Editorial Neural Computation was founded with the goal of providing a home for the best research in computational approaches to understanding brain function. With this issue Neural Computation is now all electronic (color illustrations are free) and also has a broader scope. The goal of the BRAIN Initiative, announced by President Obama on April 2, 2013, is to accelerate progress in understanding basic principles of brain function by developing innovative neurotechnologies. The BRAIN 2025 report on the BRAIN Initiative highlighted Theory, Modeling, Computation and Statistics (TMCS) as essential to this goal (http://www.braininitiative.nih.gov/2025/index.htm). The neurotechniques developed by the BRAIN Initiative will scale up the acquisition of data by three orders of magnitude in the next decade. Every area of neuroscience, from molecular to systems, can benefit from advanced computational techniques to analyze, model, and interpret these data, serving as the foundation for conceptual advances in brain theories. Neural Computation is uniquely positioned at the crossroads between Neuroscience and TMCS and welcomes the submission of original papers from all areas of TMCS, including: * Advanced experimental design * Analysis of chemical sensor data * Connectomic reconstructions * Analysis of multielectrode and optical recordings * Genetic data for cell identity * Analysis of behavioral data * Multiscale models * Analysis of molecular mechanisms * Neuroinformatics * Analysis of brain imaging data * Neuromorphic engineering * Principles of neural coding, computation, circuit dynamics, and plasticity * Theories of brain function An expanded editorial board will guide Neural Computation in this broader arena: http://www.mitpressjournals.org/page/editorial/neco As the US BRAIN Initiative and the European Human Brain Project continue to expand, and as other countries launch new brain programs, Neural Computation will be central in integrating these international efforts. Terry Sejnowski ----- Neural Computation - Volume 27, Number 1 - January 1, 2015 Available online for download now: http://www.mitpressjournals.org/toc/neco/27/1 ----- Article Spike Train SIMilarity Space (SSIMS): A Framework for Single Neuron and Ensemble Data Analysis Carlos E. Vargas-Irwin, David M. Brandman, Jonas B. Zimmermann, John P. Donoghue, Michael J. Black Note Optimizing the Representation of Orientation Preference Maps in Visual Cortex Nicholas J. Hughes, Geoffrey J. Goodhill Letters Topological Sparse Learning of Dynamic Form Patterns T. Guthier, V. Willert, J. Eggert Dynamics of Gamma Bursts in Local Field Potentials Priscilla E. Greenwood, Mark D. McDonnell, Lawrence M. Ward Spatiotemporal Conditional Inference and Hypothesis Tests for Neural Ensemble Spiking Precision Matthew T. Harrison, Asohan Amarasingham, Wilson Truccolo Toward a Multisubject Analysis of Neural Connectivity C. J. Oates, L. Costa, T. E. Nichols Using Multilayer Perceptron Computation to Discover Ideal Insect Olfactory Receptor Combinations in the Mosquito and Fruit Fly for an Efficient Electronic Nose Luqman R. Bachtiar, Charles P. Unsworth, Richard D. Newcomb Graph Degree Sequence Solely Determines the Expected Hopfield Network Pattern Stability Daniel Berend, Shlomi Dolev, Ariel Hanemann Efficient Training of Convolutional Deep Belief Networks in the Frequency Domain for Application to High-Resolution 2D and 3D Images Tom Brosch, Roger Tam Conditional Density Estimation with Dimensionality Reduction via Squared-Loss Conditional Entropy Minimization Voot Tangkaratt, Ning Xie, Masashi Sugiyama ------------ ON-LINE -- http://www.mitpressjournals.org/neuralcomp SUBSCRIPTIONS - 2015 - VOLUME 27 - 12 ISSUES Student/Retired $75 Individual $134 Institution $1,075 MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs@mit.edu ------------