Yaroslav O. Halchenko
Affiliations: | Dartmouth College, Hanover, NH, United States |
Area:
Imaging, Multimodal Analysis, PyMVPA, Category-specific Visual ProcessingWebsite:
http://www.onerussian.comGoogle:
"Yaroslav Halchenko"Mean distance: 14.47 (cluster 29) | S | N | B | C | P |
Parents
Sign in to add mentor| Barak A. Pearlmutter | grad student | 2000-2002 | Univ. of New Mexico | |
| Stephen Jose Hanson | grad student | 2002-2009 | NJIT | |
| (Predictive decoding of neural data.) | ||||
| James Haxby | post-doc | 2009- | Dartmouth | |
Collaborators
Sign in to add collaborator| Per B. Sederberg | collaborator | ||
| Matteo Visconti di Oleggio Castello | collaborator | Dartmouth | |
| Michael Hanke | collaborator | 2006- | |
| Russell A. Poldrack | collaborator | 2008- | Rutgers, Newark |
| Samuel A. Nastase | collaborator | 2012- | Dartmouth |
BETA: Related publications
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Publications
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| Subash P, Gray A, Boswell M, et al. (2023) A comparison of neuroelectrophysiology databases. Scientific Data. 10: 719 |
| Poldrack RA, Markiewicz CJ, Appelhoff S, et al. (2023) The Past, Present, and Future of the Brain Imaging Data Structure (BIDS). Arxiv |
| Zhao C, Jarecka D, Covitz S, et al. (2023) A reproducible and generalizable software workflow for analysis of large-scale neuroimaging data collections using BIDS Apps. Biorxiv : the Preprint Server For Biology |
| Subash P, Gray A, Boswell M, et al. (2023) A Comparison of Neuroelectrophysiology Databases. Arxiv |
| Kiar G, Clucas J, Feczko E, et al. (2023) Align with the NMIND consortium for better neuroimaging. Nature Human Behaviour |
| Ciric R, Thompson WH, Lorenz R, et al. (2022) TemplateFlow: FAIR-sharing of multi-scale, multi-species brain models. Nature Methods |
| Manelis A, Halchenko YO, Bonar L, et al. (2022) Working memory updating in individuals with bipolar and unipolar depression: fMRI study. Translational Psychiatry. 12: 441 |
| Satz S, Halchenko YO, Ragozzino R, et al. (2022) The Relationship Between Default Mode and Dorsal Attention Networks Is Associated With Depressive Disorder Diagnosis and the Strength of Memory Representations Acquired Prior to the Resting State Scan. Frontiers in Human Neuroscience. 16: 749767 |
| Hanke M, Pestilli F, Wagner AS, et al. (2021) In defense of decentralized research data management. Neuroforum. 27: 17-25 |
| Baranger DAA, Halchenko YO, Satz S, et al. (2021) Protocol for a machine learning algorithm predicting depressive disorders using the T1w/T2w ratio. Methodsx. 8: 101595 |