Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to
model behavioural and neural data, an approach we call 'neuroconnectionism'. ANNs have …

The breadth and complexity of natural behaviors inspires awe. Understanding how our
perceptions, actions, and internal thoughts arise from evolved circuits in the brain has …

Neuroscience research is undergoing a minor revolution. Recent advances in machine
learning and artificial intelligence research have opened up new ways of thinking about …

To understand the brain we must relate neurons' functional responses to the circuit
architecture that shapes them. Here, we present a large functional connectomics dataset …

Cortical regions apparently selective to faces, places, and bodies have provided important
evidence for domain-specific theories of human cognition, development, and evolution. But …

To increase computational flexibility, the processing of sensory inputs changes with
behavioural context. In the visual system, active behavioural states characterized by motor …

Optical microscopy methods such as calcium and voltage imaging enable fast activity
readout of large neuronal populations using light. However, the lack of corresponding …

Modelling the spatiotemporal dynamics in the activity of neural populations while also
enabling their flexible inference is hindered by the complexity and noisiness of neural …

The utility of machine learning in understanding the motor system is promising a revolution
in how to collect, measure, and analyze data. The field of movement science already …

Visual systems of primates are the gold standard of robust perception. There is thus a
general belief that mimicking the neural representations that underlie those systems will …