Optogenetics ushered in a revolution in how neuroscientists interrogate brain function.
Because of technical limitations, the majority of optogenetic studies have used low spatial …

Deep learning describes a class of machine learning algorithms that are capable of
combining raw inputs into layers of intermediate features. These algorithms have recently …

Calcium imaging has been widely adopted for its ability to record from large neuronal
populations. To summarize the time course of neural activity, dimensionality-reduction …

Neuronal activity correlations are key to understanding how populations of neurons
collectively encode information. While two-photon calcium imaging has created a unique …

Highlights•Numerous mapping efforts are generating electron-microscopy wiring diagrams
of neural circuits or entire brains.•Detailed connectivity data are now being used in the …

A key problem in systems neuroscience is to characterize how populations of neurons
encode information in their patterns of activity. An understanding of the encoding process is …

Two-photon optogenetics has transformed our ability to probe the structure and function of
neural circuits. However, achieving precise optogenetic control of neural ensemble activity …

The pattern of neural activity evoked by a stimulus can be substantially affected by ongoing
spontaneous activity. Separating these two types of activity is particularly important for …

Dynamic latent variable modelling has provided a powerful tool for understanding how
populations of neurons compute. For spiking data, such latent variable modelling can treat …

The availability of both anatomical connectivity and brain-wide neural activity measurements
in C. elegans make the worm a promising system for learning detailed, mechanistic models …