Theories of Error Back-Propagation in the Brain

Cited by (420)

Items 301–400 of 420

1. DynamicEmbedding: Extending TensorFlow for Colossal-Scale Applications
   Yun Zeng, Zuo, Siqi, Dongcai Shen · 2020 · arXiv (Cornell University)
2. Confidence-controlled Hebbian learning efficiently extracts category membership from stimuli encoded in view of a categorization task
   Kevin Berlemont, Jean‐Pierre Nadal · 2020 · bioRxiv (Cold Spring Harbor Laboratory)
3. Neurobiological models of sentence processing
   Marvin Uhlmann · 2020 · MPG.PuRe (Max Planck Society)
4. Neuronal cultures show bidirectional axonal conduction with antidromic action potentials depolarizing the soma
   José C. Mateus, Cátia D. F. Lopes, Miguel Aroso, Ana Rute Costa, Ana Gerós, Jo�ão Meneses, P Faria, Estrela Neto, Meriem Lamghari, Mónica Mendes Sousa et al. · 2021 · bioRxiv (Cold Spring Harbor Laboratory)
5. Feature Alignment for Approximated Reversibility in Neural Networks.
   Tiago de Souza Farias, Jonas Maziero · 2021 · arXiv (Cornell University)
6. Reproducing Human Motor Adaptation in Spiking Neural Simulation and known Synaptic Learning Rules
   Yufei Wu, Shlomi Haar, A. Aldo Faisal · 2021 · bioRxiv (Cold Spring Harbor Laboratory)
7. Evolution of neural activity in circuits bridging sensory and abstract knowledge
   Francesca Mastrogiuseppe, Naoki Hiratani, Peter E. Latham · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
8. Experimental validation of the free-energy principle with in vitro neural networks
   Takuya Isomura, Kiyoshi Kotani, Yasuhiko Jimbo, Karl John Friston · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
9. Differentiation and Integration of Competing Memories: A Neural Network Model
   Victoria J. H. Ritvo, Alex Nguyen, Nicholas B. Turk‐Browne, Kenneth A. Norman · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
10. An agent based model (ABM) to reproduce the boolean logic behaviour of neuronal self organized communities through pulse delay modulation and generation of logic gates
    Luis Irastorza-Valera, José María Benítez, Francisco Javier Montáns, Luis Saucedo‐Mora · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
11. Online reinforcement learning of state representation in recurrent network supported by the power of random feedback and biological constraints
    Takayuki Tsurumi, Ayaka Kato, Arvind Kumar, Kenji Morita · 2025 · eLife
12. Spiking Neural Networks for Scalable Visual Place Recognition
    Somayeh Hussaini · 2024 · Queensland University of Technology
13. Learning of state representation in recurrent network: the power of random feedback and biological constraints
    Takayuki Tsurumi, Ayaka Kato, Arvind Kumar, Kenji Morita · 2025 · eLife
14. Breaking Balance: Encoding local error signals in perturbations of excitation-inhibition balance
    Julian Rossbroich, Friedemann Zenke · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
15. Online reinforcement learning of state representation in recurrent network: the power of random feedback and biological constraints
    Takayuki Tsurumi, Ayaka Kato, Arvind Kumar, Kenji Morita · 2025 · eLife
16. Toward defining loss functions in neuroscience: an XOR-based neuronal mechanism
    María Peña Fernández, Lara Lloret Iglesias, J. Marco · 2026 · bioRxiv (Cold Spring Harbor Laboratory)
17. Closed-form predictive coding via hierarchical Gaussian filters
    Baskakovs, Aleksandrs, Estebe, Sylvain, Enevoldsen, Kenneth, Nielbo, Kristoffer, Mathys, Chris, Legrand, Nicolas · 2026 · arXiv
18. Spike-Timing-Dependent Inference of Synaptic Weights.
    Nasir Ahmad, Luca Ambrogioni, Marcel A. J. van Gerven · 2020
19. Layer-wise Learning of Kernel Dependence Networks
    Chieh Wu, Aria Masoomi, Arthur Gretton, Jennifer Dy · 2020 · arXiv (Cornell University)
20. A biological plausible audio-visual integration model for continual lifelong learning
    Wenjie Chen, Fengtong Du, Ye Wang, Lihong Cao · 2020
21. Error splitting method for training a built-in neural network storage element with SR-latch functionality
    N. Tsaikin · 2020 · International Scientific Conference Electronics (ET)
22. Estimating Model Parameters of Concrete Materials Based on Neural Networks
    Yu He, Shouju Li · 2020 · Advances in intelligent systems and computing
23. The backpropagation-based recollection hypothesis: Backpropagated action potentials mediate recall, imagination, language understanding and naming
    Zied Ben Houidi · 2021 · arXiv (Cornell University)
24. Dynamical Mechanism of Sampling-based Stochastic Inference under Probabilistic Population Codes
    Kohei Ichikawa, Asaki Kataoka · 2021 · arXiv (Cornell University)
25. Statistical Learning in Speech: A Biologically Based Predictive Learning Model
    John Rohrlich, Randall C. O’Reilly · 2021 · arXiv (Cornell University)
26. A Biologically Plausible Audio-Visual Integration Model for Continual Learning
    Wenjie Chen, Fengtong Du, Ye Wang, Lihong Cao · 2021 · International Joint Conference on Neural Networks (IJCNN)
27. The effect of synaptic weight initialization in feature-based successor representation learning.
    Hyunsu Lee · 2021 · arXiv (Cornell University)
28. IMPLEMENTATION POSSIBILITY OF A LIKE DEEP LEARNING ALGORITHMS ON NON-DEEP NETWORKS WITH HIDDEN LAYERS
    G. V. Shilovskii, V. M. Yulkova · 2020 · Vestnik komp iuternykh i informatsionnykh tekhnologii
29. Experimental and Biological Approaches
    2020 · Cambridge University Press eBooks
30. Feature Alignment As A Generative Process
    Tiago de Souza Farias, Jonas Maziero · 2022 · Research Square
31. Faculty Opinions recommendation of Direct fit to nature: an evolutionary perspective on biological and artificial neural networks.
    Noam E. Ziv · 2021 · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature
32. Resolving Linguistic Ambiguities by Visual Context
    Arianna Pavone, Alessio Plebe · 2022 · SN Computer Science
33. A comprehensive study on the cognitive mechanisms and neural substrates of hallucination proneness
    Joseph F. Johnson · 2022
34. Modeling relational responding with artificial neural networks
    Janelle Mendoza, Stefano Ghirlanda · 2022 · Behavioural Processes
35. Graphene for Silicon Optoelectronic Synaptic Devices
    Yang Xu, Khurram Shehzad, Srikrishna Chanakya Bodepudi, Muhammad Ali Imran, Bin Yu · 2023
36. Memory travels through cells backward
    José Patricio Casanova, Gisella Vetere · 2023 · Neuron
37. Gradient Expectations
    Keith L. Downing · 2023 · The MIT Press eBooks
38. Understanding how visual information is represented in humans and machines
    Kshitij Dwivedi · 2022
39. Differentiation and Integration of Competing Memories: A Neural Network Model
    Victoria J. H. Ritvo, Alex Nguyen, Nicholas B. Turk‐Browne, Kenneth A. Norman · 2023 · eLife
40. Hardware Implementation of On-Chip Learning Neural Network on FPGA
    Lanyue Bi, Xiaoqing Zhu, Xiaogang Ruan, Borui Nan · 2023 · Chinese Control Conference (CCC)
41. Application of Data Security Models Based on Neural Network Algorithms in Optimizing Social Network Order
    Liangping Wang · 2023 · IEEE India Council International Subsections Conference (INDISCON)
42. A theory of inference and learning in cortex with spiking neurons and dendritic error computation
    Fabian A. Mikulasch · 2023
43. Integrating Local STDP and Global Backpropagation Learning Using Spike-Time and Spike-Rate Representations for Improved Classification of Spatiotemporal Data in the Neucube Brain Inspired Evolving Spiking Neural Network Architecture: A Case Study on EEG Brain Data
    Xuanle Zhou, Maryam Doborjeh, Nikola Kirilov Kasabov, Zohreh Doborjeh · 2023 · SSRN Electronic Journal
44. Reward-Dependent and Locally Modulated Hebbian Rule
    Zhaofan Liu, Da‐Hui Wang · 2023 · Communications in computer and information science
45. Backpropagation-Based Recollection of Memories: Biological Plausibility and Computational Efficiency
    Zied Ben Houidi · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
46. Computer Network Security Evaluation Method Based on GABP Model
    Liang Meng, Mingfei Zeng, Wenjie Yang, Lina Chen, Siwei Li, Junbing Pan · 2023 · International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE)
47. Transformação digital e mudanças no formato de trabalho: Impactos na estrutura organizacional de instituições bancárias brasileiras
    Rafael Constantino · 2023
48. Is Learning in Biological Neural Networks Based on Stochastic Gradient Descent? An Analysis Using Stochastic Processes
    Sören Christensen, Jan Kallsen · 2024 · Neural Computation
49. Überblick und Klassifizierung von auf Schwarmintelligenz basierenden naturinspirierten Rechenalgorithmen und deren Anwendungen in der Krebserkennung und -diagnose
    Fatima Nazish Khan, Mohammad Asim, Mohammad Irfan Qureshi · 2024 · Springer eBooks
50. Variable Universe Fuzzy Control Based on Adaptive Error Integral for Uncertain Nonlinear Systems with Time-Delay
    Yinhua Guo, Jiayin Wang, Fusheng Yu, Cunqin Shi · 2024 · Lecture notes on data engineering and communications technologies
51. Reviewer #1 (Public Review): Differentiation and Integration of Competing Memories: A Neural Network Model
    2024 · eLife
52. eLife Assessment: Differentiation and Integration of Competing Memories: A Neural Network Model
    Margaret L. Schlichting · 2024 · eLife
53. Reviewer #2 (Public Review): Differentiation and Integration of Competing Memories: A Neural Network Model
    2024 · eLife
54. Author response: Differentiation and Integration of Competing Memories: A Neural Network Model
    Victoria J. H. Ritvo, Alex Nguyen, Nicholas B. Turk‐Browne, Kenneth A. Norman · 2024 · eLife
55. Reviewer #3 (Public Review): Differentiation and Integration of Competing Memories: A Neural Network Model
    2024 · eLife
56. Relating Human Error–Based Learning to Modern Deep RL Algorithms
    Michele Garibbo, Casimir J. H. Ludwig, Nathan F. Lepora, Laurence Aitchison · 2024 · Neural Computation
57. Neural Sliding Mode Control of a permanent magnet synchronous generator PMSG integrated in a wind system
    Mohammed Aoumri, Ibrahim Yaichi, Abdelkader Harrouz, Brahim Berbaoui, Seddik Baala · 2024 · STUDIES IN ENGINEERING AND EXACT SCIENCES
58. How biological synapses self-assemble gradient learning
    Qianli Liao, Liu Ziyin, Yulu Gan, Brian Cheung, Mark T. Harnett, Tomaso Poggio · 2026 · Proceedings of the National Academy of Sciences
59. Developing Variational Generative Models Using Predictive Coding
    Senhui Qiu, Saugat Bhattacharyya, Damien Coyle, Shirin Dora · 2024 · Advances in intelligent systems and computing
60. Multilevel Data Representation for Training Deep Helmholtz Machines
    Jose Miguel Ramos, Luis Sa-Couto, Andreas Wichert · 2025 · Neural Computation
61. Hierarchical recurrent temporal prediction as a model of the mammalian dorsal visual pathway
    Sebastian Klavinskis-Whiting, Andrew J. King, Nicol Spencer Harper · 2026 · PLoS Computational Biology
62. Hardware Oriented Evolutionary Spiking Neural Network
    Mahshid Rajati · 2025
63. Online reinforcement learning of state representation in recurrent network: the power of random feedback and biological constraints
    Takayuki Tsurumi, Ayaka Kato, Arvind Kumar, Kenji Morita · 2025 · eLife
64. Foreword
    Iuliia Kotseruba, John K. Tsotsos · 2025 · Oxford University Press eBooks
65. Figure
    Iuliia Kotseruba, John K. Tsotsos · 2025 · Oxford University Press eBooks
66. Learning
    Iuliia Kotseruba, John K. Tsotsos · 2025 · Oxford University Press eBooks
67. What is this book about?
    Iuliia Kotseruba, John K. Tsotsos · 2025 · Oxford University Press eBooks
68. Taxonomies of Cognitive Architectures
    Iuliia Kotseruba, John K. Tsotsos · 2025 · Oxford University Press eBooks
69. Practical Applications of Cognitive Architectures
    Iuliia Kotseruba, John K. Tsotsos · 2025 · Oxford University Press eBooks
70. Cognitive Architectures, AI, and Cognitive Science
    Iuliia Kotseruba, John K. Tsotsos · 2025 · Oxford University Press eBooks
71. Copyright Page
    Iuliia Kotseruba, John K. Tsotsos · 2025 · Oxford University Press eBooks
72. Reasoning and Decision-Making
    Iuliia Kotseruba, John K. Tsotsos · 2025 · Oxford University Press eBooks
73. Challenges of the Past and Opportunities Ahead
    Iuliia Kotseruba, John K. Tsotsos · 2025 · Oxford University Press eBooks
74. Memory
    Iuliia Kotseruba, John K. Tsotsos · 2025 · Oxford University Press eBooks
75. Cognitive Architectures in the Deep Learning Era
    Iuliia Kotseruba, John K. Tsotsos · 2025 · Oxford University Press eBooks
76. Putting It All Together
    Iuliia Kotseruba, John K. Tsotsos · 2025 · Oxford University Press eBooks
77. What Are Cognitive Architectures?
    Iuliia Kotseruba, John K. Tsotsos · 2025 · Oxford University Press eBooks
78. Evaluating Cognitive Architectures
    Iuliia Kotseruba, John K. Tsotsos · 2025 · Oxford University Press eBooks
79. Why Current AI Architectures are Not Conscious: Neural Networks as Spinfoam Networks in a Theory of Quantum Gravity
    Trevor Nestor · 2025 · SSRN Electronic Journal
80. Temporal Predictive Coding as World Model for Reinforcement Learning
    Artem Prokhorenko, Petr Kuderov, Evgenii Dzhivelikian, Aleksandr I. Panov · 2025 · Lecture notes in computer science
81. Discrimination of Ophiopogonis Radix from Different Planting Districts by using Infrared Spectroscopy Combined with One-dimensional Convolutional Neural Network
    Long Jiao, Yuanyuan Liu, Bijia Chen, Tianlong Zhang · 2025 · Current Analytical Chemistry
82. Non-negative connectivity causes bow-tie architecture in neural circuits
    Zhaofan Liu, CongCong Du, KongFatt Wong‐Lin, Dahui Wang · 2025 · Frontiers in Neural Circuits
83. How does your brain create new memories? Neuroscientists discover ‘rules’ for how neurons encode new information
    William Wright, Takaki Komiyama · 2025
84. Como seu cérebro cria novas memórias? Neurocientistas descobrem “regras” de como os neurônios codificam novas informações
    William Wright, Takaki Komiyama · 2025
85. The curriculum effect in visual learning: The role of readout dimensionality
    Charlotte Volk, Christopher C. Pack, Shahab Bakhtiari · 2026 · PLoS Computational Biology
86. Deep Learning Algorithms and Techniques
    Muskan Syed, Vanshika Chauhan, Bhavya Mathur, Sanskriti Goyal, Priyanka Narad, Abhishek Sengupta · 2025 · Medical virology
87. Forward and reverse engineering the pain system: from computational neuroscience to neuro-engineering
    Pranav Mahajan, Ben Seymour · 2025 · Pain
88. Generative inference unifies feedback processing for learning and perception in natural and artificial vision
    Tahereh Toosi, Kenneth D. Miller · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
89. A novel CNN-based selective ensemble learning method for gearbox fault diagnosis
    Yongsen Liang, Yupeng Qi, Yujie Cheng, Dengwei Song · 2025 · Engineering Research Express
90. Goal Reduction with Loop-Removal Accelerates RL and Models Human Brain Activity in Goal-Directed Learning
    Huzi Cheng, Joshua W. Brown · 2024 · neural information processing systems
91. Towards biologically plausible DNN optimization: Replacing backpropagation and loss functions with a top-down credit assignment network
    Jianhui Chen, Tianming Yang, Cheng‐Lin Liu, Zuoren Wang · 2025 · Neurocomputing
92. A minimal recurrent neural network models the robustness of interleaved practice on motor sequence learning
    Youngjo Song, Hakjoo Kim, Taewon Kim · 2026 · Scientific Reports
93. Enhancing the Forward Forward Algorithm with Label Based Similarity for Improved Neural Network Training
    Roshan Birjais, Kevin I‐Kai Wang, Waleed Habib Abdulla · 2026 · Lecture notes in computer science
94. Convergence of Energy-Based Learning in Linear Resistive Networks
    Anne-Men Huijzer, Thomas Chaffey, Bart Besselink, Henk J. van Waarde · 2026 · IEEE Transactions on Automatic Control
95. Can Local Representation Alignment RNNs Solve Temporal Tasks?
    Nikolay Manchev, Luis C. García-Peraza-Herrera · 2025 · International Conference on Computer, Software and Modeling (ICCSM)
96. Aquila Optimization-Assisted Artificial Neural Network for Classification Problems
    Gökhan Kayhan, Seyma Hasbolat Unal · 2026 · Biomimetics
97. Digital Implementation of Neuromorphic systems using Emerging Memory devices
    Tifenn Hirtzlin · 2020 · theses.fr (ABES)
98. Neural, acoustic and information dynamics (mutually) constrain speech perception
    jeremy giroud · 2021 · theses.fr (ABES)
99. Physics-Grounded Neuromorphic Computing : From Spiking Neurons to Learning Algorithms
    Marie Drouhin · 2023 · theses.fr (ABES)
100. Analog spike-based neuromorphic computing for low-power smart IoT applications
     Zalfa Jouni · 2024