NEURAL COMPUTATION - April, 2014
Neural Computation - Contents -- Volume 26, Number 4 - April 1, 2014
Available online for download now: http://www.mitpressjournals.org/toc/neco/26/4
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Article
Parametric Inference in the Large Data Limit Using Maximally Informative Models Justin Block Kinney, Gurinder Singh Atwal
Letters
Input Statistics and Hebbian Crosstalk Effects Anca R. Radulescu
Learning Nonlinear Regularities in Natural Images by Modeling the Outer Product of Image Intensities Peng Qi, Xiaolin Hu
Dissociable Forms of Repetition Priming: A Computational Model Kirill Makukhin, Scott Bolland
Refined Rademacher Chaos Complexity Bounds With Applications to the Multi-Kernel Learning Problem Yunwen Lei, Lixin Ding
Large Margin Low Rank Tensor Analysis Guoqiang Zhong, Mohamed Cheriet
Large-scale Linear RankSVM Ching-Pei Lee, Chih-Jen Lin
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Neural Computation - Contents -- Volume 26, Number 5 - May 1, 2014
Available online for download now: http://www.mitpressjournals.org/toc/neco/26/5
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Article
A Transition to Sharp Timing in Stochastic Leaky Integrate-and-Fire Neurons Driven by Frozen Noisy Input Thibaud Taillefumier, Marcelo Magnasco
Letters
Sample Skewness as a Statistical Measurement of Neuronal Tuning Sharpness Jason Michael Samonds, Brian Richard Potetz, and Tai Sing Lee
Prewhitening High Dimensional fMRI Data Sets Without Eigendecompoistion Abd-Krim Seghouane, Yousef Saad
Signal-tuned Gabor Functions as Models for Stimulus-dependent Cortical Receptive Fields Jose R. A. Torreao, Silvia M.C. Victer, and Marcos S. Amaral
Energy Complexity of Recurrent Neural Networks Jiri Sima
On Some Classes of Sequential Spiking Neural P Systems Xingyi Zhang, Xiangxiang Zeng, Bin Luo, and Linqiang Pan
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Neural Computation - Contents -- Volume 26, Number 6 - June 1, 2014
Available online for download now: http://www.mitpressjournals.org/toc/neco/26/6
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Article
A Causal Perspective on the Analysis of Signal and Noise Correlations and Their Role in Population Coding Daniel Chicharro
Letters
Towards Unified Hybrid Simulation Techniques for Spiking Neural Networks Michiel D'Haene, Michiel Hermans, and Benjamin Schrauwen
Neural Decoding With Kernel-based Metric Learning Austin J. Brockmeier, John S. Choi, Evan G. Kriminger, Joseph T. Francis, and Jose C. Principe
Adaptive Multiclass Classification for Brain Computer Interfaces Alberto Llera, Vicenc Gomez, and Hilbert J. Kappen
On Non-negative Matrix Factorization Algorithms for Signal-dependent Noise With Application to Electromyography Data Karthik Devarajan, Vincent C.K. Cheung
Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation Song Liu, John A. Quinn, Michael U. Gutmann, Taiji Suzuki, and Masashi Sugiyama
Short Term Memory Capacity in Networks via the Restricted Isometry Property Adam Charles, Han Lun Yap, and Chris Rozell
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Neural Computation - Contents -- Volume 26, Number 7 - July 1, 2014
Available online for download now: http://www.mitpressjournals.org/toc/neco/26/7
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Article
Motor Cortex Microcircuit Simulation Based on Brain Activity Mapping George L Chadderdon, Ashutosh Mohan, Benjamin A Suter, Samuel A Neymotin, Cliff C Kerr, Joseph T Francis, Gordon MG Shepherd, and William W Lytton
Letters
Discovering Functional Neuronal Connectivity From Serial Patterns in Spike Train Data Casey Diekman, Kohinoor Dasgupta, Vijay Nair, and K.P. Unnikrishnan
Risk-sensitive Reinforcement Learning Yun Shen, Michael J. Tobia, Tobias Sommer, and Klaus Obermayer
On Criticality in High-dimensional Data Saeed Saremi, Terrence J Sejnowski
Spiking Neural P Systems With Thresholds Xiangxiang Zeng, Xingyi Zhang, Tao Song, and Linqiang Pan
Balanced Crossmodal Excitation and Inhibition Essential for Maximizing Multisensory Gain Osamu Hoshino
Universal Approximation Depth and Errors of Narrow Belief Networks With Discrete Units Guido Francisco Montufar
Multiple Tests Based on a Gaussian Approximation of the Unitary Events Method With Delayed Coincidence Count Christine Tuleau-Malot, Amel Rouis, Franck Grammont, and Patricia Reynaud-Bouret
Intrinsic Graph Structure Estimation Using Graph Laplacian Atsushi Noda, Hideitsu Hino, Masami Tatsuno, Shotaro Akaho, and Noboru Murata
Causal Discovery via Reproducing Kernel Hilbert Space Embeddings Zhitang Chen, Kun Zhang, Laiwan Chan, and Bernhard Scholkopf
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Neural Computation - Contents -- Volume 26, Number 8 - August 1, 2014
Available online for download now: http://www.mitpressjournals.org/toc/neco/26/8
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Articles
Bayesian Active Learning of Neural Firing Rate Maps With Transformed Gaussian Process Priors Mijung Park, J. Patrick Weller, Gregory D. Horwitz, and Jonathan Pillow
How to Compress Sequential Memory Patterns Into Periodic Oscillations: General Reduction Rules Kechen Zhang
Letters
The Competing Benefits of Noise and Heterogeneity in Neural Coding Eric G Hunsberger, Matthew Scott, and Chris Eliasmith
Anatomical Constraints on Lateral Competition in Columnar Cortical Architectures Dylan Richard Muir, Matthew Cook
ROC-Based Estimates of Neural-Behavioral Covariations Using Matched Filters Kamal Farah, Jackson Smith, and Erik Cook
Tonically Balancing Intracortical Excitation and Inhibition by GABAergic Gliotransmission Meihong Zheng, Takami Matsuo, Ai Miyamoto, and Osamu Hoshino
Information-theoretic Semi-supervised Metric Learning via Entropy Regularization Gang Niu, Bo Dai, Makoto Yamada, and Masashi Sugiyama
Incremental Learning by Message Passing in Hierarchical Temporal Memory Erik Mikael Rehn, Davide Maltoni
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Neural Computation - Contents -- Volume 26, Number 9 - September 1, 2014
Available online for download now: http://www.mitpressjournals.org/toc/neco/26/9
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Article
Continuous Closed-loop Decoder Adaptation With a Recursive Maximum Likelihood Algorithm Allows for Rapid Performance Acquisition in Brain-machine Interfaces Siddharth Dangi, Suraj Gowda, Helene Moorman, Amy Orsborn, Kelvin So, Maryam Shanechi, and Jose Carmena
Letters
Neuronal Spike Train Entropy Estimation by History Clustering Nicholas Watters, and George Reeke
Memory Nearly on a Spring: A Mean First Passage Time Approach to Memory Lifetimes Terry Elliott
Sparseness, Anti-Sparseness and Anything in Between: The Operating Point of a Neuron Determines Its Computational Repertoire Terry Elliott
Sequential Activity in Asymmetrically Coupled Winner-Take-All Circuits Hesham Mostafa, Giacomo Indiveri
Synchronization of Stochastic Competitive Neural Networks With Different Time Scales and Reaction-diffusion Terms Yanchao Shi, Peiyong Zhu
A Semiparametric Bayesian Model for Detecting Synchrony Among Multiple Neurons Babak Shahbaba, Bo Zhou, Shiwei Lan, Hernando Ombao, David Moorman, and Sam Behseta
A Bayesian Model of Polychronicity Mira Guise, Alistair Knott, and Lubica Benuskova
A Non-parametric Clustering Algorithm With a Quantile-based Likelihood Estimator Hideitsu Hino, Noboru Murata
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Neural Computation - Contents -- Volume 26, Number 10 - October 1, 2014
Available online for download now: http://www.mitpressjournals.org/toc/neco/26/10
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Articles
Efficient Sensory Encoding and Bayesian Inference With Heterogeneous Neural Populations Deep Ganguli, Eero P Simoncelli
Dimensionality of Object Representations in Monkey Inferotemporal Cortex Sidney Lehky, Roozbeh Kiani, Hossein Esteky, and Keiji Tanaka
Letters
Hierarchical Control Using Networks Trained With Higher-Level Forward Models Gregory Duncan Wayne, Larry Abbott
Spine Head Calcium as a Measure of Summed Postsynaptic Activity for Driving Synaptic Plasticity Bruce Graham, Ausra Saudargiene, and Stuart Cobb
Design of Charge-Balanced Time-Optimal Stimuli for Spiking Neuron Oscillators Isuru Dasanayake, Jr-Shin Li
Influence of External Inputs and Asymmetry of Connections on Information-Geometric Measures Involving Up to Ten Neuronal Interactions Yimin Nie, Jean-Marc Fellous, and Masami Tatsuno
Fragility in Dynamic Networks: Application to Neural Networks in the Epileptic Cortex Duluxan Sritharan, Sridevi Vedula Sarma
On Anti-periodic Solutions for Cohen-Grossberg Shunting Inhibitory Neural Networks With Time-varying Delays and Impulses Changjin Xu., Qiming Zhang
Learning Rates of Lq Coefficient Regularization Learning With Gaussian Kernel Shaobo Lin, Jinshan Zeng, Jian Fang, and Zongben Xu
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Neural Computation - Contents -- Volume 26, Number 11 - November 1, 2014
Available online for download now: http://www.mitpressjournals.org/toc/neco/26/11
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Article
High-dimensional Cluster Analysis With the Masked EM Algorithm Shabnam N. Kadir, Dan F.M. Goodman, and Kenneth D. Harris
Letters
Changes of Firing Rate Induced by Changes of Phase Response Curve in Bifurcation Transitions Yasuomi D. Sato., Kazuyuki Aihara
Approximate Emergent Synchrony in Spatially Coupled Spiking Neurons With Discrete Interaction Hans Super, August Romeo
Facilitation of Neuronal Responses by Intrinsic Default Mode Network Activity Hiroakira Matsui, Meihong Zheng, and Osamu Hoshino
A Hierarchical Adaptive Approach to Optimal Experimental Design Woojae Kim, Mark A. Pitt, Zhong-Lin Lu, Mark Steyvers, and Jay I. Myung
Noise Facilitation in Associative Memories of Exponential Capacity Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi, and Lav R. Varshney
A No-go Theorem for One-layer Feedforward Networks Chad D Giusti, Vladimir Itskov
Extended Robust Support Vector Machine Based on Financial Risk Minimization Akiko Takeda, Shuhei Fujiwara, and Takafumi Kanamori
Nonparametric Estimation of Kullback-Leibler Divergence Zhiyi Zhang, Michael Grabchak
Coenzyme Q10 Benefits Symptoms in Gulf War Veterans: Results of a Randomized Double-Blind Pilot Study Beatrice Golomb, Matthew Allison, Sabrina Koperski, Hayley J. Koslik, Sridevi Devaraj, and Janis B Ritchie
Visual Motion Priors Differ for Infants and Mothers Florian Raudies, Rick O Gilmore
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Neural Computation - Contents -- Volume 26, Number 12 - December 1, 2014
Available online for download now: http://www.mitpressjournals.org/toc/neco/26/12
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View
Population Coding and the Labeling Problem: Extrinsic Versus Intrinsic Representations Sidney Lehky, Margaret E. Sereno, and Anne B. Sereno
Letters
Information Transfer Through Stochastic Transmission of a Linear Combination of Rates Stelios Smirnakis, Ioannis Smyrnakis
Spike-Based Probabilistic Inference in Analog Graphical Models Using Interspike-Interval Coding Andreas Steimer, Rodney J. Douglas
An Investigation of the Stochastic Hodgkin-Huxley Models Under Noisy Rate Functions Marifi Guler
Dynamic Analysis of Naive Adaptive Brain-machine Interfaces Kevin Cai Kowalski, Bryan D He, and Lakshminarayan Srinivasan
A Bio-inspired, Computational Model Suggests Velocity Gradients of Optic Flow Locally Encode Ordinal Depth at Surface Borders and Globally They Encode Self-Motion Florian Raudies., Stefan Ringbauer, and Heiko Neumann
Exploitation of Pairwise Class Distances for Ordinal Classification Javier Sanchez-Monedero , Peter Tino, Pedro Antonio Gutierrez, and C. Hevas-Martinez
Spherical Mesh Adaptive Direct Search for Separating Quasi-uncorrelated Sources by Range-based Independent Component Analysis S. Easter Selvan, Pierre B. Borckmans, Amit Chattopadhyay, and Pierre-Antoine Absil
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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
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Neural Computation - Volume 27, Number 1 - January 1, 2015
Available online for download now: http://www.mitpressjournals.org/toc/neco/27/1
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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
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Neural Computation - Volume 27, Number 2 - February 1, 2015
Available online for download now: http://www.mitpressjournals.org/toc/neco/27/2
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Letters
Subdiffusive Dynamics of Bump Attractors: Mechanisms and Functional Roles Yang Qi, Pulin Gong, and Michael Breakspear
Reliability of Information-Based Integration of EEG and FMRI Data: A Simulation Study Sara Assecondi, Dirk Ostwald, and Andrew Philip Bagshaw
Active Inference, Evidence Accumulation and the Urn Task Thomas FitzGerald, Philipp Schwartenbeck, Michael Moutoussis, Raymond J. Dolan, and Karl Friston
A Neural Mass Model With Direct and Indirect Excitatory Feedback Loops: Identification of Bifurcations and Temporal Dynamics Miss Aurelie Garnier, Alexandre Vidal, Clement Huneau, and Habib Benali
Mismatched Training and Test Distributions Can Outperform Matched Ones Carlos Roberto Gonzalez, Yaser Said Abu-Mostafa
Foundations of Support Constraint Machines Giorgio Gnecco, Marco Gori, Stefano Melacci, and Marcello Sanguineti
Natural Gradient Learning Algorithms for RBF Networks Junsheng Zhao, Haikun Wei, Chi Zhang, Weiling Li, Weili Guo, and Kanjian Zhang
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Neural Computation - Volume 27, Number 3 - March 1, 2015
Available online for download now: http://www.mitpressjournals.org/toc/neco/27/3
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Article
Spontaneous Motion on Two-dimensional Continuous Attractors C. C. Alan Fung, Shun-ichi Amari
Letters
Oscillator-Interference Models of Path Integration Do Not Require Theta Oscillations Jeff Orchard
What Can Neuromorphic Event-driven Precise Timing Add to Spike-based Pattern Recognition? Himanshu Akolkar, Cedric Meyer, Xavier Clady, Olivier Marre, Chiara Bartolozzi, Stefano Panzeri, and Ryad Benosman
Delay Differential Analysis of Time Series Claudia Lainscsek, Terrence J Sejnowski
Delay Differential Analysis of Electroencephalographic Data Claudia Lainscsek, Manuel E. Hernandez, Howard Poizner, and Terrence J Sejnowski
Range-Based ICA Using a Nonsmooth Quasi-Newton Optimizer for Electroencephalographic Source Localization in Focal Epilepsy S. Easter Selvan, S.Thomas George, and R. Balakrishnan
Two-trace Model for Spike-timing-dependent Synaptic Plasticity Rodrigo Echeveste, Claudius Gros
On Firing Rate Estimation for Dependent Interspike Intervals Laura Sacerdote, Elisa Benedetto, and Federico Polito
Memristor Models for Machine Learning Juan Pablo Carbajal, Joni Dambre, Michiel Hermans, and Benjamin Schrauwen
On Resolving Simultaneous Congruences Using Belief Propagation Yongseok Yoo, Sriram Vishwanath
Structural Intervention Distance (SID) for Evaluating Causal Graphs Jonas Peters, Peter Buhlmann
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http://biorxiv.org/content/early/2015/03/11/016329
Hippocampal Spine Head Sizes are Highly Precise
Thomas M Bartol, Cailey Bromer, Justin P Kinney, Michael A Chirillo, Jennifer N Bourne, Kristen M Harris, Terrence J Sejnowski
The size of an EPSP is highly correlated with the the spine head volume for excitatory synapses on pyramidal cells. Spine heads on a dendrite originating from the same axon had the same volume, regardless of whether they were large or small. This has implications for the precision of the mechanisms underlying synaptic plasticity.
Terry
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NEURAL COMPUTATION - April 1, 2015
Neural Computation - Volume 27, Number 4 - April 1, 2015
Available online for download now: http://www.mitpressjournals.org/toc/neco/27/4
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Articles
Spontaneous Action Potentials and Neural Coding in Un-myelinated Axons Cian O'Donnell, Mark C.W. van Rossum
Accurate Connection Strength Estimation Based on Variational Bayes for Detecting Synaptic Plasticity Takuya Isomura, Yutaro Ogawa, Kiyoshi Kotani, and Yasuhiko Jimbo
Letters
Hardware-Amenable Structural Learning for Spike-based Pattern Classification Using a Simple Model of Active Dendrites Shaista Hussain, Shih-Chii Liu, and Arindam Basu
Neuronal Calcium Wave Propagation Varies With Changes in Endoplasmic Reticulum Parameters: A Computer Model Samuel A Neymotin, Robert A McDougal, Mohamed A Sherif, Christopher P Fall, Michael L. Hines, and William W Lytton
Visual Tracking Using Neuromorphic Asynchronous Event-based Cameras Zhenjiang Ni, Sio-Hoi Ieng, Christoph Posch, Stephane Regnier, and Ryad Benosman
The Benefits of Modelling Slack Variables in SVMs Fengzhen Tang, Peter Tino, Pedro Antonio Gutierrez, and Huanhuan Chen
A Study on the Optimal Double-Parameters for Steepest Descent With Momentum Naimin Zhang
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Neural Computation - Volume 27, Number 5 - May 1, 2015
Available online for download now: http://www.mitpressjournals.org/toc/neco/27/5
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Article
Self-Organization of Control Circuits for Invariant Fiber Projections Tomas Fernandes, Christoph von der Malsburg
Letters
A Computationally-efficient Method for Incorporating Spike Waveform Information Into Decoding Algorithms Valerie Ventura, Sonia Todorova
Coding Accuracy Is Not Fully Determined by the Neuronal Model Lubomir Kostal, Petr Lansky
Solving Stereo Transparency With an Extended Coarse-to-fine Disparity Energy Model Zhe Li, Ning Qian
Simultaneous Multi-Channel Signal Transfers Via Chaos in a Recurrent Neural Network Ken-ichiro Soma, Ryota Mori, Ryuichi Sato, Noriyuki Furumai, and Shigetoshi Nara
Input Anticipating Critical Reservoirs Show Power Law Forgetting of Unexpected Input Events Norbert Michael Mayer
Learning Dynamics of a Single Polar Variable Complex-Valued Neuron Tohru Nitta
On-line EM With Weight-Based Forgetting Enric Celaya, Alejandro Agostini
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Neural Computation - Volume 27, Number 6 - June 1, 2015
Available online for download now: http://www.mitpressjournals.org/toc/neco/27/6
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Articles
Homeostatic Plasticity for Single Node Delay-Coupled Reservoir Computing. Hazem Toutounji, Johannes Schumacher, and Gordon Pipa
Surrogate Population Models for Large-scale Neural Simulations. Bryan P Tripp
Letters
Regulation of Local Ambient GABA Levels via Transporter-mediated GABA Import and Export for Subliminal Learning. Osamu Hoshino
Cortical Spatio-Temporal Dimensionality Reduction for Visual Grouping. Giacomo Cocci, Davide Barbieri, Giovanna Citti, and Alessandro Sarti
Time-scale Separation in Recurrent Neural Networks. Thomas Flynn
Refined Generalization Bounds of Gradient Learning Over Reproducing Kernel Hilbert Spaces. Shaogao Lv
FastMMD: Ensemble of Circular Discrepancy for Efficient Two-Sample Test. Ji Zhao, Deyu Meng
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Neural Computation - Volume 27, Number 7 - July 1, 2015
Available online for download now: http://www.mitpressjournals.org/toc/neco/27/7
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Articles
Unifying Blind Separation and Clustering for Resting-State EEG/MEG Functional Connectivity Analysis Jun-ichiro Hirayama, Takeshi Ogawa, and Aapo Hyvarinen
Attentional Bias Through Oscillatory Coherence Between Excitatory Activity and Inhibitory Minima Sebastian Blaes, Thomas Burwick
Letters
Clusterless Decoding of Position From Multiunit Activity Using a Marked Point Process Filter Xinyi Deng, Daniel F. Liu, Kenneth Kay, Loren M. Frank, and Uri T. Eden
A Hebbian/Anti-Hebbian Neural Network for Linear Subspace Learning: A Derivation From Multidimensional Scaling of Streaming Data Cengiz Pehlevan, Tao Hu, and Dmitri B. Chklovskii
Learning Slowness in a Sparse Model of Invariant Feature Detection Thusitha N. Chandrapala, Bertram E. Shi
On the Spike Train Variability Characterized by Variance-to-mean Power Relationship Shinsuke koyama
Comments and Correction on "U-Processes and Preference Learning" (Neural Computation Vol. 26, Pp. 2896-2924, 2014) Wojciech Rejchel, Hong Li, Chuanbao Ren, and Luoqing Li
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Spectrum of power laws for curved hand movements Dongsung Huh and Terrence J. Sejnowski
http://www.pnas.org/content/early/2015/07/02/1510208112.abstract
In curved hand movements around ellipses, the speed tends to scale inversely with the curvature with a power law having an exponent of -1/3. We examined whether this well-known regularity in motor planning holds for more general shapes. Using an optimality principle, we identified a set of basis shapes, each with a single characteristic angular frequency, which subjects drew with power laws whose exponents ranged from 0 to -2/3. More general movements exhibited linear mixtures of power laws. The speed of arbitrary doodling movements with a broad spectrum of frequencies could also be predicted from the curvature with high accuracy.
Terry
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Neural Computation - Volume 27, Number 8 - August 1, 2015
Available online for download now: http://www.mitpressjournals.org/toc/neco/27/8
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Article
A Statistical Framework to Infer Delay and Direction of Information Flow From Measurements of Complex Systems Johannes Schumacher, Thomas Wunderle, Pascal Fries, Frank Jakel, and Gordon Pipa *FREE*
Letters
An Empirical Model for Reliable Spiking Activity Wanjie Wang, Shreejoy J Tripathy, Krishnan Padmanabhan, Nathaniel N. Urban, and Robert E. Kass
Inheritance of Hippocampal Place Fields Through Hebbian Learning: Effects of Theta Modulation and Phase Precession on Structure Formation Tiziano D'Albis, Jorge Jaramillo, Henning Sprekeler, and Richard Kempter
Competitive STDP Learning of Overlapping Spatial Patterns Dalius Krunglevicius
A Reward-Maximizing Spiking Neuron as a Bounded Rational Decision-Maker Felix Leibfried, Daniel A. Braun
Optimality of Upper-Arm Reaching Trajectories Based on the Expected Value of the Metabolic Energy Cost Yoshiaki Taniai, Jun Nishii
Active Learning Using Hint Information Chun-Liang Li, Chun-Sung Ferng, and Hsuan-Tien Lin
Subsampled Hessian Newton Methods for Supervised Learning Chien-Chih Wang, Chun-Heng Huang, and Chih-Jen Lin
Minimal Sign Representation of Boolean Functions: Algorithms and Exact Results for Low Dimensions Can Eren Sezener, Erhan Oztop
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Neural Computation - Volume 27, Number 9 - September 1, 2015
Available online for download now: http://www.mitpressjournals.org/toc/neco/27/9
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Article
Extracting Low-dimensional Latent Structure From Time Series in the Presence of Delays Karthik C. Lakshmanan, Patrick T Sadtler, Elizabeth C Tyler-Kabara, Aaron P Batista, and Byron M. Yu
Note
Is First-Order Vector Autoregressive Model Optimal for fMRI Data? Chee-Ming Ting, Abd-Krim Seghouane, Muhammad Usman Khalid, and Sh-Hussain Salleh
Letters
A Novel Reconstruction Framework for Time Encoded Signals with Integrate-and-fire Neurons Dorian Florescu, Daniel Coca
Online Direct Density-Ratio Estimation Applied to Inlier-based Outlier Detection Marthinus Christoffel du Plessis, Hiroaki Shiino, and Masashi Sugiyama
Relations Among Some Low Rank Subspace Recovery Models Hongyang Zhang, Zhouchen Lin, Chao Zhang, and Junbin Gao
A Fast Algorithm for Learning Overcomplete Dictionary for Sparse Representation Based on Proximal Operators Zhenni Li, Shuxue Ding, and Yujie Li
Fusion of Scores in a Detection Context Based on Alpha Integration Antonio Soriano, Luis Vergara, Bouziane Ahmed, and Addisson Salazar
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Neural Computation - Volume 27, Number 10 - October 1, 2015
Available online for download now: http://www.mitpressjournals.org/toc/neco/27/10
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Review
Indefinite Proximity Learning - a Review Frank-Michael Schleif, Peter Tino
Article
Understanding Emergent Dynamics: Using a Collective Activity Coordinate of a Neural Network to Recognize Time-varying Patterns John Hopfield
Note
A Note on Entropy Estimation Thomas Schuermann
Letters
Recurrent Neural Network Approach Based on the Integral Representation of the Drazin Inverse Predrag S. Stanimirovic, Ivan S. Zivkovic, and Yimin Wei
Visual Categorization With Random Projection Rosa Arriaga, David Rutter, Maya Cakmak, and Santosh Vempala
Accuracy and Efficiency in Fixed-point Neural ODE Solvers Michael Hopkins, Steve Furber
A Simple Label Switching Algorithm for Semi-supervised Structural SVMs P. Balamurugan , Shirish Shevade, and S. Sundararajan
Multi-View Bayesian Correlated Component Analysis Simon Kamronn, Andreas Trier Poulsen, and Lars Kai Hansen
Linear Methods for Efficient and Fast Separation of Two Sources Recorded With a Single Microphone Saurabh Bhargava, Florian Blaettler, Sepp Kollmorgen, Shih-Chii Liu, and Richard H.R. Hahnloser
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Neural Computation - Volume 27, Number 11 - November 1, 2015
Available online for download now: http://www.mitpressjournals.org/toc/neco/27/11
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Article
STICK: Spike Time Interval Computational Kernel, a Framework for General Purpose Computation Using Neurons, Precise Timing, Delays, and Synchrony Xavier Lagorce, Ryad Benosman
Letters
Visual Decisions in the Presence of Measurement and Stimulus Correlations Manisha Bhardwaj, Samuel Carroll, Wei Ji Ma, and Kresimir Josic
Hierarchical Error Representation: A Computational Model of Anterior Cingulate and Dorsolateral Prefrontal Cortex. William H. Alexander, Joshua W Brown
Bayesian Feature Selection With Strongly-regularizing Priors Maps to the Ising Model Charles K. Fisher, Pankaj Mehta
A Novel Parameter Estimation Method for Boltzmann Machine Takashi Takenouchi
Bandit-Based Task Assignment for Heterogeneous Crowdsourcing Hao Zhang, Yao Ma, and Masashi Sugiyama
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UCSD GRADUATE PROGRAM IN COMPUTATIONAL NEUROSCIENCE
http://healthsciences.ucsd.edu/education/neurograd/computational/pages/defau...
Application deadline: December 1, 2015 (Fall 2016) http://neurograd.ucsd.edu/2page.php?id=gradadm
*****
The goal of the Computational Neuroscience Specialization in the Neurosciences Graduate Program at UCSD is to train researchers who are equally at home measuring large-scale brain activity, analyzing the data with advanced computational techniques, and developing new models for brain development and function.
Candidates from a wide range of backgrounds are invited to apply, including Biology, Psychology, Computer Science, Physics and Mathematics. The three major themes in the training program are:
1. Neurobiology of Neural Systems: Anatomy, physiology and behavior of systems of neurons. Using modern neuroanatomical, behavioral, neuropharmacological and electrophysiological techniques. Lectures, wet laboratories and computer simulations, as well as research rotations. Major new imaging and recording techniques also will be taught, including two-photon laser scanning microscopy and functional magnetic resonance imaging (fMRI).
2. Algorithms and Realizations for the Analysis of Neuronal Data: New algorithms and techniques for analyzing data obtained from physiological recording, with an emphasis on recordings from large populations of neurons with imaging and multielectrode recording techniques. New methods for the study of co-ordinated activity, such as multi-taper spectral analysis and Delay Differential Analysis (DDA).
3. Neuroinformatics, Dynamics and Control of Systems of Neurons: Theoretical aspects of single cell function and emergent properties as many neurons interact among themselves and react to sensory inputs. A synthesis of approaches from mathematics and physical sciences as well as biology will be used to explore the collective properties and nonlinear dynamics of neuronal systems, as well as issues of sensory coding and motor control.
*****
Participating Faculty include:
* Henry Abarbanel (Physics): Nonlinear and oscillatory dynamics; modeling central pattern generators in the lobster stomatogastric ganglion. * Thomas Albright (Salk Institute): Motion processing in primate visual cortex; linking single neurons to perception; fMRI in awake, behaving monkeys. Director, Sloan Center for Theoretical Neurobiology * Darwin Berg (Neurobiology): Regulation synaptic components, assembly and localization, function and long-term stability. * Ed Callaway (Salk Institute): Neural circuits, visual perception, visual cortex Genetic tools for tracing neural pathways. * Gert Cauwenberghs (Bioengineering): Neuromorphic Engineering; analog VLSI chips; wireless recording and nanoscale instrumentation for neural systems; large-scale cortical modeling. * Sreekanth Chalasani (Salk): C. elegans: genes, networks and behavior Optical recording of olfactory processing. * Andrea Chiba (Cognitive Science): Spatial attention, associative learning, cholinergic neuromodulaiton of behavior, amygdala recordings * EJ Chichilnisky (Salk Institute): Retinal multielectrode recording; neural coding, visual perception. * Todd Coleman (Bioengineering): Brain-Machine Interfaces (BMI) * Garrison Cottrell (Computer Science and Engineering): Dynamical neural network models and learning algorithms * Virginia De Sa (Cognitive Science): Computational basis of perception and learning; multi-sensory integration and contextual influences * Mark Ellisman (Neurosciences, School of Medicine): High resolution electron and light microscopy; anatomical reconstructions. * Fred Gage (Salk Institute): Neurogenesis and models of the hippocampus; neuronal diversity, neural stem cells. * Timothy Gentner (Psychology): Birdsong learning. Neuroethology of vocal communication and audition * Robert Hecht-Nielsen (Electrical and Computer Engineering): Neural computation and the functional organization of the cerebral cortex. * Steve Hillyard (Neurosciences): EEG, perception, attention, memory, Event related potentilas, SSVEP * Harvey Karten (Neurosciences, School of Medicine): Anatomical, physiological and computational studies of the retina and optic tectum of birds and squirrels * David Kleinfeld (Physics): Active sensation in rats; properties of neuronal assemblies; optical imaging of large-scale activity. * William Kristan (Neurobiology): Computational Neuroethology; functional and developmental studies of the leech nervous system, including studies of the bending reflex and locomotion. * Scott Makeig (Institute for Neural Computation): Analysis of cognitive event-related brain dynamics and fMRI using time-frequency and Independent Component Analysis * Javier Movellan (Institute for Neural Computation): Sensory fusion and learning algorithms for continuous stochastic systems * Saket Navlakha (Salk Institute): How collections of molecules, neurons, and organisms process information and solve distributed computing problems. * Howard Poizner (Institute for Neural Computation): Motor systems, basal ganglia, reinforcment learning, Parkinson's disease. * Mikhael Rabinovich (Institute for Nonlinear Science): Dynamical systems analysis of the stomatogastric ganglion of the lobster and the antenna lobe of insects * Pamela Reinagel (Biology): Sensory and neural coding; natural scene statistics; recordings from the visual system of cats and rodents. * John Reynolds (Salk): Visual attention, cortex, psychophysics, neurophysiology, neural modeling * Massimo Scanziani (Biology): Neural circuits in the somotosensory cortex; physiology of synaptic transmission; inhibitory mechanisms. * Terrence Sejnowski (Salk Institute/Neurobiology): Computational models and physiological studies of synaptic, neuronal and network function. * Tanya Sharpee (Salk): Statistical physics and information theory approaches to sensory processing in natural auditory and visual environments. * Gabe Silva (Bioengineering): Cellular neural engineering * Nicholas Spitzer (Neurobiology): Regulation of ionic channels and neurotransmitters in developing neurons and neural function. * Charles Stevens (Salk Institute): Synaptic physiology; theoretical models of neuroanatomical scaling. * Jing Wang (Biology): Representation of olfactory information in the nervous system of Drosophila * Ruth Williams (Mathematics): Probabilistic analysis of stochastic systems and continuous learning algorithms * Angela Yu (Cognitive Science): Sensory processing, attentional selection, perceptual decision-making, sensorimotor integration, learning, and adaptation.
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On-line applications: http://healthsciences.ucsd.edu/education/neurograd/computational/Pages/Appli... https://apply.grad.ucsd.edu/departments/neurosciences
The deadline for completed application materials, including letters of recommendation, is December 1, 2015 for Fall 2016
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Neural Computation - Volume 27, Number 12 - December 1, 2015
Available online for download now: http://www.mitpressjournals.org/toc/neco/27/12
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Article
Periodic Forcing of Stabilized E-I Networks: Nonlinear Resonance Curves and Dynamics Romain Veltz, Terrence J. Sejnowski
Letters
Rhythmic Inhibition Allows Neural Networks to Search for Maximally Consistent States Hesham Mostafa, Lorenz K. Mueller and Giacomo Indiveri
Learning Spatio-Temporally Encoded Pattern Transformations in Structured Spiking Neural Networks Brian Gardner, Ioana Sporea, and Andre Gruening
A Sparse Reformulation of the Green's Function Formalism Allows Efficient Simulations of Morphological Neuron Models Willem A.M. Wybo, Daniele Boccalini, Benjamin Torben-Nielsen, and Marc-Oliver Gewaltig
Positive Neural Networks in Discrete Time Implement Monotone-Regular Behaviors Tom J Ameloot, Jan Van den Bussche
Symbolic Computation Using Cellular Automata Based Hyperdimensional Computing Ozgur Yilmaz
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Neural Computation - Volume 28, Number 1 - January 1, 2016
Available online for download now: http://www.mitpressjournals.org/toc/neco/28/1
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Articles
Neural Network Spectral Robustness Under Perturbations of the Underlying Graph Anca Radulescu
Sequential Tests for Large Scale Learning Anoop Korattikara, Yutian Chen, and Max Welling
Note
A Note on Support Vector Machines With Polynomial Kernels Hongzhi Tong
Letters
Analytical Calculation of Errors in Time and Value Perception Due to a Subjective Time Accumulator: A Mechanistic Model and the Generation of Weber's Law Vijay Mohan K Namboodiri, Stefan Mihalas, and Marshall G Hussain Shuler
Efficient Associative Computation With Discrete Synapses Andreas Knoblauch
Reduction of Trial-to-trial Perceptual Variability by Intracortical Tonic Inhibition Osamu Hoshino, Meihong Zheng, and Kazuo Watanabe
An Empirical Overview of the No Free Lunch Theorem and Its Effect on Real-World Machine Learning Classification David Gomez, Alfonso Rojas
Global Exponential Stability of Cohen-Grossberg Neural Networks With Piecewise Constant Argument of Generalized Type and Impulses Qiang Xi
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SUBSCRIPTIONS - 2016 - VOLUME 28 - 12 ISSUES
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MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs@mit.edu
------------ Neural Computation - Volume 28, Number 1 - January 1, 2016
Available online for download now: http://www.mitpressjournals.org/toc/neco/28/1
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Articles
Neural Network Spectral Robustness Under Perturbations of the Underlying Graph Anca Radulescu
Sequential Tests for Large Scale Learning Anoop Korattikara, Yutian Chen, and Max Welling
Note
A Note on Support Vector Machines With Polynomial Kernels Hongzhi Tong
Letters
Analytical Calculation of Errors in Time and Value Perception Due to a Subjective Time Accumulator: A Mechanistic Model and the Generation of Weber's Law Vijay Mohan K Namboodiri, Stefan Mihalas, and Marshall G Hussain Shuler
Efficient Associative Computation With Discrete Synapses Andreas Knoblauch
Reduction of Trial-to-trial Perceptual Variability by Intracortical Tonic Inhibition Osamu Hoshino, Meihong Zheng, and Kazuo Watanabe
An Empirical Overview of the No Free Lunch Theorem and Its Effect on Real-World Machine Learning Classification David Gomez, Alfonso Rojas
Global Exponential Stability of Cohen-Grossberg Neural Networks With Piecewise Constant Argument of Generalized Type and Impulses Qiang Xi
------------
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SUBSCRIPTIONS - 2016 - VOLUME 28 - 12 ISSUES
Student/Retired $78 Individual $138 Institution $1,108
MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs@mit.edu
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Neural Computation - Volume 28, Number 2 - February 1, 2016
Available online for download now: http://www.mitpressjournals.org/toc/neco/28/2
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Article
Correlational Neural Networks Sarath Chandar, Mitesh M Khapra, Hugo Larochelle, and Balaraman Ravindran
Letters
Timing of Cortical Events Preceding Voluntary Movement Victor L. Vvedensky, Andrey O. Prokofyev
Mutual Information, Fisher Information, and Efficient Coding Xue-Xin Wei, Alan A Stocker
Memory Stacking in Hierarchical Networks Johan Westok, Patrick J. C. May, and Hannu Tiitinen
Infinite Continuous Feature Model for Psychiatric Comorbidity Analysis Isabel Valera, Francisco J. R. Ruiz, Pablo M. Olmos, Carlos Blanco, and Fernando Perez-Cruz
Filtering With State-Observation Examples via Kernel Monte Carlo Filter Motonobu Kanagawa, Yu Nishiyama, Arthur Gretton, and Kenji Fukumizu
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Neural Computation - Volume 28, Number 3 - March 1, 2016
Available online for download now: http://www.mitpressjournals.org/toc/neco/28/3
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Article
Orthogonal Connectivity Factorization: Interpretable Decomposition of Variability in Correlation Matrices Aapo Hyvarinen, Jun-ichiro Hirayama, Vesa Kiviniemi, and Motoaki Kawanabe
Note
A Block Successive Lower-Bound Maximization Algorithm for the Maximum Pseudolikelihood Estimation of Fully Visible Boltzmann Machines Hien D Nguyen, Ian A Wood
Letters
Microdomain [Ca2+] Fluctuations Alter Temporal Dynamics in Models of Ca2+-dependent Signaling Cascades and Synaptic Vesicle Release Seth H Weinberg
Kernelized Elastic Net Regularization: Generalization Bounds and Sparse Recovery Yunlong Feng, Shao-Gao Lv, Hanyuan Hang, and Johan A.K. Suykens
An Online Policy Gradient Algorithm for Markov Decision Processes With Continuous States and Actions Yao Ma, Tingting Zhao, Kohei Hatano, and Masashi Sugiyama
The Development of an Information Criterion for Change-Point Analysis Colin H LaMont, Paul A. Wiggins
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State of the Brain - Keystone Symposium
Scientific Organizers: Terrence J. Sejnowski and Sten Grillner
May 22-26, 2016 Alpbach Congress Centrum, Alpbach, Austria
Recent years have seen rapid advances in our understanding of brain biology, driven in part by the development of novel technologies for studying neural networks. Consequently, major national research programs in the EU and US have been launched that will bring together teams of neuroscientists and engineers with the aim of achieving a major advance in understanding brain function and dysfunction. The challenge is to map the circuits of the brain, measure the fluctuating patterns of electrical and chemical activity flowing within those circuits and understand how they give rise to cognitive and behavioral capabilities. This Keystone Symposia conference brings together investigators from around the world to share their discoveries and to plan future projects in this exciting new era for brain research.
Conference Program http://www.keystonesymposia.org/index.cfm?e=Web.Meeting.Program&meetingi...
Registration http://www.keystonesymposia.org/index.cfm?e=Web.Meeting.Registration&mee...
Early Registration discount deadline: March 22, 2016
MONDAY, MAY 23
08:30 Welcome and Keynote Address Cori Bargmann, Rockefeller University, USA Understanding Brain Function and Dysfunction
09:30 International Brain Programs
Henry Markram, EPFL SV BMI LNMC, Switzerland The EU Human Brain Project
Walter J. Koroshetz, National Institute of Neurological Disorders and Stroke, NIH, USA The US BRAIN Initiative
Mu-ming Poo, Institute of Neuroscience, CAS, China China Brain Project and Non-human Primate Research
Christof Koch, Allen Institute for Brain Science, USA Project MindScope - Big Science, Team Science, Open Science to Understand Mouse Cortex
15:30 Panel 1: Coordinating International Programs
Chair: Terrence J. Sejnowski, The Salk Institute, USA Cornelia (Cori) Bargmann, Rockefeller University, USA Henry Markram, EPFL SV BMI LNMC, Switzerland Walter J. Koroshetz, National Institute of Neurological Disorders and Stroke, NIH, USA Mu-ming Poo, Institute of Neuroscience, CAS, China Christof Koch, Allen Institute for Brain Science, USA Thomas Skordas, European Commission, Belgium
17:00 Discovering Diversity: Identifying Cell Types in the Brain
Botond Roska, Friedrich Miescher Institute, Switzerland Cell Types and Circuits in the Visual System
Hongkui Zeng, Allen Institute for Brain Science, USA Genetic Approaches to Brain Circuit Mapping and Cell Type Characterization
TUESDAY, MAY 24
08:30 The Brain in Action: Large-Scale Monitoring and Manipulating Neurons
Karl Deisseroth, Stanford University, USA Optogenetic Approaches to Neural Circuits
David W. Tank, Princeton University, USA Recording Activity from Internal Brain States
Mark J. Schnitzer, Stanford University, USA Reading Neural Codes from a Thousand Neurons in Freely Behaving Mice
Susumu Tonegawa, Massachusetts Institute of Technology and RIKEN Brain Science Institute, USA Monitoring and Engineering Memory Engram Cells and their Circuits
15:30 Panel 2: Bridging the Gap between Circuits and Behavior
Chair: David W. Tank, Princeton University, USA Karl Deisseroth, Stanford University, USA Mark J. Schnitzer, Stanford University, USA Susumu Tonegawa, Massachusetts Institute of Technology and RIKEN Brain Science Institute, USA Winfried Denk, Max Planck Institute of Neurobiology, Germany R. Clay Reid, Allen Institute for Brain Science, USA
17:00 Maps in the Brain: Generating Multi-Scale Neural Circuits
Winfried Denk, Max Planck Institute of Neurobiology, Germany Revealing the Core Circuitry in Brains
R. Clay Reid, Allen Institute for Brain Science, USA Integrating Circuits, Recordings and Behavior
Terrence J. Sejnowski, The Salk Institute, USA Global Traveling Waves in Human Cortex
WEDNESDAY, MAY 25
08:30 Advancing Human Neuroscience: Understanding Brain Function and Dysfunction
John Donoghue, Wyss Center for Bio- and Neuro-Engineering, Switzerland Brain Computer Interfaces
Helen S. Mayberg, Emory University, USA Iterative Strategies to Refine and Optimize DBS for Depression
Patricia K. Kuhl, University of Washington, USA What Can Babies' Brains Tell Us About What it Means to be Human?
15:30 Panel 3: What are the Prospects for Helping Humans with Brain Disorders?
Chair: John Donoghue, Wyss Center for Bio- and Neuro-Engineering, Switzerland Helen S. Mayberg, Emory University, USA Patricia K. Kuhl, University of Washington, USA Emery N. Brown, MIT-Harvard Division of Health Sciences and Technology, USA Botond Roska, Friedrich Miescher Institute, Switzerland
17:00 Discovering Principles: Theory, Models, Computation and Statistics
Emery N. Brown, MIT-Harvard Division of Health Sciences and Technology, USA Deciphering the Dynamics of the Unconscious Brain under General Anesthesia
Sten Grillner, Karolinska Institutet, Sweden Multi-Scale Modeling of Neuronal Networks - From Ion Channels to Selection of Behavior
THURSDAY, MAY 26
08:30 Model Systems: Using Genetics to Deconstruct Neural Circuits
Gerald M. Rubin, Janelia Research Campus, USA A Comprehensive Approach to Understanding the Fly Brain
Florian Engert, Harvard University, USA
From Whole-Brain Data to Functional Circuit Models: The Zebrafish Optomotor Response
Hideyuki Okano, Keio University School of Medicine, Japan Disease Modeling and Brain Mapping Using Transgenic Marmosets
15:30 Panel 4: Evolutionary Perspectives in Understanding the Brain
Chair: Sten Grillner, Karolinska Institutet, Sweden Gerald M. Rubin, Janelia Research Campus, USA Florian Engert, Harvard University, USA Hideyuki Okano, Keio University School of Medicine, Japan Hongkui Zeng, Allen Institute for Brain Science, USA
17:00 Big Data: Analyzing High-Dimensional Brain Datasets
Joshua T. Vogelstein, Johns Hopkins University, USA NeuroData: Enabling Petascale Neuroscience
Sean Hill, Ecole Polytechnique Fedrerale de Lausanne, Switzerland Neuroinformatics: From Big Data to Knowledge Discovery
Kamil Ugurbil, University of Minnesota Medical School, USA Human Connectomics
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Neural Computation - Volume 28 Number 4 - April 1 2016
Available online for download now: http://www.mitpressjournals.org/toc/neco/28/4
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Article
Vector Symbolic Spiking Neural Network Model of Hippocampal Sub-area CA1 Novelty Detection Functionality Claus Agerskov
Note
Feature-based Attention by Lateral Spike Synchronization August Romeo, Hans Super
Letters
Downstream Effect of Ramping Neuronal Activity Through Synapses With Short-term Plasticity Wei Wei, Xiao-Jing Wang
Optimal Schedules in Multi-task Motor Learning Jeong Yoon Lee, Youngmin Oh, Sung Shin Kim, Robert A Scheidt, and Nicolas Schweighofer
Theoretical and Experimental Analyses of Tensor-Based Regression and Classification Kishan wimalawarne, Ryota Tomioka, and Masashi Sugiyama
Feature Selection for Ridge Regression With Provable Guarantees Saurabh Paul, Petros Drineas
Online Pairwise Learning Algorithms Yiming Ying, Ding-Xuan Zhou
Sampled-data State Feedback Stabilization of Boolean Control Networks Yang Liu, Jinde Cao, Liangjie Sun, and Jianquan Lu
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Neural Computation - Volume 28, Number 5 - May 1, 2016
Available online for download now: http://www.mitpressjournals.org/toc/neco/28/5
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Article
Causal Inference on Discrete Data via Estimating Distance Correlations Furui Liu, Laiwan Chan
Note
A Mathematical Motivation for Complex-valued Convolutional Networks Mark Tygert, Joan Bruna, Soumith Chintala, Yann LeCun, Serkan Piantino, and Arthur Szlam
Letters
Learning Precise Spike Train to Spike Train Transformations in Multilayer Feedforward Neuronal Networks Arunava Banerjee
Separating Spike Count Correlation From Firing Rate Correlation Giuseppe Vinci, Valerie Ventura, Matthew A. Smith, and Robert E. Kass
Effect of Reference Scheme on Power and Phase of the Local Field Potential Vinay Shirhatti, Ayon Borthakur, and Supratim Ray
State Space Analysis of Granger-Geweke Causality With Application to fMRI Victor Solo
Whole-Body Reaching Movements Formulated by Minimum Muscle-Tension Change Criterion Naoki Kudo, Kyuheong Choi, Takahiro Kagawa, and Yoji Uno
Recurrent Neural Network for Computing Outer Inverse Ivan S. Zivkovic, Predrag S. Stanimirovic, and Yimin Wei
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participants (1)
-
Terry Sejnowski