Walking naturally after spinal cord injury using a brain-spine interface.

A spinal cord injury interrupts the communication between the brain and the region of the spinal cord that produces walking, leading to paralysis. Here, we restored this communication with a digital bridge between the brain and spinal cord that enabled an individual with chronic tetraplegia to stand and walk naturally in community settings. This brain-spine interface (BSI) consists of fully implanted recording and stimulation systems that establish a direct link between cortical signals and the analogue modulation of epidural electrical stimulation targeting the spinal cord regions involved in the production of walking.

Neuromodulation in 2035: The Neurology Future Forecasting Series.

Neuromodulation devices are approved in the United States for the treatment of movement disorders, epilepsy, pain, and depression, and are used off-label for other neurologic indications. By 2035, advances in our understanding of neuroanatomical networks and in the mechanism of action of stimulation, coupled with developments in material science, miniaturization, energy storage, and delivery, will expand the use of neuromodulation devices. Neuromodulation approaches are flexible and modifiable.

Activity-dependent spinal cord neuromodulation rapidly restores trunk and leg motor functions after complete paralysis.

Epidural electrical stimulation (EES) targeting the dorsal roots of lumbosacral segments restores walking in people with spinal cord injury (SCI). However, EES is delivered with multielectrode paddle leads that were originally designed to target the dorsal column of the spinal cord. Here, we hypothesized that an arrangement of electrodes targeting the ensemble of dorsal roots involved in leg and trunk movements would result in superior efficacy, restoring more diverse motor activities after the most severe SCI.

Neuroprosthetic baroreflex controls haemodynamics after spinal cord injury.

Spinal cord injury (SCI) induces haemodynamic instability that threatens survival, impairs neurological recovery, increases the risk of cardiovascular disease, and reduces quality of life. Haemodynamic instability in this context is due to the interruption of supraspinal efferent commands to sympathetic circuits located in the spinal cord, which prevents the natural baroreflex from controlling these circuits to adjust peripheral vascular resistance. Epidural electrical stimulation (EES) of the spinal cord has been shown to compensate for interrupted supraspinal commands to motor circuits below the injury, and restored walking after paralysis.

Semi-supervised Training Data Selection Improves Seizure Forecasting in Canines with Epilepsy.

Objective: Conventional selection of pre-ictal EEG epochs for seizure prediction algorithm training data typically assumes a continuous pre-ictal brain state preceding a seizure. This is carried out by defining a fixed duration, pre-ictal time period before seizures from which pre-ictal training data epochs are uniformly sampled. However, stochastic physiological and pathological fluctuations in EEG data characteristics and underlying brain states suggest that pre-ictal state dynamics may be more complex, and selection of pre-ictal training data segments to reflect this could improve algorithm performance.

Targeted neurotechnology restores walking in humans with spinal cord injury.

Spinal cord injury leads to severe locomotor deficits or even complete leg paralysis. Here we introduce targeted spinal cord stimulation neurotechnologies that enabled voluntary control of walking in individuals who had sustained a spinal cord injury more than four years ago and presented with permanent motor deficits or complete paralysis despite extensive rehabilitation. Using an implanted pulse generator with real-time triggering capabilities, we delivered trains of spatially selective stimulation to the lumbosacral spinal cord with timing that coincided with the intended movement.

A brain-spine interface alleviating gait deficits after spinal cord injury in primates.

Spinal cord injury disrupts the communication between the brain and the spinal circuits that orchestrate movement. To bypass the lesion, brain-computer interfaces have directly linked cortical activity to electrical stimulation of muscles, and have thus restored grasping abilities after hand paralysis. Theoretically, this strategy could also restore control over leg muscle activity for walking.

Proceedings of the Eighth International Workshop on Advances in Electrocorticography.

Excerpted proceedings of the Eighth International Workshop on Advances in Electrocorticography (ECoG), which convened October 15-16, 2015 in Chicago, IL, are presented. The workshop series has become the foremost gathering to present current basic and clinical research in subdural brain signal recording and analysis.

Local field potential recordings in a non-human primate model of Parkinsons disease using the Activa PC + S neurostimulator.

Objective: Using the Medtronic Activa® PC + S system, this study investigated how passive joint manipulation, reaching behavior, and deep brain stimulation (DBS) modulate local field potential (LFP) activity in the subthalamic nucleus (STN) and globus pallidus (GP).

Approach: Five non-human primates were implanted unilaterally with one or more DBS leads. LFPs were collected in montage recordings during resting state conditions and during motor tasks that facilitate the expression of parkinsonian motor signs.

A flexible algorithm framework for closed-loop neuromodulation research systems.

Modulation of neural activity through electrical stimulation of tissue is an effective therapy for neurological diseases such as Parkinson's disease and essential tremor. Researchers are exploring improving therapy through adjustment of stimulation parameters based upon sensed data. This requires classifiers to extract features and estimate patient state.

A translational platform for prototyping closed-loop neuromodulation systems.

While modulating neural activity through stimulation is an effective treatment for neurological diseases such as Parkinson's disease and essential tremor, an opportunity for improving neuromodulation therapy remains in automatically adjusting therapy to continuously optimize patient outcomes. Practical issues associated with achieving this include the paucity of human data related to disease states, poorly validated estimators of patient state, and unknown dynamic mappings of optimal stimulation parameters based on estimated states. To overcome these challenges, we present an investigational platform including: an implanted sensing and stimulation device to collect data and run automated closed-loop algorithms; an external tool to prototype classifier and control-policy algorithms; and real-time telemetry to update the implanted device firmware and monitor its state.

An implantable bi-directional brain-machine interface system for chronic neuroprosthesis research.

An implantable bi-directional brain-machine interface (BMI) prototype is presented. With sensing, algorithm, wireless telemetry, and stimulation therapy capabilities, the system is designed for chronic studies exploring closed-loop and diagnostic opportunities for neuroprosthetics. In particular, we hope to enable fundamental chronic research into the physiology of neurological disorders, define key electrical biomarkers related to disease, and apply this learning to patient-specific algorithms for therapeutic stimulation and diagnostics.