Computational modeling of autonomic nerve stimulation: Vagus et al.

Computational models of electrical stimulation, block and recording of autonomic nerves enable analysis of mechanisms of action underlying neural responses and design of optimized stimulation parameters. We reviewed advances in computational modeling of autonomic nerve stimulation, block, and recording over the past five years, with a focus on vagus nerve stimulation, including both implanted and less invasive approaches. Few models achieved quantitative validation, but integrated computational pipelines increase the reproducibility, reusability, and accessibility of computational modeling.

Circuits and mechanisms for TMS-induced corticospinal waves: Connecting sensitivity analysis to the network graph.

Transcranial magnetic stimulation (TMS) is a non-invasive, FDA-cleared treatment for neuropsychiatric disorders with broad potential for new applications, but the neural circuits that are engaged during TMS are still poorly understood. Recordings of neural activity from the corticospinal tract provide a direct readout of the response of motor cortex to TMS, and therefore a new opportunity to model neural circuit dynamics. The study goal was to use epidural recordings from the cervical spine of human subjects to develop a computational model of a motor cortical macrocolumn through which the mechanisms underlying the response to TMS, including direct and indirect waves, could be investigated.

Reverse-engineered models reveal differential membrane properties of autonomic and cutaneous unmyelinated fibers.

Unmyelinated C-fibers constitute the vast majority of axons in peripheral nerves and play key roles in homeostasis and signaling pain. However, little is known about their ion channel expression, which controls their firing properties. Also, because of their small diameters (~ 1 μm), it has not been possible to characterize their membrane properties using voltage clamp.

Highly efficient modeling and optimization of neural fiber responses to electrical stimulation.

Peripheral neuromodulation has emerged as a powerful modality for controlling physiological functions and treating a variety of medical conditions including chronic pain and organ dysfunction. The underlying complexity of the nonlinear responses to electrical stimulation make it challenging to design precise and effective neuromodulation protocols. Computational models have thus become indispensable in advancing our understanding and control of neural responses to electrical stimulation.