Zotero | People > Catherine Hanson

Hanson, S. J., & Hanson, C. (2024). Chapter 8 - Neural graph modeling. In K. Kay (Ed.), Computational and Network Modeling of Neuroimaging Data (pp. 229–259). Academic Press. https://doi.org/10.1016/B978-0-443-13480-7.00011-9

Hanson, S. J., Yadav, V., & Hanson, C. (2024). Dense Sample Deep Learning. Neural Computation, 36(6), 1228–1244. https://doi.org/10.1162/neco_a_01666

Hanson, S. J., Yadav, V., & Hanson, C. (2023). Dense Sample Deep Learning (arXiv:2307.10991). arXiv. https://doi.org/10.48550/arXiv.2307.10991

Mastrovito, D., Hanson, C., & Hanson, S. (2023). Temporal Dynamics of Activity in Default Mode Network Suggest a Role in Top-Down Processing for Trial Responses. bioRxiv, 2023.01.08.523152. https://doi.org/10.1101/2023.01.08.523152

Mastrovito, D., Hanson, C., & Hanson, S. (2023). Temporal Dynamics of Activity in Default Mode Network Suggest a Role in Top-Down Processing for Trial Responses. bioRxiv. https://doi.org/10.1101/2023.01.08.523152

Gee, D. G., Hanson, C., Caglar, L. R., Fareri, D. S., Gabard-Durnam, L. J., Mills-Finnerty, C., Goff, B., Caldera, C. J., Lumian, D. S., Flannery, J., Hanson, S. J., & Tottenham, N. (2022). Experimental evidence for a child-to-adolescent switch in human amygdala-prefrontal cortex communication: A cross-sectional pilot study. Developmental Science, 25(4), e13238. https://onlinelibrary.wiley.com/doi/abs/10.1111/desc.13238

Gee, D. G., Hanson, C., Caglar, L. R., Fareri, D. S., Gabard-Durnam, L. J., Mills-Finnerty, C., Goff, B., Caldera, C. J., Lumian, D. S., Flannery, J., Hanson, S. J., & Tottenham, N. (2022). Experimental evidence for a child-to-adolescent switch in human amygdala-prefrontal cortex communication: A cross-sectional pilot study. Developmental Science, 25(4), e13238. https://doi.org/10.1111/desc.13238

Gee, D. G., Hanson, C., Caglar, L. R., Fareri, D. S., Gabard-Durnam, L. J., Mills-Finnerty, C., Goff, B., Caldera, C. J., Lumian, D. S., Flannery, J., Hanson, S. J., & Tottenham, N. (2022). Experimental evidence for a child-to-adolescent switch in human amygdala-prefrontal cortex communication: A cross-sectional pilot study. Developmental Science. https://doi.org/10.1111/desc.13238

Caglar, L., Hanson, C., & Hanson, S. J. (2021). Uncovering the Metricity of Representational Spaces in the Brain: Evidence from Colors and Letters. Proceedings of the Annual Meeting of the Cognitive Science Society, 43(43). https://escholarship.org/uc/item/6r11x1md

Hanson, S. J., Caglar, L. R., & Hanson, C. (2020). DECODING SECOND ORDER ISOMORPHISMS IN THE BRAIN: The case of colors and letters. bioRxiv. https://doi.org/10.1101/2020.05.04.076703

Hanson, S. J., Caglar, L. R., & Hanson, C. (2020). DECODING SECOND ORDER ISOMORPHISMS IN THE BRAIN: The case of colors and letters (p. 2020.05.04.076703). bioRxiv. https://doi.org/10.1101/2020.05.04.076703

Hanson, S. J., Caglar, L. R., & Hanson, C. (2020). DECODING SECOND ORDER ISOMORPHISMS IN THE BRAIN: The case of colors and letters. bioRxiv, 2020.05.04.076703. https://doi.org/10.1101/2020.05.04.076703

Mills-Finnerty, C., Hanson, C., Khadr, M., & José Hanson, S. (2020). Computations and Connectivity Underlying Aversive Counterfactuals. Brain Connectivity, 10(9), 467–478. https://doi.org/10.1089/brain.2020.0766

Stephen José Hanson, Leyla Roskan Caglar, & Catherine Hanson. (2020). DECODING SECOND ORDER ISOMORPHISMS IN THE BRAIN: The case of colors and letters. bioRxiv, 2020.05.04.076703. https://doi.org/10.1101/2020.05.04.076703

Hanson, S. J., Hanson, C., Sanchez-Romero, R., Ramsey, J., & Glymour, C. (2019, April). Effective Connectivity In Brain Networks III: Network Complexity and Feedback Application to Alzheimers Disease. Fifth Annual Brain Initiative Investigators Meeting.

Hanson, C., Caglar, L. R., & Hanson, S. J. (2018). Attentional Bias in Human Category Learning: The Case of Deep Learning. Frontiers in Psychology, 9. https://doi.org/10.3389/fpsyg.2018.00374

Mastrovito, D., Hanson, C., & Hanson, S. J. (2018). Differences in atypical resting-state effective connectivity distinguish autism from schizophrenia. NeuroImage : Clinical, 18, 367–376. https://doi.org/10.1016/j.nicl.2018.01.014

Mastrovito, D., Hanson, C., & Hanson, S. J. (2018). Differences in atypical resting-state effective connectivity distinguish autism from schizophrenia. NeuroImage: Clinical, 18, 367–376. https://doi.org/10.1016/j.nicl.2018.01.014

Mastrovito, D., Hanson, C., & Hanson, S. J. (2018). Differences in atypical resting-state effective connectivity distinguish autism from schizophrenia. NeuroImage : Clinical, 18, 367–376. https://doi.org/10.1016/j.nicl.2018.01.014

Mills-Finnerty, C., Hanson, C., & Hanson, S. J. (2018). Brain network connectivity underlying decisions between the “lesser of two evils” (E3340v2). PeerJ Inc. https://doi.org/10.7287/peerj.preprints.3340v2

Mills-Finnerty, C., Hanson, C., & Hanson, S. J. (2018). Brain network connectivity underlying decisions between the “lesser of two evils” [Preprint]. PeerJ Preprints. https://doi.org/10.7287/peerj.preprints.3340v2

Mohlman, J., Eldreth, D. A., Price, R. B., Staples, A. M., & Hanson, C. (2017). Prefrontal-limbic connectivity during worry in older adults with generalized anxiety disorder. Aging & Mental Health, 21(4), 426–438. https://doi.org/10.1080/13607863.2015.1109058

Ray, S., Gohel, S., Biswal, B. B., Aya, A., Srinagesh, A., Hanson, C., & Hanson, S. J. (2017). Modeling Causal Relationships among Brain Areas in the Mesocorticolimbic System during Resting-State in Cocaine Users Utilizing a Graph Theoretic Approach. Journal of Alcoholism & Drug Dependence, 05(04). https://doi.org/10.4172/2329-6488.1000279

ACNP 55th Annual Meeting: Poster Session IIDecember 6, 2016. (2016). Neuropsychopharmacology, 41, S289. https://doi.org/10.1038/npp.2016.241

Gee, D., Caglar, L. R., Colleen Mills-Finnerty, Goff, B., Gabard-Durnam, Fareri, D., Caldera, C., Lumian, D., Flannery, J., Hanson, C., Hanson, S., & Tottenham, N. (2016). ACNP 55th Annual Meeting: Poster Session II: December 6, 2016. Neuropsychopharmacology, 41(S1), S289–S454. https://doi.org/10.1038/npp.2016.241

Gee, D., Calgar, L., Mills-Finnerty, C., Goff, B., Gabard-Durnam, L., Fareri, D., Caldera, C., Lumian, D., Flannery, J., Hanson, C., & others. (2016). Novel fMRI Approaches Reveal Developmental Changes in Frontoamygdala Circuitry With Implications for the Emergence of Psychiatric Disorders During Development. NEUROPSYCHOPHARMACOLOGY, 41, S297–S297.

Glymour, C., & Hanson, C. (2016). Reverse Inference in Neuropsychology. The British Journal for the Philosophy of Science, 67(4), 1139–1153. https://doi.org/10.1093/bjps/axv019

Hanson, S. J., Mastrovito, D., Hanson, C., Ramsey, J., & Glymour, C. (2016). Scale-Free Exponents of Resting State are Biomarkers of Neuro-Typical and Atypical Brain Activity [Preprint]. Bioinformatics. https://doi.org/10.1101/068841

Smoller, J. W. (2016). The Genetics of Stress-Related Disorders: PTSD, Depression, and Anxiety Disorders. Neuropsychopharmacology, 41(1), 297–319. https://doi.org/10.1038/npp.2015.266

Vaschillo, E., Biswal, B., Buckman, J., Peyser, D., Heiss, S., Barnas, P., Banu, L., Puhalla, A., Vaschillo, B., & Eddie, D. (2016). Resonance breathing affects hemodynamic oscillations in the brain at 0.1 Hz. Psychophysiology, 29(6), 742–750.

Barbu, A., Siddharth, N., Xiong, C., Corso, J. J., Fellbaum, C. D., Hanson, C., Hanson, S. J., Hélie, S., Malaia, E., Pearlmutter, B. A., Siskind, J. M., Talavage, T. M., & Wilbur, R. B. (2015). The Compositional Nature of Event Representations in the Human Brain. arXiv:1505.06670 [q-Bio]. http://arxiv.org/abs/1505.06670

Feigenson, K. A., Hanson, C., Papathomas, T., & Silverstein, S. M. (2015). A Functional MRI Index of Spatial Context Effects in Vision. Psychology, 06(16), 2145–2154. https://doi.org/10.4236/psych.2015.616211

Ray, S., Haney, M., Hanson, C., Biswal, B., & Hanson, S. J. (2015). Modeling Causal Relationship Between Brain Regions Within the Drug-Cue Processing Network in Chronic Cocaine Smokers. Neuropsychopharmacology, 40(13), 2960–2968. https://doi.org/10.1038/npp.2015.150

Ray, S., Hanson, C., Haney, M., Biswal, B., & Hanson, S. J. (2015). Modeling causal relationship between memory and craving-related brain networks in non-treatment seeking cocaine smokers using images, a graph theoretic approach. Drug and Alcohol Dependence, 146, e77. https://doi.org/10.1016/j.drugalcdep.2014.09.578

Barbu, A., Barrett, D. P., Chen, W., Siddharth, N., Xiong, C., Corso, J. J., Fellbaum, C. D., Hanson, C., Hanson, S. J., Hélie, S., Malaia, E., Pearlmutter, B. A., Siskind, J. M., Talavage, T. M., & Wilbur, R. B. (2014). Seeing is Worse than Believing: Reading People’s Minds Better than Computer-Vision Methods Recognize Actions. In D. Fleet, T. Pajdla, B. Schiele, & T. Tuytelaars (Eds.), Computer Vision – ECCV 2014 (pp. 612–627). Springer International Publishing.

Boukrina, O., Hanson, S. J., & Hanson, C. (2014). Modeling activation and effective connectivity of VWFA in same script bilinguals. Human Brain Mapping, 35(6), 2543–2560. https://doi.org/10.1002/hbm.22348

Mills-Finnerty, C., Hanson, C., & Hanson, S. J. (2014). Brain network response underlying decisions about abstract reinforcers. NeuroImage, 103, 48–54. https://doi.org/10.1016/j.neuroimage.2014.09.019

Olga Boukrina, S. J. H. (2014). Modeling activation and effective connectivity of VWFA in same script bilinguals. Human Brain Mapping, 35(6). https://doi.org/10.1002/hbm.22348

Ray, S., Hanson, C., & Hanson, S. J. (2014). Enhanced Cue Reactivity to Cocaine Cues in Non-treatment Seeking Cocaine Smokers. Journal of Alcoholism & Drug Dependence, 02(04). https://doi.org/10.4172/2329-6488.1000169

Zhang, J., Li, X., Li, C., Lian, Z., Huang, X., Zhong, G., Zhu, D., Li, K., Jin, C., Hu, X., Han, J., Guo, L., Hu, X., Li, L., & Liu, T. (2014). Inferring Functional Interaction and Transition Patterns via Dynamic Bayesian Variable Partition Models. Human Brain Mapping, 35(7), 3314–3331. https://doi.org/10.1002/hbm.22404

Andrei Barbu, N. S. (2013). The Compositional Nature of Verb and Argument Representations in the Human Brain.

Barbu, A., Siddharth, N., Xiong, C., Corso, J. J., Fellbaum, C. D., Hanson, C., Hanson, S. J., Hélie, S., Malaia, E., Pearlmutter, B. A., Siskind, J. M., Talavage, T. M., & Wilbur, R. B. (2013). The Compositional Nature of Verb and Argument Representations in the Human Brain. arXiv:1306.2293 [q-Bio]. http://arxiv.org/abs/1306.2293

Boukrina, O., Hanson, S. J., & Hanson, C. (2013). Modeling activation and effective connectivity of VWFA in same script bilinguals. Human Brain Mapping, 35(6), 2543–2560. https://doi.org/10.1002/hbm.22348

Chenliang Xu, R. F. D. (2013). A Study of Actor and Action Semantic Retention in Video Supervoxel Segmentation. International Journal of Semantic Computing, 07(04). https://doi.org/10.1142/S1793351X13400114

Chenliang Xu, R. F. D. (2013). Are Actor and Action Semantics Retained in Video Supervoxel Segmentation? 286–293. https://doi.org/10.1109/ICSC.2013.56

Dixon, R. A., B„ckman, L., & Backman, L. (2013). Compensating for Psychological Deficits and Declines: Managing Losses and Promoting Gains. Psychology Press.

Hanson, C., Hanson, S. J., Ramsey, J., & Glymour, C. (2013). Atypical Effective Connectivity of Social Brain Networks in Individuals with Autism. Brain Connectivity, 3(6), 578–589. https://doi.org/10.1089/brain.2013.0161

Xu, C., Doell, R. F., Hanson, S. J., Hanson, C., & Corso, J. J. (2013). A STUDY OF ACTOR AND ACTION SEMANTIC RETENTION IN VIDEO SUPERVOXEL SEGMENTATION. International Journal of Semantic Computing, 07(04), 353–375. https://doi.org/10.1142/S1793351X13400114

Manelis, A., Hanson, C., & Hanson, S. J. (2011). Implicit memory for object locations depends on reactivation of encoding-related brain regions. Human Brain Mapping, 32(1), 32–50. https://doi.org/10.1002/hbm.20992

Ramsey, J. D., Hanson, S. J., Hanson, C., Halchenko, Y. O., Poldrack, R. A., & Glymour, C. (2010). Six problems for causal inference from fMRI. NeuroImage, 49(2), 1545–1558. https://doi.org/10.1016/j.neuroimage.2009.08.065

Ray, S., Hanson, C., Hanson, S. J., & Bates, M. E. (2010). fMRI BOLD Response in High-risk College Students (Part 1): During Exposure to Alcohol, Marijuana, Polydrug and Emotional Picture Cues. Alcohol and Alcoholism, 45(5), 437–443. https://doi.org/10.1093/alcalc/agq042

Ray, S., Hanson, C., Hanson, S. J., Rahman, R. M., & Bates, M. E. (2010). fMRI BOLD Response of High-risk College Students (Part 2): During Memory Priming of Alcohol, Marijuana and Polydrug Picture Cues. Alcohol and Alcoholism, 45(5), 444–448. https://doi.org/10.1093/alcalc/agq043

Ray, S., Hanson, C., Hanson, S., Rahman, R., & Bates, M. (2010). HIGH-RISK COLLEGE DRINKERS SHOW EVIDENCE OF IMPLICIT MEMORY PRIMING AND NEURAL CRAVING RESPONSES TO ALCOHOL PICTURE CUES. ALCOHOLISM-CLINICAL AND EXPERIMENTAL RESEARCH, 34, 26A-26A.

Hanson, S. J., Gagliardi, A. D., & Hanson, C. (2009). Solving the brain synchrony eigenvalue problem: conservation of temporal dynamics (fMRI) over subjects doing the same task. Journal of Computational Neuroscience, 27(1), 103–114. https://doi.org/10.1007/s10827-008-0129-z

Hanson, S. J., Gagliardi, A. D., & Hanson, C. (2009). Solving the brain synchrony eigenvalue problem: conservation of temporal dynamics (fMRI) over subjects doing the same task. Journal of Computational Neuroscience, 27(1), 103–114.

Hanson, S. J., Hanson, C., Halchenko, Y., Matsuka, T., & Zaimi, A. (2007). Bottom-up and top-down brain functional connectivity underlying comprehension of everyday visual action. Brain Structure and Function, 212(3–4), 231–244. https://doi.org/10.1007/s00429-007-0160-2

Hanson, S. J., Hanson, C., Halchenko, Y., Matsuka, T., & Zaimi, A. (2007). Bottom-up and top-down brain functional connectivity underlying comprehension of everyday visual action. Brain Structure and Function, 212(3), 231–244. https://doi.org/10.1007/s00429-007-0160-2

Hanson, S. J., Hanson, C., Halchenko, Y., Matsuka, T., & Zaimi, A. (2007). Bottom-up and top-down brain functional connectivity underlying comprehension of everyday visual action. Brain Structure and Function, 212(3–4), 231–244. https://doi.org/10.1007/s00429-007-0160-2

Hanson, S. J., Rebecchi, R., Hanson, C., & Halchenko, Y. O. (2007). Dense mode clustering in brain maps. Magnetic Resonance Imaging, 25(9), 1249–1262. https://doi.org/10.1016/j.mri.2007.03.013

Chouchourelou, A., Matsuka, T., Kozhevnikov, M., Hanson, C., & Shiffrar, M. (2005). The visual analysis of bodily emotions. Journal of Vision, 5(8), 933. https://doi.org/10.1167/5.8.933

Hanson, C., & Hanson, S. J. (2005). Chapter 5 - CATEGORIZATION IN NEUROSCIENCE: BRAIN RESPONSE TO OBJECTS AND EVENTS. In H. Cohen & C. Lefebvre (Eds.), Handbook of Categorization in Cognitive Science (pp. 119–140). Elsevier Science Ltd. https://doi.org/10.1016/B978-008044612-7/50060-3

Hanson, C., Hanson, S. J., Matsuka, T., & Yamauchi, T. (2005). Representing Categorical Knowledge: A fMRI Study. Proceedings of the Annual Meeting of the Cognitive Science Society, 27(27). https://escholarship.org/uc/item/47b6g27g

Matsuka, T., Yamauchi, T., Hanson, C., & Hanson, S. J. (2005). Representing Categorical Knowledge: An fMRI Study. The Proceedings of the 27th Annual Meeting of the Cognitive Science Society, 1425–1430.

Bellec, P., Marrelec, G., Posé, C., Jolivet, O., Pélégrini-Issac, M., & Benali, H. (2004). WE 122 An assisted data-driven procedure to select functionally connected brain regions in fMRI. 508.

Hanson, C., & Hanson, S. J. (1996). Development of Schemata during Event Parsing: Neisser’s Perceptual Cycle as a Recurrent Connectionist Network. Journal of Cognitive Neuroscience, 8(2), 119–134. https://doi.org/10.1162/jocn.1996.8.2.119

Woodruff-Pak, D., & Hanson, C. (1995). Plasticity and compensation in brain memory systems in aging. In Compensating for psychological deficits and declines: Managing losses and promoting gains (pp. 191–217).

Woodruff-Pak, D. S., & Hanson, C. (1995). Plasticity and compensation in brain memory systems in aging. Compensating for Psychological Deficits and Declines: Managing Losses and Promoting Gains, 191–217.

Hanson, C. (1991). Why we recall more about a tourist than a thief. Bulletin of the Psychonomic Society, 29(6), 519–519.

Hanson, C., & Hirst, W. (1991). Recognizing Differences in Recognition Tasks: A Reply to Lassiter and Slaw. Journal of Experimental Psychology. General, 120(2), 211–212. https://doi.org/10.1037/0096-3445.120.2.211

Weiss, R. F., McDonald, N. B., Little, C., & Shull, R. D. (1991). Pavlovian principles in human parallel distributed processing [Dataset]. American Psychological Association. https://doi.org/10.1037/e665402011-017

Hanson, C., & Hirst, W. (1989). On the representation of events: a study of orientation, recall, and recognition. Journal of Experimental Psychology: General, 118(2), 136. https://psycnet.apa.org/record/1989-31878-001

Hanson, C., & Hirst, W. (1989). On the representation of events: A study of orientation, recall, and recognition. Journal of Experimental Psychology: General, 118(2), 136–147. https://doi.org/10.1037/0096-3445.118.2.136

Caglar, L. R., Hanson, C., & Hanson, S. J. (n.d.). Uncovering the Metricity of Representational Spaces in the Brain: Evidence from Colors and Letters. 8.

Frontiers | Attentional Bias in Human Category Learning: The Case of Deep Learning | Psychology. (n.d.). Retrieved August 26, 2020, from https://www.frontiersin.org/articles/10.3389/fpsyg.2018.00374/full

Gagliardi, A. D., Hanson, C., & Hanson, S. J. (n.d.). Differences in spontaneous functional connectivity between autism spectrum disorder (ASD) and neurotypical subjects. 1.

Gee, D. G., Hanson, C., Caglar, L. R., Fareri, D. S., Gabard-Durnam, L. J., Mills-Finnerty, C., Goff, B., Caldera, C. J., Lumian, D. S., Flannery, J., Hanson, S. J., & Tottenham, N. (n.d.). Experimental evidence for a child-to-adolescent switch in human amygdala-prefrontal cortex communication: A cross-sectional pilot study. Developmental Science, n/a(n/a). https://doi.org/10.1111/desc.13238

Hanson, C., & Hirst, W. (n.d.). On the Representation of Events: A Study of Orientation, Recall, and Recognition. 12.

Hanson, C., & Hirst, W. (n.d.). Recognizing Differences in Recognition Tasks: A Reply to Lassiter and Slaw. 2.

Mills-Finnerty, C., Hanson, C., & Khadr, M. (n.d.). Computations and connectivity underlying aversive counterfactuals. Brain Connectivity. https://doi.org/10.1089/brain.2020.0766

Neuropsychopharmacology_2016.pdf. (n.d.). Retrieved June 6, 2019, from https://www-nature-com.proxy.libraries.rutgers.edu/articles/npp2016241.pdf

PSYCH_2015123110043715.pdf. (n.d.). Retrieved June 6, 2019, from https://file.scirp.org/pdf/PSYCH_2015123110043715.pdf

Representing Categorical Knowledge: An fMRI Study. (n.d.). Retrieved June 4, 2019, from http://csjarchive.cogsci.rpi.edu/Proceedings/2005/docs/p1425.pdf

Reverse Inference in Neuropsychology. (n.d.). https://doi.org/10.1093/bjps/axv019

Vaschillo, E., Biswal, B., Buckman, J. F., Peyser, D., Heiss, S., Barnas, P., Banu, L., Puhalla, A., Vaschillo, B., Eddie, D., Ray, S., Hanson, S., Hanson, C., & Bates, M. E. (n.d.). Resonance breathing affects hemodynamic oscillations in the brain at 0.1 Hz.

(N.d.).

Catherine Hanson : Curriculum Vitae