My research aims to understand the brain mechanisms underlying memory for temporal sequences using a combination of neuroimaging tools (e.g. magnetoencephalography and magnetic resonance imaging), musical memory paradigms and advanced analytical techniques.

I began my journey in music, earning the traditional 10-year diploma (now equivalent to a master’s degree) in Classical Guitar from the Conservatory of Bologna (2005-2013). During this time, while performing and memorising complex musical pieces for concerts, I became deeply intrigued by the psychology of memory. This curiosity led me to pursue both a bachelor's (2011-2014) and master’s in psychology (2014-2016) at the University of Bologna.

My interest soon expanded beyond the behavioural aspects of memory to understanding the underlying neural mechanisms. This prompted me to begin a PhD in cognitive neuroscience at the Center for Music in the Brain, Aarhus University (2017-2020), where I investigated how the brain encodes musical memory. Throughout my PhD, I developed a strong interest in data analysis and computational methods, which I deepened through research stays (e.g. at MIT in 2019) and during my subsequent Junior Research Fellowship at the University of Oxford (2021-2024).

This multidisciplinary path has allowed me to merge neuroscience with advanced analytical methods and musical paradigms, frequently drawing attention from both the media and the public, and earning me prestigious awards and grants such as the Lundbeck Foundation Talent Prize 2022. My research trajectory has also led to my appointment as Associate Professor at the Center for Music in the Brain, Aarhus University, and as a Research Fellow at the Centre for Eudaimonia and Human Flourishing, University of Oxford. At these institutions, I apply my expertise in music, psychology, neuroscience, and data science to lead a research program focused on human memory, predictive brain processes, and aging.

Throughout my career, I have primarily investigated the brain mechanisms underlying auditory memory and perception, aging, and cognitive functions using magnetoencephalography (MEG) and magnetic resonance imaging (MRI).

Brain dynamics and long-term recognition of auditory sequences

I uncovered hierarchical brain mechanisms during the encoding, recognition and prediction of auditory sequences, demonstrating interactions between the auditory cortices, hippocampus, and cingulate gyrus. I identified differential brain processing speeds for recognising previously memorised versus novel sequences, with slower processing linked to familiar sequences and faster processing to novel ones. My research showed that tonal and atonal musical sequences engage distinct neural networks, with tonal sequences involving the hippocampal and cingulate areas, and atonal sequences activating the auditory processing network. Additionally, I revealed that individuals with higher working memory abilities recruit a broader network, including visual processing areas, for successful auditory memory recognition.

Age-related changes in neurophysiology and predictive coding

I discovered that while older adults could recognise memorised auditory sequences as effectively as younger adults, their brain's functional organisation underwent significant reshaping. Older adults exhibited increased early activity in sensory regions, such as the left auditory cortex, and decreased activity in the medial temporal lobe, pointing to compensatory mechanisms. However, when processing varied sequences, older adults showed a reduced prediction error in the medial temporal lobe and lacked compensatory mechanisms, leading to poorer performance. These findings suggest that the neurophysiology of memory and sequence prediction provides critical insights into healthy aging beyond behavioural performance alone.

Automatic brain predictive processes

I discovered that automatic prediction error is modulated by a complex interplay between genetic (e.g., COMT and BDNF genes), environmental (e.g., musical training), and psychological (e.g., depression, working memory) factors. This research shed new light on prediction error, identifying MMN as a potential biomarker for disorders such as depression.

Cognitive abilities, brain networks and musical training

Computing graph theory measures on functional (from MEG resting state) and structural (from DTI) connectivity networks, I discovered that highly versus average intelligent individuals (high versus average Gf) presented a higher level of integration of information across the whole-brain and a more efficient segregation of local brain subnetworks.

 I also revealed that musical training is associated with functional and structural changes in the brain, as indexed by modulated neurophysiological signals and connectivity. Moreover, I showed that musical practice is related to cognitive abilities, with higher training associated with better cognitive performance beyond the musical domain.

1. Quiroga-Martinez, D.R., Fernandez-Rubio, G., Bonetti, L., Achyutuni, K.G., Tzovara, A., Knight, R.T., & Vuust, P. (2024). Decoding reveals the neural representation of held and manipulated musical thoughts. PLOS Biology, 22 (10), e3002858.
2. Bonetti, L., Vaengaard, A.K., Iorio, C., Vuust, P., Lumaca, M. (2024). Decreased inter-hemispheric connectivity predicts a coherent retrieval of auditory symbolic material in a laboratory model of cultural transmission. Biological Psychology, 108881.
3. Bonetti, L., Brattico, E., Carlomagno, F., Cabral, J., Stevner, A., Deco,G., Whybrow, P.C., Pearce, M., Pantazis, D., Vuust, P., Kringelbach, M.L. (2024). Spatiotemporal whole-brain activity and functional connectivity of melodies recognition. Cerebral Cortex, 34(8), bhae320.
4. Bonetti, L., Fernandez Rubio, G., Lumaca, M., Carlomagno, F., Risgaard Olsen, E., Criscuolo, A., Kotz, S.A., Vuust, P., Brattico, E., Kringelbach, M.L. (2024). Age-related neural changes underlying long-term recognition of musical sequences. Communications Biology, 7, 1036.
5. Gladys, H. J., Jiayi, Z., Bonetti, L., Hian, W. L. P., Vuust, P., Agres, K., & Chen, S. A. (2024). Understanding Music and Aging through the lens of Bayesian Inference. Neuroscience & Biobehavioral Reviews, 105768.
6. Bonetti, L., Fernandez Rubio, G., Carlomagno, F., Pantazis, D., Vuust, P., Kringelbach, M.L. (2024). Spatiotemporal brain hierarchies of auditory memory recognition and predictive coding. Nature Communications, 15(1), 4313.
7. Herff, S. A.*, Bonetti, L.*, Cecchetti, G., Vuust, P., Kringelbach, M. L., & Rohrmeier, M. A. (2024). Hierarchical syntax models of music predict theta power during music listening. Neuropsychologia, 199, 108905. *equally contributing authors
8. Bonetti, L., Bruzzone, S.E.P., Paunio, T., Kantojärvi, K., Kliuchko, M., Vuust, P., Palva, S., Brattico, E. (2023). Moderate associations between BDNF Val66Met gene polymorphism, musical expertise, and mismatch negativity. Heliyon, 9(5), e15600.
9. Fernandez Rubio, G., Olsen, E.R., Klarlund, M., Mallon, O., Carlomagno, F., Vuust, P., Kringelbach, M.L., Brattico, E., Bonetti, L. (2023). Age and musical training effects on auditory short-term, long-term, and working memory. Psychology of Music, 52 (2), 187-198.
10. Lumaca, M., Bonetti, L., Brattico, E., Baggio, G., Ravignani, A. Vuust, P. (2023). High-fidelity transmission of auditory symbolic material is associated with reduced right-left neuroanatomical asymmetry between primary auditory regions. Cerebral Cortex, bhad009.
11. Hoegholt, , Bonetti, L., Stevner, A., Andersen, C.E., Hughes, M., Fernandes, H., Vuust, P., Kringelbach, M.L. (2022). A potential marker for problematic mother–infant bonding revealed by magnetoencephalography study of first–time mothers listening to infant cries. Cerebral Cortex, 33 (10), 5896-5905.
12. Bonetti, L., Carlomagno, F., Kliuchko, M., Gold, B.P., Palva, S., Haumann, N.T., Tervaniemi, M., Huotilainen, M., Vuust, P., Brattico, E. (2022). Whole-brain computation of cognitive versus acoustic errors in music. NeuroImage: Reports, 2(4).
13. Fernández Rubio, G., Brattico, E., Kotz, S.A., Kringelbach, M.L., Vuust, P., Bonetti, L. (2022). Magnetoencephalography recordings reveal the spatiotemporal dynamics of recognition memory for complex versus simple auditory sequence. Communications Biology, 5.
14. Bonetti, L., Brattico, E.,Bruzzone,E.P., Donati, G., Deco, G.,Pantazis, D., Vuust, P., Kringelbach, M.L. (2022). Brain recognition of previously learned versus novel temporal sequences: a differential simultaneous processing. Cerebral Cortex, bhac439.
15. Fernández Rubio, G., Carlomagno, F., Vuust, P., Kringelbach, M.L., Bonetti, L. (2022). Associations between abstract working memory abilities and brain activity underlying long-term recognition of auditory sequences. PNAS Nexus, 1(4),pgac216.
16. Iorio, C., Brattico, E., Larsen, F. M., Vuust, P., Bonetti, L. (2022). The effect of mental practice on music memorization. Psychology of Music (1), 230-244.
17. Criscuolo, , Pando-Naude, V., Bonetti, L., Vuust, P., Brattico, E. (2022). An ALE meta-analytic review of musical expertise. Scientific Reports, 12 (11726).
18. Bruzzone, S.E.P., Lumaca, M., Brattico, E., Vuust, P., Kringelbach, M.L., Bonetti, L. (2022). Dissociated brain functional connectivity of fast versus slow frequencies underlying individual differences in fluid intelligence: a DTI and MEG study. Scientific Reports, 12 (1), 4746.
19. Bonetti, L., Brattico, E., Carlomagno, F., Donati, G., Cabral, J., Haumann, N. T., Deco, G., Vuust, P., Kringelbach, M. L. (2021). Rapid encoding of musical tones discovered in whole-brain connectivity. NeuroImage, 245, 118735.
20. 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.
21. Bonetti, L., Bruzzone, S. E., Sedghi, N. A., Haumann, N. T., Paunio, T., Kantojärvi, K., Kliuchko, M., Vuust, P., Brattico, E. (2021). Association between COMT gene Val158Met heterozygote polymorphism and enhanced brain predicting processes. NeuroImage, 233, 117954.
22. Brattico, E., Bonetti, L., Ferretti, G., Vuust, P., Matrone, C. (2021). Putting the cell in motion: advantages of endogenous boosting of BDNF production. Cells, 10(1), 183.
23. Costa, M., Bonetti, L. (2020). Eye and lips in artistic profiles. Psychology of Aesthetics, Creativity, and the Arts, 16 (4), 694.
24. Bonetti, L., Brattico, E., Vuust, P., Kliuchko, M., Saarikallio, S. (2020). Intelligence and music: Lower intelligent quotient is associated with higher use of music for experiencing strong sensations. Empirical Studies of the Arts, 39 (2), 194-215.
25. Criscuolo, A., Bonetti, L., Särkämö, T., Kliuchko, M., Brattico, E. (2019). On the association between musical training, intelligence and executive functions in adulthood. Frontiers in Psychology, section Auditory Cognitive Neuroscience. 10:1704.
26. Costa, M., Bonetti, L., Vignali, V., Bichicchi, A., Lantieri, C., Simone, A. (2019). Driver's visual attention to different categories of roadside advertising signs. Applied Ergonomics, 78, 127-136
27. Costa, M., Bonetti, L., Vignali, V., Lantieri, C., Simone, A. (2018). The role of peripheral vision in vertical road sign identification and discrimination. Journal of Ergonomics, 61(12), 1619-1634.
28. Bonetti, L., Haumann, N.T., Brattico, E., Klyuchko, M., Vuust, P., Särkämö, T., Näätänen, R. (2018). Auditory sensory memory and working memory skills: Association between frontal MMN and performance scores. Brain Research, 1700, 86-98.
29. Costa, M., Bonetti, L. (2018). Geometrical distortions in large-scale cognitive geographical maps. Journal of Environmental Psychology, 55, 53-69.
30. Bonetti, L., Haumann, N. T., Vuust, P., Kliuchko, M., Brattico, E. (2017). Risk of depression enhances auditory pitch discrimination in the brain as indexed by the Mismatch Negativity. Clinical Neurophysiology, 128(10), 1923-1936.
31. Bonetti, L., Costa, M. (2017). Pitch-verticality and pitch-size cross-modal interactions. Psychology of Music, 46(3), 340-356.
32. Bonetti, L., Costa, M. (2017). Musical mode and visual-spatial cross-modal associations in infants and adults. Musicae Scientiae, 23(1), 50-68.
33. Costa, M., Bonetti, L. (2017). Linear perspective and framing in the vista paradox. Perception, 46(11), 1245-1268.
34. Costa, M., Bonetti, L., Belelli, M., Lantieri, C., Vignali, V., Simone, A. (2016). Reflective tape applied to bicycle frame and conspicuity enhancement at night. Human Factors, 59(3), 485-500.
35. Costa, M., Bonetti, L. (2016). Geometrical factors in the perception of sacredness. Perception, 45, 1240-1266.
36. Bonetti, L., Costa, M. (2016). Intelligence and musical mode preference. Empirical Studies of the Arts, 34, 160-176

1. Bonetti, L., Fernandez-Rubio, G., Szabo, S. A., Carlomagno, F., Vuust, P., Kringelbach, M. L., & Brattico, E. (2024). The neural mechanisms of concept formation over time in music.bioRxiv, 2024-11.

2. Bonetti, L., Fernandez-Rubio, G., Andersen, M. H., Malvaso, C., Carlomagno, F., Testa, C., ... & Rosso, M. (2024). BROADband brain Network Estimation via Source Separation (BROAD-NESS).bioRxiv, 2024-10.

3. Wehmeyer, L., Baldermann, J.C., Pogosyan, A., Rodriguez Plazas, F., Loehrer, P.A., Bonetti, L., Yassine, S., Zur Muehlen, K., Schueller, T., Kuhn, J. and Visser-Vandewalle, V. (2024). Thalamo-frontal connectivity patterns in Tourette Syndrome: Insights from combined intracranial DBS and EEG recordings. bioRxiv.

4. Bonetti, L., Risgaard Olsen, E., Carlomagno, F., Serra, E., Szabo, S. A., Klarlund, M., ... & Fernandez-Rubio, G. (2024). Working memory predicts long-term recognition of auditory sequences: Dissociation between confirmed predictions and prediction errors. bioRxiv.

5. Rosso, M., Fernández-Rubio, G., Keller, P., Brattico, E., Vuust, P., Kringelbach, M.L., Bonetti, L. (2024). FREQuency-resolved brain Network Estimation via Source Separation (FREQ-NESS). bioRxiv.

6. Bonetti, L.*, Vestberg, T.*, Jafari, R., Seghezzi, D., Ingvar, M., Kringelbach, M.L., Goncalves, A., Petrovic, P. (2024). Decoding the elite soccer players psychological profile. bioRxiv.
   * = equally contributing authors

7. Fernández-Rubio, G., Vuust, P., Kringelbach, M.L., Bonetti, L. (2024). The neurophysiology of healthy and pathological aging: A comprehensive systematic review. bioRxiv.

8. Campo, F. F., Carlomagno, F., Vuust, P., Haumann, N. T., Bonetti, L., Grube, M., & Brattico, E. (2024). Is auditory prediction related to domain-general cognitive abilities? A neurophysiology study on MMN and cognitive performance scores. A neurophysiology study on MMN and cognitive performance scores. Preprint on SSRN.

9. Nartallo-Kaluarachchi, R., Bonetti, L., Fernández-Rubio, G., Vuust, P., Deco, G., Kringelbach, M.L., Lambiotte, R. and Goriely, A. (2024). Multilevel irreversibility reveals higher-order organisation of non-equilibrium interactions in human brain dynamics. bioRxiv.

10. Criscuolo, A., Schwartze, M., Bonetti, L., & Kotz, S. A. (2024). Ageing impacts basic auditory and timing processing. bioRxiv.

11. Serra, E., Lumaca, M., Brattico, E., Vuust, P., Kringelbach, M. L., & Bonetti, L. (2023). Neurophysiological correlates of short-term recognition of sounds: Insights from magnetoencephalography. bioRxiv.

12. Quiroga-Martinez, D. R., Rubio, G. F., Bonetti, L., Achyutuni, K. G., Tzovara, A., Knight, R. T., & Vuust, P. (2023). Decoding reveals the neural representation of held and manipulated musical thoughts. bioRxiv.

13. Carraturo, G., Pando-Naude, V., Costa, M., Vuust, P., Bonetti, L., Brattico, E. (2023). The major-minor mode dichotomy in music perception: A systematic review on its behavioural, physiological, and clinical correlates. bioRxiv.

14. Costa, M., Vuust, P., Kringelbach, M., Bonetti, L. (2023). Age-related brain mechanisms underlying short-term recognition of musical sequences: An EEG study. bioRxiv.

15. Brandl, S., Haumann, N.T., Radloff, S., Dähne, S., Bonetti, L., Vuust, P., Brattico, E., Grube, M. (2021). Fourier SPoC: A customised machine-learning analysis pipeline for auditory beat-based entrainment in the MEG. bioRxiv.