SVM decoders

Animals and humans acquire knowledge through experience allowing them to flexibly generalize to novel situations. Several findings suggest that the Hippocampus (HC) is involved in the development of this conceptual learning not only for navigational but for other non-spatial variables if relevant to a task. However, how concepts arise with learning and how the hippocampus is involved in building these from the statistical structure of episodic memories still remains unknown. To study this, we trained mice on a binary categorization task consisting of a category split between low and high tone

Recent experiments demonstrate that the brain transforms visual inputs into representations that follow straighter temporal trajectories than their initial photoreceptor encoding, facilitating prediction by linear extrapolation (Hénaff et al 2019; 2021). Can the brain use this principle to learn visual representations? Here, we develop an objective that quantifies straightening, augment it with a regularizer to prevent collapse to trivial solutions, and use it to train deep feedforward neural networks on video sequences. Decoding of the learned representation with a separately trained readout