Fabian A. Soto, Ph.D.
Affiliations: | 2015- | Psychology | FIU |
Area:
Visual categorization and object recognition, causal and predictive learning, stimulus generalization, computational cognitive neuroscience.Website:
ccnlab.fiu.eduGoogle:
"Fabian Soto"Mean distance: (not calculated yet)
Parents
Sign in to add mentor| Edward A. Wasserman | grad student | University of Iowa | |
| Greg Ashby | post-doc | 2011-2015 | UC Santa Barbara |
| Edgar Harry Vogel | research scientist |
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Publications
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| Soto FA, Vogel EH, Uribe-Bahamonde YE, et al. (2023) Why is the Rescorla-Wagner model so influential? Neurobiology of Learning and Memory. 107794 |
| Perez OD, Vogel EH, Narasiwodeyar S, et al. (2022) Subsampling of cues in associative learning. Learning & Memory (Cold Spring Harbor, N.Y.). 29: 160-170 |
| Soto FA, Escobar K, Salan J. (2020) Adaptation aftereffects reveal how categorization training changes the encoding of face identity. Journal of Vision. 20: 18 |
| Hays J, Wong C, Soto FA. (2020) FaReT: A free and open-source toolkit of three-dimensional models and software to study face perception. Behavior Research Methods |
| Perez OD, Soto FA. (2020) Author accepted manuscript: Evidence for a dissociation between causal beliefs and instrumental actions. Quarterly Journal of Experimental Psychology (2006). 1747021819899808 |
| Soto FA. (2019) Beyond the "Conceptual Nervous System": Can computational cognitive neuroscience transform learning theory? Behavioural Processes. 167: 103908 |
| Soto FA. (2019) Categorization training changes the visual representation of face identity. Attention, Perception & Psychophysics. 81: 1220-1227 |
| Soto FA, Ashby FG. (2019) Novel representations that support rule-based categorization are acquired on-the-fly during category learning. Psychological Research. 83: 544-566 |
| Soto FA. (2019) Linking general recognition theory and classification images to study invariance and configurality of visual representations Journal of Vision. 19 |
| Soto FA, Vucovich LE, Ashby FG. (2018) Linking signal detection theory and encoding models to reveal independent neural representations from neuroimaging data. Plos Computational Biology. 14: e1006470 |