Modeling the role of hippocampus in spatial navigation
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By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.
Delves into spatial memory usage in RL agents for maze navigation tasks, showing improved performance with visual landmarks but inconsistent results in path choosing.
Discusses assembling neural networks by defining space and populating it with neurons, emphasizing the challenges and strategies for accurate morphologies and volume information.
Explores the mathematics of language models, covering architecture design, pre-training, and fine-tuning, emphasizing the importance of pre-training and fine-tuning for various tasks.
