A Python library for model-centric development of adaptive deep brain stimulation (DBS).
The deployed package is available at PyPi::dbspace
This library was developed slowly over the course of my PhD work under Dr. Helen Mayberg and Dr. Robert Butera, between 2013-2022 (and beyond?). My PhD was focused on analysing timeseries from intracranial and extracranial recordings, particularly problematic ones with quirky noise sources. Combined with the "in my garage" efficacy and clinical context, this stressed to me the importance of establishing a priori models.
The goal of this library was to recenter DBS around the models we were using to treat patients, and enable a way to check in with data to shape those models.