Subthalamic nucleus deep brain stimulation modulates speech graphs in patients with Parkinson’s disease

Abstract

Graph theory enables a direct quantification of topological properties of any arbitrary network. Its application in neuroscience has unveiled topological changes of brain networks associated with various neurodegenerative diseases. This study used the graph theory to understand speech deficits in patients with Parkinson’s disease (PD). In particular, this study investigated the effect of subthalamic nucleus deep brain stimulation (STN-DBS) on the topology of speech graphs. Sixty patients with PD completed a standard semantic fluency test with DBS switched ON and OFF. A control group of sixty matched nonsurgical PD patients completed the test once. All verbal responses were recorded, transcripted, and transformed into directed speech graphs. Volumes of tissue activated (VTA) were estimated for three STN subregions, including sensorimotor, associative, and limbic parts. First, the patients with DBS OFF produced smaller and denser speech graphs than nonsurgical patients, showing fewer nodes, higher density, shorter diameter, and shorter average shortest path. Second, DBS partially reversed the effect of surgery, leading to larger and sparser speech graphs with more nodes, lower density, longer diameter, and longer average shortest path (ON versus OFF). Third, however, the left associative VTA negatively correlated with the DBS-induced diameter and average shortest path changes (ON versus OFF), suggesting that the patients with greater left associative STN stimulation tended to produce smaller and denser speech graphs. This study demonstrates that STN-DBS can partially restore the topological structure of speech graphs in PD patients. However, stimulating the left associative STN appears to disrupt speech graphs.