Using neuroscience to develop artificial intelligence

Deep learning

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Reinforcement Learning: An Introduction

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Reinforcement Learning: An Introduction

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The perceptron: A probabilistic model for information storage and organization in the brain.

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I.—COMPUTING MACHINERY AND INTELLIGENCE

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Mastering the game of Go without human knowledge

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Building machines that learn and think like people

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The Origin of Concepts

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Neuroscience-Inspired Artificial Intelligence

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Core knowledge

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Sample of AI-enabled autonomous weapons used in human–machine teaming

Johnson, J. S. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780198892182.005.0002

List of figures and tables

Johnson, J. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780198892182.002.0006

Tactical generals and strategic corporals

Johnson, J. S. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780198892182.003.0004

Copyright Page

Johnson, J. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780198892182.002.0003

Introduction

Johnson, J. S. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780198892182.003.0001

The AI commander problem

Johnson, J. S. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780198892182.003.0002

Application of Artificial Intelligence in NeuroCOVID-19

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SNN Modeling of Cricket Auditory Network with Izhikevich Model Optimized by PSO

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Start from here

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Grundlagenfragen der Neurocomputation und Neurokognition

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Bird’s Eye View of Artificial Intelligence in Neuroscience

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Systematic Analysis of the Role of Artificial Intelligence in Customer Experience in the Service Sector

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Artificial Intelligence and Its Impact on the Mental Health Field

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A brain-inspired algorithm enhances automatic speech recognition performance in multi-talker scenesPreprint

Boyd, A. D., & Sen, K. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.15.664627

Deep Spiking Neural Networks FPGA Implementation Based on Multichannel Time-Multiplexed Architecture

Lin, X., Xie, C., & Ma, R. (2025) · Communications in computer and information science · doi:10.1007/978-981-95-4094-5_33

Reimagining Tourism Research through Neuroscience and Artificial Intelligence a Dual-Model Perspective

Büşra, K. A. Y. A. (2025) · Journal of Smart Systems Research · doi:10.58769/joinssr.1794172

Knowledge flows from science to AI technology: Identifying core and brokerage technological roles

Lee, S., Hur, J., Hwang, J., Kogler, D. F., & Kim, K. (2026) · PLoS ONE · doi:10.1371/journal.pone.0341005

Neuroscientific Approach to Artificial Intelligence for Psychopathologies

Celik, K., & Çelik, S. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-1325-2.ch006

Multilevel Multimodal Visual Neural Decoding for Generalized Visual Object Recognition

Hang, W., Wang, J., Liang, S., Wang, Q., Li, G., Qin, J., & Chen, B. (2026) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2026.3674164

Droit de l'intelligence artificielle : essai d'une approche juridique du cognitivisme électronique

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Artificial Intelligence to accelerate battery cell manufacturing and design

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Near-infrared photovoltaic gating enables polarity-reconfigurable WSe 2 phototransistors for in-sensor computing

Lu, X., Lv, Y., Wu, H., Yi, J., Wu, G., Liu, H., Wang, Z., Zong, Q., Shuai, Q., Huang, L., et al. (2026) · Nanoscale · doi:10.1039/d6nr00412a

A bio-inspired neuromorphic system for fusing visual features and autonomous learning

Guo, M., Zi, Y., Liu, L., Liu, J., Yang, Q., Xu, J., Dou, G., Wang, L., & Chen, D. (2026) · Neural Networks · doi:10.1016/j.neunet.2026.109097

Use of Artificial Intelligence in Biofabrication

Uysal, G., Elçin, A. E., & Elçin, Y. M. (2026) · Stem cell biology and regenerative medicine · doi:10.1007/978-3-032-30294-6_16

Dendritic functional heterogeneity with feedback control facilitates stable spatiotemporal representation in spiking neural networks

Li, Q., Wang, J., & Wu, J. (2026) · Neural Networks · doi:10.1016/j.neunet.2026.109395 · Cited by 1

Brain-inspired navigation based on the entorhinal cortex- hippocampal neural circuit: Bridging spatial cognitive mechanisms and robotic applications

Zhang, H., Liu, X., Wang, C., Tang, J., Shen, C., & Liu, J. (2026) · Neural Networks · doi:10.1016/j.neunet.2026.109468

SORLDN2: A brain-inspired navigation decision-making framework for Mobile robots

Tan, Y., & Wang, D. (2026) · Applied Soft Computing · doi:10.1016/j.asoc.2026.116157

Artificial intelligence in pre-trial criminal proceedings: judicial oversight and admissibility of algorithmic outputs in Russia and Tajikistan

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Collaboration pattern in parallel-connected neural networks – A potential criterion for measuring the bionic level of artificial neural networks

He, G. P. (2026) · Expert Systems with Applications · doi:10.1016/j.eswa.2026.133956

Future directions in neuropsychology and neurosciences

Bhaskar, R., Singh, D. K. K., & Han, S. S. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-36544-7.00001-x

Highly Linear Perovskite Synapses for Neuromorphic Computing

Sun, Z., Wan, B., Zhang, Z., Wang, Z., Zhao, X., Si, H., Liao, Q., & Zhang, Y. (2026) · Advanced Science · doi:10.1002/advs.78461

Morphological Computation and Learning to Learn In Natural Intelligent Systems And AIPreprint

Dodig-Crnković, G. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.02304 · Cited by 1

The brain as a blueprint: a survey of brain-inspired approaches to learning in artificial intelligencePreprint

Etter, G. (2025) · arXiv (Cornell University) · doi:10.48550/arxiv.2511.04455

Network attributes describe a similarity between deep neural networks and large scale brain networks

Takagi, K. (2019) · Journal of Complex Networks · doi:10.1093/comnet/cnz044 · Cited by 1

Learning like a human

Alderton, G. K. (2019) · Science · doi:10.1126/science.363.6428.703-r

Branching into brains

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