Shiramatsu Tomoyo Isoguchi, Mori Kanato, Ishizu Kotaro, Takahashi Hirokazu
Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan.
Institute for Quantitative Biosciences, The University of Tokyo, Tokyo, Japan.
Front Hum Neurosci. 2021 Sep 17;15:721476. doi: 10.3389/fnhum.2021.721476. eCollection 2021.
When the brain tries to acquire an elaborate model of the world, multisensory integration should contribute to building predictions based on the various pieces of information, and deviance detection should repeatedly update these predictions by detecting "errors" from the actual sensory inputs. Accumulating evidence such as a hierarchical organization of the deviance-detection system indicates that the deviance-detection system can be interpreted in the predictive coding framework. Herein, we targeted mismatch negativity (MMN) as a type of prediction-error signal and investigated the relationship between multisensory integration and MMN. In particular, we studied whether and how cross-modal information processing affected MMN in rodents. We designed a new surface microelectrode array and simultaneously recorded visual and auditory evoked potentials from the visual and auditory cortices of rats under anesthesia. Then, we mapped MMNs for five types of deviant stimuli: single-modal deviants in (i) the visual oddball and (ii) auditory oddball paradigms, eliciting single-modal MMN; (iii) congruent audio-visual deviants, (iv) incongruent visual deviants, and (v) incongruent auditory deviants in the audio-visual oddball paradigm, eliciting cross-modal MMN. First, we demonstrated that visual MMN exhibited deviance detection properties and that the first-generation focus of visual MMN was localized in the visual cortex, as previously reported in human studies. Second, a comparison of MMN amplitudes revealed a non-linear relationship between single-modal and cross-modal MMNs. Moreover, congruent audio-visual MMN exhibited characteristics of both visual and auditory MMNs-its latency was similar to that of auditory MMN, whereas local blockage of -methyl-D-aspartic acid receptors in the visual cortex diminished it as well as visual MMN. These results indicate that cross-modal information processing affects MMN without involving strong top-down effects, such as those of prior knowledge and attention. The present study is the first electrophysiological evidence of cross-modal MMN in animal models, and future studies on the neural mechanisms combining multisensory integration and deviance detection are expected to provide electrophysiological evidence to confirm the links between MMN and predictive coding theory.
当大脑试图构建一个详尽的世界模型时,多感官整合应有助于基于各种信息片段进行预测,而偏差检测应通过从实际感官输入中检测“误差”来反复更新这些预测。越来越多的证据,如偏差检测系统的层次组织,表明偏差检测系统可以在预测编码框架中得到解释。在此,我们将失配负波(MMN)作为一种预测误差信号,并研究了多感官整合与MMN之间的关系。特别是,我们研究了跨模态信息处理是否以及如何影响啮齿动物的MMN。我们设计了一种新的表面微电极阵列,并在麻醉状态下同时记录大鼠视觉和听觉皮层的视觉和听觉诱发电位。然后,我们绘制了五种偏差刺激的MMN:(i)视觉奇偶数范式中的单模态偏差和(ii)听觉奇偶数范式中的单模态偏差,引发单模态MMN;(iii)一致的视听偏差、(iv)不一致的视觉偏差和(v)视听奇偶数范式中的不一致听觉偏差,引发跨模态MMN。首先,我们证明视觉MMN表现出偏差检测特性,并且视觉MMN的第一代焦点位于视觉皮层,正如之前在人类研究中所报道的那样。其次,MMN振幅的比较揭示了单模态和跨模态MMN之间的非线性关系。此外,一致的视听MMN表现出视觉和听觉MMN的特征——其潜伏期与听觉MMN相似,而视觉皮层中甲基-D-天冬氨酸受体的局部阻断会使其以及视觉MMN减弱。这些结果表明,跨模态信息处理在不涉及诸如先验知识和注意力等强烈自上而下效应的情况下影响MMN。本研究是动物模型中跨模态MMN的首个电生理证据,预计未来关于结合多感官整合和偏差检测的神经机制的研究将提供电生理证据,以证实MMN与预测编码理论之间的联系。