Topic: Interpretation of neural networks

Computational psychiatry is still 'symptomology'—but just with more elegant equations.

The hippocampus learns by forming an "orthogonalized state machine," enabling contextual separation and flexible learning.

An ICLR 2025 paper proposing that range, not just statistical independence, is the key factor that determines whether neural representations are modular or mixed.

The topic of this year's NABI symposium, we explore how hippocampal circuits reveal the principles behind flexible, context-dependent memory.

Uncovering the trade-off between space and time in the hippocampus: how single neurons competitively balance these dimensions.

A look at CogFunSearch, a new method using LLMs to automatically discover symbolic cognitive models from human and animal behavior.