Savage, P. E., Brown, S., Sakai, E. & Currie, T. E. Statistical universals reveal the structures and functions of human music. Proc. Natl Acad. Sci. USA 112, 8987–8992 (2015).
Ravignani, A., Delgado, T. & Kirby, S. Musical evolution in the lab exhibits rhythmic universals. Nat. Hum. Behav. doi.org/10.1038/s41562-016-0007 (2017).
Mehr, S. A. et al. Universality and diversity in human song. Science doi.org/10.1126/science.aax0868 (2019).
Kotz, S. A., Ravignani, A. & Fitch, W. T. The evolution of rhythm processing. Trends Cogn. Sci. doi.org/10.1016/j.tics.2018.08.002 (2018).
Pouw, W., Paxton, A., Harrison, S. J. & Dixon, J. A. Acoustic information about upper limb movement in voicing. Proc. Natl Acad. Sci. USA doi.org/10.1073/pnas.2004163117 (2020).
Large, E. W. & Jones, M. R. The dynamics of attending: how we track time varying events. Psychol. Rev. 106, 119–159 (1999).
Nobre, A. C. & Van Ede, F. Anticipated moments: temporal structure in attention. Nat. Rev. Neurosci. doi.org/10.1038/nrn.2017.141 (2018).
Hannon, E. E. & Trehub, S. E. Tuning in to musical rhythms: infants learn more readily than adults. Proc. Natl Acad. Sci. USA doi.org/10.1073/pnas.0504254102 (2005).
Winkler, I., Haden, G. P., Ladinig, O., Sziller, I. & Honing, H. Newborn infants detect the beat in music. Proc. Natl Acad. Sci. USA 106, 2468–2471 (2009).
Zentner, M. & Eerola, T. Rhythmic engagement with music in infancy. Proc. Natl Acad. Sci. USA 107, 5768–5773 (2010).
Cirelli, L. K., Trehub, S. E. & Trainor, L. J. Rhythm and melody as social signals for infants. Ann. N. Y. Acad. Sci. 1423, 66–72 (2018).
Nazzi, T., Bertoncini, J. & Mehler, J. Language discrimination by newborns: toward an understanding of the role of rhythm. J. Exp. Psychol. Hum. Percept. Perform. 24, 756–766 (1998).
Polak, R. et al. Rhythmic prototypes across cultures. Music Percept. doi.org/10.1525/mp.2018.36.1.1 (2018).
London, J., Polak, R. & Jacoby, N. Rhythm histograms and musical meter: a corpus study of Malian percussion music. Psychon. Bull. Rev. doi.org/10.3758/s13423-016-1093-7 (2017).
Clayton, M., Sager, R. & Will, U. In time with the music: the concept of entrainment and its significance for ethnomusicology. Eur. Meet. Ethnomusicol. 11, 3–142 (2005).
Polak, R. & London, J. Timing and meter in Mande drumming from Mali. Music Theory Online doi.org/10.30535/mto.20.1.1 (2014).
Polak, R., London, J. & Jacoby, N. Both isochronous and non-isochronous metrical subdivision afford precise and stable ensemble entrainment: a corpus study of Malian jembe drumming. Front. Neurosci. doi.org/10.3389/fnins.2016.00285 (2016).
Patel, A. D. & Iversen, J. R. The evolutionary neuroscience of musical beat perception: the Action Simulation for Auditory Prediction (ASAP) hypothesis. Front. Syst. Neurosci. 8, 57 (2014).
Jacoby, N. & McDermott, J. H. Integer ratio priors on musical rhythm revealed cross-culturally by iterated reproduction. Curr. Biol. doi.org/10.1016/j.cub.2016.12.031 (2017).
Cameron, D. J., Bentley, J. & Grahn, J. A. Cross-cultural influences on rhythm processing: reproduction, discrimination, and beat tapping. Front. Psychol. doi.org/10.3389/fpsyg.2015.00366 (2015).
Neuhoff, H., Polak, R. & Fischinger, T. Perception and evaluation of timing patterns in drum ensemble music from Mali. Music Percept. doi.org/10.1525/MP.2017.34.4.438 (2017).
Honing, H. On the biological basis of musicality. Ann. N. Y. Acad. Sci. doi.org/10.1111/nyas.13638 (2018).
Tarr, B., Slater, M. & Cohen, E. Synchrony and social connection in immersive virtual reality. Sci. Rep. doi.org/10.1038/s41598-018-21765-4 (2018).
Lense, M. D. & Camarata, S. PRESS-Play: musical engagement as a motivating platform for social interaction and social play in young children with ASD. Music Sci. doi.org/10.1177/2059204320933080 (2020).
Fitch, W. T. Empirical approaches to the study of language evolution. Psychon. Bull. Rev. 24, 3–33 (2017).
Savage, P. E. et al. Music as a coevolved system for social bonding. Behav. Brain Sci. doi.org/10.1017/S0140525X20000333 (2020).
Woodruff Carr, K., White-Schwoch, T., Tierney, A. T., Strait, D. L. & Kraus, N. Beat synchronization predicts neural speech encoding and reading readiness in preschoolers. Proc. Natl Acad. Sci. USA 111, 14559–14564 (2014).
Swaminathan, S. & Schellenberg, E. G. Musical ability, music training, and language ability in childhood. J. Exp. Psychol. Learn. Mem. Cogn. doi.org/10.1037/xlm0000798 (2019).
Keller, P. E., Novembre, G. & Hove, M. J. Rhythm in joint action: psychological and neurophysiological mechanisms for real-time interpersonal coordination. Phil. Trans. R. Soc. B doi.org/10.1098/rstb.2013.0394 (2014).
Ladányi, E., Persici, V., Fiveash, A., Tillmann, B. & Gordon, R. L. Is atypical rhythm a risk factor for developmental speech and language disorders? WIREs Cogn. Sci. e1528 11, e1528 (2020).
Moumdjian, L., Sarkamo, T., Leone, C., Leman, M. & Feys, P. Effectiveness of music-based interventions on motricity or cognitive functioning in neurological populations: a systematic review. Eur. J. Phys. Rehabil. Med. doi.org/10.23736/S1973-9087.16.04429-4 (2017).
Merchant, H., Grahn, J., Trainor, L., Rohrmeier, M. & Fitch, W. T. Finding the beat: a neural perspective across humans and non-human primates. Phil. Trans. R. Soc. B 370, 20140093 (2015).
Gordon, C. L., Cobb, P. R. & Balasubramaniam, R. Recruitment of the motor system during music listening: an ALE meta-analysis of fMRI data. PLoS ONE doi.org/10.1371/journal.pone.0207213 (2018).
Cannon, J. J. & Patel, A. D. How beat perception co-opts motor neurophysiology. Trends Cogn. Sci. 25, 137–150 (2021).
Dalla Bella, S. et al. BAASTA: Battery for the Assessment of Auditory Sensorimotor and Timing Abilities. Behav. Res. Methods doi.org/10.3758/s13428-016-0773-6 (2017).
Pulli, K. et al. Genome-wide linkage scan for loci of musical aptitude in Finnish families: evidence for a major locus at 4q22. J. Med. Genet. 45, 451–456 (2008).
Oikkonen, J. et al. A genome-wide linkage and association study of musical aptitude identifies loci containing genes related to inner ear development and neurocognitive functions. Mol. Psychiatry 20, 451–456 (2014).
Ullén, F., Mosing, M. A., Holm, L., Eriksson, H. & Madison, G. Psychometric properties and heritability of a new online test for musicality, the Swedish Musical Discrimination Test. Pers. Individ. Dif. 63, 87–93 (2014).
Mosing, M. A., Verweij, K. J. H., Madison, G. & Ullén, F. The genetic architecture of correlations between perceptual timing, motor timing, and intelligence. Intelligence 57, 33–40 (2016).
Seesjärvi, E. et al. The nature and nurture of melody: a twin study of musical pitch and rhythm perception. Behav. Genet. doi.org/10.1007/s10519-015-9774-y (2016).
Gingras, B., Honing, H., Peretz, I., Trainor, L. J. & Fisher, S. E. Defining the biological bases of individual differences in musicality. Phil. Trans. R. Soc. B 370, 20140092 (2015).
Wray, N. R., Goddard, M. E. & Visscher, P. M. Prediction of individual genetic risk of complex disease. Curr. Opin. Genet. Dev. 18, 257–263 (2008).
Müllensiefen, D., Gingras, B., Musil, J. & Stewart, L. The musicality of non-musicians: an index for assessing musical sophistication in the general population. PLoS ONE 9, e89642 (2014).
Musil, J. J., Iversen, J. R. & Müllensiefen, D. Measuring individual differences in musical beat alignment perception. Pers. Individ. Dif. 60, S35 (2014).
Law, L. N. C. & Zentner, M. Assessing musical abilities objectively: construction and validation of the Profile of Music Perception Skills. PLoS ONE 7, e52508 (2012).
Grahn, J. A. & Brett, M. Rhythm and beat perception in motor areas of the brain. J. Cogn. Neurosci. 19, 893–906 (2007).
Anglada-Tort, M., Harrison, P. M. C. & Jacoby, N. REPP: a robust cross-platform solution for online sensorimotor synchronization experiments. Behav. Res. Methods 1, 1–15 (2022).
Li, M. & Yue, W. VRK2, a candidate gene for psychiatric and neurological disorders. Mol. Neuropsychiatry 4, 119–133 (2018).
Dashti, H. S. et al. Genome-wide association study identifies genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates. Nat. Commun. 10, 1100 (2019).
Chang, D. et al. A meta-analysis of genome-wide association studies identifies 17 new Parkinson’s disease risk loci. Nat. Genet. doi.org/10.1038/ng.3955 (2017).
D’Angelo, D. et al. Defining the effect of the 16p11.2 duplication on cognition, behavior, and medical comorbidities. JAMA Psychiatry doi.org/10.1001/jamapsychiatry.2015.2123 (2016).
Hippolyte, L. et al. The number of genomic copies at the 16p11.2 locus modulates language, verbal memory, and inhibition. Biol. Psychiatry doi.org/10.1016/j.biopsych.2015.10.021 (2016).
Bulik-Sullivan, B. K. et al. LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).
Oikkonen, J., Onkamo, P., Järvelä, I. & Kanduri, C. Convergent evidence for the molecular basis of musical traits. Sci. Rep. 6, 39707 (2016).
Park, H. et al. Comprehensive genomic analyses associate UGT8 variants with musical ability in a Mongolian population. J. Med. Genet. 49, 747–752 (2012).
Leeuw, C. A., de, Stringer, S., Dekkers, I. A., Heskes, T. & Posthuma, D. Conditional and interaction gene-set analysis reveals novel functional pathways for blood pressure. Nat. Commun. 9, 3768 (2018).
de Leeuw, C. A., Mooij, J. M., Heskes, T. & Posthuma, D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput. Biol. doi.org/10.1371/journal.pcbi.1004219 (2015).
Watanabe, K., Taskesen, E., van Bochoven, A. & Posthuma, D. Functional mapping and annotation of genetic associations with FUMA. Nat. Commun. 8, 1826 (2017).
GTEx Consortium The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348, 648–660 (2015).
Finucane, H. K. et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat. Genet. 47, 1228–1235 (2015).
Lindblad-Toh, K. et al. A high-resolution map of human evolutionary constraint using 29 mammals. Nature doi.org/10.1038/nature10530 (2011).
Hujoel, M. L. A., Gazal, S., Hormozdiari, F., van de Geijn, B. & Price, A. L. Disease heritability enrichment of regulatory elements is concentrated in elements with ancient sequence age and conserved function across species. Am. J. Hum. Genet. 104, 611–624 (2019).
Finucane, H. K. et al. Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. Nat. Genet. doi.org/10.1038/s41588-018-0081-4 (2018).
Mithen, S. J. The Singing Neanderthals: The Origins of Music, Language, Mind, and Body (Harvard Univ. Press, 2005).
Capra, J. A., Erwin, G. D., McKinsey, G., Rubenstein, J. L. & Pollard, K. S. Many human accelerated regions are developmental enhancers. Phil. Trans. R. Soc. B 368, 20130025 (2013).
Hubisz, M. J. & Pollard, K. S. Exploring the genesis and functions of human accelerated regions sheds light on their role in human evolution. Curr. Opin. Genet. Dev. 29, 15–21 (2014).
Doan, R. N. et al. Mutations in human accelerated regions disrupt cognition and social behavior. Cell 167, 341–354e12 (2016).
Todd, E. J. et al. Next generation sequencing in a large cohort of patients presenting with neuromuscular disease before or at birth. Orphanet J. Rare Dis. doi.org/10.1186/s13023-015-0364-0 (2015).
Davies, G. et al. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function. Nat. Commun. 9, 2098 (2018).
Akman, H. O., Lossos, A. & Kakhlon, O. GBE1 adult polyglucosan body disease. GeneReviews®; www.ncbi.nlm.nih.gov/books/NBK5300/ (1993).
Niarchou, M., Lin, G. T., Lense, M. D., Gordon, R. L. & Davis, L. K. Medical phenome of musicians: an investigation of health records collected on 9803 musically active individuals. Ann. N. Y. Acad. Sci. doi.org/10.1111/NYAS.14671 (2021).
Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236–1241 (2015).
Grotzinger, A. D. et al. Genomic SEM provides insights into the multivariate genetic architecture of complex traits. Nat. Hum. Behav. doi.org/10.1038/s41562-019-0566-x (2019).
Shrine, N. et al. New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries. Nat. Genet. doi.org/10.1038/s41588-018-0321-7 (2019).
Willems, S. M. et al. Large-scale GWAS identifies multiple loci for hand grip strength providing biological insights into muscular fitness. Nat. Commun. doi.org/10.1038/ncomms16015 (2017).
Finkel, D., Ernsth-Bravell, M. & Pedersen, N. L. Temporal dynamics of motor functioning and cognitive aging. J. Gerontol. A doi.org/10.1093/gerona/glv110 (2015).
Bégel, V., Verga, L., Benoit, C. E., Kotz, S. A. & Dalla Bella, S. Test–retest reliability of the Battery for the Assessment of Auditory Sensorimotor and Timing Abilities (BAASTA). Ann. Phys. Rehabil. Med. doi.org/10.1016/j.rehab.2018.04.001 (2018).
Bonacina, S., Krizman, J., White-Schwoch, T., Nicol, T. & Kraus, N. How rhythmic skills relate and develop in school-age children. Glob. Pediatr. Health doi.org/10.1177/2333794×19852045 (2019).
Tranchant, P., Vuvan, D. T. & Peretz, I. Keeping the beat: a large sample study of bouncing and clapping to music. PLoS ONE doi.org/10.1371/journal.pone.0160178 (2016).
Tranchant, P. & Peretz, I. Basic timekeeping deficit in the beat-based form of congenital amusia. Sci. Rep. doi.org/10.1038/s41598-020-65034-9 (2020).
Coleman, J. R. I. The validity of brief phenotyping in population biobanks for psychiatric genome-wide association studies on the biobank scale. Complex Psychiatry doi.org/10.1159/000516837 (2021).
Abdellaoui, A. & Verweij, K. J. H. Dissecting polygenic signals from genome-wide association studies on human behaviour. Nat. Hum. Behav. 5, 686–694 (2021).
Watanabe, K. et al. A global overview of pleiotropy and genetic architecture in complex traits. Nat. Genet. 51, 1339–1348 (2019).
Nagel, M. et al. Meta-analysis of genome-wide association studies for neuroticism in 449,484 individuals identifies novel genetic loci and pathways. Nat. Genet. 50, 920–927 (2018).
Pardinas, A. F. et al. Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection. Nat. Genet. 50, 381–389 (2018).
Lévy, J. et al. Molecular and clinical delineation of 2p15p16. 1 microdeletion syndrome. Am. J. Med. Genet. A 173, 2081–2087 (2017).
Jones, S. E. et al. Genome-wide association analyses of chronotype in 697,828 individuals provides insights into circadian rhythms. Nat. Commun. doi.org/10.1038/s41467-018-08259-7 (2019).
Grahn, J. A. & Rowe, J. B. Feeling the beat: premotor and striatal interactions in musicians and nonmusicians during beat perception. J. Neurosci. 29, 7540–7548 (2009).
Grahn, J. A. & Rowe, J. B. Finding and feeling the musical beat: striatal dissociations between detection and prediction of regularity. Cereb. Cortex 23, 913–921 (2013).
Kung, S.-J., Chen, J. L., Zatorre, R. J. & Penhune, V. B. Interacting cortical and basal ganglia networks underlying finding and tapping to the musical beat. J. Cogn. Neurosci. 25, 401–420 (2013).
Bengtsson, S. L. et al. Listening to rhythms activates motor and premotor cortices. Cortex 45, 62–71 (2009).
Teki, S., Grube, M., Kumar, S. & Griffiths, T. D. Distinct neural substrates of duration-based and beat-based auditory timing. J. Neurosci. 31, 3805–3812 (2011).
McAuley, J. D., Henry, M. J. & Tkach, J. Tempo mediates the involvement of motor areas in beat perception. Ann. N. Y. Acad. Sci. 1252, 77–84 (2012).
Dissanayake, E. If music is the food of love, what about survival and reproductive success? Music Sci. 12, 169–195 (2008).
Mas-Herrero, E., Marco-Pallares, J., Lorenzo-Seva, U., Zatorre, R. J. & Rodriguez-Fornells, A. Individual differences in music reward experiences. Music Percept. 31, 118–138 (2013).
Tung, J. Y. et al. Efficient replication of over 180 genetic associations with self-reported medical data. PLoS ONE 6, e23473 (2011).
Haegens, S. & Golumbic, E. Z. Rhythmic facilitation of sensory processing: a critical review. Neurosci. Biobehav. Rev. 86, 150–165 (2018).
Sowiński, J. & Dalla Bella, S. Poor synchronization to the beat may result from deficient auditory–motor mapping. Neuropsychologia 51, 1952–1963 (2013).
Haworth, S. et al. Apparent latent structure within the UK Biobank sample has implications for epidemiological analysis. Nat. Commun. 10, 333 (2019).
Jacoby, N. et al. Cross-cultural work in music cognition. Music Percept. doi.org/10.1525/mp.2020.37.3.185 (2020).
Gordon, R. L. et al. Confronting ethical and social issues related to the genetics of musicality. Preprint at PsyArXiv doi.org/10.31234/osf.io/dyn6e (2022)
Border, R. et al. No support for historical candidate gene or candidate gene-by-interaction hypotheses for major depression across multiple large samples. Am. J. Psychiatry 176, 376–387 (2019).
Mosing, M. A., Madison, G., Pedersen, N. L. & Ullén, F. Investigating cognitive transfer within the framework of music practice: genetic pleiotropy rather than causality. Dev. Sci. 19, 504–512 (2016).
Marees, A. T. et al. Genetic correlates of socio-economic status influence the pattern of shared heritability across mental health traits. Nat. Hum. Behav. doi.org/10.1038/s41562-021-01053-4 (2021).
Emery, C. F., Finkel, D. & Pedersen, N. L. Pulmonary function as a cause of cognitive aging. Psychol. Sci. doi.org/10.1177/0956797612439422 (2012).
Finkel, D., Ernsth Bravell, M. & Pedersen, N. L. Role of motor function and lung function in pathways to ageing and decline. Aging Clin. Exp. Res. doi.org/10.1007/s40520-020-01494-3 (2020).
Duggan, E. C. et al. A multi-study coordinated meta-analysis of pulmonary function and cognition in aging. J. Gerontol. A doi.org/10.1093/gerona/glz057 (2019).
Clouston, S. A. P. et al. The dynamic relationship between physical function and cognition in longitudinal aging cohorts. Epidemiol. Rev. doi.org/10.1093/epirev/mxs004 (2013).
Larsson, M., Richter, J. & Ravignani, A. Bipedal steps in the development of rhythmic behavior in humans. Music Sci. doi.org/10.1177/2059204319892617 (2019).
Provasi, J., Anderson, D. I. & Barbu-Roth, M. Rhythm perception, production, and synchronization during the perinatal period. Front. Psychol. doi.org/10.3389/fpsyg.2014.01048 (2014).
Bernard, J. A., Millman, Z. B. & Mittal, V. A. Beat and metaphoric gestures are differentially associated with regional cerebellar and cortical volumes. Hum. Brain Mapp. doi.org/10.1002/hbm.22894 (2015).
Gjermunds, N., Brechan, I., Johnsen, S. Å. K. & Watten, R. G. Musicians: larks, owls or hummingbirds? J. Circadian Rhythms 17, 4 (2019).
Martin, J., Taylor, M. J. & Lichtenstein, P. Assessing the evidence for shared genetic risks across psychiatric disorders and traits. Psychol. Med. doi.org/10.1017/S0033291717003440 (2018).
Chen, T. J. H. et al. Are dopaminergic genes involved in a predisposition to pathological aggression? Hypothesizing the importance of ‘super normal controls’ in psychiatricgenetic research of complex behavioral disorders. Med. Hypotheses 65, 703–707 (2005).
Kendler, K., Chatzinakos, C. & Bacanu, S. The impact on estimations of genetic correlations by the use of super-normal, unscreened, and family-history screened controls in genome wide case-control studies. Genet. Epidemiol. 44, 283–289 (2020).
Mansens, D., Deeg, D. J. H. & Comijs, H. C. The association between singing and/or playing a musical instrument and cognitive functions in older adults. Aging Ment. Health doi.org/10.1080/13607863.2017.1328481 (2018).
Matthews, T. E., Witek, M. A. G., Lund, T., Vuust, P. & Penhune, V. B. The sensation of groove engages motor and reward networks. NeuroImage 214, 116768 (2020).
Povel, D.-J. & Essens, P. Perception of temporal patterns. Music Percept. 2, 411–440 (1985).
Grahn, J. A. & McAuley, J. D. Neural bases of individual differences in beat perception. NeuroImage 47, 1894–1903 (2009).
Gordon, R. L., Jacobs, M. S., Schuele, C. M. & Mcauley, J. D. Perspectives on the rhythm−grammar link and its implications for typical and atypical language development. Ann. N. Y. Acad. Sci.1337, 16–25 (2015).
Wieland, E. A., McAuley, J. D., Dilley, L. C. & Chang, S.-E. Evidence for a rhythm perception deficit in children who stutter. Brain Lang. 144, 26–34 (2015).
Woods, K. J. P., Siegel, M. H., Traer, J. & McDermott, J. H. Headphone screening to facilitate web-based auditory experiments. Atten. Percept. Psychophys. 79, 2064–2072 (2017).
Macmillan, N. A. & Creelman, C. D. Detection Theory: A User’s Guide (Cambridge Univ. Press, 1991).
Gordon, R. L. et al. Musical rhythm discrimination explains individual differences in grammar skills in children. Dev. Sci. doi.org/10.1111/desc.12230 (2015).
Berinsky, A. J., Margolis, M. F. & Sances, M. W. Separating the shirkers from the workers? Making sure respondents pay attention on self-administered surveys. Am. J. Polit. Sci. doi.org/10.1111/ajps.12081 (2014).
Anwyl-Irvine, A., Dalmaijer, E. S., Hodges, N. & Evershed, J. K. Realistic precision and accuracy of online experiment platforms, web browsers, and devices. Behav. Res. Methods 53, 1407–1425 (2021).
Bridges, D., Pitiot, A., MacAskill, M. R. & Peirce, J. W. The timing mega-study: comparing a range of experiment generators, both lab-based and online. PeerJ doi.org/10.7717/peerj.9414 (2020).
McKinney, M. F., Moelants, D., Davies, M. E. P. & Klapuri, A. Evaluation of audio beat tracking and music tempo extraction algorithms. J. N. Music Res. doi.org/10.1080/09298210701653252 (2007).
Repp, B. H. Rate limits of on-beat and off-beat tapping with simple auditory rhythms: 1. Qualitative observations. Music Percept. doi.org/10.1525/mp.2005.22.3.479 (2005).
Repp, B. H. & Su, Y. H. Sensorimotor synchronization: a review of recent research (2006–2012). Psychon. Bull. Rev. doi.org/10.3758/s13423-012-0371-2 (2013).
London, J. Hearing in Time: Psychological Aspects of Musical Meter (Oxford Univ. Press, 2012); doi.org/10.1093/acprof:oso/9780199744374.001.0001
R Core Team R: A Language and Environment for Statistical Computing v.3.5.1 (R Foundation for Statistical Computing, 2018).
Jansen, P. R. et al. Genome-wide analysis of insomnia in 1,331,010 individuals identifies new risk loci and functional pathways. Nat. Genet. 51, 394–403 (2019).
Ashburner, M. et al. Gene ontology: tool for the unification of biology. Nat. Genet. 25, 25–29 (2000).
The Gene Ontology Consortium The Gene Ontology Resource: 20 years and still GOing strong. Nucleic Acids Res. 47, D330–D338 (2019).
Vernot, B. et al. Excavating Neandertal and Denisovan DNA from the genomes of Melanesian individuals. Science 352, 235–239 (2016).
Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics doi.org/10.1093/bioinformatics/btq033 (2010).
Ge, T., Chen, C.-Y., Ni, Y., Feng, Y.-C. A. & Smoller, J. W. Polygenic prediction via Bayesian regression and continuous shrinkage priors. Nat. Commun. 10, 1776 (2019).
Adam, D. The promise and peril of the new science of social genomics. Nature doi.org/10.1038/d41586-019-03171-6 (2019).
Wray, N. R. et al. Research review: polygenic methods and their application to psychiatric traits. J. Child Psychol. Psychiatry doi.org/10.1111/jcpp.12295 (2014).
Devaney, J. Eugenics and musical talent: exploring Carl Seashore’s work on talent testing and performance. Am. Music Rev. 48, no. 2 (2019).
Turley, P. et al. Problems with using polygenic scores to select embryos. N. Engl. J. Med. 385, 78–86 (2021).
Read more here: Source link