A Dynamic Diversity of Dopamine Neurons

最近发现的不同亚群的中脑多巴胺(DA)神经元在 它们在体内的两种主要活动模式，紧张性(单峰)放电和相性爆裂。这些射击拍击- 燕鸥及其之间的过渡对于驱动轴突和树突多巴胺的释放是必不可少的，并且 从而用于控制皮质纹状体回路的信号处理和行为功能。我们将证明这一点 这些模式背后的离子机制以及这些模式的信息内容是不同的 在DA亚群之间，通过不同类型的多巴胺能信号对行为控制具有强烈的意义。目标1将揭示腹侧被盖的经典慢放电和新近发现的快放电DA神经元在紧张性放电上的不同的生物物理机制 面积(VTA)。这些机制可能也有助于它们在体内产生不同的爆发频率。目标 2将阐明内侧黑质(SN)爆发的生物物理基础，这是由ATP敏感引起的 K(K-ATP)通道和新奇探索所必需的K(K-ATP)通道，而不是外侧SN中的爆发 受钙激活的SK-K通道控制，可能与习惯性运动序列有关。目标3将定义 两个投射特异性DA亚群的行为功能在体内具有最独特的放电模式：VTA DA神经元投射到伏隔内侧壳的速度更快，这可能是 参与突显或奖赏信号，而不是吻侧内侧的SN DA神经元。 伏隔层的外壳，在新奇事物中介的探索过程中表现出连续和缓慢的破裂。 不同DA行为相关放电模式的不同生物物理控制机制 在许多已知的DA信号障碍中，亚群可能受到选择性的影响，包括成瘾、精神分裂症和帕金森病(PD)。例如，减少对黑质DA神经元选择性的活性依赖的钙负荷是一种有前途的帕金森病神经保护方法。进一步剖析了 VTA和SN DA亚群的动力学和分子生物物理学的差异被提出 在这里，有望导致更有选择性的量身定做的治疗策略，调整放电模式 特定的DA亚群。这个项目是基于最近在模拟生物多样性方面取得的令人兴奋的进展 这有助于解释Roeper博士开创的DA神经元的多样性。 理论和计算方法结合了非线性动力学和分叉分析 形态逼真的多隔室模型。罗珀博士的实验室使用了最先进的技术， 包括逆行追踪、成年小鼠切片电生理学、通道选择性药理学、可光切换的K-ATP阻滞剂和动态钳夹，加上细胞外记录和结合单个DA神经元的细胞旁标记和小鼠体内已识别的轴突投射，以量化多样性 对发展议程人口的综合评估，形成了一个检验模型预测的协同环路。

Recently-identified, distinct subpopulations of midbrain dopamine (DA) neurons exhibit differences in their two primary in vivo activity patterns, tonic (single spike) firing and phasic bursting. These firing pat- terns, and transitions between them, are essential for driving axonal and dendritic dopamine release, and thus for controlling signal processing and behavioral functions of cortico-striatal circuits. We will show that the ionic mechanisms underlying these patterns, as well as the information content of these patterns, differ between DA subpopulations, with strong implications for behavioral control via distinct types of dopaminergic signaling. Aim 1 will uncover the biophysical mechanisms underlying the difference in tonic firing between the classic slow-firing and the more recently identified fast-firing DA neurons in the ventral tegmental area (VTA). These mechanisms likely also contribute to their distinct frequencies of burst firing in vivo. Aim 2 will elucidate the biophysical basis of bursts in the medial substantia nigra (SN), enabled by ATP-sensitive K+ (K-ATP) channels and necessary for novelty-induced exploration, versus bursts in the lateral SN that are controlled by Ca2+-activated SK K+ channels and may gate habitual motor sequences. Aim 3 will define the behavioral functions of two projection-specific DA subpopulations with the most distinctive in vivo firing patterns: the faster bursting VTA DA neurons projecting to the medial shell of the accumbens, which might be involved in salience or reward signaling, versus the medio-rostral SN DA neurons projecting to the lateral shell of the accumbens, which display continuous and slower bursting during novelty-mediated exploration. Differential biophysical control mechanisms of behaviorally-relevant firing patterns for distinct DA subpopulations may be selectively affected in the many known disorders of DA signaling, including addiction, schizophrenia and Parkinson's disease (PD). For example, a reduction in activity-dependent Ca2+ loading selective for SN DA neurons is a promising neuroprotective approach in PD. The further dissection of differences in the dynamics and molecular biophysics of both VTA and SN DA subpopulations proposed herein promises to lead to even more selectively tailored therapeutic strategies that tune the firing pattern in specific DA subpopulations. This project is based on recent, exciting advances in modeling the diversity of DA neurons in Dr. Canavier's lab that help explain the diversity of DA neurons pioneered by Dr. Roeper. The theoretical and computational approaches combine nonlinear dynamics and bifurcation analyses with morphologically realistic multi-compartmental modeling. Dr. Roeper's lab uses state of the art techniques, including retrograde tracing, adult mouse slice electrophysiology, channel-selective pharmacology, photoswitchable K-ATP blockers, and Dynamic Clamp, plus extracellular recordings and combined with juxtacellular labeling of single DA neurons with identified axonal projections in mice in vivo, to quantify the diversity of the DA populations in a comprehensive fashion, forming a synergistic loop for testing model predictions.