A simultaneous search for footprints of early human migration processes using the genetic and folk music data in Eurasia

  • Z. Juhász
  • E. Dudás
  • A. Vágó-Zalán
  • Horolma PamjavEmail author
Original Article


In this study, we aimed to illustrate the efficiency of correlation analysis of musical and genetic data for certain common ethnic and ethno-musical roots of mankind. The comparison of the results to archaeogenetic data shows that correlations of recent musical and genetic data may reveal past cultural and migration processes resulting in recent connections. The significance tests verified our hypothesis supposing that propagation of oral musical traditions can be related to early human migration processes is well-founded, because the multidimensional point system determined by the inverse rank vectors of correlating Hg–UCT pairs has a very clear structure. We found that associations of Hgs jointly propagating with associations of UCTs (Unified Contour Type) can be identified as significant complex components in both modern and ancient populations, thus, modern populations can be considered as admixtures of these ancient Hg associations. It also seems obvious to conclude that these ancient Hg associations strewed their musical “parent languages” during their migrations, and the correlating UCTs of these musical parent languages may also be basic components of the recent folk music cultures. Thus, we can draw a hypothetical picture of the main characteristics of ancient musical cultures. Modern and prehistoric populations belonging to a common Hg–UCT association are located to very similar geographical areas, consequently, recent folk music cultures are basically determined by prehistoric migrations. Our study could be considered as an initial step in analysis of the correlations of prehistoric and recent musical and genetic characteristics of human evolution history.


MtDNA haplogroups and folk music correlation Clustering Ethnomusicology Population genetics Artificial intelligence Rank correlation 



The authors are grateful to Tibor Fehér for the assembly of the genetic database.


No funding was received.

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

Human participants and/or animals

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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  1. Bartók B (1937) Folk song research and nationalism. In: Suchoff B (ed) Béla Bartók Essays. University of Nebraska, Lincoln (1992) pp 25–28Google Scholar
  2. Bartók B (1949) On Collecting Folk Songs in Turkey Tempo, New Ser., No. 13, Bartok Number (Autumn, 1949), pp 15–19 + 38Google Scholar
  3. Bartók B (1976) Turkish Folk Music from Asia Minor, ed. Benjamin Suchoff, with an afterword by Kurt Reinhard. Princeton University Press, Princeton, p 288Google Scholar
  4. Brown S, Savage PE, Ko AM, Stoneking M, Ko YC, Loo JH, Trejaut JA (2013) Correlations in the population structure of music, genes and language. Proc Biol Sci 281(1774):20132072. CrossRefGoogle Scholar
  5. Chaubey G, Karmin M, Metspalu E, Metspalu M, Selvi-Rani D, Singh VK, Parik J, Solnik A, Naidu BP, Kumar A, Adarsh N, Mallick CB, Trivedi B, Prakash S, Reddy R, Shukla P, Bhagat S, Verma S, Vasnik S, Khan I, Barwa A, Sahoo D, Sharma A, Rashid M, Chandra V, Reddy AG, Torroni A, Foley RA, Thangaraj K, Singh L, Kivisild T, Villems R (2008) Phylogeography of mtDNA haplogroup R7 in the Indian peninsula. BMC Evol Biol 8:227. CrossRefGoogle Scholar
  6. Chiaroni J, King RJ, Underhill PA (2008) Correlation of annual precipitation with human Y-chromosome diversity and emergence of Neolithic agricultural and pastoral economies in the Fertile Crescent, Antiquity 82(316)Google Scholar
  7. Comas D, Calafell F, Bendukidze N, Fañanás L, Bertranpetit J (2000) Georgian and Kurd mtDNA sequence analysis shows a lack of correlation between languages and female genetic lineages. Am J Phys Anthropol 112(1):5–16CrossRefGoogle Scholar
  8. Conklin D (2013) Folk tune classification with multiple viewpoints. In: Proceedings of the Third International Workshop on Folk Music Analysis, June 6–7, 2013. Amsterdam, Netherlands. van Kranenburg P, Anagnostopoulou C, Volk A (eds) Amsterdam: Meertens Institute, Utrecht: Department of Information and Computing Sciences, Utrecht University, pp 99–100Google Scholar
  9. Conrad NJ, Malina S, Münzel SC (2009) New flutes document the earliest musical tradition in south-western Germany. Nature 460:737–740CrossRefGoogle Scholar
  10. Corpus Musicae Popularis Hungaricae l-XII (1951–2012) Balassi, BudapestGoogle Scholar
  11. Csébfalvy K, Havass M, Járdányi P, Vargyas L (1965) Systematization of tunes by computers. Stud Musicol VII: 253–257CrossRefGoogle Scholar
  12. Freeman LC, Merriam AP (1956) Statistical classification in anthropology: An application to ethnomusicology. Am Anthropol 58:464–472CrossRefGoogle Scholar
  13. Fucks W (1962) Mathematical analysis of formal structure of music. IRE Transactions on Information Theory Volume 8, Issue 5, September 1962Google Scholar
  14. González AM, Brehm A, Pérez JA, Maca-Meyer N, Flores C, Cabrera VM (2002) Mitochondrial DNA Affinities at the Atlantic Fringe of Europe. Am J Phys Anthropol 120(4):391–404CrossRefGoogle Scholar
  15. Gray RD, Atkinsson QD (2003) Language-tree divergence times support the Anatolian theory of Indo-European origin. Nature 426(6965):435–439CrossRefGoogle Scholar
  16. Haak W, Balanovsky O, Sanchez JJ, Koshel S, Zaporozhchenko V, Adler CJ, Der Sarkissian CS, Brandt G, Schwarz C, Nicklisch N, Dresely V, Fritsch B, Balanovska E, Villems R, Meller H, Alt KW, Cooper A, Members of the Genographic Consortium (2010) Ancient DNA from European Early Neolithic Farmers Reveals Their Near Eastern Affinities. PLoS Biol 8(11):e1000536. CrossRefGoogle Scholar
  17. Hamilton MJ, Buchanan B (2007) Spatial gradients in Clovis-age radiocarbon dates across North America suggest rapid colonization from the north. Proc Natl Acad Sci USA 104:15625–15630CrossRefGoogle Scholar
  18. Harvey AR (2018) Music and the Meeting of Human Minds. Front Psychol 9:762. (eCollection 2018. Review)CrossRefGoogle Scholar
  19. Hervella M, Izagirre N, Alonso S, Fregel R, Alonso A, Cabrera VM, de la Rúa C (2012) Ancient DNA from Hunter-Gatherer and farmer groups from Northern Spain Supports a random dispersion model for the neolithic expansion into Europe. PLoS One 7(4):e34417. CrossRefGoogle Scholar
  20. Huron D (1996) The melodic arch in Western folksongs. Comput Musicol 10:3–23 (iterative rank correlation method. Mol Genet Genom. 291(1):493–509)Google Scholar
  21. Jobling MA, Tyler-Smith C (2003) The human Y chromosome: an evolutionary marker comes of age. Nat Rev Genet 4:598–612CrossRefGoogle Scholar
  22. Juhász Z (2011) Low dimensional visualisation of folk music systems using the self organising cloud. In: Proc. of 12th International Society for music information retrieval. 2011. okt. 25–28, Miami, Florida, USAGoogle Scholar
  23. Juhász Z (2015) A Search for Structural Similarities of Oral Musical Traditions in Eurasia and America Using the Self Organizing Cloud Algorithm. J New Music Res 44(3):196–218CrossRefGoogle Scholar
  24. Juhász Z, Fehér T, Bárány G, Zalán A, Németh E, Pádár Z, Pamjav H (2015) New clustering methods for population comparison on paternal lineages. Mol Genet Genom Mol Genet Genom 290(2):767–784CrossRefGoogle Scholar
  25. Juhász Z, Dudás E, Pamjav H (2018) A new self-learning computational method for footprints of early human migration processes. Mol Genet Genomics 293(6):1579–1594CrossRefGoogle Scholar
  26. Kodály Z (1971) Folk music of Hungary. Budapest, CorvinaGoogle Scholar
  27. Kohonen T (1995) Self-organising Maps. Springer-Verlag, BerlinCrossRefGoogle Scholar
  28. Kranenburg P, Volk A, Wiering F, Veltkamp RC (2009) Musical models for folk-song melody alignment. In: Hirata K, Tzanetakis G, Yosh K, editors. 10th International Society for Music Information Retrieval Conference, (ISMIR 2009). pp 507–512Google Scholar
  29. Le Bomin S, Lecointre G, Heyer E (2016) The evolution of musical diversity: the key role of vertical transmission. PLoS One 11(3):e0151570. (eCollection 2016)CrossRefGoogle Scholar
  30. Lipson M, Szécsényi-Nagy A, Mallick S, Pósa A, Stégmár B, Keerl V, Rohland N, Stewardson K, Ferry M, Michel M, Oppenheimer J, Broomandkhoshbacht N, Harney E, Nordenfelt S, Llamas B, Gusztáv Mende B, Köhler K, Oross K, Bondár M, Marton T, Osztás A, Jakucs J, Paluch T, Horváth F, Csengeri P, Koós J, Sebők K, Anders A, Raczky P, Regenye J, Barna JP, Fábián S, Serlegi G, Toldi Z, Gyöngyvér Nagy E, Dani J, Molnár E, Pálfi G, Márk L, Melegh B, Bánfai Z, Domboróczki L, Fernández-Eraso J, Antonio Mujika-Alustiza J, Alonso Fernández C, ,Jiménez E Bollongino J, Orschiedt R, Schierhold J, Meller K, Cooper H, Burger A, Bánffy J, Alt E, Lalueza-Fox KW, Haak C, Reich WD (2017) Parallel palaeogenomic transects reveal complex genetic history of early European farmers. Nature 551(7680):368–372. CrossRefGoogle Scholar
  31. Lomax A (1968) Folk Song Style and Culture. With contributions by Conrad Arensberg. In: Edwin E, Erickson V, Grauer N, Berkowitz I, Bartenieff F, Paulay J, Halifax B, Ayres NN, Markel Roswell Rudd, Monika Vizedom, Fred Peng, Roger Wescott, David Brown. Colonial Press Inc, American Association for the Advancement of Science, Washington, DC, (publication no. 88)Google Scholar
  32. Malyarchuk B, Derenko M, Denisova G, Wozniak M, Grzybowski T, Dambueva I, Zakharov I (2010) Phylogeography of the Y-chromosome haplogroup C in northern Eurasia. Ann Hum Genet 74(6):539–546CrossRefGoogle Scholar
  33. Müllensiefen D, Freiler K (2007) Optimizing measures of melodic similarity for the exploration of a large folk song database. In: Proceedings of the ISMIR 2007Google Scholar
  34. Neparáczki E, Juhász Z, Pamjav H, Fehér T, Csányi B, · Zink A, Maixner F, Pálfi G, Molnár E, Pap I, Kustár Á, Révész L, Raskó I, Török T (2017a) Genetic structure of the early Hungarian conquerors inferred from mtDNA haplotypes and Y–chromosome haplogroups in a small cemetery. Mol Genet 292(1):201–214Google Scholar
  35. Neparáczki E, Kocsy K, Tóth GE, Maróti Z, Kalmár T, Bihari P, Nagy I, Pálfi G, Molnár E, Raskó I, Török T (2017b) Revising mtDNA haplotypes of the ancient Hungarian conquerors with next generation sequencing. PLoS One 12(4):e0174886. (eCollection 2017)CrossRefGoogle Scholar
  36. Neparáczki E, Maróti Z, Kalmár T, Kocsy K, Maár K, Bihari P, Nagy I, Fóthi E, Pap I, Kustár Á, Pálfi G, Raskó I, Zink A, Török T (2018) Mitogenomic data indicate admixture components of Asian Hun and Srubnaya origin in the Hungarian Conquerors. PLoS One 13(10):e0205920. (eCollection 2018)CrossRefGoogle Scholar
  37. Nettl B (1965) Folk and traditional music of the western continents. Prentice-Hall, New Jersey, Englewood CliffsGoogle Scholar
  38. Paksa K (1999) Magyar népzenetörténet. (Hungarian Folk Music History). Balassi Kiadó, BudapestGoogle Scholar
  39. Pamjav H, Juhász Z, Zalán A, Németh E, Damdin B (2012) A comparative phylogenetic study of genetics and folk music. Mol Genet Genom 287(4):337–349CrossRefGoogle Scholar
  40. Price JB, Schmuckler MA (2014) The Tonal-Metric Hierarchy: a corpus analysis. Music Percept 31(3):254–270CrossRefGoogle Scholar
  41. Sarno S, Boattini A, Pagani L, Sazzini M, De Fanti S, Quagliariello A, Gnecchi Ruscone GA, Guichard E, Ciani G, Bortolini E, Barbieri C, Cilli E, Petrilli R, Mikerezi I, Sineo L, Vilar M, Wells S, Luiselli D, Pettener D (2017) Ancient and recent admixture layers in Sicily and Southern Italy trace multiple migration routes along the Mediterranean. Sci Rep. Google Scholar
  42. Schmuckler MA (1999) Testing models of melodic contour similarity. Music Percept 16(3):109–150CrossRefGoogle Scholar
  43. Sharma S, Rai E, Sharma P, Jena M, Singh S, Darvishi K, Bhat AK, Bhanwer AJ, Tiwari PK, Bamezai RN (2009) The Indian origin of paternal haplogroup R1a1* substantiates the autochthonous origin of Brahmins and the caste system. J Hum Genet 54(1):47–55CrossRefGoogle Scholar
  44. Szécsényi-Nagy A, Brandt G, Haak W, Keerl V, Jakucs J, Möller-Rieker S, Köhler K, Mende BG, Oross K, Marton T, Osztás A, Kiss V, Fecher M, Pálfi G, Molnár E, Sebők K, Czene A, Paluch T, Šlaus M, Novak M, Pećina-Šlaus N, Ősz B, Voicsek V, Somogyi K, Tóth G, Kromer B, Bánffy E, Alt KW (2015) Tracing the genetic origin of Europe’s first farmers reveals insights into their social organization. Proc Biol Sci. Google Scholar
  45. Tamm E, Kivisild T, Reidla M, Metspalu M, Smith DG, Mulligan CJ, Bravi CM, Rickards O, Martinez-Labarga C, Khusnutdinova EK, Fedorova SA, Golubenko MV, Stepanov VA, Gubina MA, Zhadanov SI, Ossipova LP, Damba L, Voevoda MI, Dipierri JE, Villems R, Malhi RS (2007) Beringian standstill and spread of Native American founders. PLoS One 2(9):e829CrossRefGoogle Scholar
  46. Thangaraj K, Nandan K, Sharma A, Sharma V, Eaaswarkhanth VK, Patra M, Singh PK, Rekha S, Dua S, Verma M, Reddy N, Singh AG L (2009) Deep rooting in-situ expansion of mtDNA haplogroup R8 in South Asia. PLoS One 4(8):e6545CrossRefGoogle Scholar
  47. Toiviainen P (2000) Symbolic AI versus connectionism in music research. In: Mirinda E (ed) Readings in music and artificial intelligence. Harwood Academic Publishers, AmsterdamGoogle Scholar
  48. Underhill PA, Kivisild T (2007) Use of Y chromosome and mitochondrial DNA population structure in tracing human migrations. Annu Rev Genet 41:539–564CrossRefGoogle Scholar
  49. Vargyas L (1980) The prehistory of Hungarian folk music (In Hungarian. A magyar zene őstörténete. I–II. Ethnographia 91.1:1–34 (91. 2: 192–236)Google Scholar
  50. Vikár L, Bereczki G (1971) Cheremis Folksongs. Akadémiai Kiadó, BudapestGoogle Scholar
  51. Vikár L, Bereczki G (1979) Chuvashs Folksongs. Akadémiai Kiadó, BudapestGoogle Scholar
  52. Watkins WS, Thara R, Mowry BJ, Zhang Y, Witherspoon DJ, Tolpinrud W, Bamshad MJ, Tirupati S, Padmavati R, Smith H, Nancarrow D, Filippich C, Jorde LB (2008) Genetic variation in South Indian castes: evidence from Y-chromosome, mitochondrial, and autosomal polymorphisms. BMC Genet 9:86. CrossRefGoogle Scholar
  53. Wiora W (1950) Europäischer Volksgesang. Gemeinsame Formen in charakteristischen Abwandlungen. Arno Volk Verlag, Köln, pp 50–51Google Scholar
  54. Zhang J, Harbottle G, Wang Ch, Kong ZH (1999) Oldest playable musical instruments found at Jiahu early Neolithic site in China. Nature 401:366–368Google Scholar

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© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Centre for Energy ResearchInstitute of Technical Physics and Materials ScienceBudapestHungary
  2. 2.Hungarian Institute for Forensic SciencesInstitute of Forensic GeneticsBudapestHungary

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