Suppr超能文献

自动处理抽象音乐调性。

Automatic processing of abstract musical tonality.

机构信息

Center for Computational Neuroscience and Neural Technology, Boston University Boston, MA, USA.

Center for Computational Neuroscience and Neural Technology, Boston University Boston, MA, USA ; Department of Biomedical Engineering, Boston University Boston, MA, USA.

出版信息

Front Hum Neurosci. 2014 Dec 9;8:988. doi: 10.3389/fnhum.2014.00988. eCollection 2014.

Abstract

Music perception builds on expectancy in harmony, melody, and rhythm. Neural responses to the violations of such expectations are observed in event-related potentials (ERPs) measured using electroencephalography. Most previous ERP studies demonstrating sensitivity to musical violations used stimuli that were temporally regular and musically structured, with less-frequent deviant events that differed from a specific expectation in some feature such as pitch, harmony, or rhythm. Here, we asked whether expectancies about Western musical scale are strong enough to elicit ERP deviance components. Specifically, we explored whether pitches inconsistent with an established scale context elicit deviant components even though equally rare pitches that fit into the established context do not, and even when their timing is unpredictable. We used Markov chains to create temporally irregular pseudo-random sequences of notes chosen from one of two diatonic scales. The Markov pitch-transition probabilities resulted in sequences that favored notes within the scale, but that lacked clear melodic, harmonic, or rhythmic structure. At the random positions, the sequence contained probe tones that were either within the established scale or were out of key. Our subjects ignored the note sequences, watching a self-selected silent movie with subtitles. Compared to the in-key probes, the out-of-key probes elicited a significantly larger P2 ERP component. Results show that random note sequences establish expectations of the "first-order" statistical property of musical key, even in listeners not actively monitoring the sequences.

摘要

音乐感知建立在对和声、旋律和节奏的期望之上。在使用脑电图测量的事件相关电位(ERP)中可以观察到对这些期望的违反的神经反应。大多数先前展示对音乐违规敏感的 ERP 研究使用的刺激是时间规则且音乐结构的,较少出现违反特定期望的违规事件,这些事件在音高、和声或节奏等特征上与特定期望不同。在这里,我们想知道对西方音阶的期望是否足够强烈,足以引起 ERP 偏差成分。具体来说,我们探讨了即使在时机不可预测的情况下,与既定音阶上下文不一致的音高是否会引起偏差成分,即使它们同样罕见,并且符合既定上下文。我们使用马尔可夫链从两个全音阶之一中创建了音符的时间不规则伪随机序列。马尔可夫音高转换概率导致了有利于音阶内音符的序列,但缺乏清晰的旋律、和声或节奏结构。在随机位置,序列包含探针音,这些探针音要么在既定音阶内,要么不在调内。我们的研究对象忽略了音符序列,观看带有字幕的自选无声电影。与在调探针相比,不在调探针引起了明显更大的 P2 ERP 成分。结果表明,随机音符序列甚至在不主动监测序列的听众中建立了对音乐调的“一阶”统计属性的期望。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7563/4260496/8a9e3cd3bce2/fnhum-08-00988-g0001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验