Objective Spinal cord injury causes a drastic loss of motor, sensory and autonomic function. The goal of this project was to investigate the use of intraspinal microstimulation (ISMS) for producing long distances of walking over ground. ISMS is an electrical stimulation method developed for restoring motor function by activating spinal networks below the level of an injury. It produces movements of the legs by stimulating the ventral horn of the lumbar enlargement using fine penetrating electrodes (≤ 50µm diameter). Approach In each of five adult cats (4.2–5.5kg), ISMS was applied through 16 electrodes implanted with tips targeting lamina IX in the ventral horn bilaterally. A desktop system implemented a physiologically-based control strategy that delivered different stimulation patterns through groups of electrodes to evoke walking movements with appropriate limb kinematics and forces corresponding to swing and stance. Each cat walked over an instrumented 2.9m walkway and limb kinematics and forces were recorded. Main Results Both propulsive and supportive forces were required for over-ground walking. Cumulative walking distances ranging from 609m to 835m (longest tested) were achieved in three animals. In these three cats, the mean peak supportive force was 3.5±0.6N corresponding to full-weight-support of the hind legs, while the angular range of the hip, knee, and ankle joints were 23.1±2.0°, 29.1±0.2°, and 60.3±5.2°, respectively. To further demonstrate the viability of ISMS for future clinical use, a prototype implantable module was successfully implemented in a subset of trials and produced comparable walking performance. Significance By activating inherent locomotor networks within the lumbosacral spinal cord, ISMS was capable of producing bilaterally coordinated and functional over-ground walking with current amplitudes <100 µA. These exciting results suggest that ISMS may be an effective intervention for restoring functional walking after spinal cord injury.

Mirror neurons (MNs) have the distinguishing characteristic of modulating during both execution and observation of an action. Although most studies of MNs have focused on various features of the observed movement, MNs also may monitor the behavioral circumstances in which the movement is embedded, including time periods preceding and following the observed movement. Here, we recorded multiple MNs simultaneously from implanted electrode arrays as two male monkeys executed and observed a reach, grasp, and manipulate task involving different target objects. MNs were recorded from premotor cortex (PM-MNs) and primary motor cortex (M1-MNs). During execution trials, hidden Markov models (HMMs) applied to the activity of either PM-MN or M1-MN populations most often detected sequences of four hidden states, which we named according to the behavioral epoch during which each state began: initial, reaction, movement, and final. The hidden states of MN populations thus reflected not only the movement, but also three behavioral epochs during which no movement occurred. HMMs trained on execution trials could decode similar sequences of hidden states in observation trials, with complete hidden state sequences decoded more frequently from PM-MN populations than from M1-MN populations. Moreover, population trajectories projected in a 2D plane defined by execution trials were preserved in observation trials more for PM-MN than for M1-MN populations. These results suggest that MN populations represent entire behavioral sequences, including both movement and non-movement. PM-MN populations showed greater similarity than M1-MN populations in their representation of behavioral sequences during execution versus observation. Mirror neurons (MNs) are thought to provide a neural mechanism for understanding the actions of others. However, for an action to be understood, both the movement per se and the non-movement context before and after the movement need to be represented. We found that simultaneously recorded MN populations encoded sequential hidden neural states corresponding approximately to sequential behavioral epochs of a reach, grasp, and manipulate task. During observation trials, hidden state sequences were similar to those identified in execution trials. Hidden state similarity was stronger for MN populations in premotor cortex than for those in primary motor cortex. Execution/observation similarity of hidden state sequences may contribute to understanding the actions of others without actually performing the action oneself.

The biological central pattern generator (CPG) integrates open and closed loop control to produce over-ground walking. The goal of this study was to develop a physiologically based algorithm capable of mimicking the biological system to control multiple joints in the lower extremities for producing over-ground walking. The algorithm used state-based models of the step cycle each of which produced different stimulation patterns. Two configurations were implemented to restore over-ground walking in five adult anaesthetized cats using intramuscular stimulation (IMS) of the main hip, knee and ankle flexor and extensor muscles in the hind limbs. An open loop controller relied only on intrinsic timing while a hybrid-CPG controller added sensory feedback from force plates (representing limb loading), and accelerometers and gyroscopes (representing limb position). Stimulation applied to hind limb muscles caused extension or flexion in the hips, knees and ankles. A total of 113 walking trials were obtained across all experiments. Of these, 74 were successful in which the cats traversed 75% of the 3.5 m over-ground walkway. In these trials, the average peak step length decreased from 24.9 ± 8.4 to 21.8 ± 7.5 (normalized units) and the median number of steps per trial increased from 7 (Q1=6, Q3 = 9) to 9 (8, 11) with the hybrid-CPG controller. Moreover, these trials, the hybrid-CPG controller produced more successful steps (step length ≤ 20 cm; ground reaction force ≥ 12.5% body weight) than the open loop controller: 372 of 544 steps (68%) versus 65 of 134 steps (49%), respectively. This supports our previous preliminary findings, and affirms that physiologically based hybrid-CPG approaches produce more successful stepping than open loop controllers. The algorithm provides the foundation for a neural prosthetic controller and a framework to implement more detailed control of locomotion in the future.

Introduction In young adults, pairing a cognitive task with walking can have different effects on gait and cognitive task performance. In some cases, performance clearly declines whereas in others compensatory mechanisms maintain performance. This study investigates the preliminary finding of behavioral improvement in Go/NoGo response inhibition task performance during walking compared with sitting, which was observed at the piloting stage. Materials and Methods Mobile brain/body imaging (MoBI) was used to record electroencephalographic (EEG) activity, 3-dimensional (3D) gait kinematics and behavioral responses in the cognitive task, during sitting or walking on a treadmill. Results In a cohort of 26 young adults, 14 participants improved in measures of cognitive task performance while walking compared with sitting. These participants exhibited walking-related EEG amplitude reductions over frontal scalp regions during key stages of inhibitory control (conflict monitoring, control implementation, and pre-motor stages), accompanied by reduced stride-to-stride variability and faster responses to stimuli compared with those who did not improve. In contrast, 12 participants who did not improve exhibited no EEG amplitude differences across physical condition. Discussion The neural activity changes associated with performance improvement during dual tasking hold promise as cognitive flexibility markers that can potentially help assess cognitive decline in aging and neurodegeneration.