You have to enable JavaScript in your browser's settings in order to use the eReader.

Huang et al. show that the brain optimizes working memory by compressing information when environmental regularities exist. MEG reveals distinct neural systems for abstract structure and item details,...

Fuzzy simplicial sets have become an object of interest in dimensionality reduction and manifold learning, most prominently through their role in UMAP. However, their definition through tools from alg...

Nature Communications - Here, the authors show learning tasks with similar structures can initially cause interference and slow down learning, but both the brain and artificial networks gradually...

In the classical view of hippocampal function, the subiculum is assigned the role as the output layer. In spatial paradigms, some subiculum neurons manifest as so-called boundary vector cells (BVCs), ...

Learning depends not only on the content of what we learn, but also on how we learn and on how experiences are structured over time. To investigate how task similarity and training regime interact dur...

Sofie Valk and Daniel Reznik receive ERC Starting Grants

Neural networks now generate text, images, and speech with billions of parameters, producing a need to know how each neural unit contributes to these high-dimensional outputs. Existing explainable-AI ...

Author summary The hippocampus is a brain region which plays a crucial role in spatial navigation for both animals and humans. Contemporarily, it’s thought to store predictive representations of the e...

Efficient navigation, especially in the absence of vision, requires path integration - the continuous updating of spatial position from self-motion cues. However, path integration is prone to cumulati...

This paper examines the effect of a period of quiet wakefulness (an “offline wake” state) on the performance of a decision making task. An initial fee…