Publication
] A look back at the June 2016 BMM Workshop in Sestri Levante, Italy. (2016).
Sestri Levante Review (359.33 KB)
Sestri Levante Review (359.33 KB) A computational probe into the behavioral and neural markers of atypical facial emotion processing in autism. The Journal of Neuroscience JN-RM-2229-21 (2022). doi:10.1523/JNEUROSCI.2229-21.2022
Fast Recurrent Processing via Ventrolateral Prefrontal Cortex Is Needed by the Primate Ventral Stream for Robust Core Visual Object Recognition. Neuron 109, 164 - 176.e5 (2021).
Evidence that recurrent pathways between the prefrontal and inferior temporal cortex is critical during core object recognition . COSYNE (2020).
Evidence that recurrent pathways between the prefrontal and inferior temporal cortex is critical during core object recognition . Society for Neuroscience (2019).
Fast Recurrent Processing via Ventrolateral Prefrontal Cortex Is Needed by the Primate Ventral Stream for Robust Core Visual Object Recognition. Neuron (2020). doi:10.1016/j.neuron.2020.09.035 PIIS0896627320307595.pdf (3.92 MB)
PIIS0896627320307595.pdf (3.92 MB) Evidence that recurrent circuits are critical to the ventral stream’s execution of core object recognition behavior. Nature Neuroscience (2019). doi:10.1038/s41593-019-0392-5 Author's last draft (1.74 MB)
Author's last draft (1.74 MB) Chemogenetic suppression of macaque V4 neurons produces retinotopically specific deficits in downstream IT neural activity patterns and core object recognition behavior. Journal of Vision 21, (2021).
CNNs reveal the computational implausibility of the expertise hypothesis. iScience 26, 105976 (2023).
Using artificial neural networks to ask ‘why’ questions of minds and brains. Trends in Neurosciences 46, 240 - 254 (2023).
Using child‐friendly movie stimuli to study the development of face, place, and object regions from age 3 to 12 years. Human Brain Mapping (2022). doi:10.1002/hbm.25815
Are topographic deep convolutional neural networks better models of the ventral visual stream?. Conference on Cognitive Computational Neuroscience (2019).
To find better neural network models of human vision, find better neural network models of primate vision. BioRxiv (2019). at <https://www.biorxiv.org/content/10.1101/688390v1.full>
Large-scale hyperparameter search for predicting human brain responses in the Algonauts challenge. The Algonauts Project: Explaining the Human Visual Brain Workshop 2019 (2019). doi:10.1101/689844
Discovering Switching Autoregressive Dynamics in Neural Spike Train Recordings. (2015). cosyne2015b.pdf (7.27 MB)
cosyne2015b.pdf (7.27 MB) Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNN. 34th International Conference on Machine Learning 70, 1733-1741 (2017). 1612.05231.pdf (2.3 MB)
1612.05231.pdf (2.3 MB) Children understand that agents maximize expected utilities. Journal of Experimental Psychology: General 146, 1574 - 1585 (2017). ExpectedUtilities_Final.pdf (950.09 KB)
ExpectedUtilities_Final.pdf (950.09 KB) Not So Innocent: Toddlers’ Inferences About Costs and Culpability. Psychological Science 26, 633-40 (2015). NotSoInnocent_InPress.pdf (238.53 KB)
NotSoInnocent_InPress.pdf (238.53 KB) Children’s understanding of the costs and rewards underlying rational action. Cognition 140, 14–23 (2015). CM_inPress.pdf (438.5 KB)
CM_inPress.pdf (438.5 KB) Mastery of the logic of natural numbers is not the result of mastery of counting: Evidence from late counters. . Developmental Science (2016). doi:10.1111/desc.12459
The naive utility calculus: computational principles underlying social cognition. Trends Cogn Sci. (2016). doi:10.1016/j.tics.2016.05.011
Self-supervised intrinsic image decomposition. Annual Conference on Neural Information Processing Systems (NIPS) (2017). at <https://papers.nips.cc/paper/7175-self-supervised-intrinsic-image-decomposition> intrinsicImg_nips_2017.pdf (5.87 MB)
intrinsicImg_nips_2017.pdf (5.87 MB) Can Deep Learning Recognize Subtle Human Activities?. CVPR 2020 (2020).