Articles with public access mandates - Bria LongLearn more
Available somewhere: 18
Data availability, reusability, and analytic reproducibility: evaluating the impact of a mandatory open data policy at the journal Cognition
TE Hardwicke, MB Mathur, K MacDonald, G Nilsonne, GC Banks, ...
Royal Society open science 5 (8), 180448, 2018
Mandates: US National Science Foundation, Arnold Ventures LLC
Mid-level visual features underlie the high-level categorical organization of the ventral stream
B Long, CP Yu, T Konkle
Proceedings of the National Academy of Sciences 115 (38), E9015-E9024, 2018
Mandates: US National Institutes of Health
Neural dynamics of prediction and surprise in infants
S Kouider, B Long, L Le Stanc, S Charron, AC Fievet, LS Barbosa, ...
Nature communications 6 (1), 8537, 2015
Mandates: European Commission
Mid-level perceptual features distinguish objects of different real-world sizes.
B Long, T Konkle, MA Cohen, GA Alvarez
Journal of Experimental Psychology: General 145 (1), 95-109, 2016
Mandates: US National Science Foundation, US National Institutes of Health
Mid-level perceptual features contain early cues to animacy
B Long, VS Störmer, GA Alvarez
Journal of vision 17 (6), 20-20, 2017
Mandates: US National Science Foundation, European Commission
Analytic reproducibility in articles receiving open data badges at the journal Psychological Science: an observational study
TE Hardwicke, M Bohn, K MacDonald, E Hembacher, MB Nuijten, ...
Royal Society open science 8 (1), 201494, 2021
Mandates: Arnold Ventures LLC
Drawings as a window into developmental changes in object representations
B Long, JE Fan, MC Frank
Proceedings of the 40th Annual Conference of the Cognitive Science Society., 2018
Mandates: US National Science Foundation
Automated detections reveal the social information in the changing infant view
BL Long, A Sanchez, AM Kraus, K Agrawal, MC Frank
Child Development 93 (1), 101-116, 2022
Mandates: US National Science Foundation
Developmental changes in the ability to draw distinctive features of object categories
B Long, J Fan, Z Chai, MC Frank
Proceedings of the 41st Annual Conference of the Cognitive Science Society., 2019
Mandates: US National Science Foundation
The role of textural statistics vs. outer contours in deep CNN and neural responses to objects
B Long, T Konkle
Conference on Computational Cognitive Neuroscience 4, 2018
Mandates: US National Science Foundation, US National Institutes of Health
Detecting social information in a dense database of infants' natural visual experience.
B Long, G Kachergis, K Agrawal, MC Frank
CogSci, 2020
Mandates: US National Science Foundation
Parallel developmental changes in children’s drawing and recognition of visual concepts
B Long, J Fan, Z Chai, MC Frank
Preprint at PsyArXiv https://doi. org/10.31234/osf. io/5yv7x, 2021
Mandates: US National Science Foundation
Postural developments modulate children’s visual access to social information
A Sanchez, B Long, AM Kraus, MC Frank
PsyArXiv, 2018
Mandates: US National Science Foundation
A mid-level organization of the ventral stream
B Long, CP Yu, T Konkle
BioRxiv, 213934, 2017
Mandates: US National Institutes of Health
Peekbank: An open, large-scale repository for developmental eye-tracking data of children’s word recognition
M Zettersten, D Yurovsky, TL Xu, S Uner, ASM Tsui, RM Schneider, ...
Behavior Research Methods 55 (5), 2485-2500, 2023
Mandates: US National Institutes of Health
Developmental changes in the semantic part structure of drawn objects
H Huey, B Long, J Yang, KR George, JE Fan
Proceedings of the Annual Meeting of the Cognitive Science Society 44 (44), 2022
Mandates: US National Science Foundation, US Department of Defense
Characterizing the object categories two children see and interact with in a dense dataset of naturalistic visual experience
B Long, G Kachergis, N Bhatt, MC Frank
PsyArXiv, 2021
Mandates: US National Science Foundation
Contributions of early and mid-level visual cortex to high-level object categorization
LE Kramer, YC Chen, B Long, T Konkle, MR Cohen
bioRxiv, 2023
Mandates: US National Science Foundation, US National Institutes of Health
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