Abstract:We introduce a new class of neural implants with the topology and compliance of dura mater, the protective membrane of the brain and spinal cord. These neural interfaces, which we called e-dura, achieve chronic bio-integration within the subdural space where they conform to the statics and dynamics of neural tissue. e-dura embeds interconnects, electrodes and chemotrodes that sustain millions of mechanical stretch cycles, electrical stimulation pulses, and chemical injections. These integrated modalities enable multiple neuroprosthetic applications. e-dura extracted cortical states in freely behaving animals for brain machine interface, and delivered electrochemical spinal neuromodulation that restored locomotion after paralyzing spinal cord injury. e-dura offers a novel platform for chronic multimodal neural interfaces in basic research and neuroprosthetics.3 Neuroprosthetic medicine is improving the lives of countless individuals. Cochlear implants restore hearing in deaf children, deep brain stimulation alleviates Parkinsonian symptoms, and spinal cord neuromodulation attenuates chronic neuropathic pain (1). These interventions rely on implants developed in the 1980s (2, 3). Since then, advances in electroceutical, pharmaceutical, and more recently optogenetic treatments triggered development of myriad neural interfaces that combine multiple modalities (4-9). However, the conversion of these sophisticated technologies into chronic implants mediating long-lasting functional benefits has yet to be achieved. A recurring challenge restricting chronic bio-integration is the substantial biomechanical mismatch between implants and neural tissues (10-13). Here, we introduce a new class of soft multimodal neural interfaces that achieve chronic bio-integration, and we demonstrate their long-term efficacy in clinically relevant applications. e-dura fabrication. We designed and engineered soft interfaces that mimic the topology and mechanical behavior of the dura mater (Fig. 1A-B). The implant, which we called electronic dura mater or e-dura, integrates a transparent silicone substrate (120µm in thickness), stretchable gold interconnects (35nm in thickness), soft electrodes coated with a novel platinum-silicone composite (300µm in diameter), and a compliant fluidic microchannel (100µm x 50µm in crosssection) (Fig. 1C-D, fig. S1-S2-S3). The interconnects and electrodes transmit electrical excitation and transfer electrophysiological signals.The microfluidic channel, termed chemotrode (14), delivers drugs locally (Fig. 1C, fig. S3). Microcracks in the gold interconnects (15) and the newly developed soft platinum-silicone composite electrodes confer exceptional stretchability to the entire implant (Fig. 1B, Movie S1). The patterning techniques of metallization and microfluidics support rapid manufacturing of customized neuroprostheses.4 e-dura implantation. Most implants used experimentally or clinically to assess and treat neurological disorders are placed above the dura mater (3,(16)(17)(18). The compliance of e-...

Spinal cord injury disrupts the communication between the brain and the spinal circuits that orchestrate movement. To bypass the lesion, brain–computer interfaces1–3 have directly linked cortical activity to electrical stimulation of muscles, which have restored grasping abilities after hand paralysis1,4. Theoretically, this strategy could also restore control over leg muscle activity for walking5. However, replicating the complex sequence of individual muscle activation patterns underlying natural and adaptive locomotor movements poses formidable conceptual and technological challenges6,7. Recently, we showed in rats that epidural electrical stimulation of the lumbar spinal cord can reproduce the natural activation of synergistic muscle groups producing locomotion8–10. Here, we interfaced leg motor cortex activity with epidural electrical stimulation protocols to establish a brain–spinal interface that alleviated gait deficits after a spinal cord injury in nonhuman primates. Rhesus monkeys were implanted with an intracortical microelectrode array into the leg area of motor cortex; and a spinal cord stimulation system composed of a spatially selective epidural implant and a pulse generator with real-time triggering capabilities. We designed and implemented wireless control systems that linked online neural decoding of extension and flexion motor states with stimulation protocols promoting these movements. These systems allowed the monkeys to behave freely without any restrictions or constraining tethered electronics. After validation of the brain–spinal interface in intact monkeys, we performed a unilateral corticospinal tract lesion at the thoracic level. As early as six days post-injury and without prior training of the monkeys, the brain–spinal interface restored weight-bearing locomotion of the paralyzed leg on a treadmill and overground. The implantable components integrated in the brain–spinal interface have all been approved for investigational applications in similar human research, suggesting a practical translational pathway for proof-of-concept studies in people with spinal cord injury.

Epidural electrical stimulation (EES) of the spinal cord and real-time processing of gait kinematics are powerful methods for the study of locomotion and the improvement of motor control after injury or in neurological disorders. Here, we describe equipment and surgical procedures that can be used to acquire chronic electromyographic (EMG) recordings from leg muscles and to implant targeted spinal cord stimulation systems that remain stable up to several months after implantation in rats and nonhuman primates. We also detail how to exploit these implants to configure electrical spinal cord stimulation policies that allow control over the degree of extension and flexion of each leg during locomotion. This protocol uses real-time processing of gait kinematics and locomotor performance, and can be configured within a few days. Once configured, stimulation bursts are delivered over specific spinal cord locations with precise timing that reproduces the natural spatiotemporal activation of motoneurons during locomotion. These protocols can also be easily adapted for the safe implantation of systems in the vicinity of the spinal cord and to conduct experiments involving real-time movement feedback and closed-loop controllers.

Brain-machine interface (BMI) devices make errors in decoding. Detecting these errors online from neuronal activity can improve BMI performance by modifying the decoding algorithm and by correcting the errors made. Here, we study the neuronal correlates of two different types of errors which can both be employed in BMI: (i) the execution error, due to inaccurate decoding of the subjects' movement intention; (ii) the outcome error, due to not achieving the goal of the movement. We demonstrate that, in electrocorticographic (ECoG) recordings from the surface of the human brain, strong error-related neural responses (ERNRs) for both types of errors can be observed. ERNRs were present in the low and high frequency components of the ECoG signals, with both signal components carrying partially independent information. Moreover, the observed ERNRs can be used to discriminate between error types, with high accuracy (≥83%) obtained already from single electrode signals. We found ERNRs in multiple cortical areas, including motor and somatosensory cortex. As the motor cortex is the primary target area for recording control signals for a BMI, an adaptive motor BMI utilizing these error signals may not require additional electrode implants in other brain areas.