Alfonso Nieto-Castanon
Alfonso Nieto-Castanon is a Spanish computational neuroscientist and developer of computational neuroimaging analysis methods and tools. He is a visiting researcher at the Boston University College of Health and Rehabilitation Sciences, and research affiliate at MIT McGovern Institute for Brain Research. His research focuses on the understanding and characterization of human brain dynamics underlying mental function.
Early life and education
Nieto-Castanon was born in Spain in 1972. He was part of the first Spanish team to participate in the International Physics Olympiad in 1990. He went to college at the Universidad de Valladolid from 1991 to 1995 and earned a B.S./M.S. in Telecommunications Engineering. In 1998 he pursued graduate studies in Boston University Cognitive and Neural Systems Department and was awarded a research training fellowship from Fundación Séneca/Cedetel, and a graduate research fellowship from Boston University. He received a Ph.D. in Computational Neuroscience in 2004.Contributions to science
ROI analyses
In some of his early work Nieto-Castanon helped develop novel methods for region of interest analyses of fMRI data, with a focus on multivariate techniques and the use of subject-specific ROIs, where regions of interest are defined differently for each person based on common anatomical or functional landmarks. Subject-specific ROIs allowed researchers to probe the limits of the functional localization hypotheses common in neuroimaging, and better understand the spatial and functional specificity of different brain areas.Brain-computer interfaces
In collaboration with Boston University's Neural Prosthesis Laboratory, Nieto-Castanon helped build a Neuroprosthetic device for real-time speech synthesis. This system was designed to allow patients with locked-in syndrome to produce speech by decoding signals from a neurotrophic electrode implanted in the brain.Functional connectivity
Nieto-Castanon also developed multiple influential mathematical and computational techniques for functional connectivity analyses, with a special emphasis on the robust estimation of functional connectivity measures in the presence of subject-motion and physiological noise sources. In 2011 he developed CONN to integrate and facilitate best practices in functional connectivity studies. CONN included a combination of novel methods such as multivariate connectivity analyses and dynamic connectivity estimation, together with multiple well known techniques such as psycho-physiological interactions, graph analyses, or independent component analyses. His software has been since widely adopted in the field and it is now regularly used in functional connectivity studies, with over 900 citations during 2021 aloneNieto-Castanon has given numerous courses and lectures worldwide and his work has been cited in over 8000 refereed journal articles to date.