DARPA-funded efforts in the development of novel brain–computer interface technologies

Multiband task related components enhance rapid cognition decoding for both small and similar objects

The cortically-coupled target recognition system based on rapid serial visual presentation (RSVP) has a wide range of applications in brain computer interface (BCI) fields such as medical and military. However, in the complex natural environment backgrounds, the identification of event-related potentials (ERP) of both small and similar objects that are quickly presented is a research challenge. Therefore, we designed corresponding experimental paradigms and proposed a multi-band task related components matching (MTRCM) method to improve the rapid cognitive decoding of both small and similar objects. We compared the areas under the receiver operating characteristic curve (AUC) between MTRCM and other 9 methods under different numbers of training sample using RSVP-ERP data from 50 subjects. The results showed that MTRCM maintained an overall superiority and achieved the highest average AUC (0.6562 ± 0.0091). We also optimized the frequency band and the time parameters of the method. The verification on public data sets further showed the necessity of designing MTRCM method. The MTRCM method provides a new approach for neural decoding of both small and similar RSVP objects, which is conducive to promote the further development of RSVP-BCI.

Proto-neural networks from thermal proteins

Proteinoids are synthetic polymers that have structural similarities to natural proteins, and their formation is achieved through the application of heat to amino acid combinations in a dehydrated environment. The thermal proteins, initially synthesised by Sidney Fox during the 1960s, has the ability to undergo self-assembly, resulting in the formation of microspheres that resemble cells. These microspheres have fascinating biomimetic characteristics. In recent studies, substantial advancements have been made in elucidating the electrical signalling phenomena shown by proteinoids, hence showcasing their promising prospects in the field of neuro-inspired computing. This study demonstrates the advancement of experimental prototypes that employ proteinoids in the construction of fundamental neural network structures. The article provides an overview of significant achievements in proteinoid systems, such as the demonstration of electrical excitability, emulation of synaptic functions, capabilities in pattern recognition, and adaptability of network structures. This study examines the similarities and differences between proteinoid networks and spontaneous neural computation. We examine the persistent challenges associated with deciphering the underlying mechanisms of emergent proteinoid-based intelligence. Additionally, we explore the potential for developing bio-inspired computing systems using synthetic thermal proteins in forthcoming times. The results of this study offer a theoretical foundation for the advancement of adaptive, self-assembling electronic systems that operate using artificial bio-neural principles.

Use of Invasive Brain-Computer Interfaces in Pediatric Neurosurgery: Technical and Ethical Considerations

Invasive brain-computer interfaces hold promise to alleviate disabilities in individuals with neurologic injury, with fully implantable brain-computer interface systems expected to reach the clinic in the upcoming decade. Children with severe neurologic disabilities, like quadriplegic cerebral palsy or cervical spine trauma, could benefit from this technology. However, they have been excluded from clinical trials of intracortical brain-computer interface to date. In this manuscript, we discuss the ethical considerations related to the use of invasive brain-computer interface in children with severe neurologic disabilities. We first review the technical hardware and software considerations for the application of intracortical brain-computer interface in children. We then discuss ethical issues related to motor brain-computer interface use in pediatric neurosurgery. Finally, based on the input of a multidisciplinary panel of experts in fields related to brain-computer interface (functional and restorative neurosurgery, pediatric neurosurgery, mathematics and artificial intelligence research, neuroengineering, pediatric ethics, and pragmatic ethics), we then formulate initial recommendations regarding the clinical use of invasive brain-computer interfaces in children.

Brain augmentation and neuroscience technologies: current applications, challenges, ethics and future prospects

Ever since the dawn of antiquity, people have strived to improve their cognitive abilities. From the advent of the wheel to the development of artificial intelligence, technology has had a profound leverage on civilization. Cognitive enhancement or augmentation of brain functions has become a trending topic both in academic and public debates in improving physical and mental abilities. The last years have seen a plethora of suggestions for boosting cognitive functions and biochemical, physical, and behavioral strategies are being explored in the field of cognitive enhancement. Despite expansion of behavioral and biochemical approaches, various physical strategies are known to boost mental abilities in diseased and healthy individuals. Clinical applications of neuroscience technologies offer alternatives to pharmaceutical approaches and devices for diseases that have been fatal, so far. Importantly, the distinctive aspect of these technologies, which shapes their existing and anticipated participation in brain augmentations, is used to compare and contrast them. As a preview of the next two decades of progress in brain augmentation, this article presents a plausible estimation of the many neuroscience technologies, their virtues, demerits, and applications. The review also focuses on the ethical implications and challenges linked to modern neuroscientific technology. There are times when it looks as if ethics discussions are more concerned with the hypothetical than with the factual. We conclude by providing recommendations for potential future studies and development areas, taking into account future advancements in neuroscience innovation for brain enhancement, analyzing historical patterns, considering neuroethics and looking at other related forecasts.

The ethics of AI-assisted warfighter enhancement research and experimentation: Historical perspectives and ethical challenges

The military applications of AI raise myriad ethical challenges. Critical among them is how AI integrates with human decision making to enhance cognitive performance on the battlefield. AI applications range from augmented reality devices to assist learning and improve training to implantable Brain-Computer Interfaces (BCI) to create bionic "super soldiers." As these technologies mature, AI-wired warfighters face potential affronts to cognitive liberty, psychological and physiological health risks and obstacles to integrating into military and civil society during their service and upon discharge. Before coming online and operational, however, AI-assisted technologies and neural interfaces require extensive research and human experimentation. Each endeavor raises additional ethical concerns that have been historically ignored thereby leaving military and medical scientists without a cogent ethics protocol for sustainable research. In this way, this paper is a "prequel" to the current debate over enhancement which largely considers neuro-technologies once they are already out the door and operational. To lay the ethics foundation for AI-assisted warfighter enhancement research, we present an historical overview of its technological development followed by a presentation of salient ethics research issues (ICRC, 2006). We begin with a historical survey of AI neuro-enhancement research highlighting the ethics lacunae of its development. We demonstrate the unique ethical problems posed by the convergence of several technologies in the military research setting. Then we address these deficiencies by emphasizing how AI-assisted warfighter enhancement research must pay particular attention to military necessity, and the medical and military cost-benefit tradeoffs of emerging technologies, all attending to the unique status of warfighters as experimental subjects. Finally, our focus is the enhancement of friendly or compatriot warfighters and not, as others have focused, enhancements intended to pacify enemy warfighters.

High resolution DLP stereolithography to fabricate biocompatible hydroxyapatite structures that support osteogenesis

Lithography based additive manufacturing techniques, specifically digital light processing (DLP), are considered innovative manufacturing techniques for orthopaedic implants because of their potential for construction of complex geometries using polymers, metals, and ceramics. Hydroxyapatite (HA) coupons, printed using DLP, were evaluated for biological performance in supporting viability, proliferation, and osteogenic differentiation of the human cell line U2OS and human mesenchymal stem cells (MSCs) up to 35 days in culture to determine feasibility for future use in development of complex scaffold geometries. Contact angle, profilometry, and scanning electron microscopy (SEM) measurements showed the HA coupons to be hydrophilic, porous, and having micro size surface roughness, all within favourable cell culture ranges. The study found no impact of leachable and extractables form the DLP printing process. Cells seeded on coupons exhibited morphologies comparable to conventional tissue culture polystyrene plates. Cell proliferation rates, as determined by direct cell count and the RealTime-Glo^TM MT Cell Viability Assay, were similar on HA coupons and standard tissue culture polystyrene plates). Osteogenic differentiation of human MSCs on HA coupons was confirmed using alkaline phosphatase, Alizarin Red S and von Kossa staining. The morphology of MSCs cultured in osteogenic medium for 14 to 35 days was similar on HA coupons and tissue culture polystyrene plates, with osteogenic (geometric, cuboidal morphology with dark nodules) and adipogenic (lipid vesicles and deposits) features. We conclude that the DLP process and LithaBone HA400 slurry are biocompatible and are suitable for osteogenic applications. Coupons served as an effective evaluation design in the characterization and visualization of cell responses on DLP printed HA material. Results support the feasibility of future technical development for 3D printing of sophisticated scaffold designs, which can be constructed to meet the mechanical, chemical, and porosity requirements of an artificial bone scaffold.

A Control-Theoretical System for Modulating Hippocampal Gamma Oscillations using Stimulation of the Posterior Cingulate Cortex

Closed-loop stimulation for targeted modulation of brain signals has emerged as a promising strategy for episodic memory restoration. In parallel, closed-loop neuromodulation strategies have been applied to treat brain conditions including drug-resistant depression, Parkinson’s Disease, and epilepsy. In this study, we seek to apply control theoretical principles to achieve closed loop modulation of hippocampal oscillatory activity. We focus on hippocampal gamma power, a signal with an established association for episodic memory processing, which may be a promising ‘biomarker’ for the modulation of memory performance. To develop a closed-loop stimulation paradigm that effectively modulates hippocampal gamma power, we use a novel data-set in which open-loop stimulation was applied to the posterior cingulate cortex and hippocampal gamma power was recorded during the encoding of episodic memories. The dataset was used to design and evaluate a linear quadratic integral (LQI) servo-controller in order to determine its viability for in-vivo use. In our simulation framework, we demonstrate that applying an LQI servo controller based on an autoregressive with exogenous input (ARX) plant model achieves effective control of hippocampal gamma power in 15 out of 17 experimental subjects. We demonstrate that we are able to modulate gamma power using stimulation thresholds that are physiologically safe and on time scales that are reasonable for application in a clinical system. We outline further experimentation to test our proposed system and compare our findings to emerging closed-loop neuromodulation strategies.

Cybernetic Hive Minds: A Review

Insect swarms and migratory birds are known to exhibit something known as a hive mind, collective consciousness, and herd mentality, among others. This has inspired a whole new stream of robotics known as swarm intelligence, where small-sized robots perform tasks in coordination. The social media and smartphone revolution have helped people collectively work together and organize in their day-to-day jobs or activism. This revolution has also led to the massive spread of disinformation amplified during the COVID-19 pandemic by alt-right Neo Nazi Cults like QAnon and their counterparts from across the globe, causing increases in the spread of infection and deaths. This paper presents the case for a theoretical cybernetic hive mind to explain how existing cults like QAnon weaponize group think and carry out crimes using social media-based alternate reality games. We also showcase a framework on how cybernetic hive minds have come into existence and how the hive mind might evolve in the future. We also discuss the implications of these hive minds for the future of free will and how different malfeasant entities have utilized these technologies to cause problems and inflict harm by various forms of cyber-crimes and predict how these crimes can evolve in the future.

Smart Device-Driven Corticolimbic Plasticity in Cognitive–Emotional Restructuring of Space-Related Neuropsychiatric Disease and Injury

Escalating government and commercial efforts to plan and deploy viable manned near-to-deep solar system exploration and habitation over the coming decades now drives next-generation space medicine innovations. The application of cutting-edge precision medicine, such as brain stimulation techniques, provides powerful clinical and field/flight situation methods to selectively control vagal tone and neuroendocrine-modulated corticolimbic plasticity, which is affected by prolonged cosmic radiation exposure, social isolation or crowding, and weightlessness in constricted operational non-terran locales. Earth-based clinical research demonstrates that brain stimulation approaches may be combined with novel psychotherapeutic integrated memory structure rationales for the corrective reconsolidation of arousing or emotional experiences, autobiographical memories, semantic schema, and other cognitive structures to enhance neuropsychiatric patient outcomes. Such smart cotherapies or countermeasures, which exploit natural, pharmaceutical, and minimally invasive neuroprosthesis-driven nervous system activity, may optimize the cognitive-emotional restructuring of astronauts suffering from space-related neuropsychiatric disease and injury, including mood, affect, and anxiety symptoms of any potential severity and pathophysiology. An appreciation of improved neuropsychiatric healthcare through the merging of new or rediscovered smart theragnostic medical technologies, capable of rendering personalized neuroplasticity training and managed psychotherapeutic treatment protocols, will reveal deeper insights into the illness states experienced by astronauts. Future work in this area should emphasize the ethical role of telemedicine and/or digital clinicians to advance the (semi)autonomous, technology-assisted medical prophylaxis, diagnosis, treatment, monitoring, and compliance of astronauts for elevated health, safety, and performance in remote extreme space and extraterrestrial environments.

The Arch Electrode: A Novel Dry Electrode Concept for Improved Wearing Comfort

Electroencephalography (EEG) is increasingly used for repetitive and prolonged applications like neurofeedback, brain computer interfacing, and long-term intermittent monitoring. Dry-contact electrodes enable rapid self-application. A common drawback of existing dry electrodes is the limited wearing comfort during prolonged application. We propose a novel dry Arch electrode. Five semi-circular arches are arranged parallelly on a common baseplate. The electrode substrate material is a flexible thermoplastic polyurethane (TPU) produced by additive manufacturing. A chemical coating of Silver/Silver-Chloride (Ag/AgCl) is applied by electroless plating using a novel surface functionalization method. Arch electrodes were manufactured and validated in terms of mechanical durability, electrochemical stability, in vivo applicability, and signal characteristics. We compare the results of the dry arch electrodes with dry pin-shaped and conventional gel-based electrodes. 21-channel EEG recordings were acquired on 10 male and 5 female volunteers. The tests included resting state EEG, alpha activity, and a visual evoked potential. Wearing comfort was rated by the subjects directly after application, as well as at 30 min and 60 min of wearing. Our results show that the novel plating technique provides a well-adhering electrically conductive and electrochemically stable coating, withstanding repetitive strain and bending tests. The signal quality of the Arch electrodes is comparable to pin-shaped dry electrodes. The average channel reliability of the Arch electrode setup was 91.9 ± 9.5%. No considerable differences in signal characteristics have been observed for the gel-based, dry pin-shaped, and arch-shaped electrodes after the identification and exclusion of bad channels. The comfort was improved in comparison to pin-shaped electrodes and enabled applications of over 60 min duration. Arch electrodes required individual adaptation of the electrodes to the orientation and hairstyle of the volunteers. This initial preparation time of the 21-channel cap increased from an average of 5 min for pin-like electrodes to 15 min for Arch electrodes and 22 min for gel-based electrodes. However, when re-applying the arch electrode cap on the same volunteer, preparation times of pin-shaped and arch-shaped electrodes were comparable. In summary, our results indicate the applicability of the novel Arch electrode and coating for EEG acquisition. The novel electrode enables increased comfort for prolonged dry-contact measurement.

Waveform feature extraction and signal recovery in single-channel TVEP based on Fitzhugh-Nagumo stochastic resonance

Objective. Transient visual evoked potential (TVEP) can reflect the condition of the visual pathway and has been widely used in brain-computer interface. TVEP signals are typically obtained by averaging the time-locked brain responses across dozens or even hundreds of stimulations, in order to remove different kinds of interferences. However, this procedure increases the time needed to detect the brain status in realistic applications. Meanwhile, long repeated stimuli can vary the evoked potentials and discomfort the subjects. Therefore, a novel unsupervised framework was developed in this study to realize the fast extraction of single-channel TVEP signals with a high signal-to-noise ratio.Approach.Using the principle of nonlinear aperiodic FitzHugh-Nagumo (FHN) model, a fast extraction and signal restoration technology of TVEP waveform based on FHN stochastic resonance is proposed to achieve high-quality acquisition of signal features with less average times.Results:A synergistic effect produced by noise, aperiodic signal and nonlinear system can force the energy of noise to be transferred into TVEP and hence amplifying the useful P100 feature while suppressing multi-scale noise.Significance. Compared with the conventional average and average-singular spectrum analysis-independent component analysis(average-SSA-ICA) method, the average-FHN method has a shorter stimulation time which can greatly improve the comfort of patients in clinical TVEP detection and a better performance of TVEP waveform i.e. a higher accuracy of P100 latency. The FHN recovery method is not only highly correlated with the original signal, but also can better highlight the P100 amplitude, which has high clinical application value.

Towards real-life EEG applications: novel superporous hydrogel-based semi-dry EEG electrodes enabling automatically "charge-discharge" electrolyte

A novel polyacrylamide/polyvinyl alcohol superporous hydrogel (PAAm/PVA SPH)-based semi-dry electrode was constructed for capturing EEG signals at the hairy scalp, showing automatically "charge-discharge" electrolyte concept in EEG electrode development. In this regard, PAAm/PVA SPH was polymerized in-situ in the hollow electrode cavity by freezing polymerization, which acted as a dynamic reservoir of electrolyte fluid. The superporous hydrogel can be completely "charged" with electrolyte fluid, such as saline, in just a few seconds and can be "discharged" through a few tiny pillars into the scalp at a desirable rate. In this way, an ideal local skin hydration effect was achieved at electrode-skin contact sites, facilitating the bioelectrical signal pathway and significantly reducing electrode-skin impedance. Moreover, the electrode interface effectively avoids short circuit and inconvenient issues. The results show that the semi-dry electrode displayed low and stable contact impedance, showing non-polarization properties with low off-set potential and negligible potential drift. The average temporal cross-correlation coefficient between the semi-dry and conventional wet electrodes was 0.941. Frequency spectra also showed almost identical responses with anticipated neural electrophysiology responses. Considering prominent advantages such as a rapid setup, robust signal, and user-friendliness, the new concept of semi-dry electrodes shows excellent potential in emerging real-life EEG applications.

Stimulation and Recording of the Hippocampus Using the Same Pt-Ir Coated Microelectrodes

Same-electrode stimulation and recording with high spatial resolution, signal quality, and power efficiency is highly desirable in neuroscience and neural engineering. High spatial resolution and signal-to-noise ratio is necessary for obtaining unitary activities and delivering focal stimulations. Power efficiency is critical for battery-operated implantable neural interfaces. This study demonstrates the capability of recording single units as well as evoked potentials in response to a wide range of electrochemically safe stimulation pulses through high-resolution microelectrodes coated with co-deposition of Pt-Ir. It also compares signal-to-noise ratio, single unit activity, and power efficiencies between Pt-Ir coated and uncoated microelectrodes. To enable stimulation and recording with the same microelectrodes, microelectrode arrays were treated with electrodeposited platinum-iridium coating (EPIC) and tested in the CA1 cell body layer of rat hippocampi. The electrodes' ability to (1) inject a large range of electrochemically reversable stimulation pulses to the tissue, and (2) record evoked potentials and single unit activities were quantitively assessed over an acute time period. Compared to uncoated electrodes, EPIC electrodes recorded signals with higher signal-to-noise ratios (coated: 9.77 ± 1.95 dB; uncoated: 1.95 ± 0.40 dB) and generated lower voltages (coated: 100 mV; uncoated: 650 mV) for a given stimulus (5 μA). The improved performance corresponded to lower energy consumptions and electrochemically safe stimulation above 5 μA (>0.38 mC/cm2), which enabled elicitation of field excitatory post synaptic potentials and population spikes. Spontaneous single unit activities were also modulated by varying stimulation intensities and monitored through the same electrodes. This work represents an example of stimulation and recording single unit activities from the same microelectrode, which provides a powerful tool for monitoring and manipulating neural circuits at the single neuron level.

Regenerative peripheral nerve interface free muscle graft mass and function

BACKGROUND

Regenerative peripheral nerve interfaces (RPNIs) transduce neural signals to provide high-fidelity control of neuroprosthetic devices. Traditionally, rat RPNIs are constructed with ~150 mg of free skeletal muscle grafts. It is unknown whether larger free muscle grafts allow RPNIs to transduce greater signal.

METHODS

RPNIs were constructed by securing skeletal muscle grafts of various masses (150, 300, 600, or 1200 mg) to the divided peroneal nerve. In the control group, the peroneal nerve was transected without repair. Endpoint assessments were conducted 3 mo postoperatively.

RESULTS

Compound muscle action potentials (CMAPs), maximum tetanic isometric force, and specific muscle force were significantly higher for both the 150 and 300 mg RPNI groups compared to the 600 and 1200 mg RPNIs. Larger RPNI muscle groups contained central areas lacking regenerated muscle fibers.

CONCLUSIONS

Electrical signaling and tissue viability are optimal in smaller as opposed to larger RPNI constructs in a rat model.

Developing a Motor Imagery-Based Real-Time Asynchronous Hybrid BCI Controller for a Lower-Limb Exoskeleton

This study aimed to develop an intuitive gait-related motor imagery (MI)-based hybrid brain-computer interface (BCI) controller for a lower-limb exoskeleton and investigate the feasibility of the controller under a practical scenario including stand-up, gait-forward, and sit-down. A filter bank common spatial pattern (FBCSP) and mutual information-based best individual feature (MIBIF) selection were used in the study to decode MI electroencephalogram (EEG) signals and extract a feature matrix as an input to the support vector machine (SVM) classifier. A successive eye-blink switch was sequentially combined with the EEG decoder in operating the lower-limb exoskeleton. Ten subjects demonstrated more than 80% accuracy in both offline (training) and online. All subjects successfully completed a gait task by wearing the lower-limb exoskeleton through the developed real-time BCI controller. The BCI controller achieved a time ratio of 1.45 compared with a manual smartwatch controller. The developed system can potentially be benefit people with neurological disorders who may have difficulties operating manual control.

A 0.0023 mm 2/ch. Delta-Encoded, Time-Division Multiplexed Mixed-Signal ECoG Recording Architecture With Stimulus Artifact Suppression

This article demonstrates a scalable, time-division multiplexed biopotential recording front-end capable of real-time differential- and common-mode artifact suppression. A delta-encoded recording architecture exploits the power spectral density (PSD) characteristics of Electrocorticography (ECoG) recordings, combining an 8-bit ADC, and an 8-bit DAC to achieve 14 bits of dynamic range. The flexibility of the digital feedback architecture is leveraged to time-division multiplex 64 differential input channels onto a shared mixed-signal front-end, reducing channel area by 2x compared to the state-of-the-art. The feedback DAC used for delta-encoding also serves to cancel differential artifacts with an off-chip adaptive loop. Analysis of this architecture and measured silicon performance of a 65 nm CMOS test-chip implementation, both on the bench and in-vivo, are included with this paper.

A Parallel Multiscale Filter Bank Convolutional Neural Networks for Motor Imagery EEG Classification

OBJECTIVE

Electroencephalogram (EEG) based brain-computer interfaces (BCI) in motor imagery (MI) have developed rapidly in recent years. A reliable feature extraction method is essential because of a low signal-to-noise ratio (SNR) and time-dependent covariates of EEG signals. Because of efficient application in various fields, deep learning has been adopted in EEG signal processing and has obtained competitive results compared with the traditional methods. However, designing and training an end-to-end network to fully extract potential features from EEG signals remains a challenge in MI.

APPROACH

In this study, we propose a parallel multiscale filter bank convolutional neural network (MSFBCNN) for MI classification. We introduce a layered end-to-end network structure, in which a feature-extraction network is used to extract temporal and spatial features. To enhance the transfer learning ability, we propose a network initialization and fine-tuning strategy to train an individual model for inter-subject classification on small datasets. We compare our MSFBCNN with the state-of-the-art approaches on open datasets.

RESULTS

The proposed method has a higher accuracy than the baselines in intra-subject classification. In addition, the transfer learning experiments indicate that our network can build an individual model and obtain acceptable results in inter-subject classification. The results suggest that the proposed network has superior performance, robustness, and transfer learning ability.

Transcending the brain: is there a cost to hacking the nervous system?

Great advancements have recently been made to understand the brain and the potential that we can extract out of it. Much of this has been centred on modifying electrical activity of the nervous system for improved physical and cognitive performance in those with clinical impairment. However, there is a risk of going beyond purely physiological performance improvements and striving for human enhancement beyond traditional human limits. Simple ethical guidelines and legal doctrine must be examined to keep ahead of technological advancement in light of the impending mergence between biology and machine. By understanding the role of modern ethics, this review aims to appreciate the fine boundary between what is considered ethically justified for current neurotechnology.

Precision electronic medicine in the brain

Periodically throughout history developments from adjacent fields of science and technology reach a tipping point where together they produce unparalleled advances, such as the Allen Brain Atlas and the Human Genome Project. Today, research focused at the interface between the nervous system and electronics is not only leading to advances in fundamental neuroscience, but also unlocking the potential of implants capable of cellular-level therapeutic targeting. Ultimately, these personalized electronic therapies will provide new treatment modalities for neurodegenerative and neuropsychiatric illness; powerful control of prosthetics for restorative function in degenerative diseases, trauma and amputation; and even augmentation of human cognition. Overall, we believe that emerging advances in tissue-like electronics will enable minimally invasive devices capable of establishing a stable long-term cellular neural interface and providing long-term treatment for chronic neurological conditions.

Neuroethics at 15: The Current and Future Environment for Neuroethics

Neuroethics research and scholarship intersect with dynamic academic disciplines in science, engineering, and the humanities. On the occasion of the 15th anniversary of the formation of the International Neuroethics Society, we identify current and future topics for neuroethics and discuss the many social and political challenges that emerge from the converging dynamics of neurotechnologies and artificial intelligence. We also highlight the need for a global, transdisciplinary, and integrated community of researchers to address the challenges that are precipitated by this rapid sociotechnological transformation.

EEG Artifacts Handling in a Real Practical Brain-Computer Interface Controlled Vehicle

One of the main issues restricting the practical efficiency of brain-computer interface (BCI) systems is the inevitable occurrence of physiological artifacts during electroencephalography (EEG) recordings. The effects of the artifacts are, however, mostly discarded in practical BCI systems, due to the time-consuming and complicated computational processes. This paper presents the influences of the artifacts and the efficiency of reducing these influences in a practical BCI. Ocular and muscular artifacts are considered due to the high-amplitude and frequent presence. The paradigm is designed based on the mental controlling of a radio-control (RC) car. Two motor imagery commands, containing the imagination of movement of left/right hand, are used to navigate the BCI-based RC car to turn left/right. The results indicate that the artifacts can highly affect the system performance; reducing their influence significantly improves the efficiency.

Emerging and Enabling Technologies in Biodefense

The emergence of new biotechnologies provides great promise for biodefense, especially for key objectives of biosurveillance and early warning, microbial forensics, risk and threat assessment, horizon scanning in biotechnology, and medical countermeasure (MCM) development, scale-up, and delivery. Understanding and leveraging the newly developed capabilities afforded by emerging biotechnologies require knowledge about cutting-edge research and its real or proposed application(s), the process through which biotechnologies advance, and the educational and research infrastructure that promotes multi-disciplinary science. Innovation in research and technology development are driven by sector-specific needs and the convergence of the physical, chemical, material, computer, engineering, and/or life sciences. Biotechnologies developed for other sectors could be applied to biodefense, especially if the individuals involved are able to innovate in concept design and development. Of all biodefense objectives, biosurveillance seems to have reaped the most benefit from emerging biotechnologies, specifically the integration and analysis of diverse clinical, biological, demographic, and other relevant data. More recently, scientists have begun applying synthetic biology, genomics, and microfluidics to the development of new products and platforms for MCMs. Unlike these objectives, investments in microbial forensics have been few, limiting its ability to harness biotechnology advances for collecting and analyzing data. Looking to the future, emerging biotechnologies can provide new opportunities for enhancing biodefense by addressing capability gaps.

Latent common source extraction via a generalized canonical correlation framework for frequency recognition in SSVEP based brain-computer interfaces

OBJECTIVE

This study introduces and evaluates a novel target identification method, latent common source extraction (LCSE), that uses subject-specific training data for the enhancement of detection of steady-state visual evoked potential (SSVEP).

APPROACH

LCSE seeks to construct a common latent representation of the SSVEP signal subspace that is stable across multiple trials of electroencephalographic (EEG) data. The spatial filter thus obtained improves the signal-to-noise ratio (SNR) of the SSVEP components by removing nuisance signals that are irrelevant to the generalized signal representation learnt from the given data. In this study a comparison of SSVEP identification performance between the proposed method, extended canonical correlation analysis (ExtCCA) and multiset canonical correlation analysis (MsetCCA) was conducted using SSVEP benchmark data of 40 targets recorded from 35 subjects to validate the effectiveness of the LCSE framework.

MAIN RESULTS

The results indicate that the LCSE framework significantly outperforms the other two methods in terms of both classification accuracy and information transfer rates (ITRs).

SIGNIFICANCE

The significant improvement in the target identification performance demonstrates that the proposed LCSE method can be seen as a promising potential candidate for efficient SSVEP detection in brain-computer interface (BCI) systems.

A Novel Single-Character Visual BCI Paradigm With Multiple Active Cognitive Tasks

OBJECTIVE

To introduce a novel event-related potential (ERP)-based brain-computer interface (BCI) paradigm with active mental tasks multiplying precise judgment and visual cognitive capacities and evaluate its performance.

METHODS

This study employed a paradigm with three types of targets (true-, pseudo-, and non-), double flash codes, colors and color terms, and four test conditions. The primary hypothesis was that active mental tasks combining multiple cognitive capacities and clear judgment for different categories of stimuli increase the BCI performance and evoke stronger or specific ERPs. Classification methods were proposed and evaluated, and two were used in online experiments.

RESULTS

The modes containing active mental tasks provided higher accuracy than the control mode (by up to 19.06%). The color-word matching mode had the highest judgment level and achieved the best performance. True-stimuli evoked strong P3b, while pseudotarget signals provided obvious N4, but the control mode seemed less sensitive to both of them. Different types of stimuli evoked distinctive N2 and P3a components.

CONCLUSION

An appropriate boost in the judgment level using multiple stimuli and cognitive approaches could be investigated to improve the BCI performance and evoke or enhance ERPs. Utilizing active mental tasks may be a promising way to promote BCIs.

SIGNIFICANCE

Active mental tasks combining multiple cognitive capacities and precise judgments were adopted in an ERP-based BCI. Color and color words were introduced as stimuli to construct an alternative paradigm, and the judgment levels of different conditions were calculated. High accuracies and the participants' preferences were obtained, which may promote the effective use of BCIs.

Ethical considerations on the complicity of psychologists and scientists in torture

INTRODUCTION

The long-standing debate on medical complicity in torture has overlooked the complicity of cognitive scientists-psychologists, psychiatrists and neuroscientists-in the practice of torture as a distinct phenomenon. In this paper, we identify the risk of the re-emergence of torture as a practice in the USA, and the complicity of cognitive scientists in these practices.

METHODS

We review arguments for physician complicity in torture. We argue that these defences fail to defend the complicity of cognitive scientists. We address objections to our account, and then provide recommendations for professional associations in resisting complicity in torture.

RESULTS

Arguments for cognitive scientist complicity in torture fail when those actions stem from the same reasons as physician complicity. Cognitive scientist involvement in the torture programme has, from the outset, been focused on the outcomes of interrogation rather than supportive care. Any possibility of a therapeutic relationship between cognitive therapists and detainees is fatally undermined by therapists' complicity with torture.

CONCLUSION

Professional associations ought to strengthen their commitment to refraining from engaging in any aspect of torture. They should also move to protect whistle-blowers against torture programmes who are members of their association. If the political institutions that are supposed to prevent the practice of torture are not strengthened, cognitive scientists should take collective action to compel intelligence agencies to refrain from torture.

Neurotechnologies for Human Cognitive Augmentation: Current State of the Art and Future Prospects

Recent advances in neuroscience have paved the way to innovative applications that cognitively augment and enhance humans in a variety of contexts. This paper aims at providing a snapshot of the current state of the art and a motivated forecast of the most likely developments in the next two decades. Firstly, we survey the main neuroscience technologies for both observing and influencing brain activity, which are necessary ingredients for human cognitive augmentation. We also compare and contrast such technologies, as their individual characteristics (e.g., spatio-temporal resolution, invasiveness, portability, energy requirements, and cost) influence their current and future role in human cognitive augmentation. Secondly, we chart the state of the art on neurotechnologies for human cognitive augmentation, keeping an eye both on the applications that already exist and those that are emerging or are likely to emerge in the next two decades. Particularly, we consider applications in the areas of communication, cognitive enhancement, memory, attention monitoring/enhancement, situation awareness and complex problem solving, and we look at what fraction of the population might benefit from such technologies and at the demands they impose in terms of user training. Thirdly, we briefly review the ethical issues associated with current neuroscience technologies. These are important because they may differentially influence both present and future research on (and adoption of) neurotechnologies for human cognitive augmentation: an inferior technology with no significant ethical issues may thrive while a superior technology causing widespread ethical concerns may end up being outlawed. Finally, based on the lessons learned in our analysis, using past trends and considering other related forecasts, we attempt to forecast the most likely future developments of neuroscience technology for human cognitive augmentation and provide informed recommendations for promising future research and exploitation avenues.

Progress in the Field of Micro-Electrocorticography

Since the 1940s electrocorticography (ECoG) devices and, more recently, in the last decade, micro-electrocorticography (µECoG) cortical electrode arrays were used for a wide set of experimental and clinical applications, such as epilepsy localization and brain⁻computer interface (BCI) technologies. Miniaturized implantable µECoG devices have the advantage of providing greater-density neural signal acquisition and stimulation capabilities in a minimally invasive fashion. An increased spatial resolution of the µECoG array will be useful for greater specificity diagnosis and treatment of neuronal diseases and the advancement of basic neuroscience and BCI research. In this review, recent achievements of ECoG and µECoG are discussed. The electrode configurations and varying material choices used to design µECoG arrays are discussed, including advantages and disadvantages of µECoG technology compared to electroencephalography (EEG), ECoG, and intracortical electrode arrays. Electrode materials that are the primary focus include platinum, iridium oxide, poly(3,4-ethylenedioxythiophene) (PEDOT), indium tin oxide (ITO), and graphene. We discuss the biological immune response to µECoG devices compared to other electrode array types, the role of µECoG in clinical pathology, and brain⁻computer interface technology. The information presented in this review will be helpful to understand the current status, organize available knowledge, and guide future clinical and research applications of µECoG technologies.

Trends in research participant categories and descriptions in abstracts from the International BCI Meeting series, 1999 to 2016

Much brain-computer interface (BCI) research is intended to benefit people with disabilities (PWD), but inclusion of these individuals as study participants remains relatively rare. When participants with disabilities are included, they are described with a range of clinical and non-clinical terms with varying degrees of specificity, often leading to difficulty in interpreting or replicating results. This study examined trends in inclusion and description of study participants with disabilities across six International BCI Meetings from 1999 to 2016. Abstracts from each Meeting were analyzed by two trained independent reviewers. Results suggested a decline in participation by PWD across Meetings until the 2016 Meeting. Increased diagnostic specificity was noted at the 2013 and 2016 Meetings. Fifty-eight percent of the abstracts identified PWD as being the target beneficiaries of BCI research, though only twenty-two percent included participants with disabilities, suggesting evidence of a persistent translational gap. Participants with disabilities were most commonly described as having physical and/or communication impairments compared to impairments in other areas. Implementing participatory action research principles and user-centered design strategies continues to be necessary within BCI research to bridge the translational gap and facilitate use of BCI systems within functional environments for PWD.

Implantable Neural Probes for Brain-Machine Interfaces - Current Developments and Future Prospects

A Brain-Machine interface (BMI) allows for direct communication between the brain and machines. Neural probes for recording neural signals are among the essential components of a BMI system. In this report, we review research regarding implantable neural probes and their applications to BMIs. We first discuss conventional neural probes such as the tetrode, Utah array, Michigan probe, and electroencephalography (ECoG), following which we cover advancements in next-generation neural probes. These next-generation probes are associated with improvements in electrical properties, mechanical durability, biocompatibility, and offer a high degree of freedom in practical settings. Specifically, we focus on three key topics: (1) novel implantable neural probes that decrease the level of invasiveness without sacrificing performance, (2) multi-modal neural probes that measure both electrical and optical signals, (3) and neural probes developed using advanced materials. Because safety and precision are critical for practical applications of BMI systems, future studies should aim to enhance these properties when developing next-generation neural probes.

Volitional modulation of higher-order visual cortex alters human perception

Can we change our perception by controlling our brain activation? Awareness during binocular rivalry is shaped by the alternating perception of different stimuli presented separately to each monocular view. We tested the possibility of causally influencing the likelihood of a stimulus entering awareness. To do this, participants were trained with neurofeedback, using realtime functional magnetic resonance imaging (rt-fMRI), to differentially modulate activation in stimulus-selective visual cortex representing each of the monocular images. Neurofeedback training led to altered bistable perception associated with activity changes in the trained regions. The degree to which training influenced perception predicted changes in grey and white matter volumes of these regions. Short-term intensive neurofeedback training therefore sculpted the dynamics of visual awareness, with associated plasticity in the human brain.

Regenerative peripheral nerve interfaces for real-time, proportional control of a Neuroprosthetic hand

INTRODUCTION

Regenerative peripheral nerve interfaces (RPNIs) are biological constructs which amplify neural signals and have shown long-term stability in rat models. Real-time control of a neuroprosthesis in rat models has not yet been demonstrated. The purpose of this study was to: a) design and validate a system for translating electromyography (EMG) signals from an RPNI in a rat model into real-time control of a neuroprosthetic hand, and; b) use the system to demonstrate RPNI proportional neuroprosthesis control.

METHODS

Animals were randomly assigned to three experimental groups: (1) Control; (2) Denervated, and; (3) RPNI. In the RPNI group, the extensor digitorum longus (EDL) muscle was dissected free, denervated, transferred to the lateral thigh and neurotized with the residual end of the transected common peroneal nerve. Rats received tactile stimuli to the hind-limb via monofilaments, and electrodes were used to record EMG. Signals were filtered, rectified and integrated using a moving sample window. Processed EMG signals (iEMG) from RPNIs were validated against Control and Denervated group outputs.

RESULTS

Voluntary reflexive rat movements produced signaling that activated the prosthesis in both the Control and RPNI groups, but produced no activation in the Denervated group. Signal-to-Noise ratio between hind-limb movement and resting iEMG was 3.55 for Controls and 3.81 for RPNIs. Both Control and RPNI groups exhibited a logarithmic iEMG increase with increased monofilament pressure, allowing graded prosthetic hand speed control (R2 = 0.758 and R2 = 0.802, respectively).

CONCLUSION

EMG signals were successfully acquired from RPNIs and translated into real-time neuroprosthetic control. Signal contamination from muscles adjacent to the RPNI was minimal. RPNI constructs provided reliable proportional prosthetic hand control.

Neuroethics of Non-primary Brain Computer Interface: Focus on Potential Military Applications

The field of neuroethics has had to adapt rapidly in the face of accelerating technological advancement; a particularly striking example is the realm of Brain-Computer Interface (BCI). A significant source of funding for the development of new BCI technologies has been the United States Department of Defense, and while the predominant focus has been restoration of lost function for those wounded in battle, there is also significant interest in augmentation of function to increase survivability, coordination, and lethality of US combat forces. While restoration of primary motor and sensory function (primary BCI) has been the main focus of research, there has been marked progress in interface with areas of the brain subserving memory and association. Non-Primary BCI has a different subset of potential applications, each of which also carries its own ethical considerations. Given the amount of BCI research funding coming from the Department of Defense, it is particularly important that potential military applications be examined from a neuroethical standpoint.

Characterization of the Neuroinflammatory Response to Thiol-ene Shape Memory Polymer Coated Intracortical Microelectrodes

Thiol-ene based shape memory polymers (SMPs) have been developed for use as intracortical microelectrode substrates. The unique chemistry provides precise control over the mechanical and thermal glass-transition properties. As a result, SMP substrates are stiff at room temperature, allowing for insertion into the brain without buckling and subsequently soften in response to body temperatures, reducing the mechanical mismatch between device and tissue. Since the surface chemistry of the materials can contribute significantly to the ultimate biocompatibility, as a first step in the characterization of our SMPs, we sought to isolate the biological response to the implanted material surface without regards to the softening mechanics. To accomplish this, we tightly controlled for bulk stiffness by comparing bare silicon 'dummy' devices to thickness-matched silicon devices dip-coated with SMP. The neuroinflammatory response was evaluated after devices were implanted in the rat cortex for 2 or 16 weeks. We observed no differences in the markers tested at either time point, except that astrocytic scarring was significantly reduced for the dip-coated implants at 16 weeks. The surface properties of non-softening thiol-ene SMP substrates appeared to be equally-tolerated and just as suitable as silicon for neural implant substrates for applications such as intracortical microelectrodes, laying the groundwork for future softer devices to improve upon the prototype device performance presented here.

Automated reactive accelerated aging for rapid in vitro evaluation of neural implant performance

Novel therapeutic applications for neural implants require miniaturized devices. Miniaturization imposes stricter requirements for reliability of materials. Pilot clinical studies suggest that rapid failure of the miniaturized neural implants in the body presents a major challenge for this type of technology. Traditional evaluations of neural implant performance over clinically relevant durations present time- and resource-intensive experiments in animals. Reactive accelerated aging (RAA) is an in vitro test platform that was developed to expedite durability testing of neural implants, as a screening technique designed to simulate the aggressive physiological environment experienced by the implants. This approach employs hydrogen peroxide, which mimics reactive oxygen species, and a high temperature to accelerate chemical reactions that lead to device degradation similar to that found with devices implanted in vivo. The original RAA system required daily manual maintenance and was prone to variability in performance. To address these limitations, this work introduces automated reactive accelerated aging (aRAA) with closed-loop monitoring components that make the system simple, robust, and scalable. The core novel technology in the aRAA is electrochemical detection for feedback control of hydrogen peroxide concentration, implemented with simple off-the-shelf components. The aRAA can run multiple parallel experiments for high-throughput device testing and optimization. For this reason, the aRAA provides a simple tool for rapid in vitro evaluation of the durability of neural implants, ultimately expediting the development of a new generation of miniaturized devices with a long functional lifespan.

Self-Paced Operation of a Wheelchair Based on a Hybrid Brain-Computer Interface Combining Motor Imagery and P300 Potential

This paper presents a hybrid brain-computer interface (BCI) that combines motor imagery (MI) and P300 potential for the asynchronous operation of a brain-controlled wheelchair whose design is based on a Mecanum wheel. This paradigm is completely user-centric. By sequentially performing MI tasks or paying attention to P300 flashing, the user can use eleven functions to control the wheelchair: move forward/backward, move left/right, move left45/right45, accelerate/decelerate, turn left/right, and stop. The practicality and effectiveness of the proposed approach were validated in eight subjects, all of whom achieved good performance. The preliminary results indicated that the proposed hybrid BCI system with different mental strategies operating sequentially is feasible and has potential applications for practical self-paced control.

Potential for thermal damage to the blood-brain barrier during craniotomy: implications for intracortical recording microelectrodes

OBJECTIVE

Our objective was to determine how readily disruption of the blood-brain barrier (BBB) occurred as a result of bone drilling during a craniotomy to implant microelectrodes in rat cortex. While the phenomenon of heat production during bone drilling is well known, practices to evade damage to the underlying brain tissue are inconsistently practiced and reported in the literature.

APPROACH

We conducted a review of the intracortical microelectrode literature to summarize typical approaches to mitigate drill heating during rodent craniotomies. Post mortem skull-surface and transient brain-surface temperatures were experimentally recorded using an infrared camera and thermocouple, respectively. A number of drilling conditions were tested, including varying drill speed and continuous versus intermittent contact. In vivo BBB permeability was assayed 1 h after the craniotomy procedure using Evans blue dye.

MAIN RESULTS

Of the reviewed papers that mentioned methods to mitigate thermal damage during craniotomy, saline irrigation was the most frequently cited (in six of seven papers). In post mortem tissues, we observed increases in skull-surface temperature ranging from  +3 °C to  +21 °C, dependent on drill speed. In vivo, pulsed-drilling (2 s-on/2 s-off) and slow-drilling speeds (1000 r.p.m.) were the most effective methods we studied to mitigate heating effects from drilling, while inconclusive results were obtained with saline irrigation.

SIGNIFICANCE

Neuroinflammation, initiated by damage to the BBB and perpetuated by the foreign body response, is thought to play a key role in premature failure of intracortical recording microelectrodes. This study demonstrates the extreme sensitivity of the BBB to overheating caused by bone drilling. To avoid damage to the BBB, the authors recommend that craniotomies be drilled with slow speeds and/or with intermittent drilling with complete removal of the drill from the skull during 'off' periods. While saline alone was ineffective at preventing overheating, its use is still recommended to remove bone dust from the surgical site and to augment other cooling methods.

Real-time decoding of covert attention in higher-order visual areas

Brain-computer-interfaces (BCI) provide a means of using human brain activations to control devices for communication. Until now this has only been demonstrated in primary motor and sensory brain regions, using surgical implants or non-invasive neuroimaging techniques. Here, we provide proof-of-principle for the use of higher-order brain regions involved in complex cognitive processes such as attention. Using realtime fMRI, we implemented an online 'winner-takes-all approach' with quadrant-specific parameter estimates, to achieve single-block classification of brain activations. These were linked to the covert allocation of attention to real-world images presented at 4-quadrant locations. Accuracies in three target regions were significantly above chance, with individual decoding accuracies reaching upto 70%. By utilising higher order mental processes, 'cognitive BCIs' access varied and therefore more versatile information, potentially providing a platform for communication in patients who are unable to speak or move due to brain injury.

A Bit-Encoding Based New Data Structure for Time and Memory Efficient Handling of Spike Times in an Electrophysiological Setup

Recent neuroscientific and technical developments of brain machine interfaces have put increasing demands on neuroinformatic databases and data handling software, especially when managing data in real time from large numbers of neurons. Extrapolating these developments we here set out to construct a scalable software architecture that would enable near-future massive parallel recording, organization and analysis of neurophysiological data on a standard computer. To this end we combined, for the first time in the present context, bit-encoding of spike data with a specific communication format for real time transfer and storage of neuronal data, synchronized by a common time base across all unit sources. We demonstrate that our architecture can simultaneously handle data from more than one million neurons and provide, in real time (< 25 ms), feedback based on analysis of previously recorded data. In addition to managing recordings from very large numbers of neurons in real time, it also has the capacity to handle the extensive periods of recording time necessary in certain scientific and clinical applications. Furthermore, the bit-encoding proposed has the additional advantage of allowing an extremely fast analysis of spatiotemporal spike patterns in a large number of neurons. Thus, we conclude that this architecture is well suited to support current and near-future Brain Machine Interface requirements.

Fluoropolymer-Based Flexible Neural Prosthetic Electrodes for Reliable Neural Interfacing

We covalently bound fluoropolymer (FP) films by plasma treatment followed by thermal pressing at temperatures below their melting point and fabricated an adhesion-metal-free flexible gold electrode array entirely encapsulated by the FP film, excepting the active electrode openings. The fabricated device was chemically resistant and was modified to have a lower impedance and efficient charge injection capability. The fabricated device was evaluated in vivo in rats and was confirmed to record the epidural epileptiform activity induced by chemical administration. The chemically inert nature of FPs and the gold electrode is expected to facilitate reliable neural interfacing without abiotic issues. Plasma treatment-induced covalent binding of FP films can also be utilized in a variety of applications requiring durability, such as implantable biosensors and sensor platforms operating under chemically harsh environments, including humid conditions.

Interfacing with the nervous system: a review of current bioelectric technologies

The aim of this study is to discuss the state of the art with regard to established or promising bioelectric therapies meant to alter or control neurologic function. We present recent reports on bioelectric technologies that interface with the nervous system at three potential sites-(1) the end organ, (2) the peripheral nervous system, and (3) the central nervous system-while exploring practical and clinical considerations. A literature search was executed on PubMed, IEEE, and Web of Science databases. A review of the current literature was conducted to examine functional and histomorphological effects of neuroprosthetic interfaces with a focus on end-organ, peripheral, and central nervous system interfaces. Innovations in bioelectric technologies are providing increasing selectivity in stimulating distinct nerve fiber populations in order to activate discrete muscles. Significant advances in electrode array design focus on increasing selectivity, stability, and functionality of implantable neuroprosthetics. The application of neuroprosthetics to paretic nerves or even directly stimulating or recording from the central nervous system holds great potential in advancing the field of nerve and tissue bioelectric engineering and contributing to clinical care. Although current physiotherapeutic and surgical treatments seek to restore function, structure, or comfort, they bear significant limitations in enabling cosmetic or functional recovery. Instead, the introduction of bioelectric technology may play a role in the restoration of function in patients with neurologic deficits.