Fueled by breakthrough technology developments, the biological, biomedical, and
behavioral sciences are now collecting more data than ever before. There is a critical need …

Addressing the multiscale organization of the brain, which is fundamental to the dynamic
repertoire of the organ, remains challenging. In principle, it should be possible to model …

Abstract Machine learning is increasingly recognized as a promising technology in the
biological, biomedical, and behavioral sciences. There can be no argument that this …

Self-organized criticality (SOC) refers to the ability of complex systems to evolve toward a
second-order phase transition at which interactions between system components lead to …

Structural rules underlying functional properties of cortical circuits are poorly understood. To
explore these rules systematically, we integrated information from extensive literature …

Elucidating the intricate neural mechanisms underlying brain functions requires integrative
brain dynamics modeling. To facilitate this process, it is crucial to develop a general-purpose …

Magneto-and electro-encephalography (MEG/EEG) non-invasively record human brain
activity with millisecond resolution providing reliable markers of healthy and disease states …

Electrically activating mechanoreceptive afferents inhibits pain. However, paresthesia
evoked by spinal cord stimulation (SCS) at 40–60 Hz becomes uncomfortable at high pulse …

Deep learning (DL) has proven to be a highly effective approach for developing models in
diverse contexts, including visual perception, speech recognition, and machine translation …

A complete understanding of the brain requires an integrated description of the numerous
scales and levels of neural organization. This means studying the interplay of genes and …