IEEE Trans Neural Syst Rehabil Eng. 2017 Sep;25(9):1387-1396. doi: 10.1109/TNSRE.2016.2636133. Epub 2016 Dec 6.
The dopamine (DA) neurons found in the ventral tegmental area (VTA) are widely involved in the addiction and natural reward circuitry of the brain. Their firing patterns were shown to be important modulators of dopamine release and repetitive burst-like firing activity was highlighted as a major firing pattern of DA neurons in the VTA. In the present study we use a state space model to characterize the DA neurons firing patterns, and trace transitions of neural activity through bursting and non-bursting states. The hidden semi-Markov model (HSMM) framework, which we use, offers a statistically principled inference of bursting states and considers VTA DA firing patterns to be generated according to a Gamma process. Additionally, the explicit Gamma-based modeling of state durations allows efficient decoding of underlying neural information. Consequently, we decode and segment our single unit recordings from DA neurons in VTA according to the sequence of statistically discriminated HSMM states. The segmentation is used to study bursting state characteristics in data recorded from rats prenatally exposed to nicotine (6 mg/kg/day starting with gestational day 3) and rats from saline treated dams. Our results indicate that prenatal nicotine exposure significantly alters burst firing patterns of a subset of DA neurons in adolescent rats, suggesting nicotine exposure during gestation may induce severe effects on the neural networks involved in addiction and reward.
腹侧被盖区(VTA)中的多巴胺(DA)神经元广泛参与大脑的成瘾和自然奖励回路。它们的放电模式被证明是多巴胺释放的重要调节剂,重复爆发样放电活动被突出为 VTA 中 DA 神经元的主要放电模式。在本研究中,我们使用状态空间模型来描述 DA 神经元的放电模式,并通过爆发和非爆发状态跟踪神经活动的转变。我们使用的隐藏半马尔可夫模型(HSMM)框架提供了爆发状态的统计推理,并认为 VTA DA 放电模式是根据伽马过程产生的。此外,基于 Gamma 的状态持续时间的显式建模允许对潜在神经信息进行有效的解码。因此,我们根据统计上有区别的 HSMM 状态的序列对 VTA 中的 DA 神经元进行了单单位记录的解码和分段。分段用于研究从产前暴露于尼古丁(从妊娠第 3 天开始每天 6mg/kg)的大鼠和来自盐水处理的母体的大鼠中记录的数据的爆发状态特征。我们的结果表明,产前尼古丁暴露显著改变了青春期大鼠中一部分 DA 神经元的爆发放电模式,这表明妊娠期间暴露于尼古丁可能对成瘾和奖励相关的神经网络产生严重影响。