Massimo Lumaca

482 total citations
19 papers, 253 citations indexed

About

Massimo Lumaca is a scholar working on Cognitive Neuroscience, Signal Processing and Cultural Studies. According to data from OpenAlex, Massimo Lumaca has authored 19 papers receiving a total of 253 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Cognitive Neuroscience, 4 papers in Signal Processing and 4 papers in Cultural Studies. Recurrent topics in Massimo Lumaca's work include Neuroscience and Music Perception (13 papers), Neural dynamics and brain function (11 papers) and Language and cultural evolution (4 papers). Massimo Lumaca is often cited by papers focused on Neuroscience and Music Perception (13 papers), Neural dynamics and brain function (11 papers) and Language and cultural evolution (4 papers). Massimo Lumaca collaborates with scholars based in Denmark, Italy and Norway. Massimo Lumaca's co-authors include Giosuè Baggio, Peter Vuust, Elvira Brattico, Niels Trusbak Haumann, Manon Grube, Andrea Ravignani, Gisella Vetere, Massimiliano Aceti, Leonardo Restivo and Martine Ammassari‐Teule and has published in prestigious journals such as Nature Communications, NeuroImage and Scientific Reports.

In The Last Decade

Massimo Lumaca

19 papers receiving 247 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Massimo Lumaca Denmark 11 195 54 53 35 33 19 253
Joaquín Valdés Chile 7 147 0.8× 52 1.0× 49 0.9× 22 0.6× 19 0.6× 14 245
Deborah Ross United States 10 291 1.5× 52 1.0× 22 0.4× 40 1.1× 31 0.9× 12 328
Ben Dichter United States 8 206 1.1× 37 0.7× 22 0.4× 52 1.5× 16 0.5× 15 276
Germán Mendoza Mexico 9 336 1.7× 69 1.3× 30 0.6× 43 1.2× 34 1.0× 14 397
Janani Sundararajan United States 6 230 1.2× 59 1.1× 39 0.7× 51 1.5× 44 1.3× 6 303
Claire Kabdebon France 8 272 1.4× 45 0.8× 28 0.5× 30 0.9× 27 0.8× 10 368
Tobias Overath United States 10 479 2.5× 137 2.5× 66 1.2× 7 0.2× 35 1.1× 21 510
Greta Tuckute United States 9 298 1.5× 57 1.1× 17 0.3× 23 0.7× 62 1.9× 19 454
Megan Malloy United States 4 264 1.4× 64 1.2× 9 0.2× 35 1.0× 44 1.3× 4 311
Fleur L. Bouwer Netherlands 10 341 1.7× 104 1.9× 82 1.5× 6 0.2× 50 1.5× 20 372

Countries citing papers authored by Massimo Lumaca

Since Specialization
Citations

This map shows the geographic impact of Massimo Lumaca's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Massimo Lumaca with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo Lumaca more than expected).

Fields of papers citing papers by Massimo Lumaca

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Massimo Lumaca. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Massimo Lumaca. The network helps show where Massimo Lumaca may publish in the future.

Co-authorship network of co-authors of Massimo Lumaca

This figure shows the co-authorship network connecting the top 25 collaborators of Massimo Lumaca. A scholar is included among the top collaborators of Massimo Lumaca based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Massimo Lumaca. Massimo Lumaca is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Kvamme, Timo L., Massimo Lumaca, Claude J. Bajada, et al.. (2025). Neural network topologies supporting individual variations in vividness of visual imagery. NeuroImage. 321. 121520–121520. 1 indexed citations
2.
Lumaca, Massimo, Peter E. Keller, Giosuè Baggio, et al.. (2024). Frontoparietal network topology as a neural marker of musical perceptual abilities. Nature Communications. 15(1). 8160–8160. 6 indexed citations
3.
Bonetti, Leonardo, Massimo Lumaca, Sonja A. Kotz, et al.. (2024). Age-related neural changes underlying long-term recognition of musical sequences. Communications Biology. 7(1). 1036–1036. 2 indexed citations
4.
Bonetti, Leonardo, et al.. (2024). Decreased inter-hemispheric connectivity predicts a coherent retrieval of auditory symbolic material. Biological Psychology. 193. 108881–108881. 1 indexed citations
5.
Lumaca, Massimo, Leonardo Bonetti, Elvira Brattico, et al.. (2023). High-fidelity transmission of auditory symbolic material is associated with reduced right–left neuroanatomical asymmetry between primary auditory regions. Cerebral Cortex. 33(11). 6902–6916. 3 indexed citations
6.
7.
Ravignani, Andrea, Massimo Lumaca, & Sonja A. Kotz. (2022). Interhemispheric Brain Communication and the Evolution of Turn-Taking in Mammals. Frontiers in Ecology and Evolution. 10. 2 indexed citations
8.
Lumaca, Massimo, Giosuè Baggio, & Peter Vuust. (2021). White matter variability in auditory callosal pathways contributes to variation in the cultural transmission of auditory symbolic systems. Brain Structure and Function. 226(6). 1943–1959. 9 indexed citations
9.
Haumann, Niels Trusbak, et al.. (2021). Extracting human cortical responses to sound onsets and acoustic feature changes in real music, and their relation to event rate. Brain Research. 1754. 147248–147248. 22 indexed citations
10.
Lumaca, Massimo, Peter Vuust, & Giosuè Baggio. (2021). Network Analysis of Human Brain Connectivity Reveals Neural Fingerprints of a Compositionality Bias in Signaling Systems. Cerebral Cortex. 32(8). 1704–1720. 6 indexed citations
11.
Lumaca, Massimo, Martin Dietz, Niels Chr. Hansen, David Ricardo Quiroga‐Martinez, & Peter Vuust. (2020). Perceptual learning of tone patterns changes the effective connectivity between Heschl's gyrus and planum temporale. Human Brain Mapping. 42(4). 941–952. 12 indexed citations
12.
Lumaca, Massimo, Boris Kleber, Elvira Brattico, Peter Vuust, & Giosuè Baggio. (2019). Functional connectivity in human auditory networks and the origins of variation in the transmission of musical systems. eLife. 8. 23 indexed citations
13.
Lumaca, Massimo, Andrea Ravignani, & Giosuè Baggio. (2018). Music Evolution in the Laboratory: Cultural Transmission Meets Neurophysiology. Frontiers in Neuroscience. 12. 246–246. 17 indexed citations
14.
Ravignani, Andrea, William Forde Thompson, Massimo Lumaca, & Manon Grube. (2018). Why Do Durations in Musical Rhythms Conform to Small Integer Ratios?. Frontiers in Computational Neuroscience. 12. 86–86. 11 indexed citations
15.
Lumaca, Massimo, Niels Trusbak Haumann, Elvira Brattico, Manon Grube, & Peter Vuust. (2018). Weighting of neural prediction error by rhythmic complexity: A predictive coding account using mismatch negativity. European Journal of Neuroscience. 49(12). 1597–1609. 38 indexed citations
16.
Lumaca, Massimo, Niels Trusbak Haumann, Peter Vuust, Elvira Brattico, & Giosuè Baggio. (2018). From random to regular: neural constraints on the emergence of isochronous rhythm during cultural transmission. Social Cognitive and Affective Neuroscience. 13(8). 877–888. 11 indexed citations
17.
Lumaca, Massimo & Giosuè Baggio. (2017). Cultural Transmission and Evolution of Melodic Structures in Multi-generational Signaling Games. Artificial Life. 23(3). 406–423. 23 indexed citations
18.
Lumaca, Massimo & Giosuè Baggio. (2016). Brain potentials predict learning, transmission and modification of an artificial symbolic system. Social Cognitive and Affective Neuroscience. 11(12). 1970–1979. 17 indexed citations
19.
Vetere, Gisella, Leonardo Restivo, Giovanni Novembre, et al.. (2011). Extinction partially reverts structural changes associated with remote fear memory. Learning & Memory. 18(9). 554–557. 39 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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