Neural mechanisms of perceptual decision making have been extensively studied in
experimental settings that mimic stable environments with repeating stimuli, fixed rules, and …

Attractor networks are a popular computational construct used to model different brain
systems. These networks allow elegant computations that are thought to represent a number …

The ability to recall discrete memories is thought to depend on the formation of attractor
states in recurrent neural networks,,,. In such networks, representations can be reactivated …

We develop further here the only quantitative theory of the storage of information in the
hippocampal episodic memory system and its recall back to the neocortex. The theory is …

How does the brain learn to recognize objects visually, and perform this difficult feat robustly
in the face of many sources of ambiguity and variability? We present a computational model …

Standard models of the visual object recognition pathway hold that a largely feedforward
process from the retina through inferotemporal cortex leads to object identification. A …

First, neurophysiological evidence for the learning of invariant representations in the inferior
temporal visual cortex is described. This includes object and face representations with …

Highlights•Object representation is intermediate between parts-based and holistic
descriptions.•Intrinsic dimensionality of object representations is approximately one …

In primates, neuronal representations of objects are processed hierarchically in
occipitotemporal cortices. A “novel” feature of objects is thought to emerge and become …

One obstacle to understanding the exact processes unfolding inside the hippocampus is that
it is still difficult to clearly define what the hippocampus actually does, at the system level …