Brain-inspired artificial intelligence research: A review

GY Wang, HN Bao, Q Liu, TG Zhou, S Wu… - Science China …, 2024 - Springer
Artificial intelligence (AI) systems surpass certain human intelligence abilities in a statistical
sense as a whole, but are not yet the true realization of these human intelligence abilities …

[HTML][HTML] The generative neural microdynamics of cognitive processing

DC McNamee - Current Opinion in Neurobiology, 2024 - Elsevier
The entorhinal cortex and hippocampus form a recurrent network that informs many
cognitive processes, including memory, planning, navigation, and imagination. Neural …

Firing rate adaptation affords place cell theta sweeps, phase precession, and procession

T Chu, Z Ji, J Zuo, Y Mi, W Zhang, T Huang, D Bush… - Elife, 2024 - elifesciences.org
Hippocampal place cells in freely moving rodents display both theta phase precession and
procession, which is thought to play important roles in cognition, but the neural mechanism …

Adaptation accelerating sampling-based bayesian inference in attractor neural networks

X Dong, Z Ji, T Chu, T Huang… - Advances in Neural …, 2022 - proceedings.neurips.cc
The brain performs probabilistic Bayesian inference to interpret the external world. The
sampling-based view assumes that the brain represents the stimulus posterior distribution …

Sequential predictive learning is a unifying theory for hippocampal representation and replay

D Levenstein, A Efremov, RH Eyono, A Peyrache… - bioRxiv, 2024 - biorxiv.org
The mammalian hippocampus contains a cognitive map that represents an animal's position
in the environment and generates offline “replay”, for the purposes of recall, planning,, and …

Modeling of Fuzzy Cognitive Maps with a Metaheuristics-Based Rainfall Prediction System

M Al Duhayyim, HG Mohamed, JS Alzahrani… - Sustainability, 2022 - mdpi.com
Rainfall prediction remains a hot research topic in smart city environments. Precise rainfall
prediction in smart cities becomes essential for planning security measures before …

Micro drill defect detection with hybrid BP networks, clusters selection and crossover

D Ge, R Su, X Yao, J Li - Neural Computing and Applications, 2024 - Springer
According to the solution requirements, linear BP neural networks are designed which are
consistent with the feature curves of the fitted equation, when the neural networks reach the …

AI of brain and cognitive sciences: from the perspective of first principles

L Chen, Z Chen, L Jiang, X Liu, L Xu, B Zhang… - arxiv preprint arxiv …, 2023 - arxiv.org
Nowadays, we have witnessed the great success of AI in various applications, including
image classification, game playing, protein structure analysis, language translation, and …

Dynamics of Adaptive Continuous Attractor Neural Networks

Y Li, T Chu, S Wu - arxiv preprint arxiv:2410.06517, 2024 - arxiv.org
Attractor neural networks consider that neural information is stored as stationary states of a
dynamical system formed by a large number of interconnected neurons. The attractor …

Firing rate adaptation in continuous attractor neural networks accounts for theta phase shift of hippocampal place cells

T Chu, Z Ji, J Zuo, Y Mi, W Zhang, T Huang, D Bush… - bioRxiv, 2022 - biorxiv.org
Hippocampal place cells of freely moving animals display 'theta phase precession', whereby
spikes are fired at successively earlier phases of the 6-10 Hz local field potential (LFP) theta …