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Spatial Navigation

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Brain-Controlled 2D Navigation Robot Based on a Spatial Gradient Controller and Predictive Environmental Coordinator.

IEEE journal of biomedical and health informatics
OBJECTIVE: Brain-computer interfaces (BCIs) have been used in two-dimensional (2D) navigation robotic devices, such as brain-controlled wheelchairs and brain-controlled vehicles. However, contemporary BCI systems are driven by binary selective contro...

A robotic model of hippocampal reverse replay for reinforcement learning.

Bioinspiration & biomimetics
Hippocampal reverse replay, a phenomenon in which recently active hippocampal cells reactivate in the reverse order, is thought to contribute to learning, particularly reinforcement learning (RL), in animals. Here, we present a novel computational mo...

An explainable artificial intelligence approach to spatial navigation based on hippocampal circuitry.

Neural networks : the official journal of the International Neural Network Society
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...

A robot-rodent interaction arena with adjustable spatial complexity for ethologically relevant behavioral studies.

Cell reports
Outside of the laboratory, animals behave in spaces where they can transition between open areas and coverage as they interact with others. Replicating these conditions in the laboratory can be difficult to control and record. This has led to a domin...

A recurrent network model of planning explains hippocampal replay and human behavior.

Nature neuroscience
When faced with a novel situation, people often spend substantial periods of time contemplating possible futures. For such planning to be rational, the benefits to behavior must compensate for the time spent thinking. Here, we capture these features ...

Inductive biases of neural network modularity in spatial navigation.

Science advances
The brain may have evolved a modular architecture for daily tasks, with circuits featuring functionally specialized modules that match the task structure. We hypothesize that this architecture enables better learning and generalization than architect...

Understanding Learning from EEG Data: Combining Machine Learning and Feature Engineering Based on Hidden Markov Models and Mixed Models.

Neuroinformatics
Theta oscillations, ranging from 4-8 Hz, play a significant role in spatial learning and memory functions during navigation tasks. Frontal theta oscillations are thought to play an important role in spatial navigation and memory. Electroencephalograp...

I2Bot: an open-source tool for multi-modal and embodied simulation of insect navigation.

Journal of the Royal Society, Interface
Achieving a comprehensive understanding of animal intelligence demands an integrative approach that acknowledges the interplay between an organism's brain, body and environment. Insects, despite their limited computational resources, demonstrate rema...

Deep Learning-Emerged Grid Cells-Based Bio-Inspired Navigation in Robotics.

Sensors (Basel, Switzerland)
Grid cells in the brain's entorhinal cortex are essential for spatial navigation and have inspired advancements in robotic navigation systems. This paper first provides an overview of recent research on grid cell-based navigation in robotics, focusin...

PanoGen++: Domain-adapted text-guided panoramic environment generation for vision-and-language navigation.

Neural networks : the official journal of the International Neural Network Society
Vision-and-language navigation (VLN) tasks require agents to navigate three-dimensional environments guided by natural language instructions, offering substantial potential for diverse applications. However, the scarcity of training data impedes prog...