Ana Luísa Pinho

Selected Publications

1. Research Article

   Connecting to create: expertise in musical improvisation is associated with increased functional connectivity between premotor and prefrontal areas

   Ana Luísa Pinho, Örjan Manzano, Peter Fransson, Helene Eriksson, and Fredrik Ullén

   J Neurosci Apr 2014

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   Musicians have been used extensively to study neural correlates of long-term practice, but no studies have investigated the specific effects of training musical creativity. Here, we used human functional MRI to measure brain activity during improvisation in a sample of 39 professional pianists with varying backgrounds in classical and jazz piano playing. We found total hours of improvisation experience to be negatively associated with activity in frontoparietal executive cortical areas. In contrast, improvisation training was positively associated with functional connectivity of the bilateral dorsolateral prefrontal cortices, dorsal premotor cortices, and presupplementary areas. The effects were significant when controlling for hours of classical piano practice and age. These results indicate that even neural mechanisms involved in creative behaviors, which require a flexible online generation of novel and meaningful output, can be automated by training. Second, improvisational musical training can influence functional brain properties at a network level. We show that the greater functional connectivity seen in experienced improvisers may reflect a more efficient exchange of information within associative networks of importance for musical creativity.

   @article{Pinho2014,
     title = {Connecting to create: expertise in musical improvisation is associated with increased functional connectivity between premotor and prefrontal areas},
     author = {Pinho, Ana Lu{\'i}sa and de Manzano, {\"O}rjan and Fransson, Peter and Eriksson, Helene and Ull{\'e}n, Fredrik},
     journal = {J Neurosci},
     volume = {34},
     number = {18},
     pages = {6156--6163},
     month = apr,
     year = {2014},
     publisher = {Society for Neuroscience},
     url = {https://doi.org/10.1523/JNEUROSCI.4769-13.2014},
   }

2. Research Article

   Subject-specific segregation of functional territories based on deep phenotyping

   Ana Luísa Pinho, Alexis Amadon, Murielle Fabre, Elvis Dohmatob, Isabelle Denghien, Juan Jesús Torre, Chantal Ginisty, Séverine Becuwe-Desmidt, and 13 more authors

   Hum Brain Mapp Mar 2021

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   Functional magnetic resonance imaging (fMRI) has opened the possibility to investigatehow brain activity is modulated by behavior. Most studies so far are bound to one singletask, in which functional responses to a handful of contrasts are analyzed and reported asa group average brain map. Contrariwise, recent data-collection efforts have started to tar-get a systematic spatial representation of multiple mental functions. In this paper, weleverage the Individual Brain Charting (IBC) dataset—a high-resolution task-fMRI datasetacquired in a fixed environment—in order to study the feasibility of individual mapping.First, we verify that the IBC brain maps reproduce those obtained from previous, large-scale datasets using the same tasks. Second, we confirm that the elementary spatial com-ponents, inferred across all tasks, are consistently mapped within and, to a lesser extent,across participants. Third, we demonstrate the relevance of the topographic informationof the individual contrast maps, showing that contrasts from one task can be predicted bycontrasts from other tasks. At last, we showcase the benefit of contrast accumulation forthe fine functional characterization of brain regions within a prespecified network. To thisend, we analyze the cognitive profile of functional territories pertaining to the languagenetwork and prove that these profiles generalize across participants.

   @article{Pinho2021,
     author = {Pinho, Ana Lu{\'i}sa and Amadon, Alexis and Fabre, Murielle and Dohmatob, Elvis and Denghien, Isabelle and Torre, Juan Jes{\'u}s and Ginisty, Chantal and Becuwe-Desmidt, S{\'e}verine and Roger, S{\'e}verine and Laurier, Laurence and Joly-Testault, V{\'e}ronique and M{\'e}diouni-Cloarec, Ga{\"e}lle and Doubl{\'e}, Christine and Martins, Bernadette and Pinel, Philippe and Eger, Evelyn and Varoquaux, Ga{\"e}l and Pallier, Christophe and Dehaene, Stanislas and Hertz-Pannier, Lucie and Thirion, Bertrand},
     title = {Subject-specific segregation of functional territories based on deep phenotyping},
     journal = {Hum Brain Mapp},
     volume = {42},
     number = {4},
     pages = {841-870},
     month = mar,
     year = {2021},
     keywords = {atlases, brain imaging, cognitive function, data set, functional magnetic resonance imaging},
     url = {https://doi.org/10.1002/hbm.25189},
     annotate = {* This paper introduces several key experiments on a fraction of the IBC dataset, namely the first release. In particular, it introduces the application of dictionary learning to summarize contrast maps to topographies. It studies the stability of the dictionary components across data resamplings. It also shows that some contrast maps can be successfully reconstructed from other contrasts. Finally, it illustrates how the accumulation of functional contrasts can help to distinguish between the functional specialization of several regions taken from the language network.},
   }

3. Data Descriptor

   Individual Brain Charting dataset extension, third release for movie watching and retinotopy data

   Ana Luísa Pinho, Hugo Richard, Ana Fernanda Ponce, Michael Eickenberg, Alexis Amadon, Elvis Dohmatob, Isabelle Denghien, Juan Jesús Torre, and 18 more authors

   Sci Data Jun 2024

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   The Individual Brain Charting (IBC) is a multi-task functional Magnetic Resonance Imaging dataset acquired at high spatialresolution, which is intended to facilitate the cognitive mapping of the human brain. It consists in the deep phenotyping of twelve individuals in a fixed environment, covering a broad range of psychological domains that allows, in turn, the investigation of atlasing techniques in functional neuroimaging. Here, we present the inclusion of task data from both naturalistic stimuli and trial-based designs, to uncover core structures of brain activation. We rely on the Fast Shared Response Model (FastSRM): an analytical tool that provides a data-driven solution to model naturalistic stimuli, typically containing many features. We show that data from left-out runs can be reconstructed using FastSRM, thus enabling the extraction of functional networks pertaining to vision, audio and language systems. We also present an in-depth study of the topographic organization of the visual system through a retinotopy task. IBC is open access: source plus derivatives imaging data and meta-data are available in public repositories.

   @article{Pinho2024a,
     title = {{Individual Brain Charting dataset extension, third release for movie watching and retinotopy data}},
     author = {Pinho, Ana Lu{\'i}sa and Richard, Hugo and Ponce, Ana Fernanda and Eickenberg, Michael and Amadon, Alexis and Dohmatob, Elvis and Denghien, Isabelle and Torre, Juan Jes{\'u}s and Shankar, Swetha and Aggarwal, Himanshu and Thual, Alexis and Chapalain, Thomas and Ginisty, Chantal and Becuwe-Desmidt, S{\'e}verine and Roger, S{\'e}verine and Lecomte, Yann and Berland, Val{\'e}rie and Laurier, Laurence and Joly-Testault, V{\'e}ronique and M{\'e}diouni-Cloarec, Ga{\"e}lle and Doubl{\'e}, Christine and Martins, Bernadette and Varoquaux, Ga{\"e}l and Dehaene, Stanislas and Hertz-Pannier, Lucie and Thirion, Bertrand},
     journal = {{Sci Data}},
     volume = {11},
     number = {590},
     month = jun,
     year = {2024},
     url = {https://doi.org/10.1038/s41597-024-03390-1},
   }