| Year |
Citation |
Score |
| 2024 |
DiMattina C, Pipitone RN, Renteria MR, Ryan KJ. Trypophobia, skin disease, and the visual discomfort of natural textures. Scientific Reports. 14: 5050. PMID 38424465 DOI: 10.1038/s41598-024-55149-8 |
0.684 |
|
| 2022 |
DiMattina C, Burnham JJ, Guner BN, Yerxa HB. Distinguishing shadows from surface boundaries using local achromatic cues. Plos Computational Biology. 18: e1010473. PMID 36103558 DOI: 10.1371/journal.pcbi.1010473 |
0.316 |
|
| 2022 |
Pipitone RN, DiMattina C, Martin ER, Pavela Banai I, Bellmore K, De Angelis M. Evaluating the 'skin disease-avoidance' and 'dangerous animal' frameworks for understanding trypophobia. Cognition & Emotion. 1-14. PMID 35503506 DOI: 10.1080/02699931.2022.2071236 |
0.692 |
|
| 2022 |
DiMattina C. Luminance texture boundaries and luminance step boundaries are segmented using different mechanisms. Vision Research. 190: 107968. PMID 34794083 DOI: 10.1016/j.visres.2021.107968 |
0.38 |
|
| 2021 |
DiMattina C, Baker CL. Segmenting surface boundaries using luminance cues. Scientific Reports. 11: 10074. PMID 33980899 DOI: 10.1038/s41598-021-89277-2 |
0.523 |
|
| 2020 |
Pipitone RN, DiMattina C. Object Clusters or Spectral Energy? Assessing the Relative Contributions of Image Phase and Amplitude Spectra to Trypophobia. Frontiers in Psychology. 11: 1847. PMID 32793086 DOI: 10.3389/Fpsyg.2020.01847 |
0.674 |
|
| 2019 |
DiMattina C, Baker CL. Modeling second-order boundary perception: A machine learning approach. Plos Computational Biology. 15: e1006829. PMID 30883556 DOI: 10.1371/journal.pcbi.1006829 |
0.648 |
|
| 2018 |
DiMattina C, Baker C. How texture elements are combined to detect boundaries: A machine learning approach Journal of Vision. 18: 795. DOI: 10.1167/18.10.795 |
0.519 |
|
| 2016 |
DiMattina C. Comparing models of contrast gain using psychophysical experiments. Journal of Vision. 16: 1. PMID 27380470 DOI: 10.1167/16.9.1 |
0.536 |
|
| 2016 |
DiMattina C. Estimating and comparing models of neural encoding and decoding using psychophysical experiments Journal of Vision. 16: 962. DOI: 10.1167/16.12.962 |
0.447 |
|
| 2015 |
DiMattina C, Zhang K. Efficient implementations of the adaptive PSI procedure for estimating multi-dimensional psychometric functions. Journal of Vision. 15: 477. PMID 26326165 DOI: 10.1167/15.12.477 |
0.713 |
|
| 2015 |
DiMattina C. Fast adaptive estimation of multidimensional psychometric functions. Journal of Vision. 15: 5. PMID 26200886 DOI: 10.1167/15.9.5 |
0.501 |
|
| 2015 |
DiMattina C. Fast adaptive estimation of multidimensional psychometric functions Journal of Vision. 15. DOI: 10.1167/15.9.5 |
0.291 |
|
| 2013 |
DiMattina C, Zhang K. Adaptive stimulus optimization for sensory systems neuroscience. Frontiers in Neural Circuits. 7: 101. PMID 23761737 DOI: 10.3389/fncir.2013.00101 |
0.706 |
|
| 2012 |
DiMattina C, Fox SA, Lewicki MS. Detecting natural occlusion boundaries using local cues. Journal of Vision. 12. PMID 23255731 DOI: 10.1167/12.13.15 |
0.687 |
|
| 2011 |
DiMattina C, Zhang K. Active data collection for efficient estimation and comparison of nonlinear neural models. Neural Computation. 23: 2242-88. PMID 21671794 DOI: 10.1162/NECO_a_00167 |
0.696 |
|
| 2010 |
DiMattina C, Zhang K. How to modify a neural network gradually without changing its input-output functionality. Neural Computation. 22: 1-47. PMID 19842986 DOI: 10.1162/neco.2009.05-08-781 |
0.67 |
|
| 2008 |
DiMattina C, Zhang K. How optimal stimuli for sensory neurons are constrained by network architecture. Neural Computation. 20: 668-708. PMID 18045019 DOI: 10.1162/neco.2007.11-05-076 |
0.698 |
|
| 2006 |
DiMattina C, Wang X. Virtual vocalization stimuli for investigating neural representations of species-specific vocalizations. Journal of Neurophysiology. 95: 1244-62. PMID 16207780 DOI: 10.1152/jn.00818.2005 |
0.515 |
|
| 2001 |
Kotak VC, DiMattina C, Sanes DH. GABA(B) and Trk receptor signaling mediates long-lasting inhibitory synaptic depression. Journal of Neurophysiology. 86: 536-40. PMID 11431532 DOI: 10.1152/Jn.2001.86.1.536 |
0.203 |
|
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