Yaroslav O. Halchenko

Affiliations: 
Dartmouth College, Hanover, NH, United States 
Area:
Imaging, Multimodal Analysis, PyMVPA, Category-specific Visual Processing
Website:
http://www.onerussian.com
Google:
"Yaroslav Halchenko"
Mean distance: 14.47 (cluster 29)
 
SNBCP

Parents

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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
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Publications

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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
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
Markiewicz CJ, Gorgolewski KJ, Feingold F, et al. (2021) The OpenNeuro resource for sharing of neuroscience data. Elife. 10
Nastase SA, Liu YF, Hillman H, et al. (2021) The "Narratives" fMRI dataset for evaluating models of naturalistic language comprehension. Scientific Data. 8: 250
Baranger DAA, Halchenko YO, Satz S, et al. (2021) Aberrant levels of cortical myelin distinguish individuals with depressive disorders from healthy controls. Neuroimage. Clinical. 32: 102790
Manelis A, Soehner A, Halchenko YO, et al. (2021) White matter abnormalities in adults with bipolar disorder type-II and unipolar depression. Scientific Reports. 11: 7541
Bannier E, Barker G, Borghesani V, et al. (2021) The Open Brain Consent: Informing research participants and obtaining consent to share brain imaging data. Human Brain Mapping
Cheng CP, Halchenko YO. (2020) A new virtue of phantom MRI data: explaining variance in human participant data. F1000research. 9: 1131
Esteban O, Ciric R, Finc K, et al. (2020) Analysis of task-based functional MRI data preprocessed with fMRIPrep. Nature Protocols
Yarkoni T, Markiewicz CJ, de la Vega A, et al. (2019) PyBIDS: Python tools for BIDS datasets. Journal of Open Source Software. 4
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