Katharina A. Schindlbeck, The Feinstein Institutes for Medical Research, USA
Martin H. Niethammer, The Feinstein Institutes for Medical Research, USA
Translational research has furthered our understanding of neurodegenerative diseases like Parkinson’s disease (PD), in which neuronal dysfunction spreads along discrete brain circuits despite the heterogeneity of symptomatic disease manifestations.
The greatest unmet needs in PD are treatments that slow the progression of symptoms. The discovery of genetic variants causing or increasing the risk for PD has provided the field with a new array of potential therapies that are now entering clinical trials. Beyond that, efforts are on the way to target circuit dysfunction using focused and personalized interventions including deep brain stimulation, and transcranial Direct-Current Stimulation (tDCS). Modern neuroimaging in conjunction with computational algorithms based on spatial pattern recognition and machine learning have led to the development of biomarkers, allowing clinical trials to target genetically defined subtypes or serve as secondary outcome measures in clinical trials. Network imaging techniques also hold great promise in studying prodromal stages of the disease and the changes underlying the phenoconversion to manifest disease and tackle disease progression.
This thematic series aims to provide a collection of Reviews and Primary Research Articles that will provide a valuable overview of novel personalized therapeutic approaches and highlight the advances of network imaging biomarkers in facilitating novel therapeutic approaches and furthering our understanding of the complexities of this disease. We welcome the submission of additional manuscripts to this series*.
*Articles must be submitted through Editorial Manager. Please indicate at the Additional Information stage of submission that you are submitting to the “Parkinson's disease as a circuit disorder…” thematic series. All manuscripts received will be subject to peer review as is standard for the journal.