In this Review, we describe the singular success of attractor neural network models in
describing how the brain maintains persistent activity states for working memory, corrects …

There is growing interest in diffusion models to represent the cognitive and neural processes
of speeded decision making. Sequential-sampling models like the diffusion model have a …

Modeling human cognition is challenging because there are infinitely many mechanisms
that can generate any given observation. Some researchers address this by constraining the …

Most research in cognitive neuroscience explores how external stimuli are processed by the
brain. However, the brain also receives input from the internal body. We discuss here how …

My major motivation to think about swarm robotics is the question of how probabilistic local
actions of small robots sum up to rational global patterns shown by the swarm. For the …

Automatically describing an image with a sentence is a long-standing challenge in computer
vision and natural language processing. Due to recent progress in object detection, attribute …

Rewards are crucial objects that induce learning, approach behavior, choices, and
emotions. Whereas emotions are difficult to investigate in animals, the learning function is …

A sizeable literature exists on the use of frequentist power analysis in the null-hypothesis
significance testing (NHST) paradigm to facilitate the design of informative experiments. In …

Depression is linked to deficits in cognitive control and a host of other cognitive impairments
arise as a consequence of these deficits. Despite of their important role in depression, there …

What happens in our brain when we make a decision? What triggers a neuron to send out a
signal? What is the neural code? This textbook for advanced undergraduate and beginning …