Neural Computation

Papers
(The TQCC of Neural Computation is 5. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-08-01 to 2025-08-01.)
ArticleCitations
Conductance-Based Phenomenological Nonspiking Model: A Dimensionless and Simple Model That Reliably Predicts the Effects of Conductance Variations on Nonspiking Neuronal Dynamics103
Sensitivity of Sparse Codes to Image Distortions88
Optimizing Attention and Cognitive Control Costs Using Temporally Layered Architectures55
Mean-Field Approximations With Adaptive Coupling for Networks With Spike-Timing-Dependent Plasticity53
Bounded Rational Decision Networks With Belief Propagation49
On Suspicious Coincidences and Pointwise Mutual Information31
Generalized Low-Rank Update: Model Parameter Bounds for Low-Rank Training Data Modifications30
Permitted Sets and Convex Coding in Nonthreshold Linear Networks28
Self-Organization of Nonlinearly Coupled Neural Fluctuations Into Synergistic Population Codes28
Understanding the Computational Demands Underlying Visual Reasoning25
Top-Down Priors Disambiguate Target and Distractor Features in Simulated Covert Visual Search22
A Model of Semantic Completion in Generative Episodic Memory21
Bridging the Functional and Wiring Properties of V1 Neurons Through Sparse Coding20
Modeling the Ventral and Dorsal Cortical Visual Pathways Using Artificial Neural Networks18
Asymmetric Weights and Retrieval Practice in an Autoassociative Neural Network Model of Paired-Associate Learning18
Task-Agnostic Continual Learning Using Online Variational Bayes with Fixed-Point Updates17
Synergistic Pathways of Modulation Enable Robust Task Packing Within Neural Dynamics17
Adaptive Filter Model of Cerebellum for Biological Muscle Control With Spike Train Inputs16
Realizing Active Inference in Variational Message Passing: The Outcome-Blind Certainty Seeker16
Toward Generalized Entropic Sparsification for Convolutional Neural Networks15
Extended Poisson Gaussian-Process Latent Variable Model for Unsupervised Neural Decoding15
Understanding Dynamics of Nonlinear Representation Learning and Its Application14
CA3 Circuit Model Compressing Sequential Information in Theta Oscillation and Replay14
Learning Fixed Points of Recurrent Neural Networks by Reparameterizing the Network Model13
Advantages of Persistent Cohomology in Estimating Animal Location From Grid Cell Population Activity13
Reduced-Dimension, Biophysical Neuron Models Constructed From Observed Data13
On the Search for Data-Driven and Reproducible Schizophrenia Subtypes Using Resting State fMRI Data From Multiple Sites13
Least kth-Order and Rényi Generative Adversarial Networks13
Learning Only on Boundaries: A Physics-Informed Neural Operator for Solving Parametric Partial Differential Equations in Complex Geometries12
Quantifying and Maximizing the Information Flux in Recurrent Neural Networks12
UAdam: Unified Adam-Type Algorithmic Framework for Nonconvex Optimization12
Expansion of Information in the Binary Autoencoder with Random Binary Weights12
Active Learning for Discrete Latent Variable Models12
Maximal Memory Capacity Near the Edge of Chaos in Balanced Cortical E-I Networks11
Generalization Guarantees of Gradient Descent for Shallow Neural Networks11
Multimodal and Multifactor Branching Time Active Inference10
Decoding Pixel-Level Image Features From Two-Photon Calcium Signals of Macaque Visual Cortex10
Deconstructing Deep Active Inference: A Contrarian Information Gatherer10
Deep Nonnegative Matrix Factorization With Beta Divergences10
Differential Geometry Methods for Constructing Manifold-Targeted Recurrent Neural Networks9
Attention in a Family of Boltzmann Machines Emerging From Modern Hopfield Networks9
Neuromorphic Engineering: In Memory of Misha Mahowald9
The Limiting Dynamics of SGD: Modified Loss, Phase-Space Oscillations, and Anomalous Diffusion9
Decision Threshold Learning in the Basal Ganglia for Multiple Alternatives9
Learning in Associative Networks Through Pavlovian Dynamics8
Electrical Signaling Beyond Neurons8
Bioplausible Unsupervised Delay Learning for Extracting Spatiotemporal Features in Spiking Neural Networks8
A Mean Field to Capture Asynchronous Irregular Dynamics of Conductance-Based Networks of Adaptive Quadratic Integrate-and-Fire Neuron Models8
Model Based or Model Free? Comparing Adaptive Methods for Estimating Thresholds in Neuroscience8
Hypothesis Test and Confidence Analysis With Wasserstein Distance on General Dimension8
Using Global t-SNE to Preserve Intercluster Data Structure7
Toward Network Intelligence7
Desiderata for Normative Models of Synaptic Plasticity7
Prototype Analysis in Hopfield Networks With Hebbian Learning7
Statistical Properties of Color Matching Functions7
How Does the Inner Retinal Network Shape the Ganglion Cells Receptive Field? A Computational Study7
Probing the Structure and Functional Properties of the Dropout-Induced Correlated Variability in Convolutional Neural Networks7
Temporal Variabilities Provide Additional Category-Related Information in Object Category Decoding: A Systematic Comparison of Informative EEG Features7
eSPA+: Scalable Entropy-Optimal Machine Learning Classification for Small Data Problems7
Implicit Contact Dynamics Modeling With Explicit Inertia Matrix Representation for Real-Time, Model-Based Control in Physical Environment6
Positive Competitive Networks for Sparse Reconstruction6
Neural Circuits for Dynamics-Based Segmentation of Time Series6
Memoryless Optimality: Neurons Do Not Need Adaptation to Optimally Encode Stimuli With Arbitrarily Complex Statistics6
Computation With Sequences of Assemblies in a Model of the Brain6
Astrocytes Learn to Detect and Signal Deviations From Critical Brain Dynamics6
Mechanism of Duration Perception in Artificial Brains Suggests New Model of Attentional Entrainment6
Is Learning in Biological Neural Networks Based on Stochastic Gradient Descent? An Analysis Using Stochastic Processes6
Semisupervised Ordinal Regression Based on Empirical Risk Minimization6
Bayesian Quadrature Optimization for Probability Threshold Robustness Measure6
A Normative Account of Confirmation Bias During Reinforcement Learning6
Generalization Analysis of Transformers in Distribution Regression6
Disentangled Representation Learning and Generation With Manifold Optimization6
Visuomotor Mismatch Responses as a Hallmark of Explaining Away in Causal Inference5
Flexible Transmitter Network5
Chance-Constrained Active Inference5
Distributed Phase Oscillatory Excitation Efficiently Produces Attractors Using Spike-Timing-Dependent Plasticity5
Spiking Neuron-Astrocyte Networks for Image Recognition5
Active Inference and Intentional Behavior5
Strong Allee Effect Synaptic Plasticity Rule in an Unsupervised Learning Environment5
Simple Convolutional-Based Models: Are They Learning the Task or the Data?5
Reducing Catastrophic Forgetting With Associative Learning: A Lesson From Fruit Flies5
Sequential Learning in the Dense Associative Memory5
Promoting the Shift From Pixel-Level Correlations to Object Semantics Learning by Rethinking Computer Vision Benchmark Data Sets5
Fast Multigroup Gaussian Process Factor Models5
Toward a Free-Response Paradigm of Decision Making in Spiking Neural Networks5
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