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ORCIDNeural Computation, Volume 36
Volume 36, Number 1, January 2024
- Rajesh P. N. Rao, Dimitrios C. Gklezakos, Vishwas Sathish:
Active Predictive Coding: A Unifying Neural Model for Active Perception, Compositional Learning, and Hierarchical Planning. 1-32 - Salman Khan, Alexander Wong, Bryan P. Tripp
:
Modeling the Role of Contour Integration in Visual Inference. 33-74 - Anca Radulescu, Danae Evans, Amani-Dasia Augustin, Anthony Cooper, Johan Nakuci, Sarah Muldoon:
Synchronization and Clustering in Complex Quadratic Networks. 75-106
- Anru R. Zhang, Ryan P. Bell, Chen An, Runshi Tang, Shana A. Hall, Cliburn Chan, Kareem Al-Khalil, Christina S. Meade:
Cocaine Use Prediction With Tensor-Based Machine Learning on Multimodal MRI Connectome Data. 107-127 - Yusuke Endo, Koujin Takeda:
Performance Evaluation of Matrix Factorization for fMRI Data. 128-150 - Daniel Kunin, Javier Sagastuy-Breña, Lauren E. Gillespie, Eshed Margalit, Hidenori Tanaka, Surya Ganguli, Daniel L. K. Yamins:
The Limiting Dynamics of SGD: Modified Loss, Phase-Space Oscillations, and Anomalous Diffusion. 151-174
Volume 36, Number 2, February 2024
- C. Daniel Greenidge, Benjamin Scholl, Jacob L. Yates, Jonathan W. Pillow:
Efficient Decoding of Large-Scale Neural Population Responses With Gaussian-Process Multiclass Regression. 175-226
- Joan Gort:
Emergence of Universal Computations Through Neural Manifold Dynamics. 227-270 - Jan Karbowski, Paulina Urban:
Cooperativity, Information Gain, and Energy Cost During Early LTP in Dendritic Spines. 271-311 - Kota Kawamoto, Masato Uchida:
Q&A Label Learning. 312-349
Volume 36, Number 3, March 2024
- Claus Metzner, Marius E. Yamakou, Dennis Voelkl, Achim Schilling, Patrick Krauss:
Quantifying and Maximizing the Information Flux in Recurrent Neural Networks. 351-384
- Daisuke Kawahara, Shigeyoshi Fujisawa:
Advantages of Persistent Cohomology in Estimating Animal Location From Grid Cell Population Activity. 385-411 - Hamid Karimi-Rouzbahani:
Evidence for Multiscale Multiplexed Representation of Visual Features in EEG. 412-436 - Aditi Jha, Zoe C. Ashwood, Jonathan W. Pillow:
Active Learning for Discrete Latent Variable Models. 437-474 - Zhiwei Fang, Sifan Wang, Paris Perdikaris:
Learning Only on Boundaries: A Physics-Informed Neural Operator for Solving Parametric Partial Differential Equations in Complex Geometries. 475-498
Volume 36, Number 4, April 2024
- Satoshi Kuroki, Kenji Mizuseki:
CA3 Circuit Model Compressing Sequential Information in Theta Oscillation and Replay. 501-548 - Madison Cotteret, Hugh Greatorex, Martin Ziegler, Elisabetta Chicca:
Vector Symbolic Finite State Machines in Attractor Neural Networks. 549-595 - Vidyesh Rao Anisetti, Ananth Kandala, Benjamin Scellier, J. M. Schwarz:
Frequency Propagation: Multimechanism Learning in Nonlinear Physical Networks. 596-620 - Xu Pan, Ruben Coen Cagli, Odelia Schwartz:
Probing the Structure and Functional Properties of the Dropout-Induced Correlated Variability in Convolutional Neural Networks. 621-644
- Alireza Poshtkohi, John J. Wade, Liam McDaid, Junxiu Liu, Mark Dallas, Angela Bithell:
Mathematical Modeling of PI3K/Akt Pathway in Microglia. 645-676 - Toon Van de Maele, Tim Verbelen, Pietro Mazzaglia, Stefano Ferraro, Bart Dhoedt:
Object-Centric Scene Representations Using Active Inference. 677-704 - Garrett Crutcher:
Lateral Connections Improve Generalizability of Learning in a Simple Neural Network. 705-717 - Zhiying Fang, Tong Mao, Jun Fan:
Learning Korobov Functions by Correntropy and Convolutional Neural Networks. 718-743 - Seong-il Im, Jae-Seung Jeong, Junseo Lee, Changhwan Shin, Jeong Ho Cho, Hyunsu Ju:
Column Row Convolutional Neural Network: Reducing Parameters for Efficient Image Processing. 744-758
Volume 36, Number 5, May 2024
- Beck Strohmer, Elias Najarro, Jessica Ausborn, Rune W. Berg, Silvia Tolu:
Sparse Firing in a Hybrid Central Pattern Generator for Spinal Motor Circuits. 759-780 - Mohammad Samavat, Thomas M. Bartol, Kristen M. Harris, Terrence J. Sejnowski:
Synaptic Information Storage Capacity Measured With Information Theory. 781-802 - William F. Podlaski, Christian K. Machens:
Approximating Nonlinear Functions With Latent Boundaries in Low-Rank Excitatory-Inhibitory Spiking Networks. 803-857
- Patrick Emami, Pan He, Sanjay Ranka, Anand Rangarajan:
Toward Improving the Generation Quality of Autoregressive Slot VAEs. 858-896 - Bin Gu, Xiyuan Wei, Hualin Zhang, Yi Chang, Heng Huang:
Obtaining Lower Query Complexities Through Lightweight Zeroth-Order Proximal Gradient Algorithms. 897-935 - Guanyu Yang, Kaizhu Huang, Rui Zhang, Xi Yang:
Instance-Specific Model Perturbation Improves Generalized Zero-Shot Learning. 936-962 - Zhengquan Zhang, Feng Xu:
An Overview of the Free Energy Principle and Related Research. 963-1021 - BethAnna Jones, Lawrence Snyder, ShiNung Ching:
Heterogeneous Forgetting Rates and Greedy Allocation in Slot-Based Memory Networks Promotes Signal Retention. 1022-1040
Volume 36, Number 6, 2024
- Evgenia Kartsaki, Gerrit Hilgen, Evelyne Sernagor, Bruno Cessac:
How Does the Inner Retinal Network Shape the Ganglion Cells Receptive Field? A Computational Study. 1041-1083 - Netanel Raviv:
Linear Codes for Hyperdimensional Computing. 1084-1120 - Vincent Painchaud, Patrick Desrosiers, Nicolas Doyon:
The Determining Role of Covariances in Large Networks of Stochastic Neurons. 1121-1162 - Veronica Centorrino, Anand Gokhale, Alexander Davydov, Giovanni Russo, Francesco Bullo:
Positive Competitive Networks for Sparse Reconstruction. 1163-1197 - Edoardo Vecchi, Davide Bassetti, Fabio Graziato, Lukás Pospísil, Illia Horenko:
Gauge-Optimal Approximate Learning for Small Data Classification. 1198-1227 - Stephen José Hanson, Vivek Yadav, Catherine Hanson:
Dense Sample Deep Learning. 1228-1244
Volume 36, Number 7, 2024
- Colin Bredenberg, Cristina Savin:
Desiderata for Normative Models of Synaptic Plasticity. 1245-1285 - Alessio Paolo Buccino, Tanguy Damart, Julian Bartram, Darshan Mandge, Xiaohan Xue, Mickael Zbili, Tobias Gänswein, Aurélien Jaquier, Vishalini Emmenegger, Henry Markram, Andreas Hierlemann, Werner Van Geit:
A Multimodal Fitting Approach to Construct Single-Neuron Models With Patch Clamp and High-Density Microelectrode Arrays. 1286-1331 - Alireza Nadafian, Mohammad Ganjtabesh:
Bioplausible Unsupervised Delay Learning for Extracting Spatiotemporal Features in Spiking Neural Networks. 1332-1352 - K. Michael Martini, Ilya Nemenman:
Data Efficiency, Dimensionality Reduction, and the Generalized Symmetric Information Bottleneck. 1353-1379 - Kexin Lv, Jia Cai, Junyi Huo, Chao Shang, Xiaolin Huang, Jie Yang:
Sparse Generalized Canonical Correlation Analysis: Distributed Alternating Iteration-Based Approach. 1380-1409 - Niels J. Verosky:
Associative Learning of an Unnormalized Successor Representation. 1410-1423 - Sören Christensen, Jan Kallsen:
Is Learning in Biological Neural Networks Based on Stochastic Gradient Descent? An Analysis Using Stochastic Processes. 1424-1432 - Christoffer G. Alexandersen, Chloé Duprat, Aitakin Ezzati, Pierre Houzelstein, Ambre Ledoux, Yuhong Liu, Sandra Saghir, Alain Destexhe, Federico Tesler, Damien Depannemaecker:
A Mean Field to Capture Asynchronous Irregular Dynamics of Conductance-Based Networks of Adaptive Quadratic Integrate-and-Fire Neuron Models. 1433-1448
Volume 36, Number 8, 2024
- Della Daiyi Luo, Bapun Giri, Kamran Diba, Caleb Kemere:
Extended Poisson Gaussian-Process Latent Variable Model for Unsupervised Neural Decoding. 1449-1475 - Bastian Pietras:
Pulse Shape and Voltage-Dependent Synchronization in Spiking Neuron Networks. 1476-1540 - Kei Uchizawa, Haruki Abe:
Trade-Offs Between Energy and Depth of Neural Networks. 1541-1567 - Vicky Zhu, Robert Rosenbaum:
Learning Fixed Points of Recurrent Neural Networks by Reparameterizing the Network Model. 1568-1600 - Jirí Síma, Petra Vidnerová, Vojtech Mrazek:
Energy Complexity of Convolutional Neural Networks. 1601-1625 - Maria Osório, Andreas Wichert:
Promoting the Shift From Pixel-Level Correlations to Object Semantics Learning by Rethinking Computer Vision Benchmark Data Sets. 1626-1642 - Mark A. Kramer, Catherine Jean Chu:
A General, Noise-Driven Mechanism for the 1/f-Like Behavior of Neural Field Spectra. 1643-1668
Volume 36, Number 9, 2024
- Jan Melchior, Robin Schiewer, Laurenz Wiskott:
Hebbian Descent: A Unified View on Log-Likelihood Learning. 1669-1712 - Minkyu Choi, Yizhen Zhang, Kuan Han, Xiaokai Wang, Zhongming Liu:
Human Eyes-Inspired Recurrent Neural Networks Are More Robust Against Adversarial Noises. 1713-1743 - Martin Magris, Mostafa Shabani, Alexandros Iosifidis:
Manifold Gaussian Variational Bayes on the Precision Matrix. 1744-1798 - Lærke Karen Krohne, Ingeborg H. Hansen, Kristoffer H. Madsen:
On the Search for Data-Driven and Reproducible Schizophrenia Subtypes Using Resting State fMRI Data From Multiple Sites. 1799-1831 - J. Petkovic, Rita Fioresi:
Spontaneous Emergence of Robustness to Light Variation in CNNs With a Precortically Inspired Module. 1832-1853 - Theodore Jerome Tinker, Kenji Doya, Jun Tani:
Intrinsic Rewards for Exploration Without Harm From Observational Noise: A Simulation Study Based on the Free Energy Principle. 1854-1885 - Jeff Orchard, P. Michael Furlong, Kathryn Simone:
Efficient Hyperdimensional Computing With Spiking Phasors. 1886-1911 - Yiming Jiang, Jinlan Liu, Dongpo Xu, Danilo P. Mandic:
UAdam: Unified Adam-Type Algorithmic Framework for Nonconvex Optimization. 1912-1938
Volume 36, Number 10, 2024
- Travis Monk, Nik Dennler, Nicholas Ralph, Shavika Rastogi, Saeed Afshar, Pablo Urbizagastegui, Russell Jarvis, André van Schaik, Andrew Adamatzky:
Electrical Signaling Beyond Neurons. 1939-2029 - Parvin Malekzadeh, Konstantinos N. Plataniotis:
Active Inference and Reinforcement Learning: A Unified Inference on Continuous State and Action Spaces Under Partial Observability. 2073-2135 - Zeyuan Wang, Luis Cruz:
Trainable Reference Spikes Improve Temporal Information Processing of SNNs With Supervised Learning. 2136-2169 - Ali Tehrani-Saleh, J. Devin McAuley, Christoph Adami:
Mechanism of Duration Perception in Artificial Brains Suggests New Model of Attentional Entrainment. 2170-2200 - Justin D. Theiss, Michael A. Silver:
Top-Down Priors Disambiguate Target and Distractor Features in Simulated Covert Visual Search. 2201-2224
Volume 36, Number 11, 2024
- Wilka Carvalho, Momchil S. Tomov, William de Cothi, Caswell Barry, Samuel J. Gershman:
Predictive Representations: Building Blocks of Intelligence. 2225-2298 - Michal Markiewicz, Ireneusz Brzozowski, Szymon Janusz:
Spiking Neural Network Pressure Sensor. 2299-2321 - Hayden McAlister, Anthony Robins, Lech Szymanski:
Prototype Analysis in Hopfield Networks With Hebbian Learning. 2322-2364 - Valentin Leplat, Le Thi Khanh Hien, Akwum Onwunta, Nicolas Gillis:
Deep Nonnegative Matrix Factorization With Beta Divergences. 2365-2402 - Théophile Champion, Marek Grzes, Lisa Bonheme, Howard Bowman:
Deconstructing Deep Active Inference: A Contrarian Information Gatherer. 2403-2445 - Onur Boyar, Ichiro Takeuchi:
Latent Space Bayesian Optimization With Latent Data Augmentation for Enhanced Exploration. 2446-2478 - Marissa Connor, Bruno A. Olshausen, Christopher Rozell:
Learning Internal Representations of 3D Transformations From 2D Projected Inputs. 2505-2539 - Yusuke Endo, Koujin Takeda:
ℓ 1 -Regularized ICA: A Novel Method for Analysis of Task-Related fMRI Data. 2540-2570
Volume 36, Number 12, 2024
- Victor Geadah, Gabriel Barello, C. Daniel Greenidge, Adam S. Charles, Jonathan W. Pillow:
Sparse-Coding Variational Autoencoders. 2571-2601 - Petr Anokhin, Artyom Y. Sorokin, Mikhail Burtsev, Karl Friston:
Associative Learning and Active Inference. 2602-2635 - Chunming Jiang, Yilei Zhang:
KLIF: An Optimized Spiking Neuron Unit for Tuning Surrogate Gradient Function. 2636-2650 - Vasily Zadorozhnyy, Edison Mucllari, Cole Pospisil, Duc Duy Nguyen, Qiang Ye:
Orthogonal Gated Recurrent Unit With Neumann-Cayley Transformation. 2651-2676 - Alex Heyman, Joel Zylberberg:
Fine Granularity Is Critical for Intelligent Neural Network Pruning. 2677-2709 - Zeyu Jing, Markus Meister:
A Fast Algorithm for All-Pairs-Shortest-Paths Suitable for Neural Networks. 2710-2733 - Devdhar Patel, Terrence Sejnowski, Hava T. Siegelmann:
Optimizing Attention and Cognitive Control Costs Using Temporally Layered Architectures. 2734-2763
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