mlsanityData to 7 Oct 2026

Cognitive computational neuroscience

arXiv 1807.11819 ↗First posted 31 Jul 2018q-bio.NCcited by 43

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Abstract (arXiv)

To learn how cognition is implemented in the brain, we must build computational models that can perform cognitive tasks, and test such models with brain and behavioral experiments. Cognitive science has developed computational models of human cognition, decomposing task performance into computational components. However, its algorithms still fall short of human intelligence and are not grounded in neurobiology. Computational neuroscience has investigated how interacting neurons can implement component functions of brain computation. However, it has yet to explain how those components interact to explain human cognition and behavior. Modern technologies enable us to measure and manipulate brain activity in unprecedentedly rich ways in animals and humans. However, experiments will yield theoretical insight only when employed to test brain-computational models. It is time to assemble the pieces of the puzzle of brain computation. Here we review recent work in the intersection of cognitive science, computational neuroscience, and artificial intelligence. Computational models that mimic brain information processing during perceptual, cognitive, and control tasks are beginning to be developed and tested with brain and behavioral data.

Key facts. Cited by 43 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Jul 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 6; 2022: 8; 2023: 10; 2024: 6; 2025: 8; 2026: 5.

43 papers.

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  1. 2023Neither hype nor gloom do DNNs justicecited by 40
  2. 2023The Topology and Geometry of Neural Representationscited by 13
  3. 2022Visual representations in the human brain are aligned with large language modelscited by 11
  4. 2022Neural Network based Successor Representations of Space and Languagecited by 9
  5. 2023Word class representations spontaneously emerge in a deep neural network trained on next word predictioncited by 9
  6. 2021The Tensor Brain: A Unified Theory of Perception, Memory and Semantic Decodingcited by 8
  7. 2022Neural Network based Formation of Cognitive Maps of Semantic Spaces and the Emergence of Abstract Conceptscited by 8
  8. 2026VLRS-Bench: A Vision-Language Reasoning Benchmark for Remote Sensingcited by 6
  9. 2021The whole brain architecture approach: Accelerating the development of artificial general intelligence by referring to the braincited by 5
  10. 2023Complex Recurrent Spectral Networkcited by 5
  11. 2024AlignedCut: Visual Concepts Discovery on Brain-Guided Universal Feature Spacecited by 5
  12. 2021A Whole Brain Probabilistic Generative Model: Toward Realizing Cognitive Architectures for Developmental Robotscited by 4
31 more
  1. 2021Controlled-rearing studies of newborn chicks and deep neural networkscited by 4
  2. 2022Computational Inference in Cognitive Science: Operational, Societal and Ethical Considerationscited by 4
  3. 2022Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environmentscited by 4
  4. 2024Computational Models to Study Language Processing in the Human Brain: A Surveycited by 4
  5. 2025LaVCa: LLM-assisted Visual Cortex Captioningcited by 4
  6. 2023DreamCatcher: Revealing the Language of the Brain with fMRI using GPT Embeddingcited by 3
  7. 2024Analysis of Argument Structure Constructions in a Deep Recurrent Language Modelcited by 3
  8. 2026Linguistics and Human Brain: A Perspective of Computational Neurosciencecited by 3
  9. 2021Continuous Homeostatic Reinforcement Learning for Self-Regulated Autonomous Agentscited by 2
  10. 2024Learning in Wilson-Cowan model for metapopulationcited by 2
  11. 2021Development of collective behavior in newborn artificial agentscited by 1
  12. 2023Beyond the limitations of any imaginable mechanism: large language models and psycholinguisticscited by 1
  13. 2023Flexible and Inherently Comprehensible Knowledge Representation for Data-Efficient Learning and Trustworthy Human-Machine Teaming in Manufacturing Environmentscited by 1
  14. 2023Life-inspired Interoceptive Artificial Intelligence for Autonomous and Adaptive Agentscited by 1
  15. 2023Beyond Labels: Advancing Cluster Analysis with the Entropy of Distance Distribution (EDD)cited by 1
  16. 2024Brain-like emergent properties in deep networks: impact of network architecture, datasets and trainingcited by 1
  17. 2025BI-RADS prediction of mammographic masses using uncertainty information extracted from a Bayesian Deep Learning modelcited by 1
  18. 2025Image-to-Brain Signal Generation for Visual Prosthesis with CLIP Guided Multimodal Diffusion Modelscited by 1
  19. 2022Predictive coding and stochastic resonance as fundamental principles of auditory perceptioncited by 0
  20. 2022Brain-inspired probabilistic generative model for double articulation analysis of spoken languagecited by 0
  21. 2022Collaboration between parallel connected neural networks -- A possible criterion for distinguishing artificial neural networks from natural organscited by 0
  22. 2023Fixing the problems of deep neural networks will require better training data and learning algorithmscited by 0
  23. 2024Continuous Time Continuous Space Homeostatic Reinforcement Learning (CTCS-HRRL) : Towards Biological Self-Autonomous Agentcited by 0
  24. 2025Inherited or produced? Inferring protein production kinetics when protein counts are shaped by a cell's division historycited by 0
  25. 2025Industrial brain: a human-like autonomous neuro-symbolic cognitive decision-making systemcited by 0
  26. 2025Learning Personalised Human Internal Cognition from External Expressive Behaviours for Real Personality Recognitioncited by 0
  27. 2025Cycle is All You Need: More Is Differentcited by 0
  28. 2025Uncovering Brain-Like Hierarchical Patterns in Vision-Language Models through fMRI-Based Neural Encodingcited by 0
  29. 2026Not Too Generative, Not Too Discriminative: The Human Alignment Sweet Spotcited by 0
  30. 2026Recovery-Directed Symbolic Distillation of Neural Likelihoodscited by 0
  31. 2026Future Video Generation Better Aligns with the Human Visual Cortex than Observed Videocited by 0