Symbolic analysis of swimming trajectories reveals scale invariance and provides a model for fish locomotion
Symbolic analysis of swimming trajectories reveals scale invariance and provides a model for fish locomotion
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DOI：
10.1142/s0218348x03002166
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发表时间：
2003-09-01
影响因子：
4.7
通讯作者：
Korn, H
中科院分区：
文献类型：
--
作者：
Faure, P;Neumeister, H;Korn, H
我们质疑是否可以将复杂的行为（例如鱼的游泳）更好地定量描述为一系列离散事件或状态，而不是使用可能受到固有变异性影响的经典运动学测量。在这里，不同的状态以符号的组合表示，是根据动物的位置（A：水族箱的外围，B：水族箱的内部）和速度（快和慢）来定义的。我们观察到，连续状态中花费的时间间隔的分布不是高斯分布。相反，它们符合与潜在的类似列维过程相关的幂律，该过程具有更长的间隔，主要是由于长时间的相对不活动。此外，我们的数据表明游泳行为可归因于两个内在系统之间的相互作用。第一个由状态之间的概率转换矩阵表示，并控制它们的顺序组织，而第二个由区间分布定义，确定每个状态所花费的时间。该动力学模型可检测低剂量神经活性化合物的微妙影响，并确定其特定的作用位点。我们建议这种范式可以应用于表征正常行为及其通过遗传或药理学操作的修改。
We have questioned whether a complex behavior, such as fish swimming, can be better described quantitatively as a sequence of discrete events or states than with classical kinematic measures which can be compromised by inherent variability. Here, the different states, expressed as combinations of symbols, were defined on the basis of the animal's location (A: periphery, and B: inner part of the aquarium) and speed (Fast and Slow). We observed that the distributions of time intervals spent in the successive states were not gaussian. Rather, they were fit by power laws associated with an underlying Levy-like process which has more long intervals, primarily due to prolonged periods of relative inactivity. Furthermore, our data suggest that the swimming behavior can be attributed to interactions between two intrinsic systems. One is represented by the matrix of transition of probabilities between states and controls their sequential organization while the second, which is defined by interval distributions, determines the time spent in each state. This kinetic model detects subtle effects of low doses of neuroactive compounds, and identifies their specific locus of action. We propose that this paradigm can be applied to characterize normal behavior and its modifications by genetic or pharmacological manipulations.