Balerna Myriam, Ghosh Arko
1Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
2Institute of Psychology, Cognitive Psychology Unit, Leiden University, Leiden, The Netherlands.
NPJ Digit Med. 2018 Mar 7;1:4. doi: 10.1038/s41746-017-0011-3. eCollection 2018.
Unconstrained day-to-day activities are difficult to quantify and how the corresponding movements shape the brain remain unclear. Here, we recorded all touchscreen smartphone interactions at a sub-second precision and show that the unconstrained day-to-day behavior captured on the phone reflects in the simple sensorimotor computations measured in the laboratory. The behavioral diversity on the phone, the speed of interactions, the amount of social & non-social interactions, all uniquely influenced the trial-to-trial motor variability used to measure the amount of intrinsic neuronal noise. Surprisingly, both the motor performance and the early somatosensory cortical signals (assessed using EEG in passive conditions) became noisier with increased social interactions. Inter-individual differences in how people use the smartphone can help thus decompose the structure of low-level sensorimotor computations.
无约束的日常活动难以量化,且相应的运动如何塑造大脑仍不清楚。在这里,我们以亚秒级精度记录了所有触摸屏智能手机交互,并表明在手机上捕捉到的无约束日常行为反映在实验室测量的简单感觉运动计算中。手机上的行为多样性、交互速度、社交与非社交交互的数量,都独特地影响了用于测量内在神经元噪声量的逐次运动变异性。令人惊讶的是,随着社交互动的增加,运动表现和早期体感皮层信号(在被动条件下使用脑电图评估)都变得更嘈杂。人们使用智能手机方式的个体差异因此有助于分解低水平感觉运动计算的结构。