@article {5090,
	title = {Using child-friendly movie stimuli to study the development of face, place, and object regions from age 3 to 12 years},
	journal = {Human Brain Mapping},
	year = {2022},
	month = {03/2022},
	abstract = {<p>Scanning young children while they watch short, engaging, commercially-produced movies has emerged as a promising approach for increasing data retention and quality. Movie stimuli also evoke a richer variety of cognitive processes than traditional experiments, allowing the study of multiple aspects of brain development simultaneously. However, because these stimuli are uncontrolled, it is unclear how effectively distinct profiles of brain activity can be distinguished from the resulting data. Here we develop an approach for identifying multiple distinct subject-specific Regions of Interest (ssROIs) using fMRI data collected during movie-viewing. We focused on the test case of higher-level visual regions selective for faces, scenes, and objects. Adults (N = 13) were scanned while viewing a 5.6-min child-friendly movie, as well as a traditional localizer experiment with blocks of faces, scenes, and objects. We found that just 2.7 min of movie data could identify subject-specific face, scene, and object regions. While successful, movie-defined ssROIS still showed weaker domain selectivity than traditional ssROIs. Having validated our approach in adults, we then used the same methods on movie data collected from 3 to 12-year-old children (N = 122). Movie response timecourses in 3-year-old children{\textquoteright}s face, scene, and object regions were already significantly and specifically predicted by timecourses from the corresponding regions in adults. We also found evidence of continued developmental change, particularly in the face-selective posterior superior temporal sulcus. Taken together, our results reveal both early maturity and functional change in face, scene, and object regions, and more broadly highlight the promise of short, child-friendly movies for developmental cognitive neuroscience.</p>
},
	issn = {1065-9471},
	doi = {10.1002/hbm.25815},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/hbm.25815},
	author = {Kamps, Frederik S. and Richardson, Hilary and N. Apurva Ratan Murty and Nancy Kanwisher and Rebecca Saxe}
}
@article {5070,
	title = {Computational models of category-selective brain regions enable high-throughput tests of selectivity},
	journal = {Nature Communications},
	volume = {12},
	year = {2021},
	month = {12/2021},
	abstract = {<p>Cortical regions apparently selective to faces, places, and bodies have provided important evidence for domain-specific theories of human cognition, development, and evolution. But claims of category selectivity are not quantitatively precise and remain vulnerable to empirical refutation. Here we develop artificial neural network-based encoding models that accurately predict the response to novel images in the fusiform face area, parahippocampal place area, and extrastriate body area, outperforming descriptive models and experts. We use these models to subject claims of category selectivity to strong\&nbsp;tests, by screening for and synthesizing images predicted to produce high responses. We find that these high-response-predicted images are all unambiguous members of the hypothesized preferred category for each region. These results provide accurate, image-computable encoding models of each category-selective region, strengthen evidence for domain specificity in the brain, and point the way for future research characterizing the functional organization of the brain with unprecedented computational precision.</p>
},
	doi = {10.1038/s41467-021-25409-6},
	url = {https://www.nature.com/articles/s41467-021-25409-6},
	author = {N. Apurva Ratan Murty and Pouya Bashivan and Abate, Alex and James J. DiCarlo and Nancy Kanwisher}
}
@article {4810,
	title = {Integrative Benchmarking to Advance Neurally Mechanistic Models of Human Intelligence},
	journal = {Neuron},
	volume = {108},
	year = {2020},
	month = {11/2020},
	pages = {413 - 423},
	issn = {08966273},
	doi = {10.1016/j.neuron.2020.07.040},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S089662732030605X},
	author = {Martin Schrimpf and Kubilius, Jonas and Lee, Michael J. and N. Apurva Ratan Murty and Ajemian, Robert and James J. DiCarlo}
}
@article {3392,
	title = {A Balanced Comparison of Object Invariances in Monkey IT Neurons},
	journal = {eneuro},
	volume = {4},
	year = {2017},
	month = {Jan-04-2018},
	pages = {ENEURO.0333-16.2017},
	doi = {10.1523/ENEURO.0333-16.2017},
	url = {http://eneuro.sfn.org/lookup/doi/10.1523/ENEURO.0333-16.2017https://syndication.highwire.org/content/doi/10.1523/ENEURO.0333-16.2017},
	author = {N. Apurva Ratan Murty and Arun, Sripati P.}
}
@article {3393,
	title = {Effect of silhouetting and inversion on view invariance in the monkey inferotemporal cortex},
	journal = {Journal of Neurophysiology},
	volume = {11823},
	year = {2017},
	month = {Jan-07-2017},
	pages = {353 - 362},
	issn = {0022-3077},
	doi = {10.1152/jn.00008.2017},
	url = {http://www.physiology.org/doi/10.1152/jn.00008.2017http://www.physiology.org/doi/pdf/10.1152/jn.00008.2017},
	author = {N. Apurva Ratan Murty and Arun, S. P.}
}
@article {3394,
	title = {Seeing a straight line on a curved surface: decoupling of patterns from surfaces by single IT neurons},
	journal = {Journal of Neurophysiology},
	volume = {11773},
	year = {2017},
	month = {Jan-01-2017},
	pages = {104 - 116},
	issn = {0022-3077},
	doi = {10.1152/jn.00551.2016},
	url = {http://www.physiology.org/doi/10.1152/jn.00551.2016http://www.physiology.org/doi/pdf/10.1152/jn.00551.2016},
	author = {N. Apurva Ratan Murty and Arun, S. P.}
}
@article {3395,
	title = {To What Extent Does Global Shape Influence Category Representation in the Brain?},
	journal = {Journal of Neuroscience},
	volume = {36},
	year = {2016},
	month = {Jan-04-2017},
	pages = {4149 - 4151},
	issn = {0270-6474},
	doi = {10.1523/JNEUROSCI.0387-16.2016},
	url = {http://www.jneurosci.org/cgi/doi/10.1523/JNEUROSCI.0387-16.2016},
	author = {N. Apurva Ratan Murty and Pramod, R. T.}
}
@article {3396,
	title = {Dynamics of 3D view invariance in monkey inferotemporal cortex},
	journal = {Journal of Neurophysiology},
	volume = {11319212373232821},
	year = {2015},
	month = {Jan-04-2015},
	pages = {2180 - 2194},
	issn = {0022-3077},
	doi = {10.1152/jn.00810.2014},
	url = {http://www.physiology.org/doi/10.1152/jn.00810.2014http://www.physiology.org/doi/pdf/10.1152/jn.00810.2014},
	author = {N. Apurva Ratan Murty and Arun, Sripati P.}
}
