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Neuroprosthetics that combine a brain computer interface (BCI) with functional electrical stimulation (FES) can restore voluntary control of a patients’ own paralyzed limbs. To date, human studies have demonstrated an “all-or-none” type of control for a fixed number of pre-determined states, like hand-open and hand-closed. To be practical for everyday use, a BCI-FES system should enable smooth control of limb movements through a continuum of states and generate situationally appropriate, graded muscle contractions. Crucially, this functionality will allow users of BCI-FES neuroprosthetics to manipulate objects of different sizes and weights without dropping or crushing them. In this study, we present the first evidence that using a BCI-FES system, a human with tetraplegia can regain volitional, graded control of muscle contraction in his paralyzed limb. In addition, we show the critical ability of the system to generalize beyond training states and accurately generate wrist flexion states that are intermediate to training levels. These innovations provide the groundwork for enabling enhanced and more natural fine motor control of paralyzed limbs by BCI-FES neuroprosthetics.

Following traumatic brain injury (TBI), ischemia and hypoxia play a major role in further worsening of the damage, a process referred to as ‘secondary injury’. Protecting neurons from causative factors of secondary injury has been the guiding principle of modern TBI management. Stimulation of trigeminal nerve induces pressor response and improves cerebral blood flow (CBF) by activating the rostral ventrolateral medulla. Moreover, it causes cerebrovasodilation through the trigemino-cerebrovascular system and trigemino-parasympathetic reflex. These effects are capable of increasing cerebral perfusion, making trigeminal nerve stimulation (TNS) a promising strategy for TBI management. Here, we investigated the use of electrical TNS for improving CBF and brain oxygen tension (PbrO2), with the goal of decreasing secondary injury. Severe TBI was produced using controlled cortical impact (CCI) in a rat model, and TNS treatment was delivered for the first hour after CCI. In comparison to TBI group, TBI animals with TNS treatment demonstrated significantly increased systemic blood pressure, CBF and PbrO2 at the hyperacute phase of TBI. Furthermore, rats in TNS-treatment group showed significantly reduced brain edema, blood-brain barrier disruption, lesion volume, and brain cortical levels of TNF-α and IL-6. These data provide strong early evidence that TNS could be an effective neuroprotective strategy.

Neuroprosthetic technology has been used to restore cortical control of discrete (non-rhythmic) hand movements in a paralyzed person. However, cortical control of rhythmic movements which originate in the brain but are coordinated by Central Pattern Generator (CPG) neural networks in the spinal cord has not been demonstrated previously. Here we show a demonstration of an artificial neural bypass technology that decodes cortical activity and emulates spinal cord CPG function allowing volitional rhythmic hand movement. The technology uses a combination of signals recorded from the brain, machine-learning algorithms to decode the signals, a numerical model of CPG network, and a neuromuscular electrical stimulation system to evoke rhythmic movements. Using the neural bypass, a quadriplegic participant was able to initiate, sustain, and switch between rhythmic and discrete finger movements, using his thoughts alone. These results have implications in advancing neuroprosthetic technology to restore complex movements in people living with paralysis.