Agam Yigal, Bullock Daniel, Sekuler Robert
Volen Center for Complex Systems, Brandeis University, Waltham, MA 02454, USA.
J Neurophysiol. 2005 Oct;94(4):2832-43. doi: 10.1152/jn.00366.2005. Epub 2005 Jul 13.
A fundamental challenge in neuroscience is to understand the mechanisms by which multicomponent actions are represented and sequenced for production. We addressed this challenge with a movement-imitation task in which subjects viewed the quasi-random, two-dimensional movements of a disc and then used a stylus to reproduce the remembered trajectory. The stimulus disc moved along straight segments, which differed sufficiently from one another that it was possible to trace individual segments' fate in the resulting movement imitation. A biologically based segmentation algorithm decomposed each imitation into segments whose directions could be compared with those of homologous segments in the model. As the number of linked segments in a stimulus model grew from three to seven, imitation became less accurate, with segments more likely to be deleted, particularly from a model's final stages. When fidelity of imitation was assessed segment by segment, the resulting serial position curves showed a strong primacy effect and a moderate recency effect. Analysis of pairwise transposition errors revealed a striking preponderance of exchanges between adjacent segments that, along with the serial position effects, supports a competitive queuing model of sequencing. In analogy to results with verbal serial recall, repetition of one directed segment in the model reduced imitation quality. Results with longer stimulus models suggest that the segment-by-segment imitation generator may be supplemented in the final stages of imitation by an error-signal driven overlay that produces a late-course, real-time correction. Results are related to neural mechanisms that are known to support sequential motor behavior and working memory.
神经科学中的一个基本挑战是理解多组分动作被表征和排序以进行产生的机制。我们通过一项动作模仿任务来应对这一挑战,在该任务中,受试者观看一个圆盘的准随机二维运动,然后使用触控笔重现记忆中的轨迹。刺激圆盘沿直线段移动,各直线段之间差异足够大,以至于可以追踪各个线段在后续动作模仿中的走向。一种基于生物学的分割算法将每次模仿分解为多个线段,其方向可与模型中同源线段的方向进行比较。随着刺激模型中相连线段的数量从三条增加到七条,模仿的准确性降低,线段更有可能被删除,尤其是在模型的最后阶段。当逐段评估模仿的保真度时,得到的系列位置曲线显示出强烈的首因效应和适度的近因效应。对成对换位错误的分析揭示了相邻线段之间的交换明显占优势,这与系列位置效应一起,支持了一种排序的竞争排队模型。与言语系列回忆的结果类似,模型中一个有向线段的重复会降低模仿质量。较长刺激模型的结果表明,逐段模仿生成器在模仿的最后阶段可能会由一个误差信号驱动的叠加层进行补充,该叠加层会产生后期的实时校正。这些结果与已知支持顺序运动行为和工作记忆的神经机制有关。