Neural Computation

Article	Citations
Conductance-Based Phenomenological Nonspiking Model: A Dimensionless and Simple Model That Reliably Predicts the Effects of Conductance Variations on Nonspiking Neuronal Dynamics	103
Sensitivity of Sparse Codes to Image Distortions	88
Optimizing Attention and Cognitive Control Costs Using Temporally Layered Architectures	55
Mean-Field Approximations With Adaptive Coupling for Networks With Spike-Timing-Dependent Plasticity	53
Bounded Rational Decision Networks With Belief Propagation	49
On Suspicious Coincidences and Pointwise Mutual Information	31
Generalized Low-Rank Update: Model Parameter Bounds for Low-Rank Training Data Modifications	30
Permitted Sets and Convex Coding in Nonthreshold Linear Networks	28
Self-Organization of Nonlinearly Coupled Neural Fluctuations Into Synergistic Population Codes	28
Understanding the Computational Demands Underlying Visual Reasoning	25
Top-Down Priors Disambiguate Target and Distractor Features in Simulated Covert Visual Search	22
A Model of Semantic Completion in Generative Episodic Memory	21
Bridging the Functional and Wiring Properties of V1 Neurons Through Sparse Coding	20
Modeling the Ventral and Dorsal Cortical Visual Pathways Using Artificial Neural Networks	18
Asymmetric Weights and Retrieval Practice in an Autoassociative Neural Network Model of Paired-Associate Learning	18
Synergistic Pathways of Modulation Enable Robust Task Packing Within Neural Dynamics	17
Task-Agnostic Continual Learning Using Online Variational Bayes with Fixed-Point Updates	17
Realizing Active Inference in Variational Message Passing: The Outcome-Blind Certainty Seeker	16
Adaptive Filter Model of Cerebellum for Biological Muscle Control With Spike Train Inputs	16
Toward Generalized Entropic Sparsification for Convolutional Neural Networks	15
Extended Poisson Gaussian-Process Latent Variable Model for Unsupervised Neural Decoding	15
Understanding Dynamics of Nonlinear Representation Learning and Its Application	14
CA3 Circuit Model Compressing Sequential Information in Theta Oscillation and Replay	14
Learning Fixed Points of Recurrent Neural Networks by Reparameterizing the Network Model	13
Advantages of Persistent Cohomology in Estimating Animal Location From Grid Cell Population Activity	13

Reduced-Dimension, Biophysical Neuron Models Constructed From Observed Data	13
On the Search for Data-Driven and Reproducible Schizophrenia Subtypes Using Resting State fMRI Data From Multiple Sites	13
Least kth-Order and Rényi Generative Adversarial Networks	13
Learning Only on Boundaries: A Physics-Informed Neural Operator for Solving Parametric Partial Differential Equations in Complex Geometries	12
Quantifying and Maximizing the Information Flux in Recurrent Neural Networks	12
UAdam: Unified Adam-Type Algorithmic Framework for Nonconvex Optimization	12
Expansion of Information in the Binary Autoencoder with Random Binary Weights	12
Active Learning for Discrete Latent Variable Models	12
Maximal Memory Capacity Near the Edge of Chaos in Balanced Cortical E-I Networks	11
Generalization Guarantees of Gradient Descent for Shallow Neural Networks	11
Multimodal and Multifactor Branching Time Active Inference	10
Decoding Pixel-Level Image Features From Two-Photon Calcium Signals of Macaque Visual Cortex	10
Deconstructing Deep Active Inference: A Contrarian Information Gatherer	10
Deep Nonnegative Matrix Factorization With Beta Divergences	10
Decision Threshold Learning in the Basal Ganglia for Multiple Alternatives	9
Differential Geometry Methods for Constructing Manifold-Targeted Recurrent Neural Networks	9
Attention in a Family of Boltzmann Machines Emerging From Modern Hopfield Networks	9
Neuromorphic Engineering: In Memory of Misha Mahowald	9
The Limiting Dynamics of SGD: Modified Loss, Phase-Space Oscillations, and Anomalous Diffusion	9
Model Based or Model Free? Comparing Adaptive Methods for Estimating Thresholds in Neuroscience	8
Hypothesis Test and Confidence Analysis With Wasserstein Distance on General Dimension	8
Learning in Associative Networks Through Pavlovian Dynamics	8
Electrical Signaling Beyond Neurons	8
Bioplausible Unsupervised Delay Learning for Extracting Spatiotemporal Features in Spiking Neural Networks	8
A Mean Field to Capture Asynchronous Irregular Dynamics of Conductance-Based Networks of Adaptive Quadratic Integrate-and-Fire Neuron Models	8
eSPA+: Scalable Entropy-Optimal Machine Learning Classification for Small Data Problems	7
Using Global t-SNE to Preserve Intercluster Data Structure	7
Toward Network Intelligence	7
Desiderata for Normative Models of Synaptic Plasticity	7
Prototype Analysis in Hopfield Networks With Hebbian Learning	7
Statistical Properties of Color Matching Functions	7
How Does the Inner Retinal Network Shape the Ganglion Cells Receptive Field? A Computational Study	7
Probing the Structure and Functional Properties of the Dropout-Induced Correlated Variability in Convolutional Neural Networks	7
Temporal Variabilities Provide Additional Category-Related Information in Object Category Decoding: A Systematic Comparison of Informative EEG Features	7
Implicit Contact Dynamics Modeling With Explicit Inertia Matrix Representation for Real-Time, Model-Based Control in Physical Environment	6
Positive Competitive Networks for Sparse Reconstruction	6
Neural Circuits for Dynamics-Based Segmentation of Time Series	6
Memoryless Optimality: Neurons Do Not Need Adaptation to Optimally Encode Stimuli With Arbitrarily Complex Statistics	6
Computation With Sequences of Assemblies in a Model of the Brain	6
Astrocytes Learn to Detect and Signal Deviations From Critical Brain Dynamics	6
Mechanism of Duration Perception in Artificial Brains Suggests New Model of Attentional Entrainment	6
Is Learning in Biological Neural Networks Based on Stochastic Gradient Descent? An Analysis Using Stochastic Processes	6
Semisupervised Ordinal Regression Based on Empirical Risk Minimization	6
Bayesian Quadrature Optimization for Probability Threshold Robustness Measure	6
A Normative Account of Confirmation Bias During Reinforcement Learning	6
Generalization Analysis of Transformers in Distribution Regression	6
Disentangled Representation Learning and Generation With Manifold Optimization	6
Sequential Learning in the Dense Associative Memory	5
Promoting the Shift From Pixel-Level Correlations to Object Semantics Learning by Rethinking Computer Vision Benchmark Data Sets	5
Fast Multigroup Gaussian Process Factor Models	5

Toward a Free-Response Paradigm of Decision Making in Spiking Neural Networks	5
Visuomotor Mismatch Responses as a Hallmark of Explaining Away in Causal Inference	5
Flexible Transmitter Network	5
Chance-Constrained Active Inference	5
Distributed Phase Oscillatory Excitation Efficiently Produces Attractors Using Spike-Timing-Dependent Plasticity	5
Spiking Neuron-Astrocyte Networks for Image Recognition	5
Active Inference and Intentional Behavior	5
Strong Allee Effect Synaptic Plasticity Rule in an Unsupervised Learning Environment	5
Simple Convolutional-Based Models: Are They Learning the Task or the Data?	5
Reducing Catastrophic Forgetting With Associative Learning: A Lesson From Fruit Flies	5
Linear Codes for Hyperdimensional Computing	4
Gauge-Optimal Approximate Learning for Small Data Classification	4
Distributed Synaptic Connection Strength Changes Dynamics in a Population Firing Rate Model in Response to Continuous External Stimuli	4
Understanding Memories of the Past in the Context of Different Complex Neural Network Architectures	4
Learning in Wilson-Cowan Model for Metapopulation	4
Toward a Biomimetic Neural Circuit Model of Sensory-Motor Processing	4
Synaptic Information Storage Capacity Measured With Information Theory	4
A Generalized Time Rescaling Theorem for Temporal Point Processes	4
Cooperativity, Information Gain, and Energy Cost During Early LTP in Dendritic Spines	4
Capacity Limitations of Visual Search in Deep Convolutional Neural Networks	4
Predictive Coding as a Neuromorphic Alternative to Backpropagation: A Critical Evaluation	4
Learning the Synaptic and Intrinsic Membrane Dynamics Underlying Working Memory in Spiking Neural Network Models	4
Uncovering Dynamical Equations of Stochastic Decision Models Using Data-Driven SINDy Algorithm	4
Role of Interaction Delays in the Synchronization of Inhibitory Networks	4
A Survey on Artificial Neural Networks in Human—Robot Interaction	4
An Overview of the Free Energy Principle and Related Research	4
A Correspondence Between Normalization Strategies in Artificial and Biological Neural Networks	3
Context-Sensitive Processing in a Model Neocortical Pyramidal Cell With Two Sites of Input Integration	3
Selective Inference for Change Point Detection by Recurrent Neural Network	3
A Predictive Processing Model of Episodic Memory and Time Perception	3
Emergence of Universal Computations Through Neural Manifold Dynamics	3
On the Compressive Power of Autoencoders With Linear and ReLU Activation Functions	3
Neural Information Processing and Computations of Two-Input Synapses	3
Posterior Covariance Information Criterion for Weighted Inference	3
Beyond Backpropagation: Bilevel Optimization Through Implicit Differentiation and Equilibrium Propagation	3
Neural Networks with Disabilities: An Introduction to Complementary Artificial Intelligence	3
Cocaine Use Prediction With Tensor-Based Machine Learning on Multimodal MRI Connectome Data	3
Vector Symbolic Finite State Machines in Attractor Neural Networks	3
Replay in Deep Learning: Current Approaches and Missing Biological Elements	3
Excitation–Inhibition Balance Controls Synchronization in a Simple Model of Coupled Phase Oscillators	3
Evidence for Multiscale Multiplexed Representation of Visual Features in EEG	3
Generalization Analysis of Pairwise Learning for Ranking With Deep Neural Networks	3
Trainable Reference Spikes Improve Temporal Information Processing of SNNs With Supervised Learning	3
Automatic Hyperparameter Tuning in Sparse Matrix Factorization	3
Multistream-Based Marked Point Process With Decomposed Cumulative Hazard Functions	3
Macroscopic Gamma Oscillation With Bursting Neuron Model Under Stochastic Fluctuation	3
Column Row Convolutional Neural Network: Reducing Parameters for Efficient Image Processing	3
Nearly Optimal Learning Using Sparse Deep ReLU Networks in Regularized Empirical Risk Minimization With Lipschitz Loss	2
An FPGA Accelerator for High-Speed Moving Objects Detection and Tracking With a Spike Camera	2
Intrinsic Rewards for Exploration Without Harm From Observational Noise: A Simulation Study Based on the Free Energy Principle	2
Knowledge as a Breaking of Ergodicity	2
Restricted Boltzmann Machines as Models of Interacting Variables	2
Categorical Perception: A Groundwork for Deep Learning	2
Large Language Models and the Reverse Turing Test	2
Full-Span Log-Linear Model and Fast Learning Algorithm	2
Errata to “A Tutorial on the Spectral Theory of Markov Chains” by Eddie Seabrook and Laurenz Wiskott (Neural Computation, November 2023, Vol. 35, No. 11, pp. 1713–1796, https://doi.org/10.1162/	2
Recurrent Neural-Linear Posterior Sampling for Nonstationary Contextual Bandits	2
Predictive Coding Approximates Backprop Along Arbitrary Computation Graphs	2
Sensitivity to Control Signals in Triphasic Rhythmic Neural Systems: A Comparative Mechanistic Analysis via Infinitesimal Local Timing Response Curves	2
Fixed-Time Stable Neurodynamic Flow to Sparse Signal Recovery via Nonconvex L1-β2-Norm	2
A Neural Model for Insect Steering Applied to Olfaction and Path Integration	2
Inferring Mechanisms of Auditory Attentional Modulation with Deep Neural Networks	2
On PDE Characterization of Smooth Hierarchical Functions Computed by Neural Networks	2
Gradual Domain Adaptation via Normalizing Flows	2
A Categorical Framework for Quantifying Emergent Effects in Network Topology	2
Formal Verification of Deep Brain Stimulation Controllers for Parkinson's Disease Treatment	2
Predictive Coding Model Detects Novelty on Different Levels of Representation Hierarchy	2
A Generalized Framework of Multifidelity Max-Value Entropy Search Through Joint Entropy	2
Mirror Descent of Hopfield Model	2
Lateral Connections Improve Generalizability of Learning in a Simple Neural Network	2
Learning With Proper Partial Labels	2
Predictive Coding, Variational Autoencoders, and Biological Connections	2
Multilevel Data Representation for Training Deep Helmholtz Machines	2
Adding Space to Random Networks of Spiking Neurons: A Method Based on Scaling the Network Size	2
Human Eyes–Inspired Recurrent Neural Networks Are More Robust Against Adversarial Noises	2
Winning the Lottery With Neural Connectivity Constraints: Faster Learning Across Cognitive Tasks With Spatially Constrained Sparse RNNs	2
Bayesian Brains and the Rényi Divergence	2
Learning Internal Representations of 3D Transformations From 2D Projected Inputs	2
Gaussian Process Koopman Mode Decomposition	2
Few-Shot Learning in Spiking Neural Networks by Multi-Timescale Optimization	2

A Fast Algorithm for the Real-Valued Combinatorial Pure Exploration of the Multi-Armed Bandit	2
Relating Human Error–Based Learning to Modern Deep RL Algorithms	2
Active Role of Self-Sustained Neural Activity on Sensory Input Processing: A Minimal Theoretical Model	2
Manifold Gaussian Variational Bayes on the Precision Matrix	2
The Leaky Integrate-and-Fire Neuron Is a Change-Point Detector for Compound Poisson Processes	2
Nonconvex Sparse Regularization for Deep Neural Networks and Its Optimality	2
Sparse-Coding Variational Autoencoders	2