Neural correlates of magno- and parvocellular contributions to emotional perception and emotional learning

人类的情绪视觉已经在几种通路模型的背景下得到了解释。例如，双路径模型（LeDoux，1994）和多波模型（Pessoa和Adolphs，2010）提出，原始的情感相关信息沿着沿着双或多个视觉通道流动。重要的是，这两个模型都假设最初的情绪大脑反应是由快速的信号传输沿着大细胞（M）纤维介导的，而不是（较慢的）小细胞（P）系统。令人惊讶的是，很少有人知道这两种视觉信息对情绪视觉的确切贡献。申请人和其他人最近的发现表明，大脑活动的情绪调节可以发生在视觉处理的非常早期的时间窗口中，这可能与情绪信息经由大细胞通道的快速传输有关。为了揭示大细胞和小细胞对人类情感视觉的影响，该项目提出使用等亮度（p偏置）和低亮度对比度（m偏置）的视觉情感刺激，如面部和场景，这些刺激是专门设计用于直接偏置两个流之一的处理。大细胞和小细胞的贡献将在情绪感知和情绪学习的背景下进行检查，刺激，要么有一个固有的情感价值（研究I，II）或将获得情感意义，通过情感联想学习与经典（研究III）或新的MultiCS条件反射程序（研究IV）。使用脑电图，大细胞和小细胞情绪处理的时间过程将被跟踪与高时间分辨率和神经发电机将被识别使用逆源建模技术。从拟议的研究中获得的结果是感兴趣的，不仅为基础的情绪研究，但也可能是未来的临床研究有关焦虑症。

Human emotional vision has been explained in the context of several pathway models. For instance, the Dual route model (LeDoux, 1994) and the multiple waves model (Pessoa and Adolphs, 2010) propose that crude emotion-related information flows along dual or multiple visual channels. This information can be processed very rapidly to influence brain activity at several processing stages later on. Importantly, both models assume that initial emotional brain responses are mediated by fast signal transmission along magnocellular (M) fibers as opposed to the (slower) parvocellular (P) system. Surprisingly, little is known about the exact contributions of both kinds of visual information to emotional vision. Very recent findings by the applicant and others show that emotional modulations of brain activity can occur in a very early time-window of visual processing, which might relate to this fast transmission of emotional information via magnocellular channels. To reveal the impact of magno- and parvocellular contributions on human emotional vision, the project proposes the use of isoluminant (p-biased) and low-luminance-contrast (m-biased) visual emotional stimuli such as faces and scenes, which are specifically designed to directly bias processing in one of the two streams. Magno- and parvocellular contributions will be examined in the context of emotional perception and emotional learning with stimuli that either have an inherent emotional value (study I, II) or that will gain emotional significance via affective associative learning with a classical (study III) or novel MultiCS conditioning procedure (study IV). Using electroencephalography, the time-course of magno- and parvocellular emotional processing will be tracked with high temporal resolution and neural generators will be identified using inverse source modeling techniques. The results obtained from the proposed studies are of interest not only for basic emotion research but may also be of relevance for future clinical research concerning anxiety disorders.