Thomas Naselaris
Affiliations: | Medical University of South Carolina, Charleston, SC, United States | ||
| University of Minnesota, Twin Cities, Minneapolis, MN |
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"Thomas Naselaris"Mean distance: 13.48 (cluster 29) | S | N | B | C | P |
Parents
Sign in to add mentor| Apostolos P. Georgopoulos | grad student | 2005 | UMN | |
| (Mapping of preferred directions in the motor cortex.) | ||||
| Jack L. Gallant | post-doc | 2005- | UC Berkeley | |
Children
Sign in to add trainee| Hayden R Johnson | research assistant | 2023-2024 | University of Minnesota - Minneapolis |
| Maggie Mae Mell | grad student | 2015- | MUSC |
| Koustav Banerjee | grad student | 2022-2024 | UMN |
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Publications
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| Lin R, Naselaris T, Kay K, et al. (2024) Stacked regressions and structured variance partitioning for interpretable brain maps. Neuroimage. 298: 120772 |
| Ye Z, Zhao Y, Allen EJ, et al. (2024) Temporal asymmetry of neural representations predicts memory decisions. Biorxiv : the Preprint Server For Biology |
| Kay K, Prince JS, Gebhart T, et al. (2024) Disentangling signal and noise in neural responses through generative modeling. Biorxiv : the Preprint Server For Biology |
| Kneeland R, Ojeda J, St-Yves G, et al. (2023) Brain-optimized inference improves reconstructions of fMRI brain activity. Arxiv |
| Zou F, Wanjia G, Allen EJ, et al. (2023) Re-expression of CA1 and entorhinal activity patterns preserves temporal context memory at long timescales. Nature Communications. 14: 4350 |
| Kneeland R, Ojeda J, St-Yves G, et al. (2023) Second Sight: Using brain-optimized encoding models to align image distributions with human brain activity. Arxiv |
| St-Yves G, Allen EJ, Wu Y, et al. (2023) Brain-optimized deep neural network models of human visual areas learn non-hierarchical representations. Nature Communications. 14: 3329 |
| Kneeland R, Ojeda J, St-Yves G, et al. (2023) Reconstructing seen images from human brain activity via guided stochastic search. Arxiv |
| Lin R, Naselaris T, Kay K, et al. (2023) Stacked regressions and structured variance partitioning for interpretable brain maps. Biorxiv : the Preprint Server For Biology |
| Pennock IML, Racey C, Allen EJ, et al. (2022) Color-biased regions in the ventral visual pathway are food selective. Current Biology : Cb. 33: 134-146.e4 |