01152nas a2200145   4500008004100000022001400041245003100055210002900086300001200115490000800127520078900135653001300924100002100937856004800958       2013                        eng d  a0072-975200aBrain-computer interfaces.0 aBraincomputer interfaces  a67–740 v1103 aBrain-computer interfaces (BCIs) are systems that give their users communication and control capabilities that do not depend on muscles. The user&#39;s intentions are determined from activity recorded by electrodes on the scalp, on the cortical surface, or within the brain. BCIs can enable people who are paralyzed by amyotrophic lateral sclerosis (ALS), brainstem stroke, or other disorders to convey their needs and wishes to others, to operate word-processing programs or other software, or possibly to control a wheelchair or a neuroprosthesis. BCI technology might also augment rehabilitation protocols aimed at restoring useful motor function. With continued development and clinical implementation, BCIs could substantially improve the lives of those with severe disabilities.10aSoftware1 aWolpaw, Jonathan  uhttp://www.ncbi.nlm.nih.gov/pubmed/2331263107041nas a2200313   4500008004100000022001400041245008200055210006900137260001200206300001100218490000600229520615100235653002806386653001006414653001806424653002706442653002106469653003106490653001106521653002406532653001306556653002806569100001906597700001506616700001306631700001606644700001906660856004806679       2011                        eng d  a1741-255200aCurrent Trends in Hardware and Software for Brain-Computer Interfaces (BCIs).0 aCurrent Trends in Hardware and Software for BrainComputer Interf  c04/2011  a0250010 v83 a<p><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">A&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">brain-computer interface</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;(</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">BCI</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">) provides a non-muscular communication channel to people with and without disabilities.&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">BCI</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;devices consist of hardware and software.&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">BCI</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;hardware records signals from the&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">brain</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">, either invasively or non-invasively, using a series of device components.&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">BCI</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;software then translates these signals into device output commands and provides feedback. One may categorize different types of&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">BCI</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;applications into the following four categories: basic&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">research</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">, clinical/translational&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">research</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">, consumer products, and emerging applications. These four categories use&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">BCI</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;hardware and software, but have different sets of requirements. For example, while basic&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">research</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;needs to explore a wide range of system configurations, and thus requires a wide range of hardware and software capabilities, applications in the other three categories may be designed for relatively narrow purposes and thus may only need a very limited subset of capabilities. This paper summarizes technical aspects for each of these four categories of&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">BCI</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;applications. The results indicate that&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">BCI</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;technology is in transition from isolated demonstrations to systematic&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">research</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;and commercial&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">development</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">. This process requires several multidisciplinary efforts, including the&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">development</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;of better integrated and more robust&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">BCI</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;hardware and software, the definition of standardized&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">interfaces</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">, and the&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">development</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">of certification, dissemination and reimbursement procedures.</span></p>10aBiofeedback, Psychology10aBrain10aBrain Mapping10aElectroencephalography10aEquipment Design10aEquipment Failure Analysis10aHumans10aMan-Machine Systems10aSoftware10aUser-Computer Interface1 aBrunner, Peter1 aBianchi, L1 aGuger, C1 aCincotti, F1 aSchalk, Gerwin  uhttp://www.ncbi.nlm.nih.gov/pubmed/2143653604251nas a2200505   4500008004100000022001400041245009900055210006900154260001200223300001200235490000700247520283600254653003103090653001503121653001003136653001003146653001003156653002703166653002903193653001103222653001103233653001303244653000903257653001603266653001703282653003303299653001903332653002803351653001303379653002203392653001303414653004303427653002803470653001303498100001603511700002203527700001803549700002103567700001903588700002103607700002203628700002703650700002003677856004803697       2008                        eng d  a0361-923000aNon-invasive brain-computer interface system: towards its application as assistive technology.0 aNoninvasive braincomputer interface system towards its applicati  c04/2008  a796-8030 v753 a<p><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">The quality of life of people suffering from severe motor disabilities can benefit from the use of current assistive technology capable of ameliorating communication, house-environment management and mobility, according to the user's residual motor abilities.&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">Brain-computer interfaces</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;(BCIs) are systems that can translate&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">brain</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;activity into signals that control external devices. Thus they can represent the only technology for severely paralyzed patients to increase or maintain their communication and control options. Here we report on a pilot study in which a system was implemented and validated to allow disabled persons to improve or recover their mobility (directly or by emulation) and communication within the surrounding environment. The system is based on a software controller that offers to the user a communication interface that is matched with the individual's residual motor abilities. Patients (n=14) with severe motor disabilities due to progressive neurodegenerative disorders were trained to use the system prototype under a rehabilitation program carried out in a house-like furnished space. All users utilized regular assistive control options (e.g., microswitches or head trackers). In addition, four subjects learned to operate the system by means of a non-invasive EEG-based BCI. This system was controlled by the subjects' voluntary modulations of EEG sensorimotor rhythms recorded on the scalp; this skill was learnt even though the subjects have not had control over their limbs for a long time. We conclude that such a prototype system, which integrates several different assistive technologies including a BCI system, can potentially facilitate the translation from pre-</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">clinical</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;demonstrations to a&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">clinical</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;useful BCI.</span></p>10aActivities of Daily Living10aAdolescent10aAdult10aBrain10aChild10aElectroencephalography10aEvoked Potentials, Motor10aFemale10aHumans10aLearning10aMale10aMiddle Aged10aMotor Skills10aMuscular Dystrophy, Duchenne10aPilot Projects10aProstheses and Implants10aRobotics10aSelf-Help Devices10aSoftware10aSpinal Muscular Atrophies of Childhood10aUser-Computer Interface10aVolition1 aCincotti, F1 aMattia, Donatella1 aAloise, Fabio1 aBufalari, Simona1 aSchalk, Gerwin1 aOriolo, Giuseppe1 aCherubini, Andrea1 aMarciani, Maria Grazia1 aBabiloni, Fabio  uhttp://www.ncbi.nlm.nih.gov/pubmed/1839452601670nas a2200289   4500008004100000022001400041245011900055210006900174260001200243300001200255490000600267520076600273653004001039653002501079653002201104653002401126653001301150653002801163100002201191700001701213700001701230700002701247700002101274700001801295700001901313856004801332       2008                        eng d  a1750-279900aSPIDER image processing for single-particle reconstruction of biological macromolecules from electron micrographs.0 aSPIDER image processing for singleparticle reconstruction of bio  c10/2008  a1941-740 v33 a<p><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">This protocol describes the reconstruction of biological molecules from the electron micrographs of single particles. Computation here is performed using the image-processing software SPIDER and can be managed using a graphical user interface, termed the SPIDER Reconstruction Engine. Two approaches are described to obtain an initial reconstruction: random-conical tilt and common lines. Once an existing model is available, reference-based alignment can be used, a procedure that can be iterated. Also described is supervised classification, a method to look for homogeneous subsets when multiple known conformations of the molecule may coexist.</span></p>10aImage Processing, Computer-Assisted10aMicroscopy, Electron10aModels, Molecular10aMolecular Structure10aSoftware10aUser-Computer Interface1 aShaikh, Tanvir, R1 aGao, Haixiao1 aBaxter, Bill1 aAsturias, Francisco, J1 aBoisset, Nicolas1 aLeith, ArDean1 aFrank, Joachim  uhttp://www.ncbi.nlm.nih.gov/pubmed/1918007803153nas a2200481   4500008004100000022001400041245008200055210006900137260001200206300001000218490000700228520180600235653001002041653002802051653002002079653003602099653002402135653002702159653002402186653001102210653001102221653001602232653000902248653001602257653001902273653001702292653004102309653001302350653002502363653001702388653002802405653001202433100002002445700001802465700001302483700002502496700002402521700001802545700001802563700002102581700002102602856004802623       2008                        eng d  a1525-506900aVoluntary brain regulation and communication with electrocorticogram signals.0 aVoluntary brain regulation and communication with electrocortico  c08/2008  a300-60 v133 a<p><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">Brain-computer interfaces</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;(BCIs) can be used for communication in writing without muscular activity or for learning to control seizures by voluntary regulation of&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">brain</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;signals such as the electroencephalogram (EEG). Three of five patients with epilepsy were able to spell their names with electrocorticogram (ECoG) signals derived from motor-related areas within only one or two training sessions. Imagery of finger or tongue movements was classified with support-vector classification of autoregressive coefficients derived from the ECoG signals. After training of the classifier, binary classification responses were used to select letters from a&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">computer</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">-generated menu. Offline analysis showed increased theta activity in the unsuccessful patients, whereas the successful patients exhibited dominant sensorimotor rhythms that they could control. The high spatial resolution and increased signal-to-noise ratio in ECoG signals, combined with short training periods, may offer an alternative for communication in complete paralysis, locked-in syndrome, and motor restoration.</span></p>10aAdult10aBiofeedback, Psychology10aCerebral Cortex10aCommunication Aids for Disabled10aDominance, Cerebral10aElectroencephalography10aEpilepsies, Partial10aFemale10aHumans10aImagination10aMale10aMiddle Aged10aMotor Activity10aMotor Cortex10aSignal Processing, Computer-Assisted10aSoftware10aSomatosensory Cortex10aTheta Rhythm10aUser-Computer Interface10aWriting1 aHinterberger, T1 aWidman, Guido1 aLal, T N1 aHill, Jeremy, Jeremy1 aTangermann, Michael1 aRosenstiel, W1 aSchölkopf, B1 aElger, Christian1 aBirbaumer, Niels  uhttp://www.ncbi.nlm.nih.gov/pubmed/1849554101913nas a2200349   4500008004100000022001400041245007900055210006900134260001200203300001100215520081300226653001001039653003601049653002101085653001101106653003101117653002001148653002201168653001301190653002801203100001601231700001801247700002101265700001901286700002101305700002201326700002101348700002001369700002701389700002201416856012501438       2007                        eng d  a1557-170X00aNon-invasive brain-computer interface system to operate assistive devices.0 aNoninvasive braincomputer interface system to operate assistive   c04/2007  a2532-53 aIn this pilot study, a system that allows disabled persons to improve or recover their mobility and communication within the surrounding environment was implemented and validated. The system is based on a software controller that offers to the user a communication interface that is matched with the individual's residual motor abilities. Fourteen patients with severe motor disabilities due to progressive neurodegenerative disorders were trained to use the system prototype under a rehabilitation program. All users utilized regular assistive control options (e.g., microswitches or head trackers) while four patients learned to operate the system by means of a non-invasive EEG-based Brain-Computer Interface, based on the subjects' voluntary modulations of EEG sensorimotor rhythms recorded on the scalp.10aBrain10aCommunication Aids for Disabled10aComputer Systems10aHumans10aNeurodegenerative Diseases10aQuality of Life10aSelf-Help Devices10aSoftware10aUser-Computer Interface1 aCincotti, F1 aAloise, Fabio1 aBufalari, Simona1 aSchalk, Gerwin1 aOriolo, Giuseppe1 aCherubini, Andrea1 aDavide, Fabrizio1 aBabiloni, Fabio1 aMarciani, Maria Grazia1 aMattia, Donatella  uhttps://www.neurotechcenter.org/publications/2007/non-invasive-brain-computer-interface-system-operate-assistive-devices01572nas a2200217   4500008004100000022001400041245004500055210004300100260001200143300001000155490000800165520098000173653002601153653004001179653001301219653002001232100001701252700001801269700001901287856004801306       2007                        eng d  a1047-847700aSPIRE: the SPIDER reconstruction engine.0 aSPIRE the SPIDER reconstruction engine  c01/2007  a56-630 v1573 a<p><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">SPIRE is a Python program written to modernize the user interaction with SPIDER, the image processing system for electron microscopical reconstruction projects. SPIRE provides a graphical user interface (GUI) to SPIDER for executing batch files of SPIDER commands. It also lets users quickly view the status of a project by showing the last batch files that were run, as well as the data files that were generated. SPIRE handles the flexibility of the SPIDER programming environment through configuration files: XML-tagged documents that describe the batch files, directory trees, and presentation of the GUI for a given type of reconstruction project. It also provides the capability to connect to a laboratory database, for downloading parameters required by batch files at the start of a project, and uploading reconstruction results at the end of a project.</span></p>10aComputational Biology10aImage Processing, Computer-Assisted10aSoftware10aSoftware Design1 aBaxter, Bill1 aLeith, ArDean1 aFrank, Joachim  uhttp://www.ncbi.nlm.nih.gov/pubmed/1705574301675nas a2200397   4500008004100000022001400041245007000055210006600125260001200191300001100203490000700214520056900221653001500790653001800805653001000823653003600833653001400869653002700883653002100910653001100931653002100942653002400963653002700987653001301014653002801027100001601055700001501071700001601086700001301102700002301115700002201138700002301160700002701183700001901210856004801229       2006                        eng d  a1534-432000aBCI meeting 2005 - Workshop on Technology: Hardware and Software.0 aBCI meeting 2005 Workshop on Technology Hardware and Software  c06/2006  a128-310 v143 a<p><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">This paper describes the outcome of discussions held during the Third International BCI Meeting at a workshop to review and evaluate the current state of BCI-related hardware and software. Technical requirements and current technologies, standardization procedures and future trends are covered. The main conclusion was recognition of the need to focus technical requirements on the users' needs and the need for consistent standards in BCI research.</span></p>10aAlgorithms10aBiotechnology10aBrain10aCommunication Aids for Disabled10aComputers10aElectroencephalography10aEquipment Design10aHumans10aInternationality10aMan-Machine Systems10aNeuromuscular Diseases10aSoftware10aUser-Computer Interface1 aCincotti, F1 aBianchi, L1 aBirch, Gary1 aGuger, C1 aMellinger, Jürgen1 aScherer, Reinhold1 aSchmidt, Robert, N1 aYáñez Suárez, Oscar1 aSchalk, Gerwin  uhttp://www.ncbi.nlm.nih.gov/pubmed/1679227602034nas a2200361   4500008004100000022001400041245010100055210006900156260001200225300001100237490000800248520093900256653001501195653002001210653002801230653005301258653004001311653003101351653001301382653001801395653001401413653002601427653001301453653002401466100001701490700001701507700002101524700001801545700001901563700001901582700002301601856004801624       2005                        eng d  a1047-847700aParticle picking by segmentation: a comparative study with SPIDER-based manual particle picking.0 aParticle picking by segmentation a comparative study with SPIDER  c12/2005  a211-200 v1523 a<p><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">Boxing hundreds of thousands of particles in low-dose electron micrographs is one of the major bottle-necks in advancing toward achieving atomic resolution reconstructions of biological macromolecules. We have shown that a combination of pre-processing operations and segmentation can be used as an effective, automatic tool for identifying and boxing single-particle images. This paper provides a brief description of how this method has been applied to a large data set of micrographs of ice-embedded ribosomes, including a comparative analysis of the efficiency of the method. Some results on processing micrographs of tripeptidyl peptidase II particles are also shown. In both cases, we have achieved our goal of selecting at least 80% of the particles that an expert would select with less than 10% false positives.</span></p>10aAlgorithms10aAminopeptidases10aCryoelectron Microscopy10aDipeptidyl-Peptidases and Tripeptidyl-Peptidases10aImage Processing, Computer-Assisted10aImaging, Three-Dimensional10aInternet10aParticle Size10aRibosomes10aSerine Endopeptidases10aSoftware10aSoftware Validation1 aAdiga, Umesh1 aBaxter, Bill1 aHall, Richard, J1 aRockel, Beate1 aRath, Bimal, K1 aFrank, Joachim1 aGlaeser, Robert, M  uhttp://www.ncbi.nlm.nih.gov/pubmed/1633022903311nas a2200229   4500008004100000022001400041245009200055210006900147260001200216300001400228490000800242520262900250653002202879653001402901653002702915653002102942653001302963653001602976100002102992700002103013856004703034       1994                        eng d  a0021-996700aTriceps surae motoneuron morphology in the rat: a quantitative light microscopic study.0 aTriceps surae motoneuron morphology in the rat a quantitative li  c05/1994  a143–1570 v3433 aThe rat is now the model of choice for many studies of motor function. However, little quantitative information on the structure of rat motoneurons is available. In conjunction with efforts to define the physiologic and anatomic substrates of operantly conditioned plasticity in the spinal cord, 13 physiologically identified triceps surae motoneurons in the rat lumbar spinal cord were labeled intracellularly with horseradish peroxidase and completely reconstructed and measured with a computer-based neuron-tracing system. Somata were all located in the ventral horn of lumbar segments 4-5, had an average diameter of 35 microns, and had 6-12 dendrites. Dendrites ramified throughout the ventral horn and also penetrated the white matter. Their spread was greater in the rostrocaudal and dorsoventral directions (1.53 +/- 0.24 mm and 1.35 +/- 0.23 mm, respectively) than in the mediolateral direction (0.85 +/- 0.14 mm). Regardless of soma location, dendritic fields usually extended throughout the ipsilateral coronal cross-section of the ventral horn. As a result, the ventral or lateral extent of the field was correlated strongly with the soma's distance from the ventral or lateral border, respectively, of the ventral horn. Furthermore, although soma locations in the coronal plane varied widely, the centers of the dendritic fields tended to cluster near the center of the ventral horn. Dendrites constituted 96.2-98.4% (mean +/- SD = 97.3 +/- 0.7%) of the total neuronal surface area. Each of the 104 dendrites studied had an average of 13 branch points and 27 segments. First-order segment diameters ranged from 1.4 to 11.7 microns (mean +/- SD = 5.3 +/- 2.1 microns). Total dendritic length, surface area, volume, number of dendritic segments, and maximum segment order were correlated strongly with diameter of the first-order segment. Proceeding distally between branch points, the mean decrease in dendritic diameter (i.e., tapering) +/- the standard deviation was 22 +/- 8% of the proximal diameter. The average ratio +/- the standard deviation of the sum of the average diameters of each daughter segment raised to the 1.5 power to the average diameter of the parent segment raised to the 1.5 power (i.e., Rall's ratio; Rall, 1959) was 0.87 +/- 0.08. In comparison with cat alpha-motoneurons, rat motoneurons had smaller soma diameters, fewer dendrites, smaller total surface areas, and shorter total dendritic lengths. However, the number of terminations per dendrite was similar in the two species, so that rat motoneurons had more terminations per unit dendritic length.(ABSTRACT TRUNCATED AT 400 WORDS)10acomputer assisted10adendrites10ahorseradish peroxidase10aimage processing10aSoftware10aSpinal Cord1 aChen, Xiang Yang1 aWolpaw, Jonathan  uhttp://www.ncbi.nlm.nih.gov/pubmed/8027432