Towards a neural hierarchy of time scales for motor control

Animals show remarkable rich motion skills which are still far from realizable with robots. Inspired by the neural circuits which generate rhythmic motion patterns in the spinal cord of all vertebrates, one main research direction points towards the use of central pattern generators in robots. On of the key advantages of this, is that the dimensionality of the control problem is reduced. In this work we investigate this further by introducing a multi-timescale control hierarchy with at its core a hierarchy of recurrent neural networks. By means of some robot experiments, we demonstrate that this hierarchy can embed any rhythmic motor signal by imitation learning. Furthermore, the proposed hierarchy allows the tracking of several high level motion properties (e.g.: amplitude and offset), which are usually observed at a slower rate than the generated motion. Although these experiments are preliminary, the results are promising and have the potential to open the door for rich motor skills and advanced control

Clinical and Immunological Diversity of Recombination Defects

__abstract__ The immune system is capable to detect a large variability of pathogens and distinguish them from the body’s own healthy tissue. The immune system consists of the innate- and adaptive immune system. The adaptive immune system consists of B-and T-lymphocytes, which can recognize pathogens with an antigen-specific receptor. B-lymphocytes can adapt their responses during an infection to improve recognition of the pathogen and they generate long-term immunological memory. These antigen-specific receptors are called B-cell receptor (BR) and T-cell receptor (TR), respectively. Since the number of possible antigens is innumerable, an enormous diversity of the antigen-specific receptors is required. To achieve this, the BR and TR contain a variable domain that is unique for each individual T or B cell. This variable domain is generated by recombination of the antigen receptor genes in a process which is called V(D

Evolution of central pattern generators for the control of a five-link bipedal walking mechanism

Central pattern generators (CPGs), with a basis is neurophysiological studies, are a type of neural network for the generation of rhythmic motion. While CPGs are being increasingly used in robot control, most applications are hand-tuned for a specific task and it is acknowledged in the field that generic methods and design principles for creating individual networks for a given task are lacking. This study presents an approach where the connectivity and oscillatory parameters of a CPG network are determined by an evolutionary algorithm with fitness evaluations in a realistic simulation with accurate physics. We apply this technique to a five-link planar walking mechanism to demonstrate its feasibility and performance. In addition, to see whether results from simulation can be acceptably transferred to real robot hardware, the best evolved CPG network is also tested on a real mechanism. Our results also confirm that the biologically inspired CPG model is well suited for legged locomotion, since a diverse manifestation of networks have been observed to succeed in fitness simulations during evolution.Comment: 11 pages, 9 figures; substantial revision of content, organization, and quantitative result

Neuromuscular Controller Embedded in a Powered Ankle Exoskeleton:Effects on Gait, Clinical Features and Subjective Perspective of Incomplete Spinal Cord Injured Subjects

Powered exoskeletons are among the emerging technologies claiming to assist functional ambulation. The potential to adapt robotic assistance based on specific motor abilities of incomplete spinal cord injury (iSCI) subjects, is crucial to optimize Human-Robot Interaction (HRI). Achilles, an autonomous wearable robot able to assist ankle during walking, was developed for iSCI subjects and utilizes a NeuroMuscular Controller (NMC). NMC can be used to adapt robotic assistance based on specific residual functional abilities of subjects. The main aim of this pilot study was to analyze the effects of the NMC-controlled Achilles, used as an assistive device, on chronic iSCI participants' performance, by assessing gait speed during 10-session training of robot-aided walking. Secondary aims were to assess training impact on participants' motion, clinical and functional features and to evaluate subjective perspective in terms of attitude towards technology, workload, usability and satisfaction. Results showed that 5 training sessions were necessary to significantly improve robot-aided gait speed on short paths and consequently to optimize HRI. Moreover, the training allowed participants who initially were not able to walk for 6 minutes, to improve gait endurance during Achilles-aided walking and to reduce perceived fatigue. Improvements were obtained also in gait speed during free walking, thus suggesting a potential rehabilitative impact, even if Achilles-aided walking was not faster than free walking. Participants' subjective evaluations indicated a positive experience

ImmunoGlobulin galaxy (IGGalaxy) for simple determination and quantitation of immunoglobulin heavy chain rearrangements from NGS

Background: Sequence analysis of immunoglobulin heavy chain (IGH) gene rearrangements and frequency analysis is a powerful tool for studying the immune repertoire, immune responses and immune dysregulation in health and disease. The challenge is to provide user friendly, secure and reproducible analytical services that are available for both small and large laboratories which are determining VDJ repertoire using NGS technology. Results: In this study we describe ImmunoGlobulin Galaxy (IGGalaxy)- a convenient web based application for analyzing next-generation sequencing results and reporting IGH gene rearrangements for both repertoire and clonality studies. IGGalaxy has two analysis options one using the built in igBLAST algorithm and the second using output from IMGT; in either case repertoire summaries for the B-cell populations tested are available. IGGalaxy supports multi-sample and multi-replicate input analysis for both igBLAST and IMGT/HIGHV-QUEST. We demonstrate the technical validity of this platform using a standard dataset, S22, used for benchmarking the performance of antibody alignment utilities with a 99.9 % concordance with previous results. Re-analysis of NGS data from our samples of RAG-deficient patients demonstrated the validity and user friendliness of this tool. Conclusions: IGGalaxy provides clinical researchers with detailed insight into the repertoire of the B-cell population per individual sequenced and between control and pathogenic genomes. IGGalaxy was developed for 454 NGS results but is capable of analyzing alternative NGS data (e.g. Illumina, Ion Torrent). We demonstrate the use of a Galaxy virtual machine to determine the VDJ repertoire for reference data and from B-cells taken from immune deficient patients. IGGalaxy is available as a VM for download and use on a desktop PC or on a server

Immunodeficiency in Bloom’s Syndrome

Bloom’s syndrome (BS) is an autosomal recessive disease, caused by mutations in the BLM gene. This gene codes for BLM protein, which is a helicase involved in DNA repair. DNA repair is especially important for the development and maturation of the T and B cells. Since BLM is involved in DNA repair, we aimed to study if BLM deficiency affects T and B cell development and especially somatic hypermutation (SHM) and class switch recombination (CSR) processes. Clinical data of six BS patients was collected, and immunoglobulin serum levels were measured at different time points. In addition, we performed immune phenotyping of the B and T cells and analyzed the SHM and CSR in detail by analyzing IGHA and IGHG transcripts using next-generation sequencing. The serum immunoglobulin levels were relatively low, and patients had an increased number of infections. The absolute number of T, B, and NK cells were low but still in the normal range. Remarkably, all BS patients studied had a high percentage (20–80%) of CD4+ and CD8+ effector memory T cells. The process of SHM seems normal; however, the Ig subclass distribution was not normal, since the BS patients had more IGHG1 and IGHG3 transcripts. In conclusion, BS patients have low number of lymphocytes, but the immunodeficiency seems relatively mild since they have no severe or opportunistic infections. Most changes in the B cell development were seen in the CSR process; however, further studies are necessary to elucidate the exact role of BLM in CSR

Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors

Nonlinear dynamical systems have been used in many disciplines to model complex behaviors, including biological motor control, robotics, perception, economics, traffic prediction, and neuroscience. While often the unexpected emergent behavior of nonlinear systems is the focus of investigations, it is of equal importance to create goal-directed behavior (e.g., stable locomotion from a system of coupled oscillators under perceptual guidance). Modeling goal-directed behavior with nonlinear systems is, however, rather difficult due to the parameter sensitivity of these systems, their complex phase transitions in response to subtle parameter changes, and the difficulty of analyzing and predicting their long-term behavior; intuition and time-consuming parameter tuning play a major role. This letter presents and reviews dynamical movement primitives, a line of research for modeling attractor behaviors of autonomous nonlinear dynamical systems with the help of statistical learning techniques. The essence of our approach is to start with a simple dynamical system

Protein functionality as a potential bottleneck for somatic revertant variants

Transplantation and immunomodulatio