Brain-wide circuits that coordinate affective and social behaviours intersect in the amygdala.
Consequently, amygdala lesions cause a heterogeneous array of social and non-social …

Neural network models are potential tools for improving our understanding of complex brain
functions. To address this goal, these models need to be neurobiologically realistic …

The curse of dimensionality plagues models of reinforcement learning and decision making.
The process of abstraction solves this by constructing variables describing features shared …

In Consciousness We Trust is a synthesis of Hakwan Lau's 20-year research programme
exploring the neuroscience of consciousness. Discussing studies from his own laboratory …

Working memory is fundamental to cognition, allowing one to hold information" in mind." A
defining characteristic of working memory is its flexibility: we can hold anything in mind …

Lifelong learning and adaptability are two defining aspects of biological agents. Modern
reinforcement learning (RL) approaches have shown significant progress in solving complex …

The firing rates of individual neurons displaying mixed selectivity are modulated by multiple
task variables. When mixed selectivity is nonlinear, it confers an advantage by generating a …

The design of modern convolutional artificial neural networks (ANNs) composed of formal
neurons copies the architecture of the visual cortex. Signals proceed through a hierarchy …

Neurons are often considered specialized functional units that encode a single variable.
However, many neurons are observed to respond to a mix of disparate sensory, cognitive …

Brain networks exist within the confines of resource limitations. As a result, a brain network
must overcome the metabolic costs of growing and sustaining the network within its physical …