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 2022-05-01 to 2026-05-01.)

Article	Citations
Conductance-Based Phenomenological Nonspiking Model: A Dimensionless and Simple Model That Reliably Predicts the Effects of Conductance Variations on Nonspiking Neuronal Dynamics	116
Sensitivity of Sparse Codes to Image Distortions	75
Bounded Rational Decision Networks With Belief Propagation	67
Optimizing Attention and Cognitive Control Costs Using Temporally Layered Architectures	42
On Suspicious Coincidences and Pointwise Mutual Information	35
Perceptual Processes as Charting Operators	31
Mean-Field Approximations With Adaptive Coupling for Networks With Spike-Timing-Dependent Plasticity	31
Top-Down Priors Disambiguate Target and Distractor Features in Simulated Covert Visual Search	26
Generalized Low-Rank Update: Model Parameter Bounds for Low-Rank Training Data Modifications	26
Permitted Sets and Convex Coding in Nonthreshold Linear Networks	24
A Model of Semantic Completion in Generative Episodic Memory	23
Self-Organization of Nonlinearly Coupled Neural Fluctuations Into Synergistic Population Codes	23
Synergistic Pathways of Modulation Enable Robust Task Packing Within Neural Dynamics	20
Implicit Generative Modeling by Kernel Similarity Matching	20
Inhibitory Feedback Enables Predictive Learning of Multiple Sequences in Neural Networks	19
Toward Generalized Entropic Sparsification for Convolutional Neural Networks	18
Extended Poisson Gaussian-Process Latent Variable Model for Unsupervised Neural Decoding	17
Adaptive Filter Model of Cerebellum for Biological Muscle Control With Spike Train Inputs	17
Reframing the Expected Free Energy: Four Formulations and a Unification	16
Object Detection, Recognition, Deep Learning, and the Universal Law of Generalization	16
Similarity Matching Networks: Hebbian Learning and Convergence Over Multiple Time Scales	15
Learning Fixed Points of Recurrent Neural Networks by Reparameterizing the Network Model	15
On the Search for Data-Driven and Reproducible Schizophrenia Subtypes Using Resting State fMRI Data From Multiple Sites	14
Estimating Phase From Observed Trajectories Using the Temporal 1-Form	14
Active Learning for Discrete Latent Variable Models	14

Learning Only on Boundaries: A Physics-Informed Neural Operator for Solving Parametric Partial Differential Equations in Complex Geometries	14
UAdam: Unified Adam-Type Algorithmic Framework for Nonconvex Optimization	13
Reduced-Dimension, Biophysical Neuron Models Constructed From Observed Data	12
Advantages of Persistent Cohomology in Estimating Animal Location From Grid Cell Population Activity	11
CA3 Circuit Model Compressing Sequential Information in Theta Oscillation and Replay	11
Echoes of the Past: A Unified Perspective on Fading Memory and Echo States	11
Quantifying and Maximizing the Information Flux in Recurrent Neural Networks	11
Encoding of Numerosity With Robustness to Object and Scene Identity in Biologically Inspired Object Recognition Networks	10
Multimodal and Multifactor Branching Time Active Inference	10
Decoding Pixel-Level Image Features From Two-Photon Calcium Signals of Macaque Visual Cortex	10
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
Attention in a Family of Boltzmann Machines Emerging From Modern Hopfield Networks	9
Differential Geometry Methods for Constructing Manifold-Targeted Recurrent Neural Networks	9
The Limiting Dynamics of SGD: Modified Loss, Phase-Space Oscillations, and Anomalous Diffusion	9
Deconstructing Deep Active Inference: A Contrarian Information Gatherer	9
Decision Threshold Learning in the Basal Ganglia for Multiple Alternatives	9
Neuromorphic Engineering: In Memory of Misha Mahowald	8
Comparing Dynamical Models Through Diffeomorphic Vector Field Alignment	8
Bioplausible Unsupervised Delay Learning for Extracting Spatiotemporal Features in Spiking Neural Networks	8
Learning in Associative Networks Through Pavlovian Dynamics	8
Hypothesis Test and Confidence Analysis With Wasserstein Distance on General Dimension	8
Using Global t-SNE to Preserve Intercluster Data Structure	8
Deep Nonnegative Matrix Factorization With Beta Divergences	8
Electrical Signaling Beyond Neurons	8
A Mean Field to Capture Asynchronous Irregular Dynamics of Conductance-Based Networks of Adaptive Quadratic Integrate-and-Fire Neuron Models	8
Computation With Sequences of Assemblies in a Model of the Brain	7
Astrocytes Learn to Detect and Signal Deviations From Critical Brain Dynamics	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
Prototype Analysis in Hopfield Networks With Hebbian Learning	7
Working Memory and Self-Directed Inner Speech Enhance Multitask Generalization in Active Inference	7
Probing the Structure and Functional Properties of the Dropout-Induced Correlated Variability in Convolutional Neural Networks	7
Mechanism of Duration Perception in Artificial Brains Suggests New Model of Attentional Entrainment	6
Generalization Analysis of Transformers in Distribution Regression	6
Visuomotor Mismatch Responses as a Hallmark of Explaining Away in Causal Inference	6
Disentangled Representation Learning and Generation With Manifold Optimization	6
Active Inference and Intentional Behavior	6
Is Learning in Biological Neural Networks Based on Stochastic Gradient Descent? An Analysis Using Stochastic Processes	6
Memoryless Optimality: Neurons Do Not Need Adaptation to Optimally Encode Stimuli With Arbitrarily Complex Statistics	6
Positive Competitive Networks for Sparse Reconstruction	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	5
Spiking Neuron-Astrocyte Networks for Image Recognition	5
Distributed Synaptic Connection Strength Changes Dynamics in a Population Firing Rate Model in Response to Continuous External Stimuli	5
Sum-of-Norms Regularized Nonnegative Matrix Factorization	5
Fast Multigroup Gaussian Process Factor Models	5
Strong Allee Effect Synaptic Plasticity Rule in an Unsupervised Learning Environment	5
Toward a Free-Response Paradigm of Decision Making in Spiking Neural Networks	5

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