Tackling the functional role of multisensory interactions in behavioural benefits: A combined EEG and computational modelling approach

多种感官的可用性对控制行为非常有益。不同的感官不仅增加了可感知信号的范围，而且还提供了冗余信号，通过组合，可以更好地估计外部事件和/或更快地实现主观目标。然而，我们还没有完全了解指导多感官信号组合的大脑功能。引人注目的是，最近的一些研究已经证明了早期感觉皮层参与多感觉过程，在许多情况下，甚至包括传统上被认为只维持单感觉过程的初级感觉皮层。尽管如此，这些早期多感官互动的确切功能角色及其对行为益处的贡献仍然令人困惑（Kayser, 2010）。拟议的博士项目将通过跨学科的方法解决人类的多感官相互作用。该项目将利用一种新的多感觉整合计算模型来解释最先进的稳态视觉诱发电位（SSVEP）记录（Norcia et al., 2015）。SSVEP提供了为不同感官提供频率标签输入的独特能力。通过标记每一种感觉的输入，就有可能跟踪从单感觉输入到多感觉交互的信息流。这些标签保留了其感官来源的明确特征，甚至在多感官过程组合之后。其次，我们将分析一种新的计算建模方法所提供的神经生理学数据，该方法可以精确预测处理交互作用，这些交互作用有助于在行为和潜在感知决策中观察到的好处（Otto & Mamassian, 2012）。将先进的生理记录与尖端的计算模型相结合，将使人们对大脑如何结合各种感官的信息有前所未有的了解。

The availability of multiple senses is highly beneficial to control behaviour. Different senses not only increase the spectrum of perceivable signals but also provide redundant signals that, by combination, enable better estimates of external events and/or faster achievements of subjective goals. However, we do not yet fully understand the brain functions that guide the combination of multisensory signals. Strikingly, a number of recent studies have demonstrated the involvement of early sensory cortices in multisensory processes, which in many cases included even primary sensory cortices that have traditionally been considered to maintain unisensory processes only. Still, the exact functional role of these early multisensory interactions and their contribution to behavioural benefits remain puzzling (Kayser, 2010). The proposed PhD project will tackle multisensory interactions in humans by an interdisciplinary approach. The project will utilize a new computational model of multisensory integration to interpret recordings from state-of-the-art steady-state visual evoked potential (SSVEP) recordings (Norcia et al., 2015). The SSVEP provides for the unique ability to frequency-tag input presented to the different senses. By tagging the input to each sense it is possible to track the flow of information from unisensory input to multisensory interactions. These tags retain unambiguous signatures of their sensory origin even after being combined by multisensory processes. Second, we will analyse the neurophysiological data informed by a new computational modelling approach, which allows for precise predictions about the processing interactions that have contributed to the benefits observed in behaviour and the underlying perceptual decisions (Otto & Mamassian, 2012). The combination of advanced physiological recording with cutting-edge computational modelling will enable an unprecedented understanding of how the brain combines information across the senses.