Automated lever task with minimum antigravity movement for rats with cervical spinal cord injury.

BACKGROUND: Although there is currently no cure for paralysis due to spinal cord injury (SCI), the highest treatment priority is restoring arm and hand function for people with cervical SCI. Preclinical animal models provide an opportunity to test innovative treatments, but severe cervical injury models require significant time and effort to assess responses to novel interventions. Moreover, there is no behavioral task that can assess forelimb movement in rats with severe cervical SCI unable to perform antigravity movements. NEW METHOD: We developed a novel lever pressing task for rats with severe cervical SCI. We employed an automated adaptive algorithm to train animals using open-source software and commercially available hardware. We found that using the adaptive training required only 13.3 ± 2.5 training days to achieve behavioral proficiency. The lever press task could quantify immediate and long-term improvements in severely impaired forelimb function effectively. This behavior platform has potential to facilitate rehabilitative training and assess effects of therapeutic modalities following SCI. COMPARISON WITH EXISTING METHODS: There is no existing assessment aiming to quantify forelimb extension movement in rodents without function against gravity. We found that the new lever press task in the antigravity position could assess the severity of cervical SCI as well as the compensatory movement in the proximal forelimb less affected by the injury. CONCLUSIONS: This study demonstrates that the new behavioral task is capable of tracking the functional changes with various therapies in rats with severe forelimb impairments in a cost- and time-efficient manner.

Brain-Computer-Spinal Interface Restores Upper Limb Function After Spinal Cord Injury.

Brain-computer interfaces (BCIs) are an emerging strategy for spinal cord injury (SCI) intervention that may be used to reanimate paralyzed limbs. This approach requires decoding movement intention from the brain to control movement-evoking stimulation. Common decoding methods use spike-sorting and require frequent calibration and high computational complexity. Furthermore, most applications of closed-loop stimulation act on peripheral nerves or muscles, resulting in rapid muscle fatigue. Here we show that a local field potential-based BCI can control spinal stimulation and improve forelimb function in rats with cervical SCI. We decoded forelimb movement via multi-channel local field potentials in the sensorimotor cortex using a canonical correlation analysis algorithm. We then used this decoded signal to trigger epidural spinal stimulation and restore forelimb movement. Finally, we implemented this closed-loop algorithm in a miniaturized onboard computing platform. This Brain-Computer-Spinal Interface (BCSI) utilized recording and stimulation approaches already used in separate human applications. Our goal was to demonstrate a potential neuroprosthetic intervention to improve function after upper extremity paralysis.

Ultra-Capacitive Carbon Neural Probe Allows Simultaneous Long-Term Electrical Stimulations and High-Resolution Neurotransmitter Detection.

We present a new class of carbon-based neural probes that consist of homogeneous glassy carbon (GC) microelectrodes, interconnects and bump pads. These electrodes have purely capacitive behavior with exceptionally high charge storage capacity (CSC) and are capable of sustaining more than 3.5 billion cycles of bi-phasic pulses at charge density of 0.25 mC/cm2. These probes enable both high SNR (>16) electrical signal recording and remarkably high-resolution real-time neurotransmitter detection, on the same platform. Leveraging a new 2-step, double-sided pattern transfer method for GC structures, these probes allow extended long-term electrical stimulation with no electrode material corrosion. Cross-section characterization through FIB and SEM imaging demonstrate strong attachment enabled by hydroxyl and carbonyl covalent bonds between GC microstructures and top insulating and bottom substrate layers. Extensive in-vivo and in-vitro tests confirmed: (i) high SNR (>16) recordings, (ii) highest reported CSC for non-coated neural probe (61.4 ± 6.9 mC/cm2), (iii) high-resolution dopamine detection (10 nM level - one of the lowest reported so far), (iv) recording of both electrical and electrochemical signals, and (v) no failure after 3.5 billion cycles of pulses. Therefore, these probes offer a compelling multi-modal platform for long-term applications of neural probe technology in both experimental and clinical neuroscience.