A Closed Loop Brain-machine Interface for Epilepsy Control Using Dorsal Column Electrical Stimulation

The Efficacy of Transcranial Magnetic Stimulation in the Treatment of Obsessive-Compulsive Disorder: An Umbrella Review of Meta-Analyses

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) has been increasingly used for treating obsessive-compulsive disorder (OCD). Although several meta-analyses have explored its effectiveness and safety, there is no umbrella review specifically focused on rTMS for OCD. This umbrella review followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and analyzed relevant meta-analyses on rTMS for OCD.

METHODS

Twenty-three articles were identified from PubMed, and after screening, 12 meta-analyses were included in the review. The studies analyzed in the meta-analyses ranged from 10 to 27, with total participants ranging from 282 to 791. The most commonly studied regions were the dorsolateral prefrontal cortex (DLPFC), supplementary motor area (SMA), and orbito-frontal cortex (OFC).

RESULT

The majority of the meta-analyses consistently supported the effectiveness of rTMS in reducing OCD symptoms when applied to the DLPFC and SMA. Encouraging results were also observed when targeting the medial prefrontal cortex (mPFC) and anterior cingulate cortex (ACC) through deep transcranial magnetic stimulation (dTMS). However, there was a high level of heterogeneity in the findings of nine out of 12 meta-analyses.

CONCLUSION

In conclusion, existing evidence suggests that rTMS targeting the DLPFC and SMA consistently reduces OCD symptoms, but targeting the mPFC and ACC through dTMS shows variable results. However, the high heterogeneity in the study findings indicates a need for further research and standardization in the field.

The role of stimulus periodicity on spinal cord stimulation-induced artificial sensations in rodents

Objective.Sensory feedback is critical for effectively controlling brain-machine interfaces and neuroprosthetic devices. Spinal cord stimulation (SCS) is proposed as a technique to induce artificial sensory perceptions in rodents, monkeys, and humans. However, to realize the full potential of SCS as a sensory neuroprosthetic technology, a better understanding of the effect of SCS pulse train parameter changes on sensory detection and discrimination thresholds is necessary.Approach.Here we investigated whether stimulation periodicity impacts rats' ability to detect and discriminate SCS-induced perceptions at different frequencies.Main results.By varying the coefficient of variation (CV) of interstimulus pulse interval, we showed that at lower frequencies, rats could detect highly aperiodic SCS pulse trains at lower amplitudes (i.e. decreased detection thresholds). Furthermore, rats learned to discriminate stimuli with subtle differences in periodicity, and the just-noticeable differences from a highly aperiodic stimulus were smaller than those from a periodic stimulus.Significance.These results demonstrate that the temporal structure of an SCS pulse train is an integral parameter for modulating sensory feedback in neuroprosthetic applications.

Power-to-Noise Optimization in the Design of Neural Recording Amplifier Based on Current Scaling, Source Degeneration Resistor, and Current Reuse

This article presents the design of a low-power, low-noise neural signal amplifier for neural recording. The structure reduces the current consumption of the amplifier through current scaling technology and lowers the input-referred noise of the amplifier by combining a source degeneration resistor and current reuse technologies. The amplifier was fabricated using a 0.18 μm CMOS MS RF G process. The results show the front-end amplifier exhibits a measured mid-band gain of 40 dB/46 dB and a bandwidth ranging from 0.54 Hz to 6.1 kHz; the amplifier's input-referred noise was measured to be 3.1 μVrms, consuming a current of 3.8 μA at a supply voltage of 1.8 V, with a Noise Efficiency Factor (NEF) of 2.97. The single amplifier's active silicon area is 0.082 mm2.

Spike sorting in the presence of stimulation artifacts: a dynamical control systems approach

Objective. Bi-directional electronic neural interfaces, capable of both electrical recording and stimulation, communicate with the nervous system to permit precise calibration of electrical inputs by capturing the evoked neural responses. However, one significant challenge is that stimulation artifacts often mask the actual neural signals. To address this issue, we introduce a novel approach that employs dynamical control systems to detect and decipher electrically evoked neural activity despite the presence of electrical artifacts.Approach. Our proposed method leverages the unique spatiotemporal patterns of neural activity and electrical artifacts to distinguish and identify individual neural spikes. We designed distinctive dynamical models for both the stimulation artifact and each neuron observed during spontaneous neural activity. We can estimate which neurons were active by analyzing the recorded voltage responses across multiple electrodes post-stimulation. This technique also allows us to exclude signals from electrodes heavily affected by stimulation artifacts, such as the stimulating electrode itself, yet still accurately differentiate between evoked spikes and electrical artifacts.Main results. We applied our method to high-density multi-electrode recordings from the primate retina in anex vivosetup, using a grid of 512 electrodes. Through repeated electrical stimulations at varying amplitudes, we were able to construct activation curves for each neuron. The curves obtained with our method closely resembled those derived from manual spike sorting. Additionally, the stimulation thresholds we estimated strongly agreed with those determined through manual analysis, demonstrating high reliability (R2=0.951for human 1 andR2=0.944for human 2).Significance. Our method can effectively separate evoked neural spikes from stimulation artifacts by exploiting the distinct spatiotemporal propagation patterns captured by a dense, large-scale multi-electrode array. This technique holds promise for future applications in real-time closed-loop stimulation systems and for managing multi-channel stimulation strategies.

Deep brain stimulation of the subthalamic nucleus in Parkinson disease 2013-2023: where are we a further 10 years on?

Deep brain stimulation has been in clinical use for 30 years and during that time it has changed markedly from a small-scale treatment employed by only a few highly specialized centers into a widespread keystone approach to the management of disorders such as Parkinson's disease. In the intervening decades, many of the broad principles of deep brain stimulation have remained unchanged, that of electrode insertion into stereotactically targeted brain nuclei, however the underlying technology and understanding around the approach have progressed markedly. Some of the most significant advances have taken place over the last decade with the advent of artificial intelligence, directional electrodes, stimulation/recording implantable pulse generators and the potential for remote programming among many other innovations. New therapeutic targets are being assessed for their potential benefits and a surge in the number of deep brain stimulation implantations has given birth to a flourishing scientific literature surrounding the pathophysiology of brain disorders such as Parkinson's disease. Here we outline the developments of the last decade and look to the future of deep brain stimulation to attempt to discern some of the most promising lines of inquiry in this fast-paced and rapidly evolving field.

A Model for the Propagation of Seizure Activity in Normal Brain Tissue

Epilepsies are characterized by paroxysmal electrophysiological events and seizures, which can propagate across the brain. One of the main unsolved questions in epilepsy is how epileptic activity can invade normal tissue and thus propagate across the brain. To investigate this question, we consider three computational models at the neural network scale to study the underlying dynamics of seizure propagation, understand which specific features play a role, and relate them to clinical or experimental observations. We consider both the internal connectivity structure between neurons and the input properties in our characterization. We show that a paroxysmal input is sometimes controlled by the network while in other instances, it can lead the network activity to itself produce paroxysmal activity, and thus will further propagate to efferent networks. We further show how the details of the network architecture are essential to determine this switch to a seizure-like regime. We investigated the nature of the instability involved and in particular found a central role for the inhibitory connectivity. We propose a probabilistic approach to the propagative/non-propagative scenarios, which may serve as a guide to control the seizure by using appropriate stimuli.

Brain-machine-brain interfaces as the foundation for the next generation of neuroprostheses

The future of the field of brain-machine interfaces is proposed which highlights potential clinical applications of a new paradigm: brain-machine-brain interfaces.

Electrical stimulation in animal models of epilepsy: A review on cellular and electrophysiological aspects

Epilepsy is a debilitating condition, primarily refractory individuals, leading to the search for new efficient therapies. Electrical stimulation is an important method used for years to treat several neurological disorders. Currently, electrical stimulation is used to reduce epileptic crisis in patients and shows promising results. Even though the use of electricity to treat neurological disorders has grown worldwide, there are still many caveats that must be clarified, such as action mechanisms and more efficient stimulation treatment parameters. Thus, this review aimed to explore the comprehension of the main stimulation methods in animal models of epilepsy using rodents to develop new experimental protocols and therapeutic approaches.

Freezing of Gait in Parkinson's Disease: Invasive and Noninvasive Neuromodulation

INTRODUCTION

Freezing of gait (FoG) is one of the most disabling yet poorly understood symptoms of Parkinson's disease (PD). FoG is an episodic gait pattern characterized by the inability to step that occurs on initiation or turning while walking, particularly with perception of tight surroundings. This phenomenon impairs balance, increases falls, and reduces the quality of life.

MATERIALS AND METHODS

Clinical-anatomical correlations, electrophysiology, and functional imaging have generated several mechanistic hypotheses, ranging from the most distal (abnormal central pattern generators of the spinal cord) to the most proximal (frontal executive dysfunction). Here, we review the neuroanatomy and pathophysiology of gait initiation in the context of FoG, and we discuss targets of central nervous system neuromodulation and their outcomes so far. The PubMed database was searched using these key words: neuromodulation, freezing of gait, Parkinson's disease, and gait disorders.

CONCLUSION

Despite these investigations, the pathogenesis of this process remains poorly understood. The evidence presented in this review suggests FoG to be a heterogenous phenomenon without a single unifying pathologic target. Future studies rigorously assessing targets as well as multimodal approaches will be essential to define the next generation of therapeutic treatments.

Home Use of a Percutaneous Wireless Intracortical Brain-Computer Interface by Individuals With Tetraplegia

OBJECTIVE

Individuals with neurological disease or injury such as amyotrophic lateral sclerosis, spinal cord injury or stroke may become tetraplegic, unable to speak or even locked-in. For people with these conditions, current assistive technologies are often ineffective. Brain-computer interfaces are being developed to enhance independence and restore communication in the absence of physical movement. Over the past decade, individuals with tetraplegia have achieved rapid on-screen typing and point-and-click control of tablet apps using intracortical brain-computer interfaces (iBCIs) that decode intended arm and hand movements from neural signals recorded by implanted microelectrode arrays. However, cables used to convey neural signals from the brain tether participants to amplifiers and decoding computers and require expert oversight, severely limiting when and where iBCIs could be available for use. Here, we demonstrate the first human use of a wireless broadband iBCI.

METHODS

Based on a prototype system previously used in pre-clinical research, we replaced the external cables of a 192-electrode iBCI with wireless transmitters and achieved high-resolution recording and decoding of broadband field potentials and spiking activity from people with paralysis. Two participants in an ongoing pilot clinical trial completed on-screen item selection tasks to assess iBCI-enabled cursor control.

RESULTS

Communication bitrates were equivalent between cabled and wireless configurations. Participants also used the wireless iBCI to control a standard commercial tablet computer to browse the web and use several mobile applications. Within-day comparison of cabled and wireless interfaces evaluated bit error rate, packet loss, and the recovery of spike rates and spike waveforms from the recorded neural signals. In a representative use case, the wireless system recorded intracortical signals from two arrays in one participant continuously through a 24-hour period at home.

SIGNIFICANCE

Wireless multi-electrode recording of broadband neural signals over extended periods introduces a valuable tool for human neuroscience research and is an important step toward practical deployment of iBCI technology for independent use by individuals with paralysis. On-demand access to high-performance iBCI technology in the home promises to enhance independence and restore communication and mobility for individuals with severe motor impairment.

Generating artificial sensations with spinal cord stimulation in primates and rodents

For patients who have lost sensory function due to a neurological injury such as spinal cord injury (SCI), stroke, or amputation, spinal cord stimulation (SCS) may provide a mechanism for restoring somatic sensations via an intuitive, non-visual pathway. Inspired by this vision, here we trained rhesus monkeys and rats to detect and discriminate patterns of epidural SCS. Thereafter, we constructed psychometric curves describing the relationship between different SCS parameters and the animal's ability to detect SCS and/or changes in its characteristics. We found that the stimulus detection threshold decreased with higher frequency, longer pulse-width, and increasing duration of SCS. Moreover, we found that monkeys were able to discriminate temporally- and spatially-varying patterns (i.e. variations in frequency and location) of SCS delivered through multiple electrodes. Additionally, sensory discrimination of SCS-induced sensations in rats obeyed Weber's law of just-noticeable differences. These findings suggest that by varying SCS intensity, temporal pattern, and location different sensory experiences can be evoked. As such, we posit that SCS can provide intuitive sensory feedback in neuroprosthetic devices.

Advances in Carbon-Based Microfiber Electrodes for Neural Interfacing

Neural interfacing devices using penetrating microelectrode arrays have emerged as an important tool in both neuroscience research and medical applications. These implantable microelectrode arrays enable communication between man-made devices and the nervous system by detecting and/or evoking neuronal activities. Recent years have seen rapid development of electrodes fabricated using flexible, ultrathin carbon-based microfibers. Compared to electrodes fabricated using rigid materials and larger cross-sections, these microfiber electrodes have been shown to reduce foreign body responses after implantation, with improved signal-to-noise ratio for neural recording and enhanced resolution for neural stimulation. Here, we review recent progress of carbon-based microfiber electrodes in terms of material composition and fabrication technology. The remaining challenges and future directions for development of these arrays will also be discussed. Overall, these microfiber electrodes are expected to improve the longevity and reliability of neural interfacing devices.

Adenosine A2A receptor blockade improves neuroprosthetic learning by volitional control of population calcium signal in M1 cortical neurons

Volitional control is at the core of brain-machine interfaces (BMI) adaptation and neuroprosthetic-driven learning to restore motor function for disabled patients, but neuroplasticity changes and neuromodulation underlying volitional control of neuroprosthetic learning are largely unexplored. To better study volitional control at annotated neural population, we have developed an operant neuroprosthetic task with closed-loop feedback system by volitional conditioning of population calcium signal in the M1 cortex using fiber photometry recording. Importantly, volitional conditioning of the population calcium signal in M1 neurons did not improve within-session adaptation, but specifically enhanced across-session neuroprosthetic skill learning with reduced time-to-target and the time to complete 50 successful trials. With brain-behavior causality of the neuroprosthetic paradigm, we revealed that proficiency of neuroprosthetic learning by volitional conditioning of calcium signal was associated with the stable representational (plasticity) mapping in M1 neurons with the reduced calcium peak. Furthermore, pharmacological blockade of adenosine A_2A receptors facilitated volitional conditioning of neuroprosthetic learning and converted an ineffective volitional conditioning protocol to be the effective for neuroprosthetic learning. These findings may help to harness neuroplasticity for better volitional control of neuroprosthetic training and suggest a novel pharmacological strategy to improve neuroprosthetic learning in BMI adaptation by targeting striatal A_2A receptors.

Generating Artificial Sensations with Spinal Cord Stimulation in Primates and Rodents.. [DOI: 10.1101/2020.05.09.085647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

For patients who have lost sensory function due to a neurological injury such as spinal cord injury (SCI), stroke, or amputation, spinal cord stimulation (SCS) may provide a mechanism for restoring somatic sensations via an intuitive, non-visual pathway. Inspired by this vision, here we trained rhesus monkeys and rats to detect and discriminate patterns of epidural SCS. Thereafter, we constructed psychometric curves describing the relationship between different SCS parameters and the animal’s ability to detect SCS and/or changes in its characteristics. We found that the stimulus detection threshold decreased with higher frequency, longer pulse-width, and increasing duration of SCS. Moreover, we found that monkeys were able to discriminate temporally- and spatially-varying patterns (i.e. variations in frequency and location) of SCS delivered through multiple electrodes. Additionally, sensory discrimination of SCS-induced sensations in rats obeyed Weber’s law of just noticeable differences. These findings suggest that by varying SCS intensity, temporal pattern, and location different sensory experiences can be evoked. As such, we posit that SCS can provide intuitive sensory feedback in neuroprosthetic devices.

A Brain to Spine Interface for Transferring Artificial Sensory Information

Lack of sensory feedback is a major obstacle in the rapid absorption of prosthetic devices by the brain. While electrical stimulation of cortical and subcortical structures provides unique means to deliver sensory information to higher brain structures, these approaches require highly invasive surgery and are dependent on accurate targeting of brain structures. Here, we propose a semi-invasive method, Dorsal Column Stimulation (DCS) as a tool for transferring sensory information to the brain. Using this new approach, we show that rats can learn to discriminate artificial sensations generated by DCS and that DCS-induced learning results in corticostriatal plasticity. We also demonstrate a proof of concept brain-to-spine interface (BTSI), whereby tactile and artificial sensory information are decoded from the brain of an “encoder” rat, transformed into DCS pulses, and delivered to the spinal cord of a second “decoder” rat while the latter performs an analog-to-digital conversion during a sensory discrimination task. These results suggest that DCS can be used as an effective sensory channel to transmit prosthetic information to the brain or between brains, and could be developed as a novel platform for delivering tactile and proprioceptive feedback in clinical applications of brain-machine interfaces.

Seizure control in a neural mass model by an active disturbance rejection approach

A closed-loop neuromodulation automatically adjusts stimuli according to brain response in real time. It is viewed as a promising way to control medically intractable epilepsy. A suitable closed-loop modulation strategy, which is robust enough to unknown nonlinearities, dynamics, and disturbances, is in great need in the clinic. For the specialization of epilepsy, the Jansen’s neural mass model is utilized to simulate the undesired high amplitudes epileptic activities, and active disturbance rejection control is designed to suppress the high amplitudes of epileptiform discharges. With the help of active disturbance rejection control, closed-loop roots of the system are far from the imaginary axis. Time domain response shows that active disturbance rejection control is able to control seizure no matter whether disturbances exist or not. At the same time, frequency domain response presents that enough stability margins and a broader range of tunable controller parameters can be obtained. Stable regions have also been presented to provide guidance to choose the parameters of active disturbance rejection control. Numerical results show that, compared with proportional-integral control, more accurate modulation with less energy can be achieved by active disturbance rejection control. It confirms that the active disturbance rejection control-based neuromodulation solution is able to achieve a desired performance. It is a promising closed-loop neuromodulation strategy in seizure control.

A Programmable Multi-biomarker Neural Sensor for Closed-loop DBS

Most of the current closed-loop DBS devices use a single biomarker in their feedback loop which may limit their performance and applications. This paper presents design, fabrication, and validation of a programmable multi-biomarker neural sensor which can be integrated into closed-loop DBS devices. The device is capable of sensing a combination of low-frequency (7-45 Hz), and high-frequency (200-1000 Hz) neural signals. The signals can be amplified with a digitally programmable gain within the range 50-100 dB. The neural signals can be stored into a local memory for processing and validation. The sensing and storage functions are implemented via a combination of analog and digital circuits involving preamplifiers, filters, programmable post-amplifiers, microcontroller, digital potentiometer, and flash memory. The device is fabricated, and its performance is validated through: (i) bench tests using sinusoidal and pre-recorded neural signals, (ii) in-vitro tests using pre-recorded neural signals in saline solution, and (iii) in-vivo tests by recording neural signals from freely-moving laboratory mice. The animals were implanted with a PlasticsOne electrode, and recording was conducted after recovery from the electrode implantation surgery. The experimental results are presented and discussed confirming the successful operation of the device. The size and weight of the device enable tetherless back-mountable use in pre-clinical trials.

Cortical GABAergic Interneuron/Progenitor Transplantation as a Novel Therapy for Intractable Epilepsy

Epilepsy is a severe neurological disease affecting more than 70 million people worldwide that is characterized by unpredictable and abnormal electrical discharges resulting in recurrent seizures. Although antiepileptic drugs (AEDs) are the mainstay of epilepsy treatment for seizure control, about one third of patients with epilepsy suffer from intractable seizures that are unresponsive to AEDs. Furthermore, the patients that respond to AEDs typically experience adverse systemic side effects, underscoring the urgent need to develop new therapies that target epileptic foci rather than more systemic interventions. Neurosurgical removal of affected brain tissues or implanting neurostimulator devices are effective options only for a fraction of patients with drug-refractory seizures, so it is imperative to develop treatments that are more generally applicable and restorative in nature. Considering the abnormalities of GABAergic inhibitory interneurons in epileptic brain tissues, one strategy with considerable promise is to restore normal circuit function by transplanting GABAergic interneurons/progenitors into the seizure focus. In this review, we focus on recent studies of cortical GABAergic interneuron transplantation to treat epilepsy and discuss critical issues in moving this promising experimental therapeutic treatment into clinic.

Comparative Performance of Linear Multielectrode Probes and Single-Tip Electrodes for Intracortical Microstimulation and Single-Neuron Recording in Macaque Monkey

Intracortical microstimulation (ICMS) is one of the most widely employed techniques for providing causal evidence of the relationship between neuronal activity and specific motor, perceptual, or even cognitive functions. In recent years, several new types of linear multielectrode silicon probes have been developed, allowing researchers to sample neuronal activity at different depths along the same cortical site simultaneously and with high spatial precision. Nevertheless, silicon multielectrode probes have been rarely employed for ICMS studies and, more importantly, it is unknown whether and to what extent they can be used for combined recording and stimulation experiments. Here, we addressed these issues during both acute and chronic conditions. First, we compared the behavioral outcomes of ICMS delivered to the hand region of a monkey's motor cortex with multielectrode silicon probes, commercially available multisite stainless-steel probes and single-tip glass-coated tungsten microelectrodes. The results for all three of the probes were reliable and similar. Furthermore, we tested the impact of long-train ICMS delivered through chronically implanted silicon probes at different time intervals, from 1 to 198 days after ICMS sessions, showing that although the number of recorded neurons decreased over time, in line with previous studies, ICMS did not alter silicon probes' recording capabilities. These findings indicate that in ICMS experiments, the performance of linear multielectrode silicon probes is comparable to that of both single-tip and multielectrode stainless-steel probes, suggesting that the silicon probes can be successfully used for combined recording and stimulation studies in chronic conditions.

Electrical stimulus artifact cancellation and neural spike detection on large multi-electrode arrays

Simultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces. However, interpreting these measurements is challenging because the spike sorting process (identifying and segregating action potentials arising from different neurons) is greatly complicated by electrical stimulation artifacts across the array, which can exhibit complex and nonlinear waveforms, and overlap temporarily with evoked spikes. Here we develop a scalable algorithm based on a structured Gaussian Process model to estimate the artifact and identify evoked spikes. The effectiveness of our methods is demonstrated in both real and simulated 512-electrode recordings in the peripheral primate retina with single-electrode and several types of multi-electrode stimulation. We establish small error rates in the identification of evoked spikes, with a computational complexity that is compatible with real-time data analysis. This technology may be helpful in the design of future high-resolution sensory prostheses based on tailored stimulation (e.g., retinal prostheses), and for closed-loop neural stimulation at a much larger scale than currently possible.

Electrical stimulation of the dorsal columns of the spinal cord for Parkinson's disease

Spinal cord stimulation has been used for the treatment of chronic pain for decades. In 2009, our laboratory proposed, based on studies in rodents, that electrical stimulation of the dorsal columns of the spinal cord could become an effective treatment for motor symptoms associated with Parkinson's disease (PD). Since our initial report in rodents and a more recent study in primates, several clinical studies have now described beneficial effects of dorsal column stimulation in parkinsonian patients. In primates, we have shown that dorsal column stimulation activates multiple structures along the somatosensory pathway and desynchronizes the pathological cortico-striatal oscillations responsible for the manifestation of PD symptoms. Based on recent evidence, we argue that neurological disorders such as PD can be broadly classified as diseases emerging from abnormal neuronal timing, leading to pathological brain states, and that the spinal cord could be used as a "channel" to transmit therapeutic electrical signals to disrupt these abnormalities. © 2017 International Parkinson and Movement Disorder Society.

Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation

Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from neurophysiology, computer science, and engineering in an effort to establish real-time bidirectional links between living brains and artificial actuators. Although theoretical propositions and some proof of concept experiments on directly linking the brains with machines date back to the early 1960s, BMI research only took off in earnest at the end of the 1990s, when this approach became intimately linked to new neurophysiological methods for sampling large-scale brain activity. The classic goals of BMIs are 1) to unveil and utilize principles of operation and plastic properties of the distributed and dynamic circuits of the brain and 2) to create new therapies to restore mobility and sensations to severely disabled patients. Over the past decade, a wide range of BMI applications have emerged, which considerably expanded these original goals. BMI studies have shown neural control over the movements of robotic and virtual actuators that enact both upper and lower limb functions. Furthermore, BMIs have also incorporated ways to deliver sensory feedback, generated from external actuators, back to the brain. BMI research has been at the forefront of many neurophysiological discoveries, including the demonstration that, through continuous use, artificial tools can be assimilated by the primate brain's body schema. Work on BMIs has also led to the introduction of novel neurorehabilitation strategies. As a result of these efforts, long-term continuous BMI use has been recently implicated with the induction of partial neurological recovery in spinal cord injury patients.

The Hypothesis of Connecting Two Spinal Cords as a Way of Sharing Information between Two Brains and Nervous Systems

Direct communication between different nervous systems has been recently reported through Brain-to-Brain-Interfaces and brainet. Closed loops systems between the brain and the spinal cord from the same individual have also been demonstrated. However, the connection between different nervous systems through the spinal cord has not yet been considered. This paper raises the hypothesis that connecting two spinal cords (spinal cord - spinal cord connection) is an indirect mean for communication of two brains and a direct way of communication between two nervous systems. A concept of electrical fingerprint of a drug is introduced. The notion of connection between two parts of the same spinal cord to treat a paraplegic patient is also introduced. Possible applications of this technique are discussed in the context of psychology, psychiatry and mental health. Also, it is discussed that external information injected to a spinal cord as well as spinal cord - spinal cord connection can become new tools to (1) study the physiology of the nervous system, (2) model specific behaviors, (3) study and model disease traits (4) treat neuropsychiatric disorders and (5) share information between two nervous systems.