The PDFs of the papers are provided here for personal and educational use only.
Copying, distributing, reproducing, and broadcasting these papers is strictly forbidden.
Journal papers (*) and peer reviewed conference proceedings (**):
*Hammer, R., Paul, E. J., Hillman, C. H., Kramer, A. F., Cohen, N. J., & Barbey, A. K. (2019). Individual differences in analogical reasoning revealed by multivariate task-based functional brain imaging. NeuroImage, 184, 993-1004. [PDF] [Journal site]
*Hammer, R. & Cerf, M. (forthcoming). Individual differences in risk assessment under perceptual ambiguity and their impact on visual category learning.
*Hammer, R. & Sloutsky, V. (2016). Visual category learning results in rapid changes in brain activation reflecting sensitivity to the category relation between perceived objects and to decision correctness. Journal of Cognitive Neuroscience, 28(11), 1804-1819. [PDF] [Journal site]
*Hammer, R., Klout, J., & Booth, J. R. (2016). Developmental changes in observational and feedback-based category learning between childhood and adulthood. Developmental Science, 19(6), 967-981. [PDF] [Journal site]
*Hammer, R., Cooke, G., Stein, M. A., & Booth, J. R. (2015). Functional neuroimaging of visuospatial working memory tasks enables accurate detection of attention deficit and hyperactivity disorder. NeuroImage: Clinical, 9, 244-252. [PDF] [Journal site] [Extras]
*Hammer, R., Tennekoon, M., Cooke, E. G., Gayda, J., Stein, M. A., & Booth, J. R. (2015). Feedback associated with expectation for larger-reward improves visuospatial working memory performances in children with ADHD. Developmental Cognitive Neuroscience, 14, 38-49. [PDF] [Journal site]
*Hammer, R. (2015). Impact of feature saliency on visual category learning. Frontiers in Psychology, 6(451). [PDF] [Journal site]
*Hammer, R., Sloutsky, V., & Grill-Spector, K. (2015). Feature saliency and feedback information interactively impact visual category learning. Frontiers in Psychology, 6(74). [PDF] [Journal site]
**Hammer, R., Sloutsky, V., & Grill-Spector, K. (2012). The interplay between feature-saliency and feedback information in visual category learning tasks. Proceedings to the 34th annual conference of the Cognitive Science Society. [PDF] [Journal site]
*Hammer, R., Brechmann, A., Ohl, F., Weinshall, D., & Hochstein, S. (2010). Differential category learning processes: The neural basis of comparison-based learning and induction. NeuroImage, 52, 699-709. [PDF] [Journal site]
*Hammer, R., Diesendruck, G., Weinshall, D., & Hochstein, S. (2009). The development of category learning strategies: What makes the difference? Cognition, 112(1), 105-119. [PDF] [Journal site] *Hammer, R., Hertz, T., Hochstein, S., & Weinshall, D. (2009). Category learning from equivalence constraints. Cognitive Processing, 10(3), 211-232. [PDF] [Journal site] *Hammer, R., Bar-Hillel, A., Hertz, T., Weinshall, D., & Hochstein, S. (2008). Comparison processes in category learning: From theory to behavior. Brain Research (special issue on Brain and Vision) 1225, 102-118. [PDF] [Journal site] **Hammer, R., Hertz, T., Hochstein, S., & Weinshall, D. (2007). Classification with positive and negative equivalence constraints: Theory, computation and human experiments. In F. Mele, G. Ramella, S. Santillo and F. Ventriglia (Eds). Lecture Notes in Computer Science (Advances in Brain, Vision, and Artificial Intelligence, pp. 264-276). Berlin Heidelberg: Springer-Verlag Press. [PDF] [Journal site] **Hammer, R., Hertz, T., Hochstein, S., & Weinshall, D. (2005). Category learning from equivalence constraints. Proceedings to the 27th annual conference of the Cognitive Science Society. [PDF] [Journal site] *Hammer, R. & Diesendruck, G. (2005). The role of dimensional distinctiveness in children and adults’ artifact categorization. Psychological Science, 16(2), 137-144. [PDF] [Journal site] [Stimuli examples] *Diesendruck, G., Hammer, R., & Catz, O. (2003). Mapping the similarity space of children and adults’ artifact categories. Cognitive Development, 118(2), 217-231. [PDF] [Journal site] [Stimuli examples]
In preparation (post data-collection/primary-analysis):
Hammer, R., et al. Developmental changes in the impact of reward expectation on visuospatial working memory.
Hammer, R., & Booth, J. R. Category learning with batched feedback.
Hammer, R., et al. Using sparse logistic regression classifier and fMRI data from multiple tasks for accurately diagnosing ADHD.
Hammer, R. The potential and the limits in using fMRI for deducing the nature of changes in neural firing following perceptual learning.
De la Torre, G. G., Hammer, R., et al. Neural correlates of individual differences in behavioral inhibition in children with ADHD and typically developed children.
Invited research topics:
Hammer, R., & Sloutsky, V. (2014). Impact of context on category learning. Frontiers in Psychology. [Journal site]
Patents:
Hammer, R., Booth, J. R., Brohani, R., & Kataggelos, A. K. (June 2014). Pattern analysis based on fMRI data collected while subjects perform multiple working memory tasks allows high precision diagnosis of ADHD. US20170123028 A1 Patent Pending. [Site]
PhD thesis:
The dynamics of category learning and knowledge acquisition processes