A Brain-Machine-Muscle Interface for Restoring Hindlimb Locomotion after Complete Spinal Transection in Rats

A brain-machine interface (BMI) is a neuroprosthetic device that can restore motor function of individuals with paralysis. Although the feasibility of BMI control of upper-limb neuroprostheses has been demonstrated, a BMI for the restoration of lower-limb motor functions has not yet been developed. The objective of this study was to determine if gait-related information can be captured from neural activity recorded from the primary motor cortex of rats, and if this neural information can be used to stimulate paralysed hindlimb muscles after complete spinal cord transection. Neural activity was recorded from the hindlimb area of the primary motor cortex of six female Sprague Dawley rats during treadmill locomotion before and after mid-thoracic transection. Before spinal transection there was a strong association between neural activity and the step cycle. This association decreased after spinal transection. However, the locomotive state (standing vs. walking) could still be successfully decoded from neural recordings made after spinal transection. A novel BMI device was developed that processed this neural information in real-time and used it to control electrical stimulation of paralysed hindlimb muscles. This system was able to elicit hindlimb muscle contractions that mimicked forelimb stepping. We propose this lower-limb BMI as a future neuroprosthesis for human paraplegics.     

Movements of Indian Flying Fox in Myanmar as a Guide to Human-Bat Interface Sites

EcoHealth - Frugivorous bats play a vital role in tropical ecosystems as pollinators and seed dispersers but are also important vectors of zoonotic diseases. Myanmar sits at the intersection of...     

Neural Coding of Finger and Wrist Movements

Previous work (Schieber and Hibbard, 1993) has shown that single motor cortical neurons do not discharge specifically for a particular flexion-extension finger movement but instead are active with movements of different fingers. In addition, neuronal populations active with movements of different fingers overlap extensively in their spatial locations in the motor cortex. These data suggested that control of any finger movement utilizes a distributed population of neurons. In this study we applied the neuronal population vector analysis (Georgopoulos et al., 1983) to these same data to determine (1) whether single cells are tuned in an abstract, three-dimensional (3D) instructed finger and wrist movement space with hand-like geometry and (2) whether the neuronal population encodes specific finger movements. We found that the activity of 132/176 (75%) motor cortical neurons related to finger movements was indeed tuned in this space. Moreover, the population vector computed in this space predicted well the instructed finger movement. Thus, although single neurons may be related to several disparate finger movements, and neurons related to different finger movements are intermingled throughout the hand area of the motor cortex, the neuronal population activity does specify particular finger movements.     

手动与眼动反应抑制的认知神经机制

手动与眼动反应抑制是指抑制与当前环境不相适应的优势手动或眼动反应.与经典的Go/Nogo任务、停止信号任务测量的抑制水平相比,眼动抑制任务可提供更为丰富的指标,并分离出语言及手部运动反应的污染.手动与眼动反应抑制在不同神经精神疾病以及个体发展的不同阶段表现均有不同.额叶-基底神经节网络在手动和眼动抑制中发挥类似的作用,但额下回是手动抑制的关键脑区,额叶眼区和上丘则与眼动抑制关系更密切.目前,主要的争议集中在两者的神经机制、两者涉及的高级认知加工以及在神经心理学和发展心理学中的不同行为表现和发展趋势.     

Dynamic Neural Network Models of the Premotoneuronal Circuitry Controlling Wrist Movements in Primates

Dynamic recurrent neural networks were derived to simulate neuronal populations generating bidirectional wrist movements in the monkey. The models incorporate anatomical connections of cortical and rubral neurons, muscle afferents, segmental interneurons and motoneurons; they also incorporate the response profiles of four populations of neurons observed in behaving monkeys. The networks were derived by gradient descent algorithms to generate the eight characteristic patterns of motor unit activations observed during alternating flexion-extension wrist movements. The resulting model generated the appropriate input-output transforms and developed connection strengths resembling those in physiological pathways. We found that this network could be further trained to simulate additional tasks, such as experimentally observed reflex responses to limb perturbations that stretched or shortened the active muscles, and scaling of response amplitudes in proportion to inputs. In the final comprehensive network, motor units are driven by the combined activity of cortical, rubral, spinal and afferent units during step tracking and perturbations.The model displayed many emergent properties corresponding to physiological characteristics. The resulting neural network provides a working model of premotoneuronal circuitry and elucidates the neural mechanisms controlling motoneuron activity. It also predicts several features to be experimentally tested, for example the consequences of eliminating inhibitory connections in cortex and red nucleus. It also reveals that co-contraction can be achieved by simultaneous activation of the flexor and extensor circuits without invoking features specific to co-contraction.     

Hindlimb vascular responses to sympathetic augmentation during acute anemia

The effect of increased sympathetic activity on skeletal muscle blood flow during acute anemic hypoxia was studied in 16 anesthetized dogs. Sympathetic activity was altered by clamping the carotid arteries bilaterally below the carotid sinus. One group (n = 8) was beta blocked by administration of propranolol (1 mg/kg); a second group (n = 8) was untreated. Venous outflow from the left hindlimb was isolated for measurement of blood flow and O2 uptake (VO2). After a 20-min control period, both carotid arteries were clamped (CC) for 20 min followed by a 20-min recovery period. The sequence was repeated after hematocrit was lowered to about 15% by dextran exchange for blood. Prior to anemia, CC did not alter cardiac output or limb blood flow in either group. After induction of anemia, hindlimb resistance was higher with CC in the beta block than in the no block group. Both limb blood flow and VO2 fell in the beta-block group with CC during anemia. Beta block also prevented the additive increases in whole body VO2 seen with CC and induction of anemia. The data showed that the increased vasoconstrictor tone that was obtained with beta block during anemia was successful in redistributing the lower viscosity blood away from resting skeletal muscle, even to the point that muscle VO2 was decreased.     

Using Reinforcement Learning to Provide Stable Brain-Machine Interface Control Despite Neural Input Reorganization

Brain-machine interface (BMI) systems give users direct neural control of robotic, communication, or functional electrical stimulation systems. As BMI systems begin transitioning from laboratory settings into activities of daily living, an important goal is to develop neural decoding algorithms that can be calibrated with a minimal burden on the user, provide stable control for long periods of time, and can be responsive to fluctuations in the decoder’s neural input space (e.g. neurons appearing or being lost amongst electrode recordings). These are significant challenges for static neural decoding algorithms that assume stationary input/output relationships. Here we use an actor-critic reinforcement learning architecture to provide an adaptive BMI controller that can successfully adapt to dramatic neural reorganizations, can maintain its performance over long time periods, and which does not require the user to produce specific kinetic or kinematic activities to calibrate the BMI. Two marmoset monkeys used the Reinforcement Learning BMI (RLBMI) to successfully control a robotic arm during a two-target reaching task. The RLBMI was initialized using random initial conditions, and it quickly learned to control the robot from brain states using only a binary evaluative feedback regarding whether previously chosen robot actions were good or bad. The RLBMI was able to maintain control over the system throughout sessions spanning multiple weeks. Furthermore, the RLBMI was able to quickly adapt and maintain control of the robot despite dramatic perturbations to the neural inputs, including a series of tests in which the neuron input space was deliberately halved or doubled.     

Neurogenesis in the Hippocampus of Mice Exposed to Short-Term Hindlimb Unloading

Journal of Evolutionary Biochemistry and Physiology - Long-term spaceflights and simulated microgravity negatively affect the number of cognitive functions, including memory, learning, spatial...     

How to Restore Fairness After Doping Infringement?

This article addresses the question how to restore the biggest possible amount of fairness after a discovery of doping infringement. I will analyse eight actions that could be taken: (1) disqualification and re‐ranking, (2) change in official result, (3) medal stripping and medal re‐awarding, (4) ban, (5) rematch, (6) legal action, (7) apology and (8) forgiveness. I conclude that the best way to restore the biggest possible amount of fairness seems to be a selected combination of actions. I also propose that re‐ranking and medal re‐awarding should be accompanied by a ceremony in which the new winners are celebrated because they typically did not have the possibility of enjoying their success in front of the original audience.     

Regenerating Eye Tissues to Preserve and Restore Vision

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Current and Future Immunomodulation Strategies to Restore Tolerance in Autoimmune Diseases

Autoimmune diseases reflect a breakdown in self-tolerance that results from defects in thymic deletion of potentially autoreactive T cells (central tolerance) and in T-cell intrinsic and extrinsic mechanisms that normally control potentially autoreactive T cells in the periphery (peripheral tolerance). The mechanisms leading to autoimmune diseases are multifactorial and depend on a complex combination of genetic, epigenetic, molecular, and cellular elements that result in pathogenic inflammatory responses in peripheral tissues driven by self-antigen-specific T cells. In this article, we describe the different checkpoints of tolerance that are defective in autoimmune diseases as well as specific events in the autoimmune response which represent therapeutic opportunities to restore long-term tolerance in autoimmune diseases. We present evidence for the role of different pathways in animal models and the therapeutic strategies targeting these pathways in clinical trials in autoimmune diseases.Autoimmune diseases are debilitating conditions that affect a large and growing portion of the population (∼3%–5% in the United States) (Jacobson et al. 1997). Autoimmune diseases take a devastating toll on affected families and have a considerable economic impact. Thus, improving the understanding of autoimmune diseases and developing novel therapies have been significant goals in public health. The development of autoimmune diseases reflects a loss of tolerance of the immune system for self-antigens. With the exception of a few rare monogenic diseases such as immune dysregulation, polyendocrinopathy, enteropathy, X-linked syndrome (IPEX), and autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED) syndrome, the development of autoimmunity is a complex and multifactorial process. This process usually involves genetic predispositions and poorly defined environmental factors that result in slight alterations in many different checkpoints, which in turn tilts the balance toward autoreactivity and away from immunoregulation. Although clearly there are key roles for B cells, antigen-presenting cells (APCs), and the innate immune response in the development and progression of autoimmune diseases, this article will focus on autoreactive T cells and potential targets of tolerogenic treatments (Fig. 1). In addition, we will discuss selected strategies currently available or being developed in the clinic as well as future opportunities to prevent and treat these diseases. Finally, current clinical strategies available as the standard of care for autoimmune diseases rely on immunosuppressive and anti-inflammatory treatments that curtail the pathological events, alleviate symptoms, and provide short-term relief in some patients. Thus, we will focus for the most part on immunotherapies aimed at reestablishing long-term tolerance.Open in a separate windowFigure 1.Development of the pathogenic autoimmune response and targets for immunotherapy. Autoreactive T cells that escape thymic negative selection are usually controlled by intrinsic (inhibitory receptors) and extrinsic (regulatory cell populations) mechanisms of tolerance in the periphery. In individuals genetically prone to autoimmunity, one or several of these checkpoints are defective, resulting in expansion of autoreactive T cells that cannot be controlled by Tregs (red, autoreactive effector T cells; green, Tregs; gray, polyclonal conventional T cells). Autoreactive T cells migrate to their targeted tissue where cytotoxic mechanisms and uncontrolled inflammation mediated by soluble mediators released by T cells and innate cells result in tissue damage. Various immunotherapeutic strategies target different steps in this process. (A) The ultimate goal of immunotherapy is to alter the balance of pathogenic versus regulatory T cells to restore tolerance, as detailed in Figure 2. (B) Anti-CD3 mAbs, antigen-specific therapies, and costimulation blockade alter the interactions between autoreactive T cells and antigen-presenting cells (APCs) and/or the signaling pathways resulting from productive T-cell receptor (TCR) ligation after presentation of cognate self-peptide/MHC (major histocompatibility complexes) in the presence of costimulatory signals, leading to deletion, anergy, immune deviation, or induction of Tregs. (C) Many strategies aim at boosting Tregs, either by concomitantly deleting Teff and promoting Tregs, and thus resetting the immune system to various degrees, such as antithymocyte globulin (ATG), rapamycin plus IL-2, and autologous hematopoietic stem cell transplantation (HSCT), or directly providing Tregs through cellular therapy. (D,E) Some therapies target populations of APCs, such as depletion of B cells by rituximab or the promotion of self-antigen presentation specifically by tolerogenic dendritic cells (DCs). (F) The migration of autoreactive T cells to their target tissue is being altered by inhibitors of leukocyte trafficking such as natalizumab and fingolimod. These drugs may further promote tolerance by keeping autoreactive T cells in the lymph nodes (LN) during immunosuppression, a prerequisite for efficient immunomodulation in some cases. (G) Anti-inflammatory therapies such as tumor necrosis factor (TNF) antagonists reduce tissue damage but also create an immunological environment more favorable to the induction of Tregs and restoration of tolerance.     

Adaptation to Delayed Force Perturbations in Reaching Movements

Adaptation to deterministic force perturbations during reaching movements was extensively studied in the last few decades. Here, we use this methodology to explore the ability of the brain to adapt to a delayed velocity-dependent force field. Two groups of subjects preformed a standard reaching experiment under a velocity dependent force field. The force was either immediately proportional to the current velocity (Control) or lagged it by 50 ms (Test). The results demonstrate clear adaptation to the delayed force perturbations. Deviations from a straight line during catch trials were shifted in time compared to post-adaptation to a non-delayed velocity dependent field (Control), indicating expectation to the delayed force field. Adaptation to force fields is considered to be a process in which the motor system predicts the forces to be expected based on the state that a limb will assume in response to motor commands. This study demonstrates for the first time that the temporal window of this prediction needs not to be fixed. This is relevant to the ability of the adaptive mechanisms to compensate for variability in the transmission of information across the sensory-motor system.     

生物基因技术修复石油污染土壤研究进展

植物修复油污土壤是控制环境污染的有效途径,但在实际应用中存在着植物生物量较小、生长缓慢等不足。将具有修复功能的外源基因引入植物中,使转基因植物的生物修复功能大大增强,为解决土壤石油污染问题提供了有效手段。文章系统论述了转基因植物对石油污染土壤中有机污染物,尤其是对持久性有机污染物（POPs）的吸收、转化和降解作用以及近年来所取得的突破性进展,并指出了利用生物基因修复技术进行土壤石油污染研究的发展趋势。     

Application of Assisted Natural Regeneration to Restore Degraded Tropical Forestlands

Assisted natural regeneration (ANR) is a simple, low‐cost forest restoration method that can effectively convert deforested lands of degraded vegetation to more productive forests. The method aims to accelerate, rather than replace, natural successional processes by removing or reducing barriers to natural forest regeneration such as soil degradation, competition with weedy species, and recurring disturbances (e.g., fire, grazing, and wood harvesting). Compared to conventional reforestation methods involving planting of tree seedlings, ANR offers significant cost advantages because it reduces or eliminates the costs associated with propagating, raising, and planting seedlings. It is most effectively utilized at the landscape level in restoring the protective functions of forests such as watershed protection and soil conservation. ANR techniques are flexible and allow for the integration of various values such as timber production, biodiversity recovery, and cultivation of crops, fruit trees, and non‐timber forest products in the restored forest. This paper describes the steps of applying ANR and conditions under which it will be most effective. It also discusses ANR’s comparative advantages as well as some of its constraints.