Rens Natalie, Bode Stefan, Burianová Hana, Cunnington Ross
Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia.
Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, VIC, Australia.
Front Hum Neurosci. 2017 Dec 12;11:610. doi: 10.3389/fnhum.2017.00610. eCollection 2017.
There is evidence that neural patterns are predictive of voluntary decisions, but findings come from paradigms that have typically required participants to make arbitrary choices decisions in highly abstract experimental tasks. It remains to be seen whether proactive neural activity reflects upcoming choices for individuals performing decisions in more complex, dynamic, scenarios. In this functional Magnetic Resonance Imaging (fMRI) study, we investigated proactive neural activity for voluntary decisions compared with instructed decisions in a virtual environment, which more closely mimicked a real-world decision. Using partial least squares (PLS) analysis, we found that the frontoparietal and salience networks were associated with voluntary choice selection from a time at which decisions were abstract and preceded external stimuli. Using multi-voxel pattern analysis (MVPA), we showed that participants' choices, which were decodable from motor and visual cortices, could be predicted with lower accuracy for voluntary decisions than for instructed decisions. This corresponded to eye-tracking data showing that participants made a greater number of fixations to alternative options during voluntary choices, which might have resulted in less stable choice representations. These findings suggest that voluntary decisions engage proactive choice selection, and that upcoming choices are encoded in neural representations even while individuals continue to consider their options in the environment.
有证据表明神经模式能够预测自愿决策,但这些发现来自于一些范式,这些范式通常要求参与者在高度抽象的实验任务中做出任意选择。对于在更复杂、动态的场景中做出决策的个体而言,前瞻性神经活动是否反映即将做出的选择仍有待观察。在这项功能磁共振成像(fMRI)研究中,我们调查了在虚拟环境中与指令性决策相比,自愿决策的前瞻性神经活动,该虚拟环境更接近模拟现实世界的决策。使用偏最小二乘法(PLS)分析,我们发现额顶叶和突显网络与从决策抽象且先于外部刺激的时刻起的自愿选择相关。使用多体素模式分析(MVPA),我们表明,与指令性决策相比,从运动和视觉皮层可解码的参与者选择在自愿决策时的预测准确性较低。这与眼动追踪数据一致,该数据表明参与者在自愿选择过程中对替代选项进行了更多的注视,这可能导致选择表征不太稳定。这些发现表明,自愿决策涉及前瞻性选择,并且即使个体在环境中继续考虑其选项时,即将做出的选择也会编码在神经表征中。