Department of Psychiatry, Department of Neuroscience & Physiology, New York University School of Medicine, New York, NY 10016, United States of America. Department of Biomedical Engineering, Tsinghua University, Beijing, People's Republic of China.
J Neural Eng. 2019 Apr;16(2):026038. doi: 10.1088/1741-2552/ab0474. Epub 2019 Feb 5.
The orofacial primary motor cortex (MIo) plays a critical role in controlling tongue and jaw movements during oral motor functions, such as chewing, swallowing and speech. However, the neural mechanisms of MIo during naturalistic feeding are still poorly understood. There is a strong need for a systematic study of motor cortical dynamics during feeding behavior.
To investigate the neural dynamics and variability of MIo neuronal activity during naturalistic feeding, we used chronically implanted micro-electrode arrays to simultaneously recorded ensembles of neuronal activity in the MIo of two monkeys (Macaca mulatta) while eating various types of food. We developed a Bayesian nonparametric latent variable model to reveal latent structures of neuronal population activity of the MIo and identify the complex mapping between MIo ensemble spike activity and high-dimensional kinematics.
Rhythmic neuronal firing patterns and oscillatory dynamics are evident in single-unit activity. At the population level, we uncovered the neural dynamics of rhythmic chewing, and quantified the neural variability at multiple timescales (complete feeding sequences, chewing sequence stages, chewing gape cycle phases) across food types. Our approach accommodates time-warping of chewing sequences and automatic model selection, and maps the latent states to chewing behaviors at fine timescales.
Our work shows that neural representations of MIo ensembles display spatiotemporal patterns in chewing gape cycles at different chew sequence stages, and these patterns vary in a stage-dependent manner. Unsupervised learning and decoding analysis may reveal the link between complex MIo spatiotemporal patterns and chewing kinematics.
口腔运动功能(如咀嚼、吞咽和言语)期间,口面初级运动皮层(MIo)在控制舌和颌运动方面起着关键作用。然而,自然进食过程中 MIo 的神经机制仍知之甚少。非常需要对进食行为过程中的运动皮层动力学进行系统研究。
为了研究自然进食过程中 MIo 神经元活动的神经动力学和可变性,我们使用慢性植入的微电极阵列同时记录两只猕猴(Macaca mulatta)MIo 中的神经元活动集合,同时让它们吃各种类型的食物。我们开发了一种贝叶斯非参数潜在变量模型来揭示 MIo 神经元群体活动的潜在结构,并确定 MIo 集合尖峰活动与高维运动学之间的复杂映射。
在单细胞活动中可以明显看到节律性神经元放电模式和振荡动力学。在群体水平上,我们揭示了节律性咀嚼的神经动力学,并在多个时间尺度(完整进食序列、咀嚼序列阶段、咀嚼张口周期阶段)量化了不同食物类型的神经可变性。我们的方法可以适应咀嚼序列的时间扭曲和自动模型选择,并在精细时间尺度上将潜在状态映射到咀嚼行为。
我们的工作表明,MIo 集合的神经表示在不同咀嚼序列阶段的咀嚼张口周期中显示出时空模式,并且这些模式以阶段依赖的方式变化。无监督学习和解码分析可能揭示复杂 MIo 时空模式与咀嚼运动学之间的联系。