OOIR: Observatory of International Research

Papers

(The median citation count of Neural Computation is 2. 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 2022-06-01 to 2026-06-01.)

Article	Citations
Conductance-Based Phenomenological Nonspiking Model: A Dimensionless and Simple Model That Reliably Predicts the Effects of Conductance Variations on Nonspiking Neuronal Dynamics	122
Sensitivity of Sparse Codes to Image Distortions	70
Optimizing Attention and Cognitive Control Costs Using Temporally Layered Architectures	35
Bounded Rational Decision Networks With Belief Propagation	32
On Suspicious Coincidences and Pointwise Mutual Information	31
Mean-Field Approximations With Adaptive Coupling for Networks With Spike-Timing-Dependent Plasticity	27
Perceptual Processes as Charting Operators	26
Top-Down Priors Disambiguate Target and Distractor Features in Simulated Covert Visual Search	24
Generalized Low-Rank Update: Model Parameter Bounds for Low-Rank Training Data Modifications	24
A Model of Semantic Completion in Generative Episodic Memory	23
Permitted Sets and Convex Coding in Nonthreshold Linear Networks	23
Self-Organization of Nonlinearly Coupled Neural Fluctuations Into Synergistic Population Codes	20
Synergistic Pathways of Modulation Enable Robust Task Packing Within Neural Dynamics	20
Inhibitory Feedback Enables Predictive Learning of Multiple Sequences in Neural Networks	19
Implicit Generative Modeling by Kernel Similarity Matching	17
Adaptive Filter Model of Cerebellum for Biological Muscle Control With Spike Train Inputs	17
Toward Generalized Entropic Sparsification for Convolutional Neural Networks	17
Extended Poisson Gaussian-Process Latent Variable Model for Unsupervised Neural Decoding	16
Reframing the Expected Free Energy: Four Formulations and a Unification	15
Object Detection, Recognition, Deep Learning, and the Universal Law of Generalization	15
Similarity Matching Networks: Hebbian Learning and Convergence Over Multiple Timescales	14
Learning Fixed Points of Recurrent Neural Networks by Reparameterizing the Network Model	14
UAdam: Unified Adam-Type Algorithmic Framework for Nonconvex Optimization	13
Estimating Phase From Observed Trajectories Using the Temporal 1-Form	13
On the Search for Data-Driven and Reproducible Schizophrenia Subtypes Using Resting State fMRI Data From Multiple Sites	12

Reduced-Dimension, Biophysical Neuron Models Constructed From Observed Data	11
Learning Only on Boundaries: A Physics-Informed Neural Operator for Solving Parametric Partial Differential Equations in Complex Geometries	11
CA3 Circuit Model Compressing Sequential Information in Theta Oscillation and Replay	11
Active Learning for Discrete Latent Variable Models	11
Advantages of Persistent Cohomology in Estimating Animal Location From Grid Cell Population Activity	11
Maximal Memory Capacity Near the Edge of Chaos in Balanced Cortical E-I Networks	10
Generalization Guarantees of Gradient Descent for Shallow Neural Networks	10
Quantifying and Maximizing the Information Flux in Recurrent Neural Networks	10
Echoes of the Past: A Unified Perspective on Fading Memory and Echo States	10
Encoding of Numerosity With Robustness to Object and Scene Identity in Biologically Inspired Object Recognition Networks	9
Attention in a Family of Boltzmann Machines Emerging From Modern Hopfield Networks	9
Decision Threshold Learning in the Basal Ganglia for Multiple Alternatives	9
The Limiting Dynamics of SGD: Modified Loss, Phase-Space Oscillations, and Anomalous Diffusion	9
Differential Geometry Methods for Constructing Manifold-Targeted Recurrent Neural Networks	9
Multimodal and Multifactor Branching Time Active Inference	9
Electrical Signaling Beyond Neurons	8
Learning in Associative Networks Through Pavlovian Dynamics	8
Deconstructing Deep Active Inference: A Contrarian Information Gatherer	8
A Mean Field to Capture Asynchronous Irregular Dynamics of Conductance-Based Networks of Adaptive Quadratic Integrate-and-Fire Neuron Models	8
Deep Nonnegative Matrix Factorization With Beta Divergences	8
Comparing Dynamical Models Through Diffeomorphic Vector Field Alignment	8
Bioplausible Unsupervised Delay Learning for Extracting Spatiotemporal Features in Spiking Neural Networks	8
Neuromorphic Engineering: In Memory of Misha Mahowald	8
Computation With Sequences of Assemblies in a Model of the Brain	7
Probing the Structure and Functional Properties of the Dropout-Induced Correlated Variability in Convolutional Neural Networks	7
Using Global t-SNE to Preserve Intercluster Data Structure	7
Prototype Analysis in Hopfield Networks With Hebbian Learning	7
How Does the Inner Retinal Network Shape the Ganglion Cells Receptive Field? A Computational Study	7
Toward Network Intelligence	7
Desiderata for Normative Models of Synaptic Plasticity	7
Mechanism of Duration Perception in Artificial Brains Suggests New Model of Attentional Entrainment	6
Memoryless Optimality: Neurons Do Not Need Adaptation to Optimally Encode Stimuli With Arbitrarily Complex Statistics	6
Sequential Learning in the Dense Associative Memory	6
Promoting the Shift From Pixel-Level Correlations to Object Semantics Learning by Rethinking Computer Vision Benchmark Data Sets	6
Positive Competitive Networks for Sparse Reconstruction	6
Working Memory and Self-Directed Inner Speech Enhance Multitask Generalization in Active Inference	6
Generalization Analysis of Transformers in Distribution Regression	6
Visuomotor Mismatch Responses as a Hallmark of Explaining Away in Causal Inference	6
Astrocytes Learn to Detect and Signal Deviations From Critical Brain Dynamics	6
Disentangled Representation Learning and Generation With Manifold Optimization	6
Is Learning in Biological Neural Networks Based on Stochastic Gradient Descent? An Analysis Using Stochastic Processes	6
Active Inference and Intentional Behavior	6
Boosting MCTS With Free Energy Minimization	5
Toward a Free-Response Paradigm of Decision Making in Spiking Neural Networks	5
Multiclass Linear Perceptrons With Multiplicative Margins	5
Distributed Synaptic Connection Strength Changes Dynamics in a Population Firing Rate Model in Response to Continuous External Stimuli	5
Synaptic Information Storage Capacity Measured With Information Theory	5
Spiking Neuron-Astrocyte Networks for Image Recognition	5
Fast Multigroup Gaussian Process Factor Models	5
Reducing Catastrophic Forgetting With Associative Learning: A Lesson From Fruit Flies	5

Toward a Biomimetic Neural Circuit Model of Sensory-Motor Processing	5
Strong Allee Effect Synaptic Plasticity Rule in an Unsupervised Learning Environment	5
A Generalized Time Rescaling Theorem for Temporal Point Processes	4
Infinite Horizon Control With Nonlinear Dynamics Models Reproduces Temporal Modulation of Reaching Movements	4
Learning in Wilson-Cowan Model for Metapopulation	4
Context-Sensitive Processing in a Model Neocortical Pyramidal Cell With Two Sites of Input Integration	4
Linear Codes for Hyperdimensional Computing	4
Gauge-Optimal Approximate Learning for Small Data Classification	4
A Survey on Artificial Neural Networks in Human—Robot Interaction	4
An Overview of the Free Energy Principle and Related Research	4
Neuromodulators Generate Multiple Context-Relevant Behaviors in Recurrent Neural Networks	4
Sum-of-Norms Regularized Nonnegative Matrix Factorization	4
Simulated Complex Cells Contribute to Object Recognition Through Representational Untangling	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
Uncovering Dynamical Equations of Stochastic Decision Models Using Data-Driven SINDy Algorithm	4
Cocaine Use Prediction With Tensor-Based Machine Learning on Multimodal MRI Connectome Data	3
Excitation–Inhibition Balance Controls Synchronization in a Simple Model of Coupled Phase Oscillators	3
Trainable Reference Spikes Improve Temporal Information Processing of SNNs With Supervised Learning	3
Beyond Backpropagation: Bilevel Optimization Through Implicit Differentiation and Equilibrium Propagation	3
Possible Principles for Aligned Structure Learning Agents	3
Nearly Optimal Learning Using Sparse Deep ReLU Networks in Regularized Empirical Risk Minimization With Lipschitz Loss	3
Approximation Rates in Fréchet Metrics: Barron Spaces, Paley-Wiener Spaces, and Fourier Multipliers	3
A Predictive Processing Model of Episodic Memory and Time Perception	3
Macroscopic Gamma Oscillation With Bursting Neuron Model Under Stochastic Fluctuation	3
Column Row Convolutional Neural Network: Reducing Parameters for Efficient Image Processing	3
Firing Rate Models as Associative Memory: Synaptic Design for Robust Retrieval	3
Emergence of Universal Computations Through Neural Manifold Dynamics	3
Multilevel Data Representation for Training Deep Helmholtz Machines	3
A Neural Model for Insect Steering Applied to Olfaction and Path Integration	3
Selective Inference for Change Point Detection by Recurrent Neural Network	3
Automatic Hyperparameter Tuning in Sparse Matrix Factorization	3
On the Compressive Power of Autoencoders With Linear and ReLU Activation Functions	3
Evidence for Multiscale Multiplexed Representation of Visual Features in EEG	3
Posterior Covariance Information Criterion for Weighted Inference	3
Neural Information Processing and Computations of Two-Input Synapses	3
Generalization Analysis of Pairwise Learning for Ranking With Deep Neural Networks	3
Human Eyes–Inspired Recurrent Neural Networks Are More Robust Against Adversarial Noises	3
Multistream-Based Marked Point Process With Decomposed Cumulative Hazard Functions	3
Vector Symbolic Finite State Machines in Attractor Neural Networks	3
Recurrent Neural-Linear Posterior Sampling for Nonstationary Contextual Bandits	2
Winning the Lottery With Neural Connectivity Constraints: Faster Learning Across Cognitive Tasks With Spatially Constrained Sparse RNNs	2
Sparse-Coding Variational Autoencoders	2
Formal Verification of Deep Brain Stimulation Controllers for Parkinson's Disease Treatment	2
Knowledge as a Breaking of Ergodicity	2
Measuring Stimulus Information Transfer Between Neural Populations Through the Communication Subspace	2
Modeling the Role of Contour Integration in Visual Inference	2
Rapid Reweighting of Sensory Inputs and Predictions in Visual Perception	2
Relating Human Error–Based Learning to Modern Deep RL Algorithms	2
A Fast Algorithm for the Real-Valued Combinatorial Pure Exploration of the Multi-Armed Bandit	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. 1	2
Inferring Mechanisms of Auditory Attentional Modulation with Deep Neural Networks	2
Transformer Models for Signal Processing: Scaled Dot-Product Attention Implements Constrained Filtering	2
Mirror Descent of Hopfield Model	2
Predictive Coding Model Detects Novelty on Different Levels of Representation Hierarchy	2
An FPGA Accelerator for High-Speed Moving Objects Detection and Tracking With a Spike Camera	2
Toward Enhancing RMSProp With Forward-Looking Gradient Updates for Complex Loss Landscapes	2
A Categorical Framework for Quantifying Emergent Effects in Network Topology	2
Efficient Decoding of Compositional Structure in Holistic Representations	2
Learning and Inference in Sparse Coding Models With Langevin Dynamics	2
Gradual Domain Adaptation via Normalizing Flows	2
Gaussian Process Koopman Mode Decomposition	2
Large Language Models and the Reverse Turing Test	2
Learning Internal Representations of 3D Transformations From 2D Projected Inputs	2
The Leaky Integrate-and-Fire Neuron Is a Change-Point Detector for Compound Poisson Processes	2
Effective Learning Rules as Natural Gradient Descent	2
Adding Space to Random Networks of Spiking Neurons: A Method Based on Scaling the Network Size	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
Manifold Gaussian Variational Bayes on the Precision Matrix	2
Latent Space Bayesian Optimization With Latent Data Augmentation for Enhanced Exploration	2
Dynamics and Bifurcation Structure of a Mean-Field Model of Adaptive Exponential Integrate-and-Fire Networks	2
Distance-Based Logistic Matrix Factorization	2
ReBaCCA-ss: Relevance-Balanced Continuum Correlation Analysis With Smoothing and Surrogating for Quantifying Similarity Between Population Spiking Activities	2
Learning With Proper Partial Labels	2
A Generalized Framework of Multifidelity Max-Value Entropy Search Through Joint Entropy	2
Intrinsic Rewards for Exploration Without Harm From Observational Noise: A Simulation Study Based on the Free Energy Principle	2
Lateral Connections Improve Generalizability of Learning in a Simple Neural Network	2