OOIR: Observatory of International Research

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 2021-09-01 to 2025-09-01.)

Article	Citations
Conductance-Based Phenomenological Nonspiking Model: A Dimensionless and Simple Model That Reliably Predicts the Effects of Conductance Variations on Nonspiking Neuronal Dynamics	92
Sensitivity of Sparse Codes to Image Distortions	57
Optimizing Attention and Cognitive Control Costs Using Temporally Layered Architectures	55
Mean-Field Approximations With Adaptive Coupling for Networks With Spike-Timing-Dependent Plasticity	34
On Suspicious Coincidences and Pointwise Mutual Information	30
Bounded Rational Decision Networks With Belief Propagation	30
Generalized Low-Rank Update: Model Parameter Bounds for Low-Rank Training Data Modifications	25
Self-Organization of Nonlinearly Coupled Neural Fluctuations Into Synergistic Population Codes	22
Permitted Sets and Convex Coding in Nonthreshold Linear Networks	21
Understanding the Computational Demands Underlying Visual Reasoning	20
Top-Down Priors Disambiguate Target and Distractor Features in Simulated Covert Visual Search	19
A Model of Semantic Completion in Generative Episodic Memory	18
Bridging the Functional and Wiring Properties of V1 Neurons Through Sparse Coding	18
Asymmetric Weights and Retrieval Practice in an Autoassociative Neural Network Model of Paired-Associate Learning	17
Modeling the Ventral and Dorsal Cortical Visual Pathways Using Artificial Neural Networks	17
Synergistic Pathways of Modulation Enable Robust Task Packing Within Neural Dynamics	17
Adaptive Filter Model of Cerebellum for Biological Muscle Control With Spike Train Inputs	16
Extended Poisson Gaussian-Process Latent Variable Model for Unsupervised Neural Decoding	15
Realizing Active Inference in Variational Message Passing: The Outcome-Blind Certainty Seeker	15
Toward Generalized Entropic Sparsification for Convolutional Neural Networks	14
CA3 Circuit Model Compressing Sequential Information in Theta Oscillation and Replay	14
Learning Fixed Points of Recurrent Neural Networks by Reparameterizing the Network Model	13
Advantages of Persistent Cohomology in Estimating Animal Location From Grid Cell Population Activity	13
On the Search for Data-Driven and Reproducible Schizophrenia Subtypes Using Resting State fMRI Data From Multiple Sites	13
Understanding Dynamics of Nonlinear Representation Learning and Its Application	13

Active Learning for Discrete Latent Variable Models	12
Reduced-Dimension, Biophysical Neuron Models Constructed From Observed Data	12
UAdam: Unified Adam-Type Algorithmic Framework for Nonconvex Optimization	12
Learning Only on Boundaries: A Physics-Informed Neural Operator for Solving Parametric Partial Differential Equations in Complex Geometries	12
Encoding of Numerosity With Robustness to Object and Scene Identity in Biologically Inspired Object Recognition Networks	11
Quantifying and Maximizing the Information Flux in Recurrent Neural Networks	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
Multimodal and Multifactor Branching Time Active Inference	9
Deep Nonnegative Matrix Factorization With Beta Divergences	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
Decoding Pixel-Level Image Features From Two-Photon Calcium Signals of Macaque Visual Cortex	9
Attention in a Family of Boltzmann Machines Emerging From Modern Hopfield Networks	9
Deconstructing Deep Active Inference: A Contrarian Information Gatherer	9
Neuromorphic Engineering: In Memory of Misha Mahowald	8
Bioplausible Unsupervised Delay Learning for Extracting Spatiotemporal Features in Spiking Neural Networks	8
Learning in Associative Networks Through Pavlovian Dynamics	8
Differential Geometry Methods for Constructing Manifold-Targeted Recurrent Neural Networks	8
Model Based or Model Free? Comparing Adaptive Methods for Estimating Thresholds in Neuroscience	8
Electrical Signaling Beyond Neurons	7
Hypothesis Test and Confidence Analysis With Wasserstein Distance on General Dimension	7
Computation With Sequences of Assemblies in a Model of the Brain	7
Using Global t-SNE to Preserve Intercluster Data Structure	7
Probing the Structure and Functional Properties of the Dropout-Induced Correlated Variability in Convolutional Neural Networks	7
Prototype Analysis in Hopfield Networks With Hebbian Learning	7
A Mean Field to Capture Asynchronous Irregular Dynamics of Conductance-Based Networks of Adaptive Quadratic Integrate-and-Fire Neuron Models	7
Toward Network Intelligence	7
eSPA+: Scalable Entropy-Optimal Machine Learning Classification for Small Data Problems	6
Astrocytes Learn to Detect and Signal Deviations From Critical Brain Dynamics	6
Positive Competitive Networks for Sparse Reconstruction	6
Neural Circuits for Dynamics-Based Segmentation of Time Series	6
Desiderata for Normative Models of Synaptic Plasticity	6
Implicit Contact Dynamics Modeling With Explicit Inertia Matrix Representation for Real-Time, Model-Based Control in Physical Environment	6
Disentangled Representation Learning and Generation With Manifold Optimization	6
A Normative Account of Confirmation Bias During Reinforcement Learning	6
Is Learning in Biological Neural Networks Based on Stochastic Gradient Descent? An Analysis Using Stochastic Processes	6
How Does the Inner Retinal Network Shape the Ganglion Cells Receptive Field? A Computational Study	6
Bayesian Quadrature Optimization for Probability Threshold Robustness Measure	6
Memoryless Optimality: Neurons Do Not Need Adaptation to Optimally Encode Stimuli With Arbitrarily Complex Statistics	6
Generalization Analysis of Transformers in Distribution Regression	6
Mechanism of Duration Perception in Artificial Brains Suggests New Model of Attentional Entrainment	6
Semisupervised Ordinal Regression Based on Empirical Risk Minimization	6
Active Inference and Intentional Behavior	5
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
Toward a Biomimetic Neural Circuit Model of Sensory-Motor Processing	5
Uncovering Dynamical Equations of Stochastic Decision Models Using Data-Driven SINDy Algorithm	5
Sequential Learning in the Dense Associative Memory	5
Chance-Constrained Active Inference	5

Distributed Phase Oscillatory Excitation Efficiently Produces Attractors Using Spike-Timing-Dependent Plasticity	5
Linear Codes for Hyperdimensional Computing	5
Simple Convolutional-Based Models: Are They Learning the Task or the Data?	5
Visuomotor Mismatch Responses as a Hallmark of Explaining Away in Causal Inference	5
Strong Allee Effect Synaptic Plasticity Rule in an Unsupervised Learning Environment	5
Fast Multigroup Gaussian Process Factor Models	5
Toward a Free-Response Paradigm of Decision Making in Spiking Neural Networks	5
Distributed Synaptic Connection Strength Changes Dynamics in a Population Firing Rate Model in Response to Continuous External Stimuli	5