Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
World Neurosurg. 2011 May-Jun;75(5-6):758-763.e4. doi: 10.1016/j.wneu.2010.11.008.
To describe an approach to the analysis of deep brain stimulation (DBS) of the subthalamic nucleus (STN) using a hidden semi-Markov model (HsMM) and early results of the analysis of microelectrode recordings for STN DBS.
The author simulated the anatomy and electrophysiology of STN DBS and built a seven-state model to compare Hidden Markov model (HMM) and HsMM approaches.
Accuracy of these competing models was similar for correctly identifying brain nuclei; however, HsMMs showed superior specificity in detecting microelectrode passes traversing the STN.
Further clinical work must be done; however, based on these data, HsMMs may be best suited to computer-assisted anatomic delineation for DBS.
描述一种使用隐半马尔可夫模型（HsMM）分析丘脑底核（STN）深部脑刺激（DBS）的方法，并分析 STN-DBS 的微电极记录的早期结果。
作者模拟了 STN-DBS 的解剖结构和电生理学，并构建了一个七状态模型来比较隐马尔可夫模型（HMM）和 HsMM 方法。
这些竞争模型在正确识别脑核方面的准确性相似；然而，HsMM 在检测穿过 STN 的微电极通过方面具有更高的特异性。
需要进一步开展临床工作；然而，根据这些数据，HsMM 可能最适合 DBS 的计算机辅助解剖描绘。
