Neural Computation

Papers
(The TQCC of Neural Computation is 4. 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 2022-08-01 to 2026-08-01.)
ArticleCitations
Conductance-Based Phenomenological Nonspiking Model: A Dimensionless and Simple Model That Reliably Predicts the Effects of Conductance Variations on Nonspiking Neuronal Dynamics125
Optimizing Attention and Cognitive Control Costs Using Temporally Layered Architectures73
Bounded Rational Decision Networks With Belief Propagation38
Mean-Field Approximations With Adaptive Coupling for Networks With Spike-Timing-Dependent Plasticity31
Perceptual Processes as Charting Operators27
On Suspicious Coincidences and Pointwise Mutual Information26
Generalized Low-Rank Update: Model Parameter Bounds for Low-Rank Training Data Modifications25
Permitted Sets and Convex Coding in Nonthreshold Linear Networks24
Top-Down Priors Disambiguate Target and Distractor Features in Simulated Covert Visual Search24
A Model of Semantic Completion in Generative Episodic Memory22
Self-Organization of Nonlinearly Coupled Neural Fluctuations Into Synergistic Population Codes20
Synergistic Pathways of Modulation Enable Robust Task Packing Within Neural Dynamics19
Implicit Generative Modeling by Kernel Similarity Matching18
Inhibitory Feedback Enables Predictive Learning of Multiple Sequences in Neural Networks18
Adaptive Filter Model of Cerebellum for Biological Muscle Control With Spike Train Inputs17
Toward Generalized Entropic Sparsification for Convolutional Neural Networks17
Neuronal Spike Trains as Functional-Analytic Distributions: Representation, Analysis, and Significance17
Object Detection, Recognition, Deep Learning, and the Universal Law of Generalization16
Similarity Matching Networks: Hebbian Learning and Convergence Over Multiple Timescales16
Reframing the Expected Free Energy: Four Formulations and a Unification15
Extended Poisson Gaussian-Process Latent Variable Model for Unsupervised Neural Decoding14
On the Search for Data-Driven and Reproducible Schizophrenia Subtypes Using Resting State fMRI Data From Multiple Sites13
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
Estimating Phase From Observed Trajectories Using the Temporal 1-Form13
Active Learning for Discrete Latent Variable Models13
UAdam: Unified Adam-Type Algorithmic Framework for Nonconvex Optimization12
Echoes of the Past: A Unified Perspective on Fading Memory and Echo States12
CA3 Circuit Model Compressing Sequential Information in Theta Oscillation and Replay12
Learning Only on Boundaries: A Physics-Informed Neural Operator for Solving Parametric Partial Differential Equations in Complex Geometries11
Encoding of Numerosity With Robustness to Object and Scene Identity in Biologically Inspired Object Recognition Networks10
The Limiting Dynamics of SGD: Modified Loss, Phase-Space Oscillations, and Anomalous Diffusion10
Generalization Guarantees of Gradient Descent for Shallow Neural Networks10
Maximal Memory Capacity Near the Edge of Chaos in Balanced Cortical E-I Networks10
Multimodal and Multifactor Branching Time Active Inference10
Quantifying and Maximizing the Information Flux in Recurrent Neural Networks10
Decision Threshold Learning in the Basal Ganglia for Multiple Alternatives10
Attention in a Family of Boltzmann Machines Emerging From Modern Hopfield Networks9
Deep Nonnegative Matrix Factorization With Beta Divergences9
Deconstructing Deep Active Inference: A Contrarian Information Gatherer8
A Mean Field to Capture Asynchronous Irregular Dynamics of Conductance-Based Networks of Adaptive Quadratic Integrate-and-Fire Neuron Models8
Learning in Associative Networks Through Pavlovian Dynamics8
Comparing Dynamical Models Through Diffeomorphic Vector Field Alignment8
Neuromorphic Engineering: In Memory of Misha Mahowald8
Electrical Signaling Beyond Neurons8
Toward Network Intelligence7
How Does the Inner Retinal Network Shape the Ganglion Cells Receptive Field? A Computational Study7
Positive Competitive Networks for Sparse Reconstruction7
Working Memory and Self-Directed Inner Speech Enhance Multitask Generalization in Active Inference7
Computation With Sequences of Assemblies in a Model of the Brain7
Desiderata for Normative Models of Synaptic Plasticity7
Astrocytes Learn to Detect and Signal Deviations From Critical Brain Dynamics7
Prototype Analysis in Hopfield Networks With Hebbian Learning7
Bioplausible Unsupervised Delay Learning for Extracting Spatiotemporal Features in Spiking Neural Networks7
Probing the Structure and Functional Properties of the Dropout-Induced Correlated Variability in Convolutional Neural Networks7
Hierarchical Active Inference Using Successor Representations7
Mechanism of Duration Perception in Artificial Brains Suggests New Model of Attentional Entrainment7
Memoryless Optimality: Neurons Do Not Need Adaptation to Optimally Encode Stimuli With Arbitrarily Complex Statistics6
Active Inference and Intentional Behavior6
Is Learning in Biological Neural Networks Based on Stochastic Gradient Descent? An Analysis Using Stochastic Processes6
Disentangled Representation Learning and Generation With Manifold Optimization6
Visuomotor Mismatch Responses as a Hallmark of Explaining Away in Causal Inference6
Generalization Analysis of Transformers in Distribution Regression6
Sequential Learning in the Dense Associative Memory6
Promoting the Shift From Pixel-Level Correlations to Object Semantics Learning by Rethinking Computer Vision Benchmark Data Sets5
Strong Allee Effect Synaptic Plasticity Rule in an Unsupervised Learning Environment5
Multiclass Linear Perceptrons With Multiplicative Margins5
Distributed Synaptic Connection Strength Changes Dynamics in a Population Firing Rate Model in Response to Continuous External Stimuli5
Spiking Neuron-Astrocyte Networks for Image Recognition5
Fast Multigroup Gaussian Process Factor Models5
Toward a Biomimetic Neural Circuit Model of Sensory-Motor Processing4
Boosting MCTS With Free Energy Minimization4
Linear Codes for Hyperdimensional Computing4
A Survey on Artificial Neural Networks in Human—Robot Interaction4
Predictive Coding as a Neuromorphic Alternative to Backpropagation: A Critical Evaluation4
Toward a Computational Phenomenology of Meditative Deconstruction: “Letting Go” and the Deconstruction of Experience With Active Inference4
Sum-of-Norms Regularized Nonnegative Matrix Factorization4
Uncovering Dynamical Equations of Stochastic Decision Models Using Data-Driven SINDy Algorithm4
A Hidden Markov Model–Inspired Sequence Classification Method for Hyperdimensional Computing4
Learning in Wilson-Cowan Model for Metapopulation4
Gauge-Optimal Approximate Learning for Small Data Classification4
Infinite Horizon Control With Nonlinear Dynamics Models Reproduces Temporal Modulation of Reaching Movements4
Cooperativity, Information Gain, and Energy Cost During Early LTP in Dendritic Spines4
DROP: Distributional and Regular Optimism and Pessimism for Reinforcement Learning4
Synaptic Information Storage Capacity Measured With Information Theory4
Toward a Free-Response Paradigm of Decision Making in Spiking Neural Networks4
Simulated Complex Cells Contribute to Object Recognition Through Representational Untangling4
An Overview of the Free Energy Principle and Related Research4
Neuromodulators Generate Multiple Context-Relevant Behaviors in Recurrent Neural Networks4
A Generalized Time Rescaling Theorem for Temporal Point Processes4
Reducing Catastrophic Forgetting With Associative Learning: A Lesson From Fruit Flies4
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