Striatal Activity during Intentional Switching Depends on Pattern Stability
Striatal Activity during Intentional Switching Depends on Pattern Stability
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DOI：
10.1523/jneurosci.2673-09.2010
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发表时间：
2010-03-03
影响因子：
5.3
通讯作者：
Kelso, J. A. Scott
中科院分区：
文献类型：
--
作者：
De Luca, Cinzia;Jantzen, Kelly J.;Kelso, J. A. Scott
协调动力学的理论框架假设了互补的神经机制，即在可能使行为变得不稳定的情况下维持复杂的行为模式，并在内部或外部条件需要改变时自愿在行为之间切换。基底节是已知的在选择和维持有意行为中发挥作用的候选神经结构。在这里，我们使用功能磁共振成像来探索基底节在故意切换双手协调模式中的作用，这些双手协调模式的稳定性随运动速度的不同而不同。模式动力学和转换的关键指标被用来将行为映射到相关的神经回路，以确定特定行为变量和激活的大脑区域之间的关系。结果表明，壳核的活动对模式稳定性高度敏感：当受试者被要求从更稳定的模式切换到更不稳定的模式时，双侧壳核的活动比反之亦然。由于壳蛋白的活性在切换过程之前和期间都与模式稳定性相关，因此它的作用可能是通过对内在动力学的参数调制来选择所需的动作并抑制竞争的动作。尽管我们的结果与最近关于基底神经节功能的计算模型相一致，但我们的结果进一步表明，模式稳定性决定了基底神经节如何有效和成功地在反应备选方案中进行选择。
The theoretical framework of coordination dynamics posits complementary neural mechanisms to maintain complex behavioral patterns under circumstances that may render them unstable and to voluntarily switch between behaviors if changing internal or external conditions so demand. A candidate neural structure known to play a role in both the selection and maintenance of intentional behavior is the basal ganglia. Here, we use functional magnetic resonance imaging to explore the role of basal ganglia in intentional switching between bimanual coordination patterns that are known to differ in their stability as a function of movement rate. Key measures of pattern dynamics and switching were used to map behavior onto the associated neural circuitry to determine the relation between specific behavioral variables and activated brain areas. Results show that putamen activity is highly sensitive to pattern stability: greater activity was observed in bilateral putamen when subjects were required to switch from a more to a less stable pattern than vice versa. Since putamen activity correlated with pattern stability both before and during the switching process, its role may be to select desired actions and inhibit competing ones through parametric modulation of the intrinsic dynamics. Though compatible with recent computational models of basal ganglia function, our results further suggest that pattern stability determines how the basal ganglia efficiently and successfully select among response alternatives.