@article {3081, title = {Brain-computer interfaces.}, journal = {Handbook of clinical neurology}, volume = {110}, year = {2013}, pages = {67{\textendash}74}, abstract = {Brain-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.}, keywords = {Software}, issn = {0072-9752}, doi = {10.1016/B978-0-444-52901-5.00006-X}, url = {http://www.ncbi.nlm.nih.gov/pubmed/23312631}, author = {Jonathan Wolpaw} } @article {2203, title = {Current Trends in Hardware and Software for Brain-Computer Interfaces (BCIs).}, journal = {J Neural Eng}, volume = {8}, year = {2011}, month = {04/2011}, pages = {025001}, abstract = {

A\ brain-computer interface\ (BCI) provides a non-muscular communication channel to people with and without disabilities.\ BCI\ devices consist of hardware and software.\ BCI\ hardware records signals from the\ brain, either invasively or non-invasively, using a series of device components.\ BCI\ software then translates these signals into device output commands and provides feedback. One may categorize different types of\ BCI\ applications into the following four categories: basic\ research, clinical/translational\ research, consumer products, and emerging applications. These four categories use\ BCI\ hardware and software, but have different sets of requirements. For example, while basic\ research\ 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\ BCI\ applications. The results indicate that\ BCI\ technology is in transition from isolated demonstrations to systematic\ research\ and commercial\ development. This process requires several multidisciplinary efforts, including the\ development\ of better integrated and more robust\ BCI\ hardware and software, the definition of standardized\ interfaces, and the\ developmentof certification, dissemination and reimbursement procedures.

}, keywords = {Biofeedback, Psychology, Brain, Brain Mapping, Electroencephalography, Equipment Design, Equipment Failure Analysis, Humans, Man-Machine Systems, Software, User-Computer Interface}, issn = {1741-2552}, doi = {10.1088/1741-2560/8/2/025001}, url = {http://www.ncbi.nlm.nih.gov/pubmed/21436536}, author = {Peter Brunner and Bianchi, L and Guger, C and Cincotti, F and Gerwin Schalk} } @article {2185, title = {Non-invasive brain-computer interface system: towards its application as assistive technology.}, journal = {Brain Res Bull}, volume = {75}, year = {2008}, month = {04/2008}, pages = {796-803}, abstract = {

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{\textquoteright}s residual motor abilities.\ Brain-computer interfaces\ (BCIs) are systems that can translate\ brain\ 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{\textquoteright}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{\textquoteright} 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-clinical\ demonstrations to a\ clinical\ useful BCI.

}, keywords = {Activities of Daily Living, Adolescent, Adult, Brain, Child, Electroencephalography, Evoked Potentials, Motor, Female, Humans, Learning, Male, Middle Aged, Motor Skills, Muscular Dystrophy, Duchenne, Pilot Projects, Prostheses and Implants, Robotics, Self-Help Devices, Software, Spinal Muscular Atrophies of Childhood, User-Computer Interface, Volition}, issn = {0361-9230}, doi = {10.1016/j.brainresbull.2008.01.007}, url = {http://www.ncbi.nlm.nih.gov/pubmed/18394526}, author = {Cincotti, F and Mattia, Donatella and Aloise, Fabio and Bufalari, Simona and Gerwin Schalk and Oriolo, Giuseppe and Cherubini, Andrea and Marciani, Maria Grazia and Babiloni, Fabio} } @article {2112, title = {SPIDER image processing for single-particle reconstruction of biological macromolecules from electron micrographs.}, journal = {Nat Protoc}, volume = {3}, year = {2008}, month = {10/2008}, pages = {1941-74}, abstract = {

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.

}, keywords = {Image Processing, Computer-Assisted, Microscopy, Electron, Models, Molecular, Molecular Structure, Software, User-Computer Interface}, issn = {1750-2799}, doi = {10.1038/nprot.2008.156}, url = {http://www.ncbi.nlm.nih.gov/pubmed/19180078}, author = {Shaikh, Tanvir R and Gao, Haixiao and Baxter, Bill and Asturias, Francisco J and Boisset, Nicolas and Leith, ArDean and Frank, Joachim} } @article {2137, title = {Voluntary brain regulation and communication with electrocorticogram signals.}, journal = {Epilepsy Behav}, volume = {13}, year = {2008}, month = {08/2008}, pages = {300-6}, abstract = {

Brain-computer interfaces\ (BCIs) can be used for communication in writing without muscular activity or for learning to control seizures by voluntary regulation of\ brain\ 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\ computer-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.

}, keywords = {Adult, Biofeedback, Psychology, Cerebral Cortex, Communication Aids for Disabled, Dominance, Cerebral, Electroencephalography, Epilepsies, Partial, Female, Humans, Imagination, Male, Middle Aged, Motor Activity, Motor Cortex, Signal Processing, Computer-Assisted, Software, Somatosensory Cortex, Theta Rhythm, User-Computer Interface, Writing}, issn = {1525-5069}, doi = {10.1016/j.yebeh.2008.03.014}, url = {http://www.ncbi.nlm.nih.gov/pubmed/18495541}, author = {Hinterberger, T. and Widman, Guido and Lal, T.N and Jeremy Jeremy Hill and Tangermann, Michael and Rosenstiel, W. and Sch{\"o}lkopf, B and Elger, Christian and Niels Birbaumer} } @proceedings {2245, title = {Non-invasive brain-computer interface system to operate assistive devices.}, year = {2007}, month = {04/2007}, pages = {2532-5}, abstract = {In 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{\textquoteright}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{\textquoteright} voluntary modulations of EEG sensorimotor rhythms recorded on the scalp.}, keywords = {Brain, Communication Aids for Disabled, Computer Systems, Humans, Neurodegenerative Diseases, Quality of Life, Self-Help Devices, Software, User-Computer Interface}, issn = {1557-170X}, doi = {10.1109/IEMBS.2007.4352844}, author = {Cincotti, F and Aloise, Fabio and Bufalari, Simona and Gerwin Schalk and Oriolo, Giuseppe and Cherubini, Andrea and Davide, Fabrizio and Babiloni, Fabio and Marciani, Maria Grazia and Mattia, Donatella} } @article {2109, title = {SPIRE: the SPIDER reconstruction engine.}, journal = {J Struct Biol}, volume = {157}, year = {2007}, month = {01/2007}, pages = {56-63}, abstract = {

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.

}, keywords = {Computational Biology, Image Processing, Computer-Assisted, Software, Software Design}, issn = {1047-8477}, doi = {10.1016/j.jsb.2006.07.019}, url = {http://www.ncbi.nlm.nih.gov/pubmed/17055743}, author = {Baxter, Bill and Leith, ArDean and Frank, Joachim} } @article {2176, title = {BCI meeting 2005 - Workshop on Technology: Hardware and Software.}, journal = {IEEE Trans Neural Syst Rehabil Eng}, volume = {14}, year = {2006}, month = {06/2006}, pages = {128-31}, abstract = {

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{\textquoteright} needs and the need for consistent standards in BCI research.

}, keywords = {Algorithms, Biotechnology, Brain, Communication Aids for Disabled, Computers, Electroencephalography, Equipment Design, Humans, Internationality, Man-Machine Systems, Neuromuscular Diseases, Software, User-Computer Interface}, issn = {1534-4320}, doi = {10.1109/TNSRE.2006.875584}, url = {http://www.ncbi.nlm.nih.gov/pubmed/16792276}, author = {Cincotti, F and Bianchi, L and Birch, Gary and Guger, C and Mellinger, J{\"u}rgen and Scherer, Reinhold and Schmidt, Robert N and Y{\'a}{\~n}ez Su{\'a}rez, Oscar and Gerwin Schalk} } @article {2115, title = {Particle picking by segmentation: a comparative study with SPIDER-based manual particle picking.}, journal = {J Struct Biol}, volume = {152}, year = {2005}, month = {12/2005}, pages = {211-20}, abstract = {

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.

}, keywords = {Algorithms, Aminopeptidases, Cryoelectron Microscopy, Dipeptidyl-Peptidases and Tripeptidyl-Peptidases, Image Processing, Computer-Assisted, Imaging, Three-Dimensional, Internet, Particle Size, Ribosomes, Serine Endopeptidases, Software, Software Validation}, issn = {1047-8477}, doi = {10.1016/j.jsb.2005.09.007}, url = {http://www.ncbi.nlm.nih.gov/pubmed/16330229}, author = {Adiga, Umesh and Baxter, Bill and Hall, Richard J and Rockel, Beate and Rath, Bimal K and Frank, Joachim and Glaeser, Robert M} } @article {3263, title = {Triceps surae motoneuron morphology in the rat: a quantitative light microscopic study.}, journal = {The Journal of comparative neurology}, volume = {343}, year = {1994}, month = {05/1994}, pages = {143{\textendash}157}, abstract = {The 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{\textquoteright}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{\textquoteright}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)}, keywords = {computer assisted, dendrites, horseradish peroxidase, image processing, Software, Spinal Cord}, issn = {0021-9967}, doi = {10.1002/cne.903430111}, url = {http://www.ncbi.nlm.nih.gov/pubmed/8027432}, author = {Xiang Yang Chen and Jonathan Wolpaw} }