Computer models can make transcranial electric stimulation a better tool for research and therapy.

Deep brain stimulation can selectively modify neural activity within the subthalamic nucleus to modify decisions under uncertainty in human subjects.

Direct in-vivo measurements in the human brain test validity of detailed computational models of trancranial electric stimulation and show that electric fields in the brain are weaker than currently assumed.

A general machine learning scheme for integrating time-series data from single-molecule experiments and molecular dynamics simulations is proposed and successfully demonstrated for the folding dynamics of the WW domain.

An atomic model of the bacterial chemosensory array obtained through the synthesis of cryo-electron tomography and large-scale molecular-dynamics simulations reveals a new kinase conformation during signaling events.

A cellular-level in vivo investigative method that provides unprecedented insights into the dynamics of neuronal activities evoked by transcranial magnetic stimulation.

Studying the activity of cortical neurons in rats reveals the subcellular effects of transcranial magnetic stimulation, which is used for the non-invasive treatment of a variety of brain disorders.

High-frequency stimulation of the ventromedial prefrontal cortex, which enhances memory and hippocampal neurogenesis, is a novel target for treatment of dementia-related diseases.

Simulations of the unliganded human hemoglobin tetramer, which for the first time yield a thermodynamically stable system, cast doubts on the use of standard solvent box sizes for molecular dynamics studies of biological macromolecules.

Forniceal deep brain stimulation is a promising treatment for several neuropsychiatric disorders as it upregulates synaptic and neurogenesis-associated genes, normalizes genes misregulated in Rett syndrome mice, and regulates genes altered in intellectual disability and major depression.