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The numerous [gamma]-aminobutyric acid type A receptor (GABA.sub.A R) subtypes are differentially expressed and mediate distinct functions at neuronal level. In this study we have investigated GABA.sub.A R-mediated modulation of the spontaneous activity patterns of primary neuronal networks from murine frontal cortex by characterizing the effects induced by a wide selection of pharmacological tools at a plethora of activity parameters in microelectrode array (MEA) recordings. The basic characteristics of the primary cortical neurons used in the recordings were studied in some detail, and the expression levels of various GABA.sub.A R subunits were investigated by western blotting and RT-qPCR. In the MEA recordings, the pan-GABA.sub.A R agonist muscimol and the GABA.sub.B R agonist baclofen were observed to mediate phenotypically distinct changes in cortical network activity. Selective augmentation of [alpha][beta][gamma] GABA.sub.A R signaling by diazepam and of [delta]-containing GABA.sub.A R ([delta]-GABA.sub.A R) signaling by DS1 produced pronounced changes in the majority of the activity parameters, both drugs mediating similar patterns of activity changes as muscimol. The apparent importance of [delta]-GABA.sub.A R signaling for network activity was largely corroborated by the effects induced by the functionally selective [delta]-GABA.sub.A R agonists THIP and Thio-THIP, whereas the [delta]-GABA.sub.A R selective potentiator DS2 only mediated modest effects on network activity, even when co-applied with low THIP concentrations. Interestingly, diazepam exhibited dramatically right-shifted concentration-response relationships at many of the activity parameters when co-applied with a trace concentration of DS1 compared to when applied alone. In contrast, the potencies and efficacies displayed by DS1 at the networks were not substantially altered by the concomitant presence of diazepam. In conclusion, the holistic nature of the information extractable from the MEA recordings offers interesting insights into the contributions of various GABA.sub.A R subtypes/subgroups to cortical network activity and the putative functional interplay between these receptors in these neurons.

People with chronic tetraplegia, due to high-cervical spinal cord injury, can regain limb movements through coordinated electrical stimulation of peripheral muscles and nerves, known as functional electrical stimulation (FES). Users typically command FES systems through other preserved, but unrelated and limited in number, volitional movements (eg, facial muscle activity, head movements, shoulder shrugs). We report the findings of an individual with traumatic high-cervical spinal cord injury who coordinated reaching and grasping movements using his own paralysed arm and hand, reanimated through implanted FES, and commanded using his own cortical signals through an intracortical brain–computer interface (iBCI). We recruited a participant into the BrainGate2 clinical trial, an ongoing study that obtains safety information regarding an intracortical neural interface device, and investigates the feasibility of people with tetraplegia controlling assistive devices using their cortical signals. Surgical procedures were performed at University Hospitals Cleveland Medical Center (Cleveland, OH, USA). Study procedures and data analyses were performed at Case Western Reserve University (Cleveland, OH, USA) and the US Department of Veterans Affairs, Louis Stokes Cleveland Veterans Affairs Medical Center (Cleveland, OH, USA). The study participant was a 53-year-old man with a spinal cord injury (cervical level 4, American Spinal Injury Association Impairment Scale category A). He received two intracortical microelectrode arrays in the hand area of his motor cortex, and 4 months and 9 months later received a total of 36 implanted percutaneous electrodes in his right upper and lower arm to electrically stimulate his hand, elbow, and shoulder muscles. The participant used a motorised mobile arm support for gravitational assistance and to provide humeral abduction and adduction under cortical control. We assessed the participant's ability to cortically command his paralysed arm to perform simple single-joint arm and hand movements and functionally meaningful multi-joint movements. We compared iBCI control of his paralysed arm with that of a virtual three-dimensional arm. This study is registered with ClinicalTrials.gov, number NCT00912041. The intracortical implant occurred on Dec 1, 2014, and we are continuing to study the participant. The last session included in this report was Nov 7, 2016. The point-to-point target acquisition sessions began on Oct 8, 2015 (311 days after implant). The participant successfully cortically commanded single-joint and coordinated multi-joint arm movements for point-to-point target acquisitions (80–100% accuracy), using first a virtual arm and second his own arm animated by FES. Using his paralysed arm, the participant volitionally performed self-paced reaches to drink a mug of coffee (successfully completing 11 of 12 attempts within a single session 463 days after implant) and feed himself (717 days after implant). To our knowledge, this is the first report of a combined implanted FES+iBCI neuroprosthesis for restoring both reaching and grasping movements to people with chronic tetraplegia due to spinal cord injury, and represents a major advance, with a clear translational path, for clinically viable neuroprostheses for restoration of reaching and grasping after paralysis. National Institutes of Health, Department of Veterans Affairs.

Microelectrode arrays and microprobes have been widely utilized to measure neuronal activity, both in vitro and in vivo. The key advantage is the capability to record and stimulate neurons at multiple sites simultaneously. However, unlike the single-cell or single-channel resolution of intracellular recording, microelectrodes detect signals from all possible sources around every sensor. Here, we review the current understanding of microelectrode signals and the techniques for analyzing them. We introduce the ongoing advancements in microelectrode technology, with focus on achieving higher resolution and quality of recordings by means of monolithic integration with on-chip circuitry. We show how recent advanced microelectrode array measurement methods facilitate the understanding of single neurons as well as network function.

Speech brain–computer interfaces (BCIs) have the potential to restore rapid communication to people with paralysis by decoding neural activity evoked by attempted speech into text 1 , 2 or sound 3 , 4 . Early demonstrations, although promising, have not yet achieved accuracies sufficiently high for communication of unconstrained sentences from a large vocabulary 1 – 7 . Here we demonstrate a speech-to-text BCI that records spiking activity from intracortical microelectrode arrays. Enabled by these high-resolution recordings, our study participant—who can no longer speak intelligibly owing to amyotrophic lateral sclerosis—achieved a 9.1% word error rate on a 50-word vocabulary (2.7 times fewer errors than the previous state-of-the-art speech BCI 2 ) and a 23.8% word error rate on a 125,000-word vocabulary (the first successful demonstration, to our knowledge, of large-vocabulary decoding). Our participant’s attempted speech was decoded  at 62 words per minute, which is 3.4 times as fast as the previous record 8 and begins to approach the speed of natural conversation (160 words per minute 9 ). Finally, we highlight two aspects of the neural code for speech that are encouraging for speech BCIs: spatially intermixed tuning to speech articulators that makes accurate decoding possible from only a small region of cortex, and a detailed articulatory representation of phonemes that persists years after paralysis. These results show a feasible path forward for restoring rapid communication to people with paralysis who can no longer speak. A speech-to-text brain–computer interface that records spiking activity from intracortical microelectrode arrays enabled an individual who cannot speak intelligibly to achieve 9.1 and 23.8% word error rates on a 50- and 125,000-word vocabulary, respectively.

Understanding and manipulating gas bubble evolution during electrochemical water splitting is a crucial strategy for optimizing the electrode/electrolyte/gas bubble interface. Here gas bubble dynamics are investigated during the hydrogen evolution reaction on a well-defined platinum microelectrode by varying the electrolyte composition. We find that the microbubble coalescence efficiency follows the Hofmeister series of anions in the electrolyte. This dependency yields very different types of H2 gas bubble evolution in different electrolytes, ranging from periodic detachment of a single H2 gas bubble in sulfuric acid to aperiodic detachment of small H2 gas bubbles in perchloric acid. Our results indicate that the solutal Marangoni convection, induced by the anion concentration gradient developing during the reaction, plays a critical role at practical current density conditions. The resulting Marangoni force on the H2 gas bubble and the bubble departure diameter therefore depend on how surface tension varies with concentration for different electrolytes. This insight provides new avenues for controlling bubble dynamics during electrochemical gas bubble formation.Although gas bubble dynamics during electrochemical processes dramatically affect performance, the fundamental understanding and manipulation of such dynamics have been limited. Now, electrolyte composition is found to be a key factor in inducing a solutal Marangoni instability that impacts both H2 gas detachment and coalescence between H2 microbubbles.

A smart, safe, and efficient management of water is fundamental for both developed and developing countries. Several wireless sensor networks have been proposed for real-time monitoring of drinking water quantity and quality, both in the environment and in pipelines. However, surface fouling significantly affects the long-term reliability of pipes and sensors installed in-line. To address this relevant issue, we presented a multi-parameter sensing node embedding a miniaturized slime monitor able to estimate the micrometric thickness and type of slime. The measurement of thin deposits in pipes is descriptive of water biological and chemical stability and enables early warning functions, predictive maintenance, and more efficient management processes. After the description of the sensing node, the related electronics, and the data processing strategies, we presented the results of a two-month validation in the field of a three-node pilot network. Furthermore, self-powering by means of direct energy harvesting from the water flowing through the sensing node was also demonstrated. The robustness and low cost of this solution enable its upscaling to larger monitoring networks, paving the way to water monitoring with unprecedented spatio-temporal resolution.

Microelectrode arrays (MEAs) have enabled investigation of cellular networks at sub-millisecond temporal resolution. However, current MEAs are limited by the large electrode footprint since reducing the electrode's geometric area to sub-cellular dimensions leads to a significant increase in impedance thus affecting its recording capabilities. We report a breakthrough ultra-microelectrodes platform by leveraging the outstanding surface-to-volume ratio of nanowire-templated out-of-plane synthesized three-dimensional fuzzy graphene (NT-3DFG). The enormous surface area of NT-3DFG leads to 140-fold reduction in electrode impedance compared to bare Au microelectrodes, thus enabling scaling down the geometric size by 625-fold to ca. 2 μm × 2 μm. The out-of-plane morphology of NT-3DFG leads to a tight seal with the cell membrane thus enabling recording of electrical signals with high signal-to-noise ratio (SNR) of > 6. This work highlights the possibility to push the limits of the conventional MEA technology to enable electrophysiological investigation at sub-cellular level without the need of any surface coatings. This presented approach would greatly impact our basic understanding of signal transduction within a single cell as well as complex cellular assemblies.

The alpha rhythm is the longest-studied brain oscillation and has been theorized to play a key role in cognition. Still, its physiology is poorly understood. In this study, we used microelectrodes and macroelectrodes in surgical epilepsy patients to measure the intracortical and thalamic generators of the alpha rhythm during quiet wakefulness. We first found that alpha in both visual and somatosensory cortex propagates from higher-order to lower-order areas. In posterior cortex, alpha propagates from higher-order anterosuperior areas toward the occipital pole, whereas alpha in somatosensory cortex propagates from associative regions toward primary cortex. Several analyses suggest that this cortical alpha leads pulvinar alpha, complicating prevailing theories of a thalamic pacemaker. Finally, alpha is dominated by currents and firing in supragranular cortical layers. Together, these results suggest that the alpha rhythm likely reflects short-range supragranular feedback, which propagates from higher- to lower-order cortex and cortex to thalamus. These physiological insights suggest how alpha could mediate feedback throughout the thalamocortical system.

Approximately 20% of traumatic cervical spinal cord injuries result in tetraplegia. Neuroprosthetics are being developed to manage this condition and thus improve the lives of patients. We aimed to test the feasibility of a semi-invasive technique that uses brain signals to drive an exoskeleton. We recruited two participants at Clinatec research centre, associated with Grenoble University Hospital, Grenoble, France, into our ongoing clinical trial. Inclusion criteria were age 18–45 years, stability of neurological deficits, a need for additional mobility expressed by the patient, ambulatory or hospitalised monitoring, registration in the French social security system, and signed informed consent. The exclusion criteria were previous brain surgery, anticoagulant treatments, neuropsychological sequelae, depression, substance dependence or misuse, and contraindications to magnetoencephalography (MEG), EEG, or MRI. One participant was excluded because of a technical problem with the implants. The remaining participant was a 28-year-old man, who had tetraplegia following a C4–C5 spinal cord injury. Two bilateral wireless epidural recorders, each with 64 electrodes, were implanted over the upper limb sensorimotor areas of the brain. Epidural electrocorticographic (ECoG) signals were processed online by an adaptive decoding algorithm to send commands to effectors (virtual avatar or exoskeleton). Throughout the 24 months of the study, the patient did various mental tasks to progressively increase the number of degrees of freedom. Between June 12, 2017, and July 21, 2019, the patient cortically controlled a programme that simulated walking and made bimanual, multi-joint, upper-limb movements with eight degrees of freedom during various reach-and-touch tasks and wrist rotations, using a virtual avatar at home (64·0% [SD 5·1] success) or an exoskeleton in the laboratory (70·9% [11·6] success). Compared with microelectrodes, epidural ECoG is semi-invasive and has similar efficiency. The decoding models were reusable for up to approximately 7 weeks without recalibration. These results showed long-term (24-month) activation of a four-limb neuroprosthetic exoskeleton by a complete brain–machine interface system using continuous, online epidural ECoG to decode brain activity in a tetraplegic patient. Up to eight degrees of freedom could be simultaneously controlled using a unique model, which was reusable without recalibration for up to about 7 weeks. French Atomic Energy Commission, French Ministry of Health, Edmond J Safra Philanthropic Foundation, Fondation Motrice, Fondation Nanosciences, Institut Carnot, Fonds de Dotation Clinatec.

In recent years, considerable research and development efforts are devoted to improving the performance of polymer electrolyte fuel cells. However, the power density and catalytic activities of these energy conversion devices are still far from being satisfactory for large-scale operation. Here we report performance enhancement via incorporation, in the cathode catalyst layers, of a ring-structured backbone matrix into ionomers. Electrochemical characterizations of single cells and microelectrodes reveal that high power density is obtained using an ionomer with high oxygen solubility. The high solubility allows oxygen to permeate the ionomer/catalyst interface and react with protons and electrons on the catalyst surfaces. Furthermore, characterizations of single cells and single-crystal surfaces reveal that the oxygen reduction reaction activity is enhanced owing to the mitigation of catalyst poisoning by sulfonate anion groups. Molecular dynamics simulations indicate that both the high permeation and poisoning mitigation are due to the suppression of densely layered folding of polymer backbones near the catalyst surfaces by the incorporated ring-structured matrix. These experimental and theoretical observations demonstrate that ionomer’s tailored molecular design promotes local oxygen transport and catalytic reactions. Polymer electrolyte fuel cells are promising but suffer from low performance. Here, the authors use a combination of electrochemical measurements and molecular dynamics simulations to reveal the role of the highly oxygen permeable ionomer in polymer electrolyte fuel cells that enhances the oxygen transport and catalytic activity.