Neural Computation

Article	Citations
Dynamic Modeling of Spike Count Data With Conway-Maxwell Poisson Variability	98
Lateral Connections Improve Generalizability of Learning in a Simple Neural Network	93
On the Explainability of Graph Convolutional Network With GCN Tangent Kernel	82
Do Neural Networks for Segmentation Understand Insideness?	69
Conductance-Based Phenomenological Nonspiking Model: A Dimensionless and Simple Model That Reliably Predicts the Effects of Conductance Variations on Nonspiking Neuronal Dynamics	66
Gaussian Process Koopman Mode Decomposition	49
Categorical Perception: A Groundwork for Deep Learning	38
Toward a Biomimetic Neural Circuit Model of Sensory-Motor Processing	36
Formal Verification of Deep Brain Stimulation Controllers for Parkinson's Disease Treatment	32
Few-Shot Learning in Spiking Neural Networks by Multi-Timescale Optimization	31
NetPyNE Implementation and Scaling of the Potjans-Diesmann Cortical Microcircuit Model	31
Sensitivity of Sparse Codes to Image Distortions	27
Attention in a Family of Boltzmann Machines Emerging From Modern Hopfield Networks	27
Training Deep Convolutional Spiking Neural Networks With Spike Probabilistic Global Pooling	26
Multimodal and Multifactor Branching Time Active Inference	21
The Limiting Dynamics of SGD: Modified Loss, Phase-Space Oscillations, and Anomalous Diffusion	21
Synaptic Information Storage Capacity Measured With Information Theory	20
Deep Nonnegative Matrix Factorization With Beta Divergences	20
On an Interpretation of ResNets via Gate-Network Control	20
Deconstructing Deep Active Inference: A Contrarian Information Gatherer	19
Learning in Volatile Environments With the Bayes Factor Surprise	18
Classification of Autism Spectrum Disorder From EEG-Based Functional Brain Connectivity Analysis	18
Reducing Catastrophic Forgetting With Associative Learning: A Lesson From Fruit Flies	16
On Neural Associative Memory Structures: Storage and Retrieval of Sequences in a Chain of Tournaments	15
Neuromorphic Engineering: In Memory of Misha Mahowald	14

Stability Conditions of Bicomplex-Valued Hopfield Neural Networks	14
Approximating Nonlinear Functions With Latent Boundaries in Low-Rank Excitatory-Inhibitory Spiking Networks	13
Linear Codes for Hyperdimensional Computing	12
Restricted Boltzmann Machines as Models of Interacting Variables	12
Information Geometrically Generalized Covariate Shift Adaptation	12
The Tensor Brain: A Unified Theory of Perception, Memory, and Semantic Decoding	12
Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting	12
On Neural Network Kernels and the Storage Capacity Problem	12
Parameter Estimation in Multiple Dynamic Synaptic Coupling Model Using Bayesian Point Process State-Space Modeling Framework	11
Differential Geometry Methods for Constructing Manifold-Targeted Recurrent Neural Networks	11
From Univariate to Multivariate Coupling Between Continuous Signals and Point Processes: A Mathematical Framework	11
Enhanced Equivalence Projective Simulation: A Framework for Modeling Formation of Stimulus Equivalence Classes	11
Distributed Phase Oscillatory Excitation Efficiently Produces Attractors Using Spike-Timing-Dependent Plasticity	11
A Biologically Plausible Neural Network for Multichannel Canonical Correlation Analysis	10
Obtaining Lower Query Complexities Through Lightweight Zeroth-Order Proximal Gradient Algorithms	10
Efficient Decoding of Large-Scale Neural Population Responses With Gaussian-Process Multiclass Regression	10
A Simple Model of Nonspiking Neurons	9
Nonlinear Decoding of Natural Images From Large-Scale Primate Retinal Ganglion Recordings	8
Efficient Hyperdimensional Computing With Spiking Phasors	8
From Pavlov Conditioning to Hebb Learning	8
Orthogonal Gated Recurrent Unit With Neumann-Cayley Transformation	8
Manifold Gaussian Variational Bayes on the Precision Matrix	8
A Fast Algorithm for All-Pairs-Shortest-Paths Suitable for Neural Networks	8
Mean-Field Approximations With Adaptive Coupling for Networks With Spike-Timing-Dependent Plasticity	8
Implicit Regularization and Momentum Algorithms in Nonlinearly Parameterized Adaptive Control and Prediction	7
A Generalized Framework of Multifidelity Max-Value Entropy Search Through Joint Entropy	7
Optimizing Attention and Cognitive Control Costs Using Temporally Layered Architectures	7
On Suspicious Coincidences and Pointwise Mutual Information	7
Online Mental Fatigue Monitoring via Indirect Brain Dynamics Evaluation	6
Relating Human Error–Based Learning to Modern Deep RL Algorithms	6
Bounded Rational Decision Networks With Belief Propagation	6
Large Language Models and the Reverse Turing Test	6
A Computational Study on Synaptic Plasticity Regulation and Information Processing in Neuron-Astrocyte Networks	6
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/	6
A Dynamic Neural Field Model of Multimodal Merging: Application to the Ventriloquist Effect	6
Probing the Relationship Between Latent Linear Dynamical Systems and Low-Rank Recurrent Neural Network Models	6
Toward a Free-Response Paradigm of Decision-Making in Spiking Neural Networks	6
Toward a Kernel-Based Uncertainty Decomposition Framework for Data and Models	5
Recurrent Connections in the Primate Ventral Visual Stream Mediate a Trade-Off Between Task Performance and Network Size During Core Object Recognition	5
Cooperativity, Information Gain, and Energy Cost During Early LTP in Dendritic Spines	5
Inference on the Macroscopic Dynamics of Spiking Neurons	5
Uncovering Dynamical Equations of Stochastic Decision Models Using Data-Driven SINDy Algorithm	5
Efficient Decoding of Compositional Structure in Holistic Representations	5
Replay as a Basis for Backpropagation Through Time in the Brain	5
Fine Granularity Is Critical for Intelligent Neural Network Pruning	5
Learning the Synaptic and Intrinsic Membrane Dynamics Underlying Working Memory in Spiking Neural Network Models	5
On PDE Characterization of Smooth Hierarchical Functions Computed by Neural Networks	5
A Neurodynamic Model of Saliency Prediction in V1	5
Spiking Neural Network Pressure Sensor	5
Mathematical Modeling of PI3K/Akt Pathway in Microglia	4

Body Mechanics, Optimality, and Sensory Feedback in the Human Control of Complex Objects	4
Permitted Sets and Convex Coding in Nonthreshold Linear Networks	4
Unsupervised Learning of Temporal Abstractions With Slot-Based Transformers	4
Generalized Low-Rank Update: Model Parameter Bounds for Low-Rank Training Data Modifications	4
Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses	4
Modeling the Role of Contour Integration in Visual Inference	4
Model Based or Model Free? Comparing Adaptive Methods for Estimating Thresholds in Neuroscience	4
A Mean Field to Capture Asynchronous Irregular Dynamics of Conductance-Based Networks of Adaptive Quadratic Integrate-and-Fire Neuron Models	4
Realizing Synthetic Active Inference Agents, Part II: Variational Message Updates	4
Principal Component Analysis for Gaussian Process Posteriors	4
Progressive Interpretation Synthesis: Interpreting Task Solving by Quantifying Previously Used and Unused Information	4
Direction Matters: On Influence-Preserving Graph Summarization and Max-Cut Principle for Directed Graphs	4
Gradual Domain Adaptation via Normalizing Flows	4
Lifelong Classification in Open World With Limited Storage Requirements	4
Object-Centric Scene Representations Using Active Inference	4
Single Circuit in V1 Capable of Switching Contexts During Movement Using an Inhibitory Population as a Switch	4
A Double-Layer Multi-Resolution Classification Model for Decoding Spatiotemporal Patterns of Spikes With Small Sample Size	4
Heterogeneity in Neuronal Dynamics Is Learned by Gradient Descent for Temporal Processing Tasks	3
Learning and Inference in Sparse Coding Models With Langevin Dynamics	3
Role of Interaction Delays in the Synchronization of Inhibitory Networks	3
Latent Space Bayesian Optimization With Latent Data Augmentation for Enhanced Exploration	3
A Model of Semantic Completion in Generative Episodic Memory	3
Statistical Properties of Color Matching Functions	3
Bridging the Functional and Wiring Properties of V1 Neurons Through Sparse Coding	3
Self-Organization of Nonlinearly Coupled Neural Fluctuations Into Synergistic Population Codes	3
Hypothesis Test and Confidence Analysis With Wasserstein Distance on General Dimension	3
An Overview of the Free Energy Principle and Related Research	3
Predictive Coding as a Neuromorphic Alternative to Backpropagation: A Critical Evaluation	3
A General, Noise-Driven Mechanism for the 1/f-Like Behavior of Neural Field Spectra	3
Top-Down Priors Disambiguate Target and Distractor Features in Simulated Covert Visual Search	3
Electrical Signaling Beyond Neurons	3
Learning in Associative Networks Through Pavlovian Dynamics	3
Deeply Felt Affect: The Emergence of Valence in Deep Active Inference	3
Direct Discriminative Decoder Models for Analysis of High-Dimensional Dynamical Neural Data	3
Gauge-Optimal Approximate Learning for Small Data Classification	3
Bioplausible Unsupervised Delay Learning for Extracting Spatiotemporal Features in Spiking Neural Networks	3
Understanding the Computational Demands Underlying Visual Reasoning	3
Active Inference and Reinforcement Learning: A Unified Inference on Continuous State and Action Spaces Under Partial Observability	3
Using Global t-SNE to Preserve Intercluster Data Structure	3
Toward Network Intelligence	3
Erratum to “A Mean-Field Description of Bursting Dynamics in Spiking Neural Networks with Short-Term Adaptation” by Richard Gast, Helmut Schmidt, and Thomas R.	3
Modern Artificial Neural Networks: Is Evolution Cleverer?	3
Unsupervised Discovery, Control, and Disentanglement of Semantic Attributes With Applications to Anomaly Detection	2
Exploring Trade-Offs in Spiking Neural Networks	2
Grid Cell Percolation	2
Might a Single Neuron Solve Interesting Machine Learning Problems Through Successive Computations on Its Dendritic Tree?	2
A Correspondence Between Normalization Strategies in Artificial and Biological Neural Networks	2
Dynamic Spatiotemporal Pattern Recognition with Recurrent Spiking Neural Network	2
Modeling the Ventral and Dorsal Cortical Visual Pathways Using Artificial Neural Networks	2
Detecting Scene-Plausible Perceptible Backdoors in Trained DNNs Without Access to the Training Set	2
Column Row Convolutional Neural Network: Reducing Parameters for Efficient Image Processing	2
X-DC: Explainable Deep Clustering Based on Learnable Spectrogram Templates	2
Reinforcement Learning in Sparse-Reward Environments With Hindsight Policy Gradients	2
Frequency Selectivity of Neural Circuits With Heterogeneous Discrete Transmission Delays	2
Identifying and Localizing Multiple Objects Using Artificial Ventral and Dorsal Cortical Visual Pathways	2
Beyond Backpropagation: Bilevel Optimization Through Implicit Differentiation and Equilibrium Propagation	2
Statistical Analysis of Decoding Performances of Diverse Populations of Neurons	2
Composite Optimization Algorithms for Sigmoid Networks	2
Research on Imbalanced Data Classification Based on Classroom-Like Generative Adversarial Networks	2
How to Represent Part-Whole Hierarchies in a Neural Network	2
Hierarchical Dynamical Model for Multiple Cortical Neural Decoding	2
Pulse Shape and Voltage-Dependent Synchronization in Spiking Neuron Networks	2
Training a Hyperdimensional Computing Classifier Using a Threshold on Its Confidence	2
Frequency Propagation: Multimechanism Learning in Nonlinear Physical Networks	2
Trainable Reference Spikes Improve Temporal Information Processing of SNNs With Supervised Learning	2
Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks	2
Task-Agnostic Continual Learning Using Online Variational Bayes with Fixed-Point Updates	2
Asymmetric Weights and Retrieval Practice in an Autoassociative Neural Network Model of Paired-Associate Learning	2
Capacity Limitations of Visual Search in Deep Convolutional Neural Networks	2
Desiderata for Normative Models of Synaptic Plasticity	2
Understanding Memories of the Past in the Context of Different Complex Neural Network Architectures	2
Parameter Identification Problem in the Hodgkin-Huxley Model	2
Asymptotic Input-Output Relationship Predicts Electric Field Effect on Sublinear Dendritic Integration of AMPA Synapses	2
Temporal Variabilities Provide Additional Category-Related Information in Object Category Decoding: A Systematic Comparison of Informative EEG Features	2
Analysis of EEG Data Using Complex Geometric Structurization	2
Large-Scale Algorithmic Search Identifies Stiff and Sloppy Dimensions in Synaptic Architectures Consistent With Murine Neocortical Wiring	2
Optimal Quadratic Binding for Relational Reasoning in Vector Symbolic Neural Architectures	2
Data Efficiency, Dimensionality Reduction, and the Generalized Symmetric Information Bottleneck	2
Inference of Multiplicative Factors Underlying Neural Variability in Calcium Imaging Data	2
Predicting the Future With a Scale-Invariant Temporal Memory for the Past	2

Inference and Learning for Generative Capsule Models	2
Scalable Variational Inference for Low-Rank Spatiotemporal Receptive Fields	1
Adaptive Filter Model of Cerebellum for Biological Muscle Control With Spike Train Inputs	1
Energy Complexity of Convolutional Neural Networks	1
Skip-Connected Self-Recurrent Spiking Neural Networks With Joint Intrinsic Parameter and Synaptic Weight Training	1
Transfer Learning With Singular Value Decomposition of Multichannel Convolution Matrices	1
Emergence of Universal Computations Through Neural Manifold Dynamics	1
A Tutorial on the Spectral Theory of Markov Chains	1
Spatial Attention Enhances Crowded Stimulus Encoding Across Modeled Receptive Fields by Increasing Redundancy of Feature Representations	1
Evidence for Multiscale Multiplexed Representation of Visual Features in EEG	1
How Does the Inner Retinal Network Shape the Ganglion Cells Receptive Field? A Computational Study	1
Multilinear Common Component Analysis via Kronecker Product Representation	1
Optimization and Learning With Randomly Compressed Gradient Updates	1
Selective Inference for Change Point Detection by Recurrent Neural Network	1
Computing With Residue Numbers in High-Dimensional Representation	1
The Effect of Class Imbalance on Precision-Recall Curves	1
Semisupervised Ordinal Regression Based on Empirical Risk Minimization	1
Realizing Active Inference in Variational Message Passing: The Outcome-Blind Certainty Seeker	1
Advancements in Algorithms and Neuromorphic Hardware for Spiking Neural Networks	1
Bridging the Gap Between Neurons and Cognition Through Assemblies of Neurons	1
A Multimodal Fitting Approach to Construct Single-Neuron Models With Patch Clamp and High-Density Microelectrode Arrays	1
Sophisticated Inference	1
A Predictive Processing Model of Episodic Memory and Time Perception	1
Spontaneous Emergence of Robustness to Light Variation in CNNs With a Precortically Inspired Module	1
eSPA+: Scalable Entropy-Optimal Machine Learning Classification for Small Data Problems	1
Randomized Self-Organizing Map	1
Associative Learning and Active Inference	1
Bayesian Quadrature Optimization for Probability Threshold Robustness Measure	1
Posterior Covariance Information Criterion for Weighted Inference	1
Predictive Representations: Building Blocks of Intelligence	1
The Perils of Being Unhinged: On the Accuracy of Classifiers Minimizing a Noise-Robust Convex Loss	1
Noise Robust Projection Rule for Klein Hopfield Neural Networks	1
Adaptive Learning Neural Network Method for Solving Time–Fractional Diffusion Equations	1
Completion of the Infeasible Actions of Others: Goal Inference by Dynamical Invariant	1
Implicit Contact Dynamics Modeling With Explicit Inertia Matrix Representation for Real-Time, Model-Based Control in Physical Environment	1
Vector Symbolic Finite State Machines in Attractor Neural Networks	1
Extended Poisson Gaussian-Process Latent Variable Model for Unsupervised Neural Decoding	1
Differential Dopamine Receptor-Dependent Sensitivity Improves the Switch Between Hard and Soft Selection in a Model of the Basal Ganglia	1
Active Classification With Uncertainty Comparison Queries	1
Positive Competitive Networks for Sparse Reconstruction	1
Enhanced Signal Detection by Adaptive Decorrelation of Interspike Intervals	1
Invariance, Encodings, and Generalization: Learning Identity Effects With Neural Networks	1
Macroscopic Gamma Oscillation With Bursting Neuron Model Under Stochastic Fluctuation	1
Disentangled Representation Learning and Generation With Manifold Optimization	1
Computation With Sequences of Assemblies in a Model of the Brain	1
Neural Information Processing and Computations of Two-Input Synapses	1
Probing the Structure and Functional Properties of the Dropout-Induced Correlated Variability in Convolutional Neural Networks	1
Dense Sample Deep Learning	1
Neural Networks with Disabilities: An Introduction to Complementary Artificial Intelligence	1
Prototype Analysis in Hopfield Networks With Hebbian Learning	1
On the Achievability of Blind Source Separation for High-Dimensional Nonlinear Source Mixtures	1
Asymmetric Complexity in a Pupil Control Model With Laterally Imbalanced Neural Activity in the Locus Coeruleus: A Potential Biomarker for Attention-Deficit/Hyperactivity Disorder	1
The Determining Role of Covariances in Large Networks of Stochastic Neurons	1
Astrocytes Learn to Detect and Signal Deviations From Critical Brain Dynamics	1
Tracking Fast and Slow Changes in Synaptic Weights from Simultaneously Observed Pre- and Postsynaptic Spiking	1
TARA: Training and Representation Alteration for AI Fairness and Domain Generalization	1
Replay in Deep Learning: Current Approaches and Missing Biological Elements	1