Development of a multi-electrode array for spinal cord epidural stimulation to facilitate stepping and standing after a complete spinal cord injury in adult rats

Background: Stimulation of the spinal cord has been shown to have great potential for improving function after motor deficits caused by injury or pathological conditions. Using a wide range of animal models, many studies have shown that stimulation applied to the neural networks intrinsic to the spinal cord can result in a dramatic improvement of motor ability, even allowing an animal to step and stand after a complete spinal cord transection. Clinical use of this technology, however, has been slow to develop due to the invasive nature of the implantation procedures, the lack of versatility in conventional stimulation technology, and the difficulty of ascertaining specific sites of stimulation that would provide optimal amelioration of the motor deficits. Moreover, the development of tools available to control precise stimulation chronically via biocompatible electrodes has been limited. In this paper, we outline the development of this technology and its use in the spinal rat model, demonstrating the ability to identify and stimulate specific sites of the spinal cord to produce discrete motor behaviors in spinal rats using this array. Methods: We have designed a chronically implantable, rapidly switchable, high-density platinum based multi-electrode array that can be used to stimulate at 1–100 Hz and 1–10 V in both monopolar and bipolar configurations to examine the electrophysiological and behavioral effects of spinal cord epidural stimulation in complete spinal cord transected rats. Results: In this paper, we have demonstrated the effectiveness of using high-resolution stimulation parameters in the context of improving motor recovery after a spinal cord injury. We observed that rats whose hindlimbs were paralyzed can stand and step when specific sets of electrodes of the array are stimulated tonically (40 Hz). Distinct patterns of stepping and standing were produced by stimulation of different combinations of electrodes on the array located at specific spinal cord levels and by specific stimulation parameters, i.e., stimulation frequency and intensity, and cathode/anode orientation. The array also was used to assess functional connectivity between the cord dorsum to interneuronal circuits and specific motor pools via evoked potentials induced at 1 Hz stimulation in the absence of any anesthesia. Conclusions: Therefore the high density electrode array allows high spatial resolution and the ability to selectively activate different neural pathways within the lumbosacral region of the spinal cord to facilitate standing and stepping in adult spinal rats and provides the capability to evoke motor potentials and thus a means for assessing connectivity between sensory circuits and specific motor pools and muscles

An Active Learning Algorithm for Control of Epidural Electrostimulation

Epidural electrostimulation has shown promise for spinal cord injury therapy. However, finding effective stimuli on the multi-electrode stimulating arrays employed requires a laborious manual search of a vast space for each patient. Widespread clinical application of these techniques would be greatly facilitated by an autonomous, algorithmic system which choses stimuli to simultaneously deliver effective therapy and explore this space. We propose a method based on GP-BUCB, a Gaussian process bandit algorithm. In n = 4 spinally transected rats, we implant epidural electrode arrays and examine the algorithm’s performance in selecting bipolar stimuli to elicit specified muscle responses. These responses are compared with temporally interleaved intra-animal stimulus selections by a human expert. GP-BUCB successfully controlled the spinal electrostimulation preparation in 37 testing sessions, selecting 670 stimuli. These sessions included sustained autonomous operations (ten-session duration). Delivered performance with respect to the specified metric was as good as or better than that of the human expert. Despite receiving no information as to anatomically likely locations of effective stimuli, GP-BUCB also consistently discovered such a pattern. Further, GP-BUCB was able to extrapolate from previous sessions’ results to make predictions about performance in new testing sessions, while remaining sufficiently flexible to capture temporal variability. These results provide validation for applying automated stimulus selection methods to the problem of spinal cord injury therapy

Sub-threshold spinal cord stimulation facilitates spontaneous motor activity in spinal rats

BACKGROUND: Epidural stimulation of the spinal cord can be used to enable stepping on a treadmill (electrical enabling motor control, eEmc) after a complete mid-thoracic spinal cord transection in adult rats. Herein we have studied the effects of eEmc using a sub-threshold intensity of stimulation combined with spontaneous load-bearing proprioception to facilitate hindlimb stepping and standing during daily cage activity in paralyzed rats. METHODS: We hypothesized that eEmc combined with spontaneous cage activity would greatly increase the frequency and level of activation of the locomotor circuits in paralyzed rats. Spontaneous cage activity was recorded using a specially designed swivel connector to record EMG signals and an IR based camcorder to record video. RESULTS AND CONCLUSION: The spinal rats initially were very lethargic in their cages showing little movement. Without eEmc, the rats remained rather inactive with the torso rarely being elevated from the cage floor. When the rats used their forelimbs to move, the hindlimbs were extended and dragged behind with little or no flexion. In contrast, with eEmc the rats were highly active and the hindlimbs showed robust alternating flexion and extension resulting in step-like movements during forelimb-facilitated locomotion and often would stand using the sides of the cages as support. The mean and summed integrated EMG levels in both a hindlimb flexor and extensor muscle were higher with than without eEmc. These data suggest that eEmc, in combination with the associated proprioceptive input, can modulate the spinal networks to significantly amplify the amount and robustness of spontaneous motor activity in paralyzed rats

Dose-Dependent Effects of Closed-Loop tACS Delivered During Slow-Wave Oscillations on Memory Consolidation

Sleep is critically important to consolidate information learned throughout the day. Slow-wave sleep (SWS) serves to consolidate declarative memories, a process previously modulated with open-loop non-invasive electrical stimulation, though not always effectively. These failures to replicate could be explained by the fact that stimulation has only been performed in open-loop, as opposed to closed-loop where phase and frequency of the endogenous slow-wave oscillations (SWOs) are matched for optimal timing. The current study investigated the effects of closed-loop transcranial Alternating Current Stimulation (tACS) targeting SWOs during sleep on memory consolidation. 21 participants took part in a three-night, counterbalanced, randomized, single-blind, within-subjects study, investigating performance changes (correct rate and F1 score) on images in a target detection task over 24 h. During sleep, 1.5 mA closed-loop tACS was delivered in phase over electrodes at F3 and F4 and 180° out of phase over electrodes at bilateral mastoids at the frequency (range 0.5–1.2 Hz) and phase of ongoing SWOs for a duration of 5 cycles in each discrete event throughout the night. Data were analyzed in a repeated measures ANOVA framework, and results show that verum stimulation improved post-sleep performance specifically on generalized versions of images used in training at both morning and afternoon tests compared to sham, suggesting the facilitation of schematization of information, but not of rote, veridical recall. We also found a surprising inverted U-shaped dose effect of sleep tACS, which is interpreted in terms of tACS-induced faciliatory and subsequent refractory dynamics of SWO power in scalp EEG. This is the first study showing a selective modulation of long-term memory generalization using a novel closed-loop tACS approach, which holds great potential for both healthy and neuropsychiatric populations

Spinal Cord Neuronal Circuit Dynamism During Sensorimotor Control

The versatility of the spinal cord as a sophisticated processor of information has been continually supported by a growing body of literature, which indicates that the spinal cord, like the brain, is capable of reorganization, learning, and the au- tonomous evaluation and modulation of sensory and motor signals. These proper- ties are of particular interest to the clinical research community, as these intrinsic properties of the spinal cord are currently being leveraged to provide novel ther- apies for amelioration of neuromotor deficits such as those associated with acute spinal cord injury (SCI) or stroke. An important missing component of these efforts, however, is a detailed, behaviorally-relevant understanding of the physiology responsible for motor behavior and nominal spinal cord function. Though some isolated circuits and overall network behaviors have been identified under various experimental conditions, investigators are still limited by the quantity and quality of data relevant to in vivo contexts of motor control and the role of descending inputs and afferent sensory information that serve to modulate the spinal cords ac- tivity. Identifying the mechanistic and dynamic properties of spinal cord circuitry is thus critical to the refinement of existing technologies and the development of newer, more effective methodology to treat neuromotor dysfunction

Pyramid Inter-Attention for High Dynamic Range Imaging

This paper proposes a novel approach to high-dynamic-range (HDR) imaging of dynamic scenes to eliminate ghosting artifacts in HDR images when in the presence of severe misalignment (large object or camera motion) in input low-dynamic-range (LDR) images. Recent non-flow-based methods suffer from ghosting artifacts in the presence of large object motion. Flow-based methods face the same issue since their optical flow algorithms yield huge alignment errors. To eliminate ghosting artifacts, we propose a simple yet effective alignment network for solving the misalignment. The proposed pyramid inter-attention module (PIAM) performs alignment of LDR features by leveraging inter-attention maps. Additionally, to boost the representation of aligned features in the merging process, we propose a dual excitation block (DEB) that recalibrates each feature both spatially and channel-wise. Exhaustive experimental results demonstrate the effectiveness of the proposed PIAM and DEB, achieving state-of-the-art performance in terms of producing ghost-free HDR images