博碩士論文 110825004 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:13 、訪客IP:18.119.213.216
姓名 曾虹臻(Hung-Chen Tseng)  查詢紙本館藏   畢業系所 認知與神經科學研究所
論文名稱 絕對音感能力對嘈雜環境中旋律和語句辨識影響之行為和腦造影研究
(Effects of Absolute Pitch Ability on Melody and Speech Perception in Noisy Environments: Behavioral and Neuroimaging Studies)
相關論文
★ 語音知覺與中文識字能力的關係★ 於虛擬環境中之雙耳時間差偵測機制研究
★ 母語為中文與英文者偵測頻率掃描訊號方向之事件相關腦電波研究★ 動態聽覺編碼在3D空間中的神經相關機制
★ 基頻輪廓和音樂經驗對嘈雜環境中語句辨識影響之行為和腦電波實驗
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 (2028-4-24以後開放)
摘要(中) 日常生活中的聲音訊息,例如音樂及語言,通常伴隨著背景噪音,噪音中聽辨(Hearing-in-Noise; HIN)表現,即如何在背景噪音中提取目標聲音,是一項重要的能力。噪音中聽辨能力經常隨著老化和某些疾病而衰退,因此,如何提高噪音中聽辨能力是聽覺認知的重要議題。研究顯示,受過音樂訓練者在噪音中的聽辨表現較未受過音樂訓練者具優勢。然而,受過音樂訓練者在音樂能力上可能存在一些差異,因此造成了在研究中探討音樂家HIN優勢不一致的結果。本研究測試了絕對音感(absolute pitch; AP),即在無基準音的情況可正確辨識獨立音名之能力,是否為影響音樂家在噪音中聽辨表現之因子。本研究第一部分為行為實驗,實驗中以高、中、低(無)絕對音感音樂家及非音樂家在四種訊噪比(SNR = 0, -3, -6, -9 dB)的噪音環境中進行音樂聽辨測驗(Music-in-Noise Task; MINT)及中文語句聽辨測驗(Speech-in-Noise Task; SINT),受試者需辨識噪音中的目標旋律或語句並依照指示做出回答(比較兩段目標旋律是否相同,或打出目標語句),實驗中含有不同子測驗,如加入視覺或空間提示等。此外,也探討了可能會影響HIN的相關因子,如工作記憶及相對音感能力。行為實驗結果顯示,在四種訊噪比下,音樂家的旋律辨識正確率皆顯著高於非音樂家,且其準確率與絕對音感程度呈正相關,但在語句辨識中,則未看到音樂家及絕對音感的優勢。此外,結果顯示音樂工作記憶的表現與音樂聽辨表現呈正相關,說明了絕對音感能力增進噪音中之音樂聽辨表現,亦可能與其音樂工作記憶能力相關。本研究第二部分以功能性核磁共振腦造影比較高度和低度絕對音感之音樂家,以及非音樂家在音樂及中文語句聽辨任務之腦區活化以及靜息態腦區活化及功能性連結,受試者需對三種訊噪比(SNR = No Noise, 0 dB, -9 dB)中的目標旋律或語句做清晰度評分(1~5,5為最清楚)。腦造影結果顯示,高絕對音感者在主要聽覺區(i.e., superior and middle temporal gyrus; STG and MTG)對旋律及語句皆有比較好的表徵,而可能進一步增強後續高層認知任務的處理。而在辨識旋律或語句腦區活化不同之處主要為:辨識語句時,除了聽覺區外,活化的腦區大致與認知功能有關(i.e., superior frontal gyrus; SFG, and insula),且這些區域的活化程度與絕對音感能力呈正相關,但三組在噪音中辨識語句時,主要利用相似的顳葉到頂葉的功能性連結;而在噪音中辨識旋律時,絕對音感者似乎憑藉著對音樂刺激的敏感度,在初級聽覺區(i.e., Heschl’s gyrus; HG)對音樂就有較好的神經編碼,進而增進聽覺與感覺區(i.e., supramarginal gyrus; SMG)之間的連結與整合,對噪音中的旋律清晰度評分也顯著較高。此外,在靜息狀態下的神經網絡也顯示了高絕對音感者在主要聽覺區的連結較強,說明了絕對音感能力帶來的神經可塑性。總結來說,實驗結果顯示絕對音感能力會增進HIN表現,但只限於音樂而非語言刺激,且伴隨著在主要聽覺區對音樂有較好的神經表徵以及功能性連結,因此,若想要以音樂訓練來改善在複雜噪音背景中理解聲音目標的能力,應將絕對音感能力列入考量的因素之一。
摘要(英) The sound we receive in our daily life, such as music and speech, is usually accompanied by background noise. Hearing-in-noise (HIN) ability, the ability to extract sound targets from background noise is thus crucial. HIN ability usually declines with age and in certain diseases, so how to effectively extract important information from background noise is an important issue in auditory cognition. Previous research has shown that people with musical training perform significantly better on HIN tasks. However, there may be some differences in musical ability among musicians which may contribute to the inconsistent findings observed in musician HIN advantage. Therefore, the current research investigated whether absolute pitch (AP), an innate musical ability to identify isolated notes, could be one factor that affect musician HIN performance. The first part of this study consisted of behavioral experiments. We examined musicians with high-, quasi-, non-AP ability and non-musicians on performance of Music-in-Noise task (MINT) and Mandarin Speech-in-Noise task (SINT) with four signal-to-noise ratios (SNRs = 0, -3, -6, -9 dB). Participants were asked to identify the target melody or sentence in noise and to respond according to the instructions (compare whether the two target melodies were the same, or type the target sentence). The experiment contained different subtasks, such as the addition of visual cues or spatial cues, etc. In addition, we also explored related factors that may affect HIN performance, including working memory and relative pitch ability. Behavioral results showed that musicians outperformed non-musicians in perceiving melody in noise, but not speech. Musicians conferred an advantage in identifying melodies under difficult conditions, with those possessing higher AP ability having better performance. Furthermore, results showed that accuracy in working memory recall of musical notes was positively correlated with performance accuracy on music-in-noise, but not speech-in-noise task. The second part of this study consisted of functional magnetic resonance imaging (fMRI) experiments. We investigated the brain activation and functional connectivity of musicians with high-AP, non-AP ability and non-musicians when performing music- and speech-in-noise tasks and in resting state. During fMRI experiment, participants were required to use the button box to rate the intelligibility of the target melody or sentence (1~5, 5 = most intelligible) under three SNR levels (SNRs = No Noise, 0 dB, -9 dB). Results showed that musicians with high AP ability may have better representation of melody or speech in primary auditory areas (i.e., superior and middle temporal gyrus; STG and MTG), which may further enhance subsequent high-level cognitive processing. With respect to the differences between identifying music or speech, except for auditory areas, the activated regions were related to cognitive functions (i.e., superior frontal gyrus; SFG, and insula) in speech perception in noise, and the degree of activation in these areas positively correlated with AP proficiency. However, we found that the three groups shared similar major functional connectivity between auditory and parietal regions for speech perception in noise. For music perception in noise, AP possessors relied on their sensitivity to musical stimuli to have better neural encoding of music in the primary auditory area (i.e., Heschl’s gyrus; HG), thereby enhancing the connection and integration between the auditory and sensory areas (i.e., supramarginal gyrus; SMG). Compared to non-AP musicians and non-musicians, AP musicians also had significantly higher intelligibility ratings on musical targets in noise. Furthermore, resting-state results revealed AP musicians had stronger connectivity in primary auditory regions, suggesting neuroplasticity shaped by absolute pitch ability. In summary, these results suggest that absolute pitch ability is associated with improved HIN perception for music but not speech stimuli, likely underlied by enhanced activation in primary auditory regions. Therefore, if music training were to be used to enhance speech intelligibility in noisy environments, absolute pitch ability should be one of the factors to be taken into consideration.
關鍵字(中) ★ 噪音中聽辨
★ 音樂聽辨測驗
★ 語句聽辨測驗
★ 絕對音感
★ 音樂訓練
關鍵字(英) ★ Hearing-in-noise
★ Music-in-noise task
★ Speech-in-noise task
★ Absolute pitch
★ Musical training
論文目次 Chinese Abstract……………………………………………………i
English Abstract……………………………………………………iii
Acknowledgements…………………………………………………vi
Table of Contents…………………………………………………vii
List of Figures……………………………………………………ix
List of Tables……………………………………………………xii
Explanation of Symbols…………………………………………xiii
Chapter I General Introduction……………………………………1
1-1 Hearing-in-Noise (HIN) and musician advantages………………1
1-2 Functional neuroimaging evidence of musician advantage in HIN…………………………………………………………………5
1-3 Absolute pitch (AP)……………………………………………7
1-4 fMRI evidence for musical training and AP effects……………8
1-5 fMRI studies of music vs. language and neural overlap
arguments…………………………………………………………10
1-6 Resting-state fMRI reveals the neural plasticity of musical
training or AP effects……………………………………………13
1-7 Overview of experiments..………………………………… 15
Chapter II Behavioral Experiments………………………………16
2-1 Introduction…………………………………………………16
2-2 Methods………………………………………………………17
2-2-1 Participants………………………………………………17
2-2-2 Stimuli and Tasks…………………………………………19
2-2-3 Procedure…………………………………………………29
2-2-4 Data Analysis………………………………………………29
2-3 Results………………………………………………………30
2-4 Discussion……………………………………………………48
Chapter III Brain Imaging Experiments…………………………57
3-1 Introduction…………………………………………………57
3-2 Methods………………………………………………………60
3-2-1 Participants………………………………………………60
3-2-2 Stimuli and Task…………………………………………61
3-2-3 Procedure…………………………………………………65
3-2-4 Data Analysis………………………………………………66
3-3 Results………………………………………………………68
3-4 Discussion……………………………………………………88
Chapter IV General Discussion…………………………………102
Chapter V Conclusion……………………………………………104
Appendix…………………………………………………………105
References………………………………………………………126
參考文獻 Adank, P. (2012). The neural bases of difficult speech comprehension and speech production: Two Activation Likelihood Estimation (ALE) meta-analyses. Brain and language, 122, 42-54. doi:10.1016/j.bandl.2012.04.014
Alain, C., Arnott, S. R., Hevenor, S., Graham, S., & Grady, C. L. (2001). “What” and “where” in the human auditory system. Proceedings of the National Academy of Sciences, 98(21), 12301-12306. doi:10.1073/pnas.211209098
Albouy, P., Peretz, I., Bermudez, P., Zatorre, R. J., Tillmann, B., & Caclin, A. (2019). Specialized neural dynamics for verbal and tonal memory: fMRI evidence in congenital amusia. Human Brain Mapping, 40(3), 855-867. https://doi.org/10.1002/hbm.24416
Arnott, S., Binns, M., Grady, C., & Alain, C. (2004). Assessing the auditory dual-pathway model in humans. NeuroImage, 22, 401-408. doi:10.1016/j.neuroimage.2004.01.014
Astafiev, S. V., Shulman Gl Fau - Stanley, C. M., Stanley Cm Fau - Snyder, A. Z., Snyder Az Fau - Van Essen, D. C., Van Essen Dc Fau - Corbetta, M., & Corbetta, M. (2003). Functional organization of human intraparietal and frontal cortex for attending, looking, and pointing. The Journal of Neuroscience, 23(11), 4689-4699. doi:10.1523/jneurosci.23-11-04689.2003
Astafiev, S. V., Stanley, C. M., Shulman, G. L., & Corbetta, M. (2004). Extrastriate body area in human occipital cortex responds to the performance of motor actions. Nature Neuroscience, 7(5), 542-548. doi:10.1038/nn1241
Bachem, A. (1937). Various Types of Absolute Pitch. The Journal of the Acoustical Society of America, 9(2), 146-151. doi:10.1121/1.1915919
Bangert, M., Peschel, T., Schlaug, G., Rotte, M., Drescher, D., Hinrichs, H., . . . Altenmüller, E. (2006). Shared networks for auditory and motor processing in professional pianists: Evidence from fMRI conjunction. NeuroImage, 30, 917-926. doi:10.1016/j.neuroimage.2005.10.044
Başkent, D., & Gaudrain, E. (2016). Musician advantage for speech-on-speech perception. The Journal of the Acoustical Society of America, 139(3), EL51-EL56. doi:10.1121/1.4942628
Belleville, S., Clément, F., Mellah, S., Gilbert, B., Fontaine, F., & Gauthier, S. (2011). Training-related brain plasticity in subjects at risk of developing Alzheimer’s disease. Brain, 134(6), 1623-1634. doi:10.1093/brain/awr037
Belleville, S., Mellah, S., de Boysson, C., Demonet, J.-F., & Bier, B. (2014). The Pattern and Loci of Training-Induced Brain Changes in Healthy Older Adults Are Predicted by the Nature of the Intervention. PLOS ONE, 9(8), e102710. doi:10.1371/journal.pone.0102710
Bengtsson, S., & Ullén, F. (2006). Dissociation between melodic and rhythmic processing during piano performance from musical scores. NeuroImage, 30, 272-284. doi:10.1016/j.neuroimage.2005.09.019
Bidelman, G. M., Bush, L. C., & Boudreaux, A. M. (2020). Effects of Noise on the Behavioral and Neural Categorization of Speech. Frontiers in Neuroscience, 14.
Bidelman, G. M., & Krishnan, A. (2010). Effects of reverberation on brainstem representation of speech in musicians and non-musicians. Brain Research, 1355, 112-125. https://doi.org/10.1016/j.brainres.2010.07.100
Bidelman, G. M., Villafuerte, J. W., Moreno, S., & Alain, C. (2014). Age-related changes in the subcortical–cortical encoding and categorical perception of speech. Neurobiology of Aging, 35(11), 2526-2540. https://doi.org/10.1016/j.neurobiolaging.2014.05.006
Bidelman, G. M., & Yellamsetty, A. (2017). Noise and pitch interact during the cortical segregation of concurrent speech. Hearing Research, 351. doi:10.1016/j.heares.2017.05.008
Binder, J. R., Desai, R. H., Graves, W. W., & Conant, L. L. (2009). Where Is the Semantic System? A Critical Review and Meta-Analysis of 120 Functional Neuroimaging Studies. Cerebral Cortex, 19(12), 2767-2796. doi:10.1093/cercor/bhp055
Boebinger, D., Evans, S., Rosen, S., Lima, C. F., Manly, T., & Scott, S. K. (2015). Musicians and non-musicians are equally adept at perceiving masked speech. The Journal of the Acoustical Society of America, 137(1), 378-387. doi:10.1121/1.4904537
Brauchli, C., Leipold, S., & Jäncke, L. (2019). Univariate and multivariate analyses of functional networks in absolute pitch. NeuroImage, 189, 241-247. https://doi.org/10.1016/j.neuroimage.2019.01.021
Brett, M., Anton, J.-L., Valabregue, R., & Poline, J.-B. (2002). Region of Interest Analysis Using an SPM Toolbox. NeuroImage, 16. doi:10.1016/S1053-8119(02)90013-3
Brown, S., & Martinez, M. J. (2007). Activation of premotor vocal areas during musical discrimination. Brain and Cognition, 63(1), 59-69. https://doi.org/10.1016/j.bandc.2006.08.006
Broyd, S. J., Demanuele, C., Debener, S., Helps, S. K., James, C. J., & Sonuga-Barke, E. J. S. (2009). Default-mode brain dysfunction in mental disorders: A systematic review. Neuroscience & Biobehavioral Reviews, 33(3), 279-296. https://doi.org/10.1016/j.neubiorev.2008.09.002
Catani, M., Jones, D. K., & Ffytche, D. H. (2004). Perisylvian language networks of the human brain. Annals of Neurology, 57(1), 8–16. doi:10.1002/ana.20319
Chenji, S., Jha, S., Lee, D., Brown, M., Seres, P., Mah, D., & Kalra, S. (2016). Investigating Default Mode and Sensorimotor Network Connectivity in Amyotrophic Lateral Sclerosis. PLOS ONE, 11(6), e0157443. doi:10.1371/journal.pone.0157443
Choi, I., Rajaram, S., Varghese, L., & Shinn-Cunningham, B. (2013). Quantifying attentional modulation of auditory-evoked cortical responses from single-trial electroencephalography. Frontiers in Human Neuroscience, 7.
Ciaramelli, E., Grady, C. L., & Moscovitch, M. (2008). Top-down and bottom-up attention to memory: A hypothesis (AtoM) on the role of the posterior parietal cortex in memory retrieval. Neuropsychologia, 46(7), 1828-1851. https://doi.org/10.1016/j.neuropsychologia.2008.03.022
Clayton, K. K., Swaminathan, J., Yazdanbakhsh, A., Zuk, J., Patel, A. D., & Kidd, G., Jr. (2016). Executive Function, Visual Attention and the Cocktail Party Problem in Musicians and Non-Musicians. PLOS ONE, 11(7), e0157638. doi:10.1371/journal.pone.0157638
Coffey, E. B. J., Arseneau-Bruneau, I., Zhang, X., & Zatorre, R. J. (2019). The Music-In-Noise Task (MINT): A Tool for Dissecting Complex Auditory Perception. Frontiers in Neuroscience, 13(199). doi:10.3389/fnins.2019.00199
Coffey, E. B. J., Chepesiuk, A. M. P., Herholz, S. C., Baillet, S., & Zatorre, R. J. (2017). Neural Correlates of Early Sound Encoding and their Relationship to Speech-in-Noise Perception. Frontiers in Neuroscience, 11.
Coffey, E. B. J., Herholz, S., Chepesiuk, A., Baillet, S., & Zatorre, R. (2016). Cortical contributions to the auditory frequency-following response revealed by MEG. Nature Communications, 7, 11070. doi:10.1038/ncomms11070
Coffey, E. B. J., Herholz, S. C., Scala, S., & Zatorre, R. J. (2011, 2011). Montreal Music History Questionnaire: a tool for the assessment of music-related experience in music cognition research. Paper presented at the The Neurosciences and Music IV: Learning and Memory, Conference, Edinburgh, UK.
Coffey, E. B. J., Mogilever, N. B., & Zatorre, R. J. (2017). Speech-in-noise perception in musicians: A review. Hearing Research, 352, 49-69. https://doi.org/10.1016/j.heares.2017.02.006
Corbetta, M., Kincade, J. M., Ollinger, J. M., McAvoy, M. P., & Shulman, G. L. (2000). Voluntary orienting is dissociated from target detection in human posterior parietal cortex. Nature Neuroscience, 3, 521-521. doi:10.1038/74905
Corbetta, M., Patel, G., & Shulman, G. (2008). The Reorienting System of the Human Brain: From Environment to Theory of Mind. Neuron, 58, 306-324. doi:10.1016/j.neuron.2008.04.017
Corbetta, M., & Shulman, G. (1998). Human cortical mechanisms of visual attention during orienting and search. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 353, 1353-1362. doi:10.1098/rstb.1998.0289
Corbetta, M., & Shulman, G. (2002). Control of Goal-Directed and Stimulus-Driven Attention in the Brain. Nature reviews. Neuroscience, 3, 201-215. doi:10.1038/nrn755
Deng, Y., Choi, I., Shinn-Cunningham, B., & Baumgartner, R. (2019). Impoverished auditory cues limit engagement of brain networks controlling spatial selective attention. NeuroImage, 202, 116151. https://doi.org/10.1016/j.neuroimage.2019.116151
Deutsch, D., Dooley, K., Henthorn, T., & Head, B. (2009). Absolute pitch among students in an American music conservatory: Association with tone language fluency. The Journal of the Acoustical Society of America, 125, 2683. doi:10.1121/1.3081389
Doeller, C. F., Opitz, B., Mecklinger, A., Krick, C., Reith, W., & Schröger, E. (2003). Prefrontal cortex involvement in preattentive auditory deviance detection:: neuroimaging and electrophysiological evidence. NeuroImage, 20(2), 1270-1282. https://doi.org/10.1016/S1053-8119(03)00389-6
Downar, J., Crawley, A., Mikulis, D., & Davis, K. (2000). A multimodal cortical network for the detection of changes in the sensory environment. Nature neuroscience, 3, 277-283. doi:10.1038/72991
Du, Y., Buchsbaum, B., Grady, C., & Alain, C. (2016). Increased activity in frontal motor cortex compensates impaired speech perception in older adults. Nature Communications, 7, 12241. doi:10.1038/ncomms12241
Du, Y., & Zatorre, R. J. (2017). Musical training sharpens and bonds ears and tongue to hear speech better. Proceedings of the National Academy of Sciences, 114(51), 13579-13584. doi:10.1073/pnas.1712223114
Dubinsky, E., Wood, E. A., Nespoli, G., & Russo, F. A. (2019). Short-Term Choir Singing Supports Speech-in-Noise Perception and Neural Pitch Strength in Older Adults With Age-Related Hearing Loss. Frontiers in Neuroscience, 13.
Eckert, M., Menon, V., Walczak, A., Ahlstrom, J., Denslow, S., Horwitz, A., & Dubno, J. (2009). At the Heart of the Ventral Attention System: The Right Anterior Insula. Human brain mapping, 30, 2530-2541. doi:10.1002/hbm.20688
Ellis, R., & Rönnberg, J. (2021). Temporal fine structure: associations with cognition and speech-in-noise recognition in adults with normal hearing or hearing impairment. International journal of audiology, 61, 1-9. doi:10.1080/14992027.2021.1948119
Elmer, S., Rogenmoser, L., Kühnis, J., & Jäncke, L. (2014). Bridging the Gap between Perceptual and Cognitive Perspectives on Absolute Pitch. Journal of Neuroscience, 35. doi:10.1523/JNEUROSCI.3009-14.2015
Erb, J., & Obleser, J. (2013). Upregulation of cognitive control networks in older adults’ speech comprehension. Frontiers in Systems Neuroscience, 7.
Firestone, G., McGuire, K., Liang, C., Zhang, N., Blankenship, C., Xiang, J., & Zhang, F. (2020). A Preliminary Study of the Effects of Attentive Music Listening on Cochlear Implant Users’ Speech Perception, Quality of Life, and Behavioral and Objective Measures of Frequency Change Detection. Frontiers in Human Neuroscience, 14. doi:10.3389/fnhum.2020.00110
Fleming, D., Belleville, S., Peretz, I., West, G., & Zendel, B. R. (2019). The effects of short-term musical training on the neural processing of speech-in-noise in older adults. Brain and Cognition, 136, 103592. https://doi.org/10.1016/j.bandc.2019.103592
Foster, N. E. V., & Zatorre, R. J. (2010). A Role for the Intraparietal Sulcus in Transforming Musical Pitch Information. Cerebral Cortex, 20(6), 1350-1359. doi:10.1093/cercor/bhp199
Fox, M. D., Corbetta, M., Snyder, A. Z., Vincent, J. L., & Raichle, M. E. (2006). Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems. Proceedings of the National Academy of Sciences, 103(26), 10046-10051. doi:10.1073/pnas.0604187103
Fox, M. D., Snyder, A., Barch, D., Gusnard, D., & Raichle, M. (2006). Transient BOLD responses at block transitions. NeuroImage, 28, 956-966. doi:10.1016/j.neuroimage.2005.06.025
Friederici, A. D. (2011). The Brain Basis of Language Processing: From Structure to Function. Physiological Reviews, 91(4), 1357-1392. doi:10.1152/physrev.00006.2011
Fujioka, T., Ross, B., Kakigi, R., Pantev, C., & Trainor, L. (2006). One year of musical training affects development of audiory cortical-evoked fields in young children. Brain, 129, 2593-2608. doi:10.1093/brain/awl247
Fuller, C. D., Galvin, J. J., Maat, B., Free, R. H., & Başkent, D. (2014). The musician effect: does it persist under degraded pitch conditions of cochlear implant simulations? Frontiers in Neuroscience, 8.
Gaser, C., & Schlaug, G. (2003). Brain Structures Differ between Musicians and Non-Musicians. The Journal of Neuroscience, 23(27), 9240. doi:10.1523/JNEUROSCI.23-27-09240.2003
Goulden, N., Khusnulina, A., Davis, N., Bracewell, R., Bokde, A., McNulty, J., & Mullins, P. (2014). The Salience Network is responsible for switching between the Default Mode Network and the Central Executive Network: Replication from DCM. NeuroImage, 99. doi:10.1016/j.neuroimage.2014.05.052
Habibi, A., Damasio, A., Ilari, B., Veiga, R., Joshi, A., Leahy, R., . . . Damasio, H. (2017). Childhood Music Training Induces Change in Micro and Macroscopic Brain Structure: Results from a Longitudinal Study. Cerebral Cortex, 28, 1-12. doi:10.1093/cercor/bhx286
Harrington, I., Stecker, G. C., Macpherson, E., & Middlebrooks, J. (2008). Spatial sensitivity of neurons in the anterior, posterior, and primary fields of cat auditory cortex. Hearing research, 240, 22-41. doi:10.1016/j.heares.2008.02.004
Herholz, S., Coffey, E., Pantev, C., & Zatorre, R. (2015). Dissociation of Neural Networks for Predisposition and for Training-Related Plasticity in Auditory-Motor Learning. Cerebral Cortex, 26. doi:10.1093/cercor/bhv138
Hervais-Adelman, A., Carlyon, R., Johnsrude, I., & Davis, M. (2012). Brain regions recruited for the effortful comprehension of noise-vocoded words. Language and Cognitive Processes, 27, 1145-1166. doi:10.1080/01690965.2012.662280
Hickok, G., & Poeppel, D. (2004). Dorsal and ventral streams: a framework for understanding aspects of the functional anatomy of language. Cognition, 92(1), 67-99. https://doi.org/10.1016/j.cognition.2003.10.011
Hickok, G., & Poeppel, D. (2007). The Cortical Organization of Speech Processing. Nature reviews. Neuroscience, 8, 393-402. doi:10.1038/nrn2113
Hillyard, S. A., & Anllo-Vento, L. (1998). Event-related brain potentials in the study of visual selective attention. Proceedings of the National Academy of Sciences, 95(3), 781-787. doi:10.1073/pnas.95.3.781
Hoffman, P., Pobric, G., Drakesmith, M., & Ralph, M. (2011). Posterior middle temporal gyrus is involved in verbal and non-verbal semantic cognition: Evidence from rTMS. Aphasiology, 26, 1-12. doi:10.1080/02687038.2011.608838
Hove, M., Sutherland, M., & Krumhansl, C. (2010). Ethnicity effects in relative pitch. Psychonomic bulletin & review, 17, 310-316. doi:10.3758/PBR.17.3.310
Hsieh, I. H., & Saberi, K. (2008). Dissociation of procedural and semantic memory in absolute-pitch processing. Hearing research, 240, 73-79. doi:10.1016/j.heares.2008.01.017
Hyde, K. L., Lerch, J., Norton, A., Forgeard, M., Winner, E., Evans, A. C., & Schlaug, G. (2009). Musical Training Shapes Structural Brain Development. The Journal of Neuroscience, 29(10), 3019. doi:10.1523/JNEUROSCI.5118-08.2009
Hyde, K. L., Peretz, I., & Zatorre, R. J. (2008). Evidence for the role of the right auditory cortex in fine pitch resolution. Neuropsychologia, 46(2), 632-639. https://doi.org/10.1016/j.neuropsychologia.2007.09.004
Jäncke, L., Langer, N., & Hänggi, J. (2012). Diminished Whole-brain but Enhanced Peri-sylvian Connectivity in Absolute Pitch Musicians. Journal of Cognitive Neuroscience, 24(6), 1447-1461. doi:10.1162/jocn_a_00227
Josef-Golubić, S. (2020). Triple model of auditory sensory processing: a novel gating stream directly links primary auditory areas to executive prefrontal cortex. Acta clinica Croatica, 59(4), 721-728. doi:10.20471/acc.2020.59.04.19
Kim, S.-G., & Knösche, T. R. (2017). On the Perceptual Subprocess of Absolute Pitch. Frontiers in Neuroscience, 11.
Kincade, J., Abrams, R., Astafiev, S., Shulman, G., & Corbetta, M. (2005). An event-related fMRI study of voluntary and stimulus-driven orienting of attention. The Journal of neuroscience : the official journal of the Society for Neuroscience, 25, 4593-4604. doi:10.1523/JNEUROSCI.0236-05.2005
Kleber, B., Friberg, A., Zeitouni, A., & Zatorre, R. (2017). Experience-dependent modulation of right anterior insula and sensorimotor regions as a function of noise-masked auditory feedback in singers and nonsingers. NeuroImage, 147, 97-110. https://doi.org/10.1016/j.neuroimage.2016.11.059
Klein, M. E., & Zatorre, R. J. (2011). A role for the right superior temporal sulcus in categorical perception of musical chords. Neuropsychologia, 49(5), 878-887. https://doi.org/10.1016/j.neuropsychologia.2011.01.008
Koeneke, S., Lutz, K., Wüstenberg, T., & Jäncke, L. (2004). Long-term training affects cerebellar processing in skilled keyboard players. NeuroReport, 15(8).
Kraus, N., & Chandrasekaran, B. (2010). Music training for developmental auditory skills. Nature reviews. Neuroscience, 11, 599-605. doi:10.1038/nrn2882
Krings, T., Töpper, R., Foltys, H., Erberich, S., Sparing, R., Willmes, K., & Thron, A. (2000). Cortical activation patterns during complex motor tasks in piano players and control subjects. A functional magnetic resonance imaging study. Neuroscience Letters, 278(3), 189-193. https://doi.org/10.1016/S0304-3940(99)00930-1
Leipold, S., Brauchli, C., Greber, M., & Jäncke, L. (2019). Absolute and relative pitch processing in the human brain: Neural and behavioral evidence. Brain structure & function, 224, 1723-1738. doi:10.1101/526541
Leipold, S., Klein, C., & Jäncke, L. (2020). Musical expertise shapes functional and structural brain networks independent of absolute pitch ability. Journal of Neuroscience, 41(11), 2496-2511. doi:10.1523/JNEUROSCI.1985-20.2020
López-Barroso, D., Ripollés, P., Marco-Pallarés, J., Mohammadi, B., Münte, T. F., Bachoud-Lévi, A.-C., … de Diego-Balaguer, R. (2015). Multiple brain networks underpinning word learning from fluent speech revealed by independent component analysis. NeuroImage, 110, 182–193. doi: 10.1016/j.neuroimage.2014.12.085
Loui, P., Li, H., Hohmann, A., & Schlaug, G. (2011). Enhanced Cortical Connectivity in Absolute Pitch Musicians: A Model for Local Hyperconnectivity. Journal of cognitive neuroscience, 23, 1015-1026. doi:10.1162/jocn.2010.21500
MacCutcheon, D., Füllgrabe, C., Eccles, R., van der Linde, J., Panebianco, C., & Ljung, R. (2020). Investigating the Effect of One Year of Learning to Play a Musical Instrument on Speech-in-Noise Perception and Phonological Short-Term Memory in 5-to-7-Year-Old Children. Frontiers in Psychology, 10.
Mankel, K., & Bidelman, G. M. (2018). Inherent auditory skills rather than formal music training shape the neural encoding of speech. Proceedings of the National Academy of Sciences, 115(51), 13129-13134. doi:10.1073/pnas.1811793115
Menon, V., & Uddin, L. (2010). Saliency, switching, attention and control: A network model of insula function. Brain structure & function, 214, 655-667. doi:10.1007/s00429-010-0262-0
Merrill, J., Sammler, D., Bangert, M., Goldhahn, D., Lohmann, G., Turner, R., & Friederici, A. (2012). Perception of Words and Pitch Patterns in Song and Speech. Frontiers in Psychology, 3.
Miyazaki, K. i., Rakowski, A., Makomaska, S., Jiang, C., Tsuzaki, M., Oxenham, A., . . . Lipscomb, S. (2018). Absolute Pitch and Relative Pitch in Music Students in the East and the West: Implications for Aural-Skills Education. Music Perception, 36, 135-155. doi:10.1525/mp.2018.36.2.135
Musacchia, G., Sams, M., Skoe, E., & Kraus, N. (2007). Musicians have enhanced subcortical auditory and audiovisual processing of speech and music. Proceedings of the National Academy of Sciences, 104(40), 15894-15898. doi:10.1073/pnas.0701498104
Musacchia, G., Strait, D., & Kraus, N. (2008). Relationships between behavior, brainstem and cortical encoding of seen and heard speech in musicians and non-musicians. Hearing Research, 241(1), 34-42. https://doi.org/10.1016/j.heares.2008.04.013
Nieto-Castanon, A. (2020). Handbook of functional connectivity Magnetic Resonance Imaging methods in CONN. Boston, MA: Hilbert Press.
Nieto-Castanon, A., & Whitfield-Gabrieli, S. (2021). CONN functional connectivity toolbox (RRID:SCR_009550), Version 21.
Nilsson, M., Soli, S., & Sullivan, J. (1994). Development of the Hearing In Noise Test (HINT) for the measurement of speech reception thresholds in quiet and in noise. The Journal of the Acoustical Society of America, 95, 1085-1099. doi:10.1121/1.408469
Overseas Community Affairs Council, R. O. C. T. (2018). Let′s learn Chinese – Digital learning materials [Audio]. https://www.huayuworld.org/teaching-material.php
Pando-Naude, V., Patyczek, A., Bonetti, L., & Vuust, P. (2021). An ALE meta-analytic review of top-down and bottom-up processing of music in the brain. Scientific Reports, 11(1), 20813. doi:10.1038/s41598-021-00139-3
Parbery-Clark, A., Anderson, S., Hittner, E., & Kraus, N. (2012a). Musical experience offsets age-related delays in neural timing. Neurobiology of aging, 33, 1483.e1481-1484. doi:10.1016/j.neurobiolaging.2011.12.015
Parbery-Clark, A., Anderson, S., Hittner, E., & Kraus, N. (2012b). Musical experience strengthens the neural representation of sounds important for communication in middle-aged adults. Frontiers in Aging Neuroscience, 4.
Parbery-Clark, A., Skoe, E., & Kraus, N. (2009). Musical Experience Limits the Degradative Effects of Background Noise on the Neural Processing of Sound. The Journal of Neuroscience, 29(45), 14100. doi:10.1523/JNEUROSCI.3256-09.2009
Parbery-Clark, A., Skoe, E., Lam, C., & Kraus, N. (2009). Musician Enhancement for Speech-In-Noise. Ear and hearing, 30, 653-661. doi:10.1097/AUD.0b013e3181b412e9
Parbery-Clark, A., Strait, D. L., Anderson, S., Hittner, E., & Kraus, N. (2011). Musical experience and the aging auditory system: Implications for cognitive abilities and hearing speech in noise. PLoS ONE, 6. doi:10.1371/journal.pone.0018082
Parbery-Clark, A., Strait, D. L., & Kraus, N. (2011). Context-dependent encoding in the auditory brainstem subserves enhanced speech-in-noise perception in musicians. Neuropsychologia, 49(12), 3338-3345. https://doi.org/10.1016/j.neuropsychologia.2011.08.007
Paris, T., Kim, J., & Davis, C. (2016). Visual form predictions facilitate auditory processing at the N1. Neuroscience, 343. doi:10.1016/j.neuroscience.2016.09.023
Patel, A. (2011). Why would Musical Training Benefit the Neural Encoding of Speech? The OPERA Hypothesis. Frontiers in Psychology, 2.
Patterson, R. D., Uppenkamp, S., Johnsrude, I. S., & Griffiths, T. D. (2002). The Processing of Temporal Pitch and Melody Information in Auditory Cortex. Neuron, 36(4), 767-776. https://doi.org/10.1016/S0896-6273(02)01060-7
Peng, G. (2006). Temporal and tonal aspects of Chinese syllables: A corpus-based comparative study of Mandarin and Cantonese. Journal of Chinese Linguistics, 34, 134-154.
Peng, G., & Wang, W. S. Y. (2005). Tone recognition of continuous Cantonese speech based on support vector machines. Speech Communication, 45(1), 49-62. https://doi.org/10.1016/j.specom.2004.09.004
Peretz, I., Vuvan, D., Lagrois, M.-É., & Armony, J. L. (2015). Neural overlap in processing music and speech. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1664), 20140090. doi:10.1098/rstb.2014.0090
Peters, S. K., Dunlop, K., & Downar, J. (2016). Cortico-Striatal-Thalamic Loop Circuits of the Salience Network: A Central Pathway in Psychiatric Disease and Treatment. Frontiers in Systems Neuroscience, 10.
Poliva, O. (2016). From Mimicry to Language: A Neuroanatomically Based Evolutionary Model of the Emergence of Vocal Language. Frontiers in Neuroscience, 10.
Posner, M. I., & Petersen, S. E. (1990). The Attention System of the Human Brain. Annual Review of Neuroscience, 13(1), 25-42. doi:10.1146/annurev.ne.13.030190.000325
Puschmann, S., Baillet, S., & Zatorre, R. (2018). Musicians at the Cocktail Party: Neural Substrates of Musical Training During Selective Listening in Multispeaker Situations. Cerebral Cortex, 29. doi:10.1093/cercor/bhy193
Rauschecker, J. (2012). Ventral and dorsal streams in the evolution of speech and language. Frontiers in Evolutionary Neuroscience, 4.
Rauschecker, J., & Scott, S. (2009). Maps and streams in the auditory cortex: Nonhuman primates illuminate human speech processing. Nature neuroscience, 12, 718-724. doi:10.1038/nn.2331
Rinne, T., Ala-Salomäki, H., Stecker, G. C., Pätynen, J., & Lokki, T. (2014). Processing of spatial sounds in human auditory cortex during visual, discrimination and 2-back tasks. Frontiers in Neuroscience, 8.
Rogalsky, C., Rong, F., Saberi, K., & Hickok, G. (2011). Functional Anatomy of Language and Music Perception: Temporal and Structural Factors Investigated Using Functional Magnetic Resonance Imaging. The Journal of Neuroscience, 31(10), 3843. doi:10.1523/JNEUROSCI.4515-10.2011
Rosemann, S., & Thiel, C. M. (2020). Neuroanatomical changes associated with age-related hearing loss and listening effort. Brain Structure and Function, 225(9), 2689-2700. doi:10.1007/s00429-020-02148-w
Ruggles, D. R., Freyman, R. L., & Oxenham, A. J. (2014). Influence of Musical Training on Understanding Voiced and Whispered Speech in Noise. PLOS ONE, 9(1), e86980. doi:10.1371/journal.pone.0086980
Schulze, K., Gaab, N., & Schlaug, G. (2009). Perceiving pitch absolutely: Comparing absolute and relative pitch possessors in a pitch memory task. BMC Neuroscience, 10(1), 106. doi:10.1186/1471-2202-10-106
Schulze, K., Mueller, K., & Koelsch, S. (2013). Auditory stroop and absolute pitch: An fMRI study. Human brain mapping, 34. doi:10.1002/hbm.22010
Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., . . . Greicius, M. D. (2007). Dissociable Intrinsic Connectivity Networks for Salience Processing and Executive Control. The Journal of Neuroscience, 27(9), 2349. doi:10.1523/JNEUROSCI.5587-06.2007
Seither-Preisler, A., Parncutt, R., & Schneider, P. (2014). Size and Synchronization of Auditory Cortex Promotes Musical, Literacy, and Attentional Skills in Children. The Journal of Neuroscience, 34(33), 10937. doi:10.1523/JNEUROSCI.5315-13.2014
Shulman, G. L., Tansy, A. P., Kincade, M., Petersen, S. E., McAvoy, M. P., & Corbetta, M. (2002). Reactivation of Networks Involved in Preparatory States. Cerebral Cortex, 12(6), 590-600. doi:10.1093/cercor/12.6.590
Singh-Curry, V., & Husain, M. (2009). The functional role of the inferior parietal lobe in the dorsal and ventral stream dichotomy. Neuropsychologia, 47(6), 1434-1448. https://doi.org/10.1016/j.neuropsychologia.2008.11.033
Slater, J., & Kraus, N. (2015). The role of rhythm in perceiving speech in noise: a comparison of percussionists, vocalists and non-musicians. Cognitive processing, 17. doi:10.1007/s10339-015-0740-7
Slater, J., Skoe, E., Strait, D. L., O’Connell, S., Thompson, E., & Kraus, N. (2015). Music training improves speech-in-noise perception: Longitudinal evidence from a community-based music program. Behavioural Brain Research, 291, 244-252. https://doi.org/10.1016/j.bbr.2015.05.026
Song, F., Zhan, Y., Ford, J. C., Cai, D.-C., Fellows, A. M., Shan, F., . . . Buckey, J. C. (2020). Increased Right Frontal Brain Activity During the Mandarin Hearing-in-Noise Test. Frontiers in Neuroscience, 14.
Sormaz, M., Murphy, C., Wang, H.-t., Hymers, M., Karapanagiotidis, T., Poerio, G., . . . Smallwood, J. (2018). Default mode network can support the level of detail in experience during active task states. Proceedings of the National Academy of Sciences, 115(37), 9318-9323. doi:10.1073/pnas.1721259115
Spaniol, J., Davidson, P. S. R., Kim, A. S. N., Han, H., Moscovitch, M., & Grady, C. L. (2009). Event-related fMRI studies of episodic encoding and retrieval: Meta-analyses using activation likelihood estimation. Neuropsychologia, 47(8), 1765-1779. https://doi.org/10.1016/j.neuropsychologia.2009.02.028
Spyridakou, C., & Bamiou, D.-E. (2015). Need of speech-in-noise testing to assess listening difficulties in older adults. Hearing, Balance and Communication, 13. doi:10.3109/15563650.2015.1015814
Stecker, G. C., Harrington, I. A., & Middlebrooks, J. C. (2005). Location Coding by Opponent Neural Populations in the Auditory Cortex. PLOS Biology, 3(3), e78. doi:10.1371/journal.pbio.0030078
Sterzer, P., & Kleinschmidt, A. (2010). Anterior insula activations in perceptual paradigms: often observed but barely understood. Brain structure & function, 214, 611-622. doi:10.1007/s00429-010-0252-2
Stevens, C., Fanning, J., Coch, D., Sanders, L., & Neville, H. (2008). Neural mechanisms of selective auditory attention are enhanced by computerized training: Electrophysiological evidence from language-impaired and typically developing children. Brain Research, 1205, 55-69. https://doi.org/10.1016/j.brainres.2007.10.108
Strait, D., & Kraus, N. (2011). Can You Hear Me Now? Musical Training Shapes Functional Brain Networks for Selective Auditory Attention and Hearing Speech in Noise. Frontiers in Psychology, 2.
Strait, D., Kraus, N., Parbery-Clark, A., & Ashley, R. (2010). Musical experience shapes top-down auditory mechanisms: Evidence from masking and auditory attention performance. Hearing Research, 261, 22-29. doi:10.1016/j.heares.2009.12.021
Swaminathan, J., Mason, C. R., Streeter, T., Best, V., Jr, K., & Patel, A. D. (2015). Musical training, individual differences and the cocktail party problem. Science Report, 5(11628), 1-10. doi:10.1038/srep14401
Theusch, E., Basu, A., & Gitschier, J. (2009). Genome-wide Study of Families with Absolute Pitch Reveals Linkage to 8q24.21 and Locus Heterogeneity. American journal of human genetics, 85, 112-119. doi:10.1016/j.ajhg.2009.06.010
Tierney, A., Krizman, J., & Kraus, N. (2015). Music training alters the course of adolescent auditory development. Proceedings of the National Academy of Sciences of the United States of America, 112. doi:10.1073/pnas.1505114112
Uddin, L. Q., Yeo, B. T. T., & Spreng, R. N. (2019). Towards a Universal Taxonomy of Macro-scale Functional Human Brain Networks. Brain Topography, 32(6), 926-942. doi:10.1007/s10548-019-00744-6
Varnet, L., Wang, T., Peter, C., Meunier, F., & Hoen, M. (2015). How musical expertise shapes speech perception: Evidence from auditory classification images. Scientific Reports, 5, 14489. doi:10.1038/srep14489
Vigneau, M., Beaucousin, V., Hervé, P. Y., Duffau, H., Crivello, F., Houdé, O., . . . Tzourio-Mazoyer, N. (2006). Meta-analyzing left hemisphere language areas: Phonology, semantics, and sentence processing. NeuroImage, 30(4), 1414-1432. https://doi.org/10.1016/j.neuroimage.2005.11.002
Vilberg, K. L., & Rugg, M. D. (2008). Memory retrieval and the parietal cortex: A review of evidence from a dual-process perspective. Neuropsychologia, 46(7), 1787-1799. https://doi.org/10.1016/j.neuropsychologia.2008.01.004
Wehrum, S., Degé, F., Ott, U., Walter, B., Stippekohl, B., Kagerer, S., . . . Stark, R. (2011). Can you hear a difference? Neuronal correlates of melodic deviance processing in children. Brain Research, 1402, 80-92. https://doi.org/10.1016/j.brainres.2011.05.057
Wengenroth, M., Blatow, M., Heinecke, A., Reinhardt, J., Stippich, C., Hofmann, E., & Schneider, P. (2014). Increased Volume and Function of Right Auditory Cortex as a Marker for Absolute Pitch. Cerebral Cortex, 24(5), 1127-1137. doi:10.1093/cercor/bhs391
Wenhart, T., Bethlehem, R. A. I., Baron-Cohen, S., & Altenmüller, E. (2019). Autistic traits, resting-state connectivity, and absolute pitch in professional musicians: shared and distinct neural features. Molecular Autism, 10(1), 20. doi:10.1186/s13229-019-0272-6
Wenhart, T., Hwang, Y.-Y., & Altenmüller, E. (2019). Enhanced auditory disembedding in an interleaved melody recognition test is associated with absolute pitch ability. Scientific Reports, 2019. doi:10.1038/s41598-019-44297-x
Whitehead, J. C., & Armony, J. L. (2022). Intra-individual Reliability of Voice- and Music-elicited Responses and their Modulation by Expertise. Neuroscience, 487, 184-197. https://doi.org/10.1016/j.neuroscience.2022.02.011
Whitfield-Gabrieli, S., & Nieto-Castanon, A. (2012). Conn: A Functional Connectivity Toolbox for Correlated and Anticorrelated Brain Networks. Brain Connectivity, 2(3), 125-141. doi:10.1089/brain.2012.0073
Wilson, R., McArdle, R., & Smith, S. (2007). An evaluation of the BKB-SIN, HINT, QuickSIN, and WIN materials on listeners with normal hearing and listeners with hearing loss. Journal of speech, language, and hearing research, 50, 844-856. doi:10.1044/1092-4388(2007/059)
Wilson, S. J., Lusher, D., Wan, C. Y., Dudgeon, P., & Reutens, D. C. (2009). The Neurocognitive Components of Pitch Processing: Insights from Absolute Pitch. Cerebral Cortex, 19(3), 724-732. doi:10.1093/cercor/bhn121
Wong, L., Soli, S., Liu, S., Han, N., & Huang, M.-W. (2007). Development of the Mandarin Hearing in Noise Test (MHINT). Ear and hearing, 28, 70S-74S. doi:10.1097/AUD.0b013e31803154d0
Wong, P., Skoe, E., Russo-Ponsaran, N., Dees, T., & Kraus, N. (2007). Musical experience shapes human brainstem encoding of linguistic pitch patterns. Nature neuroscience, 10, 420-422. doi:10.1038/nn1872
Worschech, F., Marie, D., Jünemann, K., Sinke, C., Kruger, T., Grossbach, M., . . . Altenmüller, E. (2021). Improved Speech in Noise Perception in the Elderly After 6 Months of Musical Instruction. Frontiers in Neuroscience, 15. doi:10.3389/fnins.2021.696240
Wyart, V., Dehaene, S., & Tallon-Baudry, C. (2012). Early dissociation between neural signatures of endogenous spatial attention and perceptual awareness during visual masking. Frontiers in Human Neuroscience, 6.
Xia, M., Wang, J., & He, Y. (2013). BrainNet Viewer: A Network Visualization Tool for Human Brain Connectomics. PLOS ONE, 8(7), e68910. doi:10.1371/journal.pone.0068910
Xu, J., Wang, J., Fan, L., Li, H., Zhang, W., Hu, Q., & Jiang, T. (2015). Tractography-based Parcellation of the Human Middle Temporal Gyrus. Scientific Reports, 5, 18883. doi:10.1038/srep18883
Yan, C.-G., Wang, X., Zuo, X.-N., & Zang, Y.-F. (2016). DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging. Neuroinformatics, 14. doi:10.1007/s12021-016-9299-4
Yates, K. M., Moore, D. R., Amitay, S., & Barry, J. G. (2019). Sensitivity to Melody, Rhythm, and Beat in Supporting Speech-in-Noise Perception in Young Adults. Ear and Hearing, 40(2).
Yoo, J., & Bidelman, G. M. (2019). Linguistic, perceptual, and cognitive factors underlying musicians’ benefits in noise-degraded speech perception. Hearing Research, 377, 189-195. https://doi.org/10.1016/j.heares.2019.03.021
Yu, M., Xu, M., Li, X., Chen, Z., Song, Y., & Liu, J. (2017). The Shared Neural Basis of Music and Language. Neuroscience, 357. doi:10.1016/j.neuroscience.2017.06.003
Zatorre, R. J., Perry, D. W., Beckett, C. A., Westbury, C. F., & Evans, A. C. (1998). Functional anatomy of musical processing in listeners with absolute pitch and relative pitch. Proceedings of the National Academy of Sciences, 95(6), 3172-3177. doi:10.1073/pnas.95.6.3172
Zendel, B., & Alain, C. (2011). Musicians Experience Less Age-Related Decline in Central Auditory Processing. Psychology and aging, 27, 410-417. doi:10.1037/a0024816
Zendel, B., Tremblay, C.-D., Belleville, S., & Peretz, I. (2015). The Impact of Musicianship on the Cortical Mechanisms Related to Separating Speech from Background Noise. Journal of cognitive neuroscience, 27, 1044-1059. doi:10.1162/jocn_a_00758
Zendel, B., West, G., Belleville, S., & Peretz, I. (2019). Music training improves the ability to understand speech-in-noise in older adults. Neurobiology of Aging, 81. doi:10.1016/j.neurobiolaging.2019.05.015
Ziv, N., & Radin, S. (2014). Absolute and relative pitch: Global versus local processing of chords. Advances in cognitive psychology, 10, 15-25. doi:10.2478/v10053-008-0152-7
指導教授 謝宜蕙(I-Hui Hsieh) 審核日期 2023-4-24
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明