Alejandro de la Vega
Curriculum Vitae
Academic Positions
2019-
Research Scientist, Department of Psychology, University of Texas at Austin
2016-2019
Postdoctoral Fellow, Department of Psychology, University of Texas at Austin
Education
2016
Ph.D., Cognitive Neuroscience, University of Colorado Boulder
2012
M.A., Cognitive Psychology, University of Colorado Boulder
2009
B.A., Linguistics and Cognitive Science, Pomona College
Awards
2019
Merit Abstract Award, Organization for Human Brain Mapping
2018
Winner, Open Science Naturalistic Viewing Competition, Organization for Human Brain Mapping
2017
Fellow, Neurohackweek
2012
Fellow, Summer Institute in Cognitive Neuroscience
2011
Ford Foundation Fellowship, Honorable Mention (Alternate)
2010
National Science Foundation, Predoctoral Fellowship, Honorable Mention
2010
Fellow, fMRI Training Course, University of Michigan-Ann Arbor
Active Funding
2021-2025
R01MH096906 National Institutes of Health. Large-scale image-based meta-analysis of
functional MRI data. Role: PI.
2021-2024
R01MH109682 National Institutes of Health. NeuroScout: A cloud-based platform for
rapid re-analysis of naturalistic fMRI datasets. Role: PI.
Scientific Contributions
Peer-reviewed journal articles
2022
Rocca, R., & De La Vega, A. (2022). Evaluating the role of non-lexical markers in GPT-2’s language modeling behavior. Proceedings of the 3rd Workshop on Evaluation and Comparison of NLP Systems, 96–102.
Niso, G., Botvinik-Nezer, R., Appelhoff, S., De La Vega, A., Esteban, O., Etzel, J. A., Finc, K., Ganz, M., Gau, R., Halchenko, Y. O., & others. (2022). Open and reproducible neuroimaging: from study inception to publication. NeuroImage, 119623.
De La Vega, A., Rocca, R., Blair, R. W., Markiewicz, C. J., Mentch, J., Kent, J. D., Herholz, P., Ghosh, S. S., Poldrack, R. A., & Yarkoni, T. (2022). Neuroscout, a unified platform for generalizable and reproducible fMRI research. Elife, 11, e79277.
2021
Halchenko, Y., Meyer, K., Poldrack, B., Solanky, D., Wagner, A., Gors, J., MacFarlane, D., Pustina, D., Sochat, V., …, De La Vega, A. et al. (2021). DataLad: distributed system for joint management of code, data, and their relationship. Journal of Open Source Software, 6(63).
Levitis, E., Van Praag, C. D. G., Gau, R., Heunis, S., DuPre, E., Kiar, G., Bottenhorn, K. L., Glatard, T., Nikolaidis, A., …, De La Vega, A., et al. (2021). Centering inclusivity in the design of online conferences—An OHBM–Open Science perspective. GigaScience, 10(8), giab051.
2020
Esteban, O., Ciric, R., Finc, K., Blair, R. W., Markiewicz, C. J., Moodie, C. A., Kent, J. D., Goncalves, M., DuPre, E., …, De La Vega, A. et al.. (2020). Analysis of task-based functional MRI data preprocessed with fMRIPrep. Nature Protocols, 15(7), 2186–2202.
2019
Brieger, K., Zajac, G.J.M, Pandit, A., Foerster, J.R., Li, K.W., Annis, A.C., Schmidt, E.M., Clark, C.P., McMorrow, K., Zhou, W., Yang, J., Kwong, A.M., Boughton, A.P., Wu, J., Scheller, C., Parikh, T., __De La Vega, A.__, Brazel, D.M., Frieser, M., Rea-Sandin, G., Fritsche, L.G., Vrieze, S.I., Abecasis, G.R. (2019). Genes for Good: Engaging the Public in Genetics Research via Social Media. American Journal of Human Genetics.
Yarkoni, T., Markiewicz, C. J., De La Vega, A., Gorgolewski, K. J., Salo, T., Halchenko, Y. O., McNamara, Q., DeStasio, K., Poline, J.-B., Petrov, D., & others. (2019). PyBIDS: Python tools for BIDS datasets. Journal of Open Source Software, 4(40).
2018
Dixon, M. L., De La Vega, A., Mills, C., Andrews-Hanna, J., Spreng, R. N., Cole, M. W., & Christoff, K. (2018). Heterogeneity within the frontoparietal control network and its relationship to the default and dorsal attention networks. Proceedings of the National Academy of Sciences, 115(7), E1598–E1607. [pdf] [github]
2017
De La Vega, A., Yarkoni, T., Wager, T. D., & Banich, M. T. (2017). Large-scale meta-analysis suggests low regional modularity in lateral frontal cortex. Cerebral Cortex, 1–15.
[pdf] [github]
2017
McNamara, Q., De La Vega, A., & Yarkoni, T. (2017). Developing a comprehensive framework for multimodal feature extraction. Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1567–1574.
[pdf]
2016
De La Vega, A., Chang, L. J., Banich, M. T., Wager, T. D., & Yarkoni, T. (2016). Large-scale meta-analysis of human medial frontal cortex reveals tripartite functional organization. Journal of Neuroscience, 36(24), 6553–6562.
[pdf] [Journal Club review] [our response]
2014
De La Vega, A., Brown, M. S., Snyder, H. R., Singel, D., Munakata, Y., & Banich, M. T. (2014). Individual differences in the balance of GABA to glutamate in pFC predict the ability to select among competing options. Journal of Cognitive Neuroscience. [pdf]
2013
Michaelson, L., De La Vega, A*., Chatham, C., & Munakata, Y. (2013). Delaying gratification depends on social trust. Frontiers in Psychology, 4, 355.
[pdf]
** co-first authors
2013
Banich, M. T., De La Vega, A., Andrews-Hanna, J. R., Mackiewicz Seghete, K., Du, Y., & Claus, E. D. (2013). Developmental trends and individual differences in brain systems involved in intertemporal choice during adolescence. Psychology of Addictive Behaviors, 27(2), 416. [pdf]
Selected open-source scientific software contributions
Neuroscout. An end-to-end platform for analysis of naturalistic public fMRI datasets (https://neuroscout.org/; https://github.com/neuroscout/neuroscout; De La Vega et al., 2022).
PyBIDS. A Python library for querying and manipulating BIDS datasets (https://www.github.com/bids-standard/pybids; Yarkoni et al., 2019).
FitLins. A Python library for fitting linear models to BIDS datasets (https://www.github.com/poldracklab/fitlins; Markiewicz et al., 2019).
NeuroSynth-Compose. Platform for easily perform custom neuroimaging meta-analyses using a fully web-based platform (https://compose.neurosynth.org/; https://ww.github.com/neurostuff/neurostore).
Presentations
Conference talks and departmental lectures
2023
Best practices for robust and reproducible neuroimaging meta-analysis. Co-organizer. Organization for Human Brain Mapping Educational Course. Montreal, Canada.
2020
Automated feature extraction with Pliers. Organization for Human Brain Mapping, Analysis Methods for Naturalistic Data Educational Course. Virtual.
2019
Neuroscout: a cloud-based platform for flexible re-analysis of naturalistic fMRI datasets. Mozilla Data Club Brown Bag.
2019
Neuroscout: a cloud-based platform for flexible re-analysis of naturalistic fMRI datasets. Organization for Human Brain Mapping. Rome, Italy.
2018
An turnkey solution for rapid and flexible (re)analysis of naturalistic fMRI data. Organization for Human Brain Mapping. Singapore, Singapore.
2017
A cloud-based platform for flexible re- analysis of naturalistic fMRI datasets. International Neuroinformatics Coordinating Facility Congress. Kuala Lumpur, Malaysia.
Professional Service
2020
Americas Hub Manager, Organization of Human Brain Mapping Hackathon, Virtual, 2020.
2019
Chair, Neuroinformatics and Data Sharing Session, Organization for Human Brain Mapping, Rome, Italy, 2019
2018
Co-Organizer, Austin Code Rodeo Neuroinformatics Hackathon
Ad-hoc peer review
Neuroimage (x5), GigaScience (x3), Scientific Reports (x2), Annual Conference on Cognitive Computational Neuroscience (x2), eNeuro, Organization for Human Brain Mapping, Proceedings of the Python in Science Conferences, Cerebral Cortex, Neuropsychologia (x3), PLOS One, Human Brain Mapping.
Teaching
2013-2016
Computer Laboratory for Instruction in Psychological Research (CLIPR) TA.
- Developed and taught three part series, R for Psychologists every semester.
2012-2013
Teaching Assistant, General Statistics & Cognitive Neuroscience
Last updated: April 2023