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

Article	Citations
Conductance-Based Phenomenological Nonspiking Model: A Dimensionless and Simple Model That Reliably Predicts the Effects of Conductance Variations on Nonspiking Neuronal Dynamics	101
Sensitivity of Sparse Codes to Image Distortions	64
On Suspicious Coincidences and Pointwise Mutual Information	63
Bounded Rational Decision Networks With Belief Propagation	39
Optimizing Attention and Cognitive Control Costs Using Temporally Layered Architectures	36
Mean-Field Approximations With Adaptive Coupling for Networks With Spike-Timing-Dependent Plasticity	31
Generalized Low-Rank Update: Model Parameter Bounds for Low-Rank Training Data Modifications	28
Top-Down Priors Disambiguate Target and Distractor Features in Simulated Covert Visual Search	25
Permitted Sets and Convex Coding in Nonthreshold Linear Networks	24
Self-Organization of Nonlinearly Coupled Neural Fluctuations Into Synergistic Population Codes	23
Understanding the Computational Demands Underlying Visual Reasoning	22
Bridging the Functional and Wiring Properties of V1 Neurons Through Sparse Coding	21
A Model of Semantic Completion in Generative Episodic Memory	21
Synergistic Pathways of Modulation Enable Robust Task Packing Within Neural Dynamics	21
Modeling the Ventral and Dorsal Cortical Visual Pathways Using Artificial Neural Networks	20
Adaptive Filter Model of Cerebellum for Biological Muscle Control With Spike Train Inputs	17
Toward Generalized Entropic Sparsification for Convolutional Neural Networks	17
Reduced-Dimension, Biophysical Neuron Models Constructed From Observed Data	16
Estimating Phase From Observed Trajectories Using the Temporal 1-Form	16
Learning Only on Boundaries: A Physics-Informed Neural Operator for Solving Parametric Partial Differential Equations in Complex Geometries	16
Learning Fixed Points of Recurrent Neural Networks by Reparameterizing the Network Model	16
Extended Poisson Gaussian-Process Latent Variable Model for Unsupervised Neural Decoding	16
On the Search for Data-Driven and Reproducible Schizophrenia Subtypes Using Resting State fMRI Data From Multiple Sites	15
Active Learning for Discrete Latent Variable Models	15
Advantages of Persistent Cohomology in Estimating Animal Location From Grid Cell Population Activity	14

Understanding Dynamics of Nonlinear Representation Learning and Its Application	13
UAdam: Unified Adam-Type Algorithmic Framework for Nonconvex Optimization	13
CA3 Circuit Model Compressing Sequential Information in Theta Oscillation and Replay	13
Maximal Memory Capacity Near the Edge of Chaos in Balanced Cortical E-I Networks	12
Decoding Pixel-Level Image Features From Two-Photon Calcium Signals of Macaque Visual Cortex	12
Generalization Guarantees of Gradient Descent for Shallow Neural Networks	12
Encoding of Numerosity With Robustness to Object and Scene Identity in Biologically Inspired Object Recognition Networks	12
Quantifying and Maximizing the Information Flux in Recurrent Neural Networks	12
The Limiting Dynamics of SGD: Modified Loss, Phase-Space Oscillations, and Anomalous Diffusion	11
Multimodal and Multifactor Branching Time Active Inference	11
Deconstructing Deep Active Inference: A Contrarian Information Gatherer	11
Decision Threshold Learning in the Basal Ganglia for Multiple Alternatives	11
Attention in a Family of Boltzmann Machines Emerging From Modern Hopfield Networks	10
Differential Geometry Methods for Constructing Manifold-Targeted Recurrent Neural Networks	10
Neuromorphic Engineering: In Memory of Misha Mahowald	10
Bioplausible Unsupervised Delay Learning for Extracting Spatiotemporal Features in Spiking Neural Networks	9
Hypothesis Test and Confidence Analysis With Wasserstein Distance on General Dimension	9
Deep Nonnegative Matrix Factorization With Beta Divergences	9
Learning in Associative Networks Through Pavlovian Dynamics	9
Electrical Signaling Beyond Neurons	8
Using Global t-SNE to Preserve Intercluster Data Structure	8
Toward Network Intelligence	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	8
Model Based or Model Free? Comparing Adaptive Methods for Estimating Thresholds in Neuroscience	8
How Does the Inner Retinal Network Shape the Ganglion Cells Receptive Field? A Computational Study	8
eSPA+: Scalable Entropy-Optimal Machine Learning Classification for Small Data Problems	7
Positive Competitive Networks for Sparse Reconstruction	7
Working Memory and Self-Directed Inner Speech Enhance Multitask Generalization in Active Inference	7
Generalization Analysis of Transformers in Distribution Regression	7
Probing the Structure and Functional Properties of the Dropout-Induced Correlated Variability in Convolutional Neural Networks	7
Implicit Contact Dynamics Modeling With Explicit Inertia Matrix Representation for Real-Time, Model-Based Control in Physical Environment	7
Prototype Analysis in Hopfield Networks With Hebbian Learning	7
A Normative Account of Confirmation Bias During Reinforcement Learning	7
Mechanism of Duration Perception in Artificial Brains Suggests New Model of Attentional Entrainment	7
Desiderata for Normative Models of Synaptic Plasticity	7
Astrocytes Learn to Detect and Signal Deviations From Critical Brain Dynamics	7
Disentangled Representation Learning and Generation With Manifold Optimization	7
Memoryless Optimality: Neurons Do Not Need Adaptation to Optimally Encode Stimuli With Arbitrarily Complex Statistics	7
Neural Circuits for Dynamics-Based Segmentation of Time Series	6
Strong Allee Effect Synaptic Plasticity Rule in an Unsupervised Learning Environment	6
Toward a Biomimetic Neural Circuit Model of Sensory-Motor Processing	6
Promoting the Shift From Pixel-Level Correlations to Object Semantics Learning by Rethinking Computer Vision Benchmark Data Sets	6
Active Inference and Intentional Behavior	6
Sequential Learning in the Dense Associative Memory	6
Spiking Neuron-Astrocyte Networks for Image Recognition	6
Linear Codes for Hyperdimensional Computing	6
Visuomotor Mismatch Responses as a Hallmark of Explaining Away in Causal Inference	6
Is Learning in Biological Neural Networks Based on Stochastic Gradient Descent? An Analysis Using Stochastic Processes	6
Fast Multigroup Gaussian Process Factor Models	6

Distributed Synaptic Connection Strength Changes Dynamics in a Population Firing Rate Model in Response to Continuous External Stimuli	6
Boosting MCTS With Free Energy Minimization	5
Synaptic Information Storage Capacity Measured With Information Theory	5
Reducing Catastrophic Forgetting With Associative Learning: A Lesson From Fruit Flies	5
Toward a Free-Response Paradigm of Decision Making in Spiking Neural Networks	5
Sum-of-Norms Regularized Nonnegative Matrix Factorization	5
Learning in Wilson-Cowan Model for Metapopulation	5
Distributed Phase Oscillatory Excitation Efficiently Produces Attractors Using Spike-Timing-Dependent Plasticity	5
Uncovering Dynamical Equations of Stochastic Decision Models Using Data-Driven SINDy Algorithm	5
A Survey on Artificial Neural Networks in Human—Robot Interaction	5