With their 'all-or-none'action potential responses, single neurons (or units) are accepted as
the basic computational unit of the brain. There is extensive animal literature to support the …

Brain scientists are now capable of collecting more data in a single experiment than
researchers a generation ago might have collected over an entire career. Indeed, the brain …

The projection neurons (PNs), reconstructed from electron microscope (EM) images of the
Drosophila olfactory system, offer a detailed view of neuronal anatomy, providing glimpses …

Single-cell RNA sequencing (scRNAseq) enables the profiling of the transcriptomes of
individual cells, thus characterizing the heterogeneity of biological samples since scRNAseq …

Understanding and discriminating the spatiotemporal patterns of activity generated by in
vitro and in vivo neuronal networks is a fundamental task in neuroscience and …

Recognizing that diverse morphologies of neurons are reminiscent of structures of branched
polymers, we put forward a principled and systematic way of classifying neurons that …

Since their introduction in late 80s, convolutional neural networks and auto-encoder
architectures have shown to be powerful for automatic feature extraction and information …

Statistical methods, and in particular deep learning models, have achieved remarkable
success in computer vision, speech recognition, and natural language processing due to the …

The previous chapters have dealt with the complex adaptive nature of the genome. Similar
concepts in terms of interacting elements, selforganization and adaptation can be applied at …

Epilepsy is an archetypal brain network disorder. Despite two decades of research
elucidating network mechanisms of disease and correlating these with outcomes, the clinical …