Visual Neuroaesthetics (VisNA) Lab

What does it mean for a painting to fill us with wonder, for a sunset to be beautiful or for a film to move us? Why do some visual experiences have the power to reach inside and grab us, while others leave little impression? How can we measure these experiences scientifically?

In the VisNA Lab, we study the psychological and neural basis of aesthetic experiences, such as when a person is aesthetically “moved” by visual art, poetry, architecture, music, or natural landscapes. Much of our research relies on brain imaging (fMRI, EEG) and behavioral techniques. We also frequently use computational tools (e.g. machine learning), measurements of physiology and eyetracking. 

Our core research areas are:

  • Identifying the central cognitive and emotional processes that underly aesthetic experiences and the interacting neural systems that support them.
  • Characterizing the conditions that lead to “shared taste” across a population of individuals in different aesthetic domains.
  • Development of methods for studying aesthetic experiences in more naturalistic settings such as museums and performance halls.

 

Want to volunteer for our studies?

Go here to sign up for the Institute's Research Participant Registry.

 

News

New research from our lab explores how 'what we see’ relates to 'what we like’ using artistic video clips of nature scenes and functional magnetic resonance imaging.

The paper is also part of the research topic Examining the neurodynamics of emotional experiences with naturalistic paradigms

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Where do you find inspiration? New research from our lab suggests that you might want to go to an art museum.

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Interested in working on neuroaesthetics research?

We're looking for a talented and motivated individual to join our team as a student research assistant.

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Events

Society for Neuroscience of Creativity 2020 Virtual Conference

The SfNC Annual Meeting is going virtual! Dr. Vessel will give a data blitz presentation on recent work linking the state of being aesthetically moved with the state of creative inspirationhttps://www.tsfnc.org/2020-conference

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People

Edward A. Vessel

Team Leader

Ayse Ilkay Isik

Postdoctoral Researcher

Dominik Welke

PhD Candidate

Projects

Latest Publications

Welke, D., Purton, I., & Vessel, E. A. (2021). Inspired by art: Higher aesthetic appeal elicits increased felt inspiration in a creative writing task (Advance online publication). Psychology of Aesthetics, Creativity, and the Arts. doi:10.1037/aca0000393.
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Schlotz, W., Wallot, S., Omigie, D., Masucci, M. D., Hoelzmann, S. C., & Vessel, E. A. (2020). The Aesthetic Responsiveness Assessment (AReA): A screening tool to assess individual differences in responsiveness to art in English and German (Online First Posting). Psychology of Aesthetics, Creativity, and the Arts. doi:10.1037/aca0000348.
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Botvinik-Nezer, R., Holzmeister, F., Camerer, C. F., Dreber, A., Huber, J., Johannesson, M., Kirchler, M., Iwanir, R., Mumford, J. A., Adcock, R. A., Avesani, P., Baczkowski, B. M., Bajracharya, A., Bakst, L., Ball, S., Barilari, M., Bault, N., Beaton, D., Beitner, J., Benoit, R. G., Berkers, R. M. W. J., Bhanji, J. P., Biswal, B. B., Bobadilla-Suarez, S., Bortolini, T., Bottenhorn, K. L., Bowring, A., Braem, S., Brooks, H. R., Brudner, E. G., Calderon, C. B., Camilleri, J. A., Castrellon, J. J., Cecchetti, L., Cieslik, E. C., Cole, Z. J., Collignon, O., Cox, R. W., Cunningham, W. A., Czoschke, S., Dadi, K., Davis, C. P., Luca, A. D., Delgado, M. R., Demetriou, L., Dennison, J. B., Di, X., Dickie, E. W., Dobryakova, E., Donnat, C. L., Dukart, J., Duncan, N. W., Durnez, J., Eed, A., Eickhoff, S. B., Erhart, A., Fontanesi, L., Fricke, G. M., Fu, S., Galván, A., Gau, R., Genon, S., Glatard, T., Glerean, E., Goeman, J. J., Golowin, S. A. E., González-García, C., Gorgolewski, K. J., Grady, C. L., Green, M. A., Moreira, J. F. G., Guest, O., Hakimi, S., Hamilton, J. P., Hancock, R., Handjaras, G., Harry, B. B., Hawco, C., Herholz, P., Herman, G., Heunis, S., Hoffstaedter, F., Hogeveen, J., Holmes, S., Hu, C.-P., Huettel, S. A., Hughes, M. E., Iacovella, V., Iordan, A. D., Isager, P. M., Isik, A. I., Jahn, A., Johnson, M. R., Johnstone, T., Joseph, M. J. E., Juliano, A. C., Kable, J. W., Kassinopoulos, M., Koba, C., Kong, X.-Z., Koscik, T. R., Kucukboyaci, N. E., Kuhl, B. A., Kupek, S., Laird, A. R., Lamm, C., Langner, R., Lauharatanahirun, N., Lee, H., Lee, S., Leemans, A., Leo, A., Lesage, E., Li, F., Li, M. Y. C., Lim, P. C., Lintz, E. N., Liphardt, S. W., Vermeer, A. B. L., Love, B. C., Mack, M. L., Malpica, N., Marins, T., Maumet, C., McDonald, K., McGuire, J. T., Melero, H., Leal, A. S. M., Meyer, B., Meyer, K. N., Mihai, G., Mitsis, G. D., Moll, J., Nielson, D. M., Nilsonne, G., Notter, M. P., Olivetti, E., Onicas, A. I., Papale, P., Patil, K. R., Peelle, J. E., Pérez, A., Pischedda, D., Poline, J.-B., Prystauka, Y., Ray, S., Reuter-Lorenz, P. A., Reynolds, R. C., Ricciardi, E., Rieck, J. R., Rodriguez-Thompson, A. M., Romyn, A., Salo, T., Samanez-Larkin, G. R., Sanz-Morales, E., Schlichting, M. L., Schultz, D. H., Shen, Q., Sheridan, M. A., Silvers, J. A., Skagerlund, K., Smith, A., Smith, D. V., Sokol-Hessner, P., Steinkamp, S. R., Tashjian, S. M., Thirion, B., Thorp, J. N., Tinghög, G., Tisdall, L., Tompson, S. H., Toro-Serey, C., Tresols, J. J. T., Tozzi, L., Truong, V., Turella, L., van Veer, A. E. ‘., Verguts, T., Vettel, J. M., Vijayarajah, S., Vo, K., Wall, M. B., Weeda, W. D., Weis, S., White, D. J., Wisniewski, D., Xifra-Porxas, A., Yearling, E. A., Yoon, S., Yuan, R., Yuen, K. S. L., Zhang, L., Zhang, X., Zosky, J. E., Nichols, T. E., & Schonberg, R. A. P. &. T. (2020). Variability in the analysis of a single neuroimaging dataset by many teams. Nature,582, 84-88. doi:10.1038/s41586-020-2314-9.
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Vessel, E. A. (2020). Neuroaesthetics. In Reference Module in Neuroscience and Biobehavioral Psychology. Amsterdam: Elsevier. doi:10.1016/B978-0-12-809324-5.24104-7.
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Appelhoff, S., Sanderson, M., Brooks, T. L., van Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Höchenberger, R., Welke, D., Brunner, C., Rockhill, A. P., Larson, E., Gramfort, A., & Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. The Journal of Open Source Software,4(44): 1896. doi:10.21105/joss.01896.
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Isik, A. I., & Vessel, E. A. (2019). Continuous ratings of movie watching reveal idiosyncratic dynamics of aesthetic enjoyment. PLoS One,14(10): e0223896. doi:10.1371/journal.pone.0223896.
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Vessel, E. A., Isik, A. I., Belfi, A. M., Stahl, J. L., & Starr, a. G. G. (2019). The default-mode network represents aesthetic appeal that generalizes across visual domains. Proceedings of the National Academy of Sciences of the United States of America. doi:10.1073/pnas.1902650116.
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Belfi, A. M., Vessel, E. A., Brielmann, A., Isik, A. I., Chatterjee, A., Leder, H., Pelli, D. G., & Starr, G. (2019). Dynamics of aesthetic experience are reflected in the default-mode network. NeuroImage,188, 584-597. doi:10.1016/j.neuroimage.2018.12.017.
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Esteban, O., Markiewicz, C. J., Blair, R. W., Moodie, C. A., Isik, A. I., Erramuzpe, A., Kent, J. D., Goncalves, M., DuPre, E., Snyder, M., Oya, H., Ghosh, S. S., Wright, J., Durnez, J., Poldrack, R. A., & Gorgolewski, K. J. (2019). fMRIPrep: A robust preprocessing pipeline for functional MRI. Nature methods,16(1), 111-116. doi:10.1038/s41592-018-0235-4.
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Belfi, A. M., Kasdan, A., Rowland, J., Vessel, E. A., Starr, G. G., & Poeppel, D. (2018). Rapid timing of musical aesthetic judgments. Journal of Experimental Psychology: General,147(10), 1531-1543. doi:10.1037/xge0000474.
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Vessel, E. A., Maurer, N., Denker, A. H., & Starr, G. G. (2018). Stronger shared taste for natural aesthetic domains than for artifacts of human culture. Cognition,179, 121-131. doi:10.1016/j.cognition.2018.06.009.
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Belfi, A. M., Vessel, E. A., & Starr, G. G. (2018). Individual ratings of vividness predict aesthetic appeal in poetry. Psychology of Aesthetics, Creativity, and the Arts,12(3), 341-350. doi:10.1037/aca0000153.
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Isik, A. I., Naumer, M. J., Kaiser, J., Buschenlange, C., Wiesmann, S., Czoschke, S., & Yalachkov, Y. (2017). Automatized smoking-related action schemata are reflected by reduced fMRI activity in sensorimotor brain regions of smokers. NeuroImage: Clinical,15, 753-760. doi:10.1016/j.nicl.2017.06.021.
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Vessel, E. A., Biederman, I., Subramaniam, S., & Greene, M. R. (2016). Effective signaling of surface boundaries by L-vertices reflect the consistency of their contrast in natural images. Journal of Vision,16(9): 15. doi:doi:10.1167/16.9.15.
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