Deep Brain Stimulation of Nucleus Basalis of Meynert improves learning in rat model of dementia

Deepak Kumbhare, Megan Rajagopal,Jamie Toms,Anne Freelin, George Weistroffer, Nicholas McComb, Sindhu Karnam, Adel Azghadi, Kevin S. Murnane,Mark S. Baron,Kathryn L. Holloway

biorxiv(2024)

引用 0|浏览0
暂无评分
摘要
Background Deep brain stimulation (DBS) of the nucleus basalis of Meynert (NBM) has been preliminarily investigated as a potential treatment for dementia. The degeneration of NBM cholinergic neurons is a pathological feature of many forms of dementia. Although stimulation of the NBM has been demonstrated to improve learning, the ideal parameters for NBM stimulation have not been elucidated. This study assesses the differential effects of varying stimulation patterns and duration on learning in a dementia rat model. Methods 192-IgG-saporin (or vehicle) was injected into the NBM to produce dementia in rats. Next, all rats underwent unilateral implantation of a DBS electrode in the NBM. The experimental groups consisted of i-normal, ii-untreated demented, and iii-demented rats receiving NBM DBS. The stimulation paradigms included testing different modes (tonic and burst) and durations (1-hr, 5-hrs, and 24-hrs/day) over 10 daily sessions. Memory was assessed pre- and post-stimulation using two established learning paradigms: novel object recognition (NOR) and auditory operant chamber learning. Results Both normal and stimulated rats demonstrated improved performance in NOR and auditory learning as compared to the unstimulated demented group. The burst stimulation groups performed better than the tonic stimulated group. Increasing the daily stimulation duration to 24-hr did not further improve cognitive performance in an auditory recognition task and degraded the results on a NOR task as compared with 5-hr. Conclusion The present findings suggest that naturalistic NBM burst DBS may offer a potential effective therapy for treating dementia and suggests potential strategies for the reevaluation of current human NBM stimulation paradigms. ### Competing Interest Statement The authors have declared no competing interest.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要