I, 0.0095-0.021 Hz; II, 0.021-0.052 Hz; III, 0.052-0.145 Hz; IV, 0.145-0.6 Hz and V, 0.6-2.0 Hz), representing endothelial, neurogenic, myogenic, respiratory and heartbeat activity, respectively. CKD patients showed lower tHb average spectral amplitude within the neurogenic frequency interval compared with controls (p = 0.014), consistent with an increased sympathetic outflow observed in CKD. CKD patients also showed lower TSI average spectral amplitude within the endothelial frequency interval compared with controls (p = 0.046), consistent with a reduced endothelial function in CKD. These findings demonstrate the potential of wavelet analysis of NIRS to provide complementary information on peripheral microvascular regulation in CKD.

Neurorobotics and neuroprostheses: Towards a new anatomy

The idea of this Special Issue arose from the technological advances in bionic, robotic, and neural rehabilitation systems and the common need to comprehend in detail how human anatomical structures can be replicated or controlled. Motor control theories, among others, include the generalized control program theory, the equilibrium point hypothesis, or the optimal control approach in which neural commands to the muscles are a result of the central nervous system solving an optimization problem for a specific cost function. No matter the alternative interpretation selected to replicate biological control of human movements, artificial "anatomies" should consider not only motor capabilities from the central nervous system but integrate bioinspired mechanical features (such as compliance) in artificial limbs. The development of wearable robotics and neuroprosthetic systems for human movement compensation and control is naturally inspired by human anatomy and biology. Cutting-edge technological advances in the field of biomedical and neural engineering are bringing us more and more close to a new artificial anatomy with which humans could augment their motor capabilities or replace them after they are compromised. Either augmentative/assistive or rehabilitation technologies in the near future will require engineering solutions based on novel approaches to create usable neurorobotic and neuroprosthetic systems for the most relevant societal needs.

Beyond the brain-computer interface: Decoding brain activity as a tool to understand neuronal mechanisms subtending cognition and behavior

One of the major challenges in system neurosciences consists in developing techniques for estimating the cognitive information content in brain activity. This has an enormous potential in different domains spanning from clinical applications, cognitive enhancement to a better understanding of the neural bases of cognition. In this context, the inclusion of machine learning techniques to decode different aspects of human cognition and behavior and its use to develop brain-computer interfaces for applications in neuroprosthetics has supported a genuine revolution in the field. However, while these approaches have been shown quite successful for the study of the motor and sensory functions, success is still far from being reached when it comes to covert cognitive functions such as attention, motivation and decision making. While improvement in this field of BCIs is growing fast, a new research focus has emerged from the development of strategies for decoding neural activity. In this review, we aim at exploring how the advanced in decoding of brain activity is becoming a major neuroscience tool moving forward our understanding of brain functions, providing a robust theoretical framework to test predictions on the relationship between brain activity and cognition and behavior.

Brain death debates: from bioethics to epistemology

50 years after its introduction, brain death remains controversial among scholars. The debates focus on one question: is brain death a good criterion for determining death? This question has been answered from various perspectives: medical, metaphysical, ethical, and legal or political. Most authors either defend the criterion as it is, propose some minor or major revisions, or advocate abandoning it and finding better solutions to the problems that brain death was intended to solve when it was introduced. In short, debates about brain death have been characterized by partisanship, for or against. Here I plead for a non-partisan approach that has been overlooked in the literature: the epistemological or philosophy of science approach. Some scholars claim that human death is a matter of fact, a biological phenomenon whose occurrence can be determined empirically, based on science. We should take this claim seriously, whether we agree with it or not. The question is: how do we know that human death is a scientific matter of fact? Taking the epistemological approach means, among other things, examining how the determination of human death became an object of scientific inquiry, exploring the nature of the brain death criterion itself, and analysing the meaning of its core concepts such as "irreversibility" and "functions".

Brain death debates: from bioethics to philosophy of science

50 years after its introduction, brain death remains controversial among scholars. The debates focus on one question: is brain death a good criterion for determining death? This question has been answered from various perspectives: medical, metaphysical, ethical, and legal or political. Most authors either defend the criterion as it is, propose some minor or major revisions, or advocate abandoning it and finding better solutions to the problems that brain death was intended to solve when it was introduced. Here I plead for a different approach that has been overlooked in the literature: the philosophy of science approach. Some scholars claim that human death is a matter of fact, a biological phenomenon whose occurrence can be determined empirically, based on science. We should take this claim seriously, whether we agree with it or not. The question is: how do we know that human death is a scientific matter of fact? Taking the philosophy of science approach means, among other things, examining how the determination of human death became an object of scientific inquiry, exploring the nature of the brain death criterion itself, and analysing the meaning of its core concepts such as "irreversibility" and "functions".

An Impending Paradigm Shift in Motor Imagery Based Brain-Computer Interfaces

The development of reliable assistive devices for patients that suffer from motor impairments following central nervous system lesions remains a major challenge in the field of non-invasive Brain-Computer Interfaces (BCIs). These approaches are predominated by electroencephalography and rely on advanced signal processing and machine learning methods to extract neural correlates of motor activity. However, despite tremendous and still ongoing efforts, their value as effective clinical tools remains limited. We advocate that a rather overlooked research avenue lies in efforts to question neurophysiological markers traditionally targeted in non-invasive motor BCIs. We propose an alternative approach grounded by recent fundamental advances in non-invasive neurophysiology, specifically subject-specific feature extraction of sensorimotor bursts of activity recorded via (possibly magnetoencephalography-optimized) electroencephalography. This path holds promise in overcoming a significant proportion of existing limitations, and could foster the wider adoption of online BCIs in rehabilitation protocols.