AIMC Topic: Maze Learning

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AI-Driven Framework for Enhanced and Automated Behavioral Analysis in Morris Water Maze Studies.

Sensors (Basel, Switzerland) Mar 4, 2025
The Morris Water Maze (MWM) is a widely used behavioral test to assess the spatial learning and memory of animals, particularly valuable in studying neurodegenerative disorders such as Alzheimer's disease. Traditional methods for analyzing MWM experi...
Alzheimer Disease Behavior, Animal Maze Learning Morris Water Maze Test Neural Networks, Computer Machine Learning Algorithms Animals
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Unbiased analysis of spatial learning strategies in a modified Barnes maze using convolutional neural networks.

Scientific reports Jul 10, 2024
Assessment of spatial learning abilities is central to behavioral neuroscience and a useful tool for animal model validation and drug development. However, biases introduced by the apparatus, environment, or experimentalist represent a critical chall...
Alzheimer Disease Behavior, Animal Maze Learning Spatial Learning Mice Disease Models, Animal Mice, Inbred C57BL Neural Networks, Computer Female Animals Male
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An explainable artificial intelligence approach to spatial navigation based on hippocampal circuitry.

Neural networks : the official journal of the International Neural Network Society Mar 30, 2023
Learning to navigate a complex environment is not a difficult task for a mammal. For example, finding the correct way to exit a maze following a sequence of cues, does not need a long training session. Just a single or a few runs through a new enviro...
Hippocampus Maze Learning Spatial Navigation Brain Animals Mammals Cues Artificial Intelligence
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Modular deep reinforcement learning from reward and punishment for robot navigation.

Neural networks : the official journal of the International Neural Network Society Dec 8, 2020
Modular Reinforcement Learning decomposes a monolithic task into several tasks with sub-goals and learns each one in parallel to solve the original problem. Such learning patterns can be traced in the brains of animals. Recent evidence in neuroscienc...
Robotics Reward Motivation Maze Learning Computer Simulation Animals Deep Learning Reinforcement, Psychology Punishment
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Recognition of early stage thigmotaxis in Morris water maze test with convolutional neural network.

PloS one May 3, 2018
The Morris water maze test (MWM) is a useful tool to evaluate rodents' spatial learning and memory, but the outcome is susceptible to various experimental conditions. Thigmotaxis is a commonly observed behavioral pattern which is thought to be relate...
Maze Learning Carotid Stenosis Spatial Memory Taxis Response Reaction Time Swimming Carotid Artery, Common Neural Networks, Computer Machine Learning Sensitivity and Specificity Animals Male Mice Mice, Inbred C57BL
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Effects of docosahexaenoic acid on locomotor activity in ethanol-treated HIV-1 transgenic rats.

Journal of neurovirology Dec 19, 2017
Binge drinking affects the onset and progression of human immunodeficiency virus (HIV)-associated neurological disorders. The HIV-1 transgenic (HIV-1Tg) rat was created with a gag- and pol-deleted HIV-1 viral genome to mimic HIV-infected patients rec...
Rats, Transgenic NF-kappa B HIV Infections Docosahexaenoic Acids Binge Drinking Rats Interleukin-6 Locomotion Rats, Inbred F344 Interleukin-18 Disease Models, Animal Corpus Striatum Animals Maze Learning HIV-1 Gene Expression Endotoxins Male
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Cognitive memory and mapping in a brain-like system for robotic navigation.

Neural networks : the official journal of the International Neural Network Society Dec 7, 2016
Electrophysiological studies in animals may provide a great insight into developing brain-like models of spatial cognition for robots. These studies suggest that the spatial ability of animals requires proper functioning of the hippocampus and the en...
Memory Maze Learning Brain Entorhinal Cortex Animals Spatial Navigation Brain Mapping Cognition Robotics Neuronal Plasticity Hippocampus
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Maze learning by a hybrid brain-computer system.

Scientific reports Sep 13, 2016
The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the co...
Neural Networks, Computer Artificial Intelligence Algorithms Brain Behavior, Animal Memory Maze Learning Rats Computer Simulation Rats, Sprague-Dawley Animals Stress, Mechanical Male Brain-Computer Interfaces
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Intelligence-Augmented Rat Cyborgs in Maze Solving.

PloS one Feb 9, 2016
Cyborg intelligence is an emerging kind of intelligence paradigm. It aims to deeply integrate machine intelligence with biological intelligence by connecting machines and living beings via neural interfaces, enhancing strength by combining the biolog...
Rats Rats, Sprague-Dawley Maze Learning Artificial Intelligence Animals Time Factors
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Behavioral plasticity through the modulation of switch neurons.

Neural networks : the official journal of the International Neural Network Society Nov 12, 2015
A central question in artificial intelligence is how to design agents capable of switching between different behaviors in response to environmental changes. Taking inspiration from neuroscience, we address this problem by utilizing artificial neural ...
Neurosciences Neural Networks, Computer Problem Solving Artificial Intelligence Signal Processing, Computer-Assisted Behavior Algorithms Machine Learning Neurons Reinforcement, Psychology Computer Simulation Synapses Neuronal Plasticity Maze Learning
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