Musical Training Enhances Face Recognition:from Behavior To Neural Substrates

Music is an important achievement of human civilization, it has an important influece on human's life and production. Many stusies found that mucial training leads to improvement of cognitive ablity, and alters the structure and function of human brain. Face recognition is also an important component of social recognition. The recognition of other person's indentity and enotion is mainly dependent on face recognition, which also plays an important role in human's communication. Moreover, there are some common features between musical training and face recognition. Firstly, music reading involves the processing of spatial information. For example, during music reading, it is not only the need to recognise the spatial position of sigal note, but also the need to recognise the spatial relation between the adjacent notes. Moreover, the notes may be processed holisticly for musician. The processing of face was considered as a configural processing. The processing of the first-order relations and the second-order relations was very important for face processing. Moreover, it was suggested that the holistic processing could predict face recognition. Therefore, musical traning can improve the ability of spatial or holistic processing, which could fuether improve face processing. Secondly, multimodal neural network was recruited during musical training or practice, which including visual, motor and auditory cortex, especially the temporal cortex playing an important role in music perception. Moreover, the temporal fusiform gyrus is also an important region for face recognition, which was called the Fusiform Face Area (FFA). Therefore, long-term musical training might induce the change of the structure and function of the brain region releted to face processing, which further influence the ability of face recognition.Based on these consideration, we hypothesize that musical training would improve face recognition. In the present study, we conduct6experiments to explore the positive effect of musical training on face recognition and its cognitive and neural basis by using behavioral, ERP asn fMRI measures.In the behavioral experiment1, we explore the processing of note, face, word and meaningless picture in musician and non-musician using a visual match task. The results show that response speed for note and face is faster for musician than for non-musician. Howeve, there are no difference between musician and non-musician in processing word and meaningless picture. As for accuracy(ACC), the ACC is higher for musician than for non-musician in processing note, but there are no difference between musician and non-musician in processing other stimuli. However, the lack of the difference effect found in the word and meaningless picture processing may due to the ceiling effect as the processing of word and meaningless picture was most easy.In the behavioral experiment2, we increase the stimulus similarity to increase the difficulty of the experimental task. The results show that the response speed for note and face is faster for musician than for non-musician, and the response speed for chair and meaningless picture is also faster for musician than for non-musician. Howeve, there is no difference between musician and non-musician in processing word. As for accuracy(ACC), the ACC is higher for musician than for non-musician in processing note, and no processing difference are observed between musician and non-musician in other stimulus conditions. After increase the difficulty of the experimental task, there is still no difference of response speed between musician and non-musician, which could exclude the ceiling effect. In order to exclude the influence of response execution on the measure of reaction time(RT), we subtract the RT in word condtion from the RT in other conditions, and use the obtained datas for further analysis. The results showed that response speed for note and face is still faster for musician than for non-musician, but no RT difference observed in other conditions. This further suggested that the positive effect of musical training on face recognition is more obvious.In the experiment1and experiment2, the study picture (the first picture) and the test picture (the second picture)are presented subsequently. This task may introduce mental course of the visual memory. Therefore, in order to exclude the influence of visual memory on the present experimental effect, we conduct experiment3, in which the the study picture and the test picture are presented synchronously. The results show that the response speed for note and face is faster for musician than for non-musician, and the response speed for chair and meaningless picture is also faster for musician than for non-musician. Howeve, there is no difference between musician and non-musician in processing word. This provides the solid evidence for the postive effect of musical training on face recognition.In the experiment4, we further explore the positive effect of musical training on face recognition by using ERPs. The behavioral results show that the response speed for note and face is faster for musician than for non-musician, and the response speed for chair and meaningless picture is also faster for musician than for non-musician. Howeve, there is no difference between musician and non-musician in processing word. As for accuracy(ACC), the ACC is higher for musician than for non-musician in processing note, and no processing difference are observed between musician and non-musician in other stimulus conditions. The ERP analysis mainly focus on the N170component induced by the study picture and on the P300component induced by test picture. As for N170analysis, the N170amplitudes induced by face stimulus was smaller in musician than in non-musician, There are no N170differences between musician and non-musician in processing other stimuli. This suggests the efficient neural processing of face in musician. The correlation analysis shows that the experience of staff notation reading has positive correlation with number of N170amplitude, and has negative correlation with number of N170latency. However, there was no significant correlation between the experience of numbered musical notation reading and N170amplitude or latency.This suggests that the experience of note reading play an important role on face processing. As for P300analysis, the P300amplitudes induced by face and note stimulus was larger in musician than in non-musician. There are no P300differences between musician and non-musician in processing other stimuli. The correlation analysis shows that the behavioral RT has negative correlation with P300amplitude.In the experiment5, we only focus the N170effect modulated by musical training. Therefore, the experiment5fuether explore the N170effect by using the implicit task. The results show that the N170amplitudes induced by face stimulus was smaller in musician than in non-musician, and that the N170amplitudes induced by note and meaningless picture was also smaller in musician than in non-musician. But there are no N170differences between musician and non-musician in processing word. The correlation analysis shows that the experience of note reading has positive correlation with number of N170amplitude, and has negative correlation with number of N170latency. However, there was no significant correlation between the experience of numbered musical notation reading and N170amplitude or latency. This suggests that the effect of musical training on face processing is stable, which is not influenced by the task.In the experiment6, by using the fMRI measures, we further explore the influence of musical training on visual neural network, especially the Fusiform Face Area (FFA). The whole brain analysis shows that the processing of note with staff and note without staff induce the decreased activity in the fusiform for musician than for non-musician, suggesting the effective neutral processing of note in musician, which similar to the results in previous studies regarding perception learning and category learning. In addition, the processing of note with staff and note without staff induce the increased activity in right cerebellum and left supramarginal gyrus for musician than for non-musician. These regions are involved in motor-related processing, and reflect the activity in visual-motor neural network. More interesting, the ROI analysis on fusiform face area shows that the processing of face induces the decreased activity in left fusiform face area for musician than for non-musician. Moreover, the correlation analysis shows that the experience of note reading has negative correlation with the left FFA activity. However, there was no significant correlation between the experience of numbered musical notation reading and the left FFA activity. The decreased activity in fusiform face area demonstrates the effective neutral processing of face in musician, which provides the neural basis for the positive effect of musical training on face recognition.Take together, the present study proves that musical training improves the face recognition. The present study can (1) enhance our understanding of the efficacy of music, and provide scientific guidance for musical education;(2) enhance our understanding of the neural mechanism of face recognition;(3) prove that human visual system is plastic, and provide a new suggestion or method for exploiting the potential of brain and for curing the vision disorders.