Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences
Fueled by breakthrough technology developments, the biological, biomedical, and
behavioral sciences are now collecting more data than ever before. There is a critical need …
behavioral sciences are now collecting more data than ever before. There is a critical need …
[HTML][HTML] The quest for multiscale brain modeling
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 …
repertoire of the organ, remains challenging. In principle, it should be possible to model …
Multiscale modeling meets machine learning: What can we learn?
Abstract Machine learning is increasingly recognized as a promising technology in the
biological, biomedical, and behavioral sciences. There can be no argument that this …
biological, biomedical, and behavioral sciences. There can be no argument that this …
Self-organized criticality in the brain
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 …
second-order phase transition at which interactions between system components lead to …
[HTML][HTML] Systematic integration of structural and functional data into multi-scale models of mouse primary visual cortex
Structural rules underlying functional properties of cortical circuits are poorly understood. To
explore these rules systematically, we integrated information from extensive literature …
explore these rules systematically, we integrated information from extensive literature …
Decoding the brain: From neural representations to mechanistic models
A central principle in neuroscience is that neurons within the brain act in concert to produce
perception, cognition, and adaptive behavior. Neurons are organized into specialized brain …
perception, cognition, and adaptive behavior. Neurons are organized into specialized brain …
Generative learning for forecasting the dynamics of high-dimensional complex systems
We introduce generative models for accelerating simulations of high-dimensional systems
through learning and evolving their effective dynamics. In the proposed Generative Learning …
through learning and evolving their effective dynamics. In the proposed Generative Learning …
BrainPy, a flexible, integrative, efficient, and extensible framework for general-purpose brain dynamics programming
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 …
brain dynamics modeling. To facilitate this process, it is crucial to develop a general-purpose …
Absence of paresthesia during high-rate spinal cord stimulation reveals importance of synchrony for sensations evoked by electrical stimulation
Electrically activating mechanoreceptive afferents inhibits pain. However, paresthesia
evoked by spinal cord stimulation (SCS) at 40–60 Hz becomes uncomfortable at high pulse …
evoked by spinal cord stimulation (SCS) at 40–60 Hz becomes uncomfortable at high pulse …
Human Neocortical Neurosolver (HNN), a new software tool for interpreting the cellular and network origin of human MEG/EEG data
Magneto-and electro-encephalography (MEG/EEG) non-invasively record human brain
activity with millisecond resolution providing reliable markers of healthy and disease states …
activity with millisecond resolution providing reliable markers of healthy and disease states …