Prehension Synergies

描述（由申请人提供）：该提案的目标是探索中枢神经系统在操纵手持物体时使用的策略。最近，我们开发了一种新的数学逆优化方法-“分析逆优化”（ANIO）方法-允许从实验记录中重建未知的成本函数（CF）（Terekhov等人，2010）。研究的第一线将涉及该方法的进一步发展及其在人类大脑中的应用。实验1-A将探讨是否所有的表演者使用同一类的CF。实验1-B将测试ANIO方法是否产生在延长的时间段内可再现的CF的估计值。实验1-C将探索CF类函数对参与任务的手指数量的依赖性。实验1-D将解决多指扩展中的优化和可变性之间的相互作用。实验2-A将检验加和性假设：假设手指力量受到因素A、B、C等的影响。该假设假设与上述因素相关的神经命令的影响是加和性的。在统计学上，这意味着这些因素的影响是显著的，而它们之间的相互作用不是。实验2B将加性假设扩展到复杂动态任务。我们期望发现抓取力的变化模式是两个命令的影响之和，这两个命令分别与沿着和垂直于抓取方向的运动相关联。实验2C将处理测试模板控制假设，根据该假设，对于对象几何形状和局部摩擦的每个给定组合，表演者选择手指力模式（“模板”），然后用负载力缩放手指力。实验2- D将包括两个部分，其中将探索一个手指疲劳或所有手指疲劳的影响。目标是测试疲劳手指是否施加与疲劳前相同的当前最大力的%%。从本质上讲，实验将探索的“鲁棒性”的控制，使用局部疲劳作为扰动工具。在“鲁棒性”下，我们理解当其中一个贡献元素的性能潜力降低时执行任务的能力。

DESCRIPTION (provided by applicant): The goal of the proposal is to explore the strategies used by the central nervous system when manipulating hand- held objects. Recently we developed a new mathematical method of inverse optimization - the 'Analytic Inverse Optimization' (ANIO) method -that allows for reconstructing unknown cost functions (CF) from experimental recordings (Terekhov et al. 2010). The first line of research will deal with the further development of the method and its application to human prehension. Experiment 1-A will explore whether all performers use CFs of the same class. Experiment 1-B will test whether the ANIO method yields estimates of the CFs that are reproducible over protracted periods of time. Experiment 1-C will explore the dependence of the CF class of functions on the number of fingers involved in the task. Experiment 1-D will address interaction between the optimization and variability in multi-finger prehension. The second line of research is based on previous results obtained in our lab and is intended to test the following hypotheses: Experiment 2-A will test the additivity hypothesis: suppose that the digit forces are affected by factors A, B, C, etc. The hypothesis assumes that the effects of the neural commands associated with the above factors are additive. In statistical terms it means that the effects of the factors are significant while their interactions are not. Experiment 2B extends the additivity hypothesis to the complex dynamic tasks. We expect to find that the pattern of grasping force changes as a sum of the effects of two commands associated with the movements along and normal to grasp direction, respectively. Experiment 2C will deal with testing a template control hypothesis according to which for every given combination of the object geometry and local friction the performers select a digit force pattern ('template') and then scale the digit forces with the load force. Experiment 2- D will consist of two parts in which effects of one finger fatigue or fatigue of all fingers will be explored. The goal is to test whether the fatigued finger exerts the same %% of its current maximal force as it did prior to fatigue. Essentially, the experiment will explore the 'robustness' of prehension control, using local fatigue as a perturbation tool. Under 'robustness' we understand ability to perform a task when performance potential of one of the contributing elements is diminished.