Publications

2025

148.
Casile A., Cordier A., Kim J. G. et al. (2025) Cell Reports. 44, 3, 115429.  Abstract [All authors]

2023

147.
Ullman S., Assif L., Strugatski A., Vatashsky B. Z., Levi H., Netanyahu A. & Yaari A. (2023) Proceedings of the National Academy of Sciences of the United States of America. 120, 40, e221117912.  Abstract
146.
Segev D., Basri R., Batash T. et al. (2023) 2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023.  Abstract [All authors]
145.
Doveh S., Arbelle A., Harary S. et al. (2023) Advances in Neural Information Processing Systems. Globerson A., Oh A., Saenko K., Hardt M., Levine S. & Neumann T.(eds.). Vol. 36. p. 76137-76150  Abstract [All authors]
144.
Doveh S., Arbelle A., Harary S. et al. (2023) Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023. p. 2657-2668  Abstract [All authors]

2022

143.
Zohary E., Harari D., Ullman S., Ben-Zion I., Doron R., Attias S., Porat Y., Sklar A. Y. & Mckyton A. (2022) Proceedings of the National Academy of Sciences - PNAS. 119, 20, e211718411.  Abstract

2021

142.
Gruber L. Z., Ullman S. & Ahissar E. (2021) Proceedings of the National Academy of Sciences - PNAS. 118, 34, e202279211.  Abstract
141.
Nam Y., Sato T., Uchida G., Malakhova E., Ullman S. & Tanifuji M. (2021) Scientific Reports. 11, 7827.  Abstract
140.
Arbelle A., Doveh S., Alfassy A. et al. (2021) Proceedings - 2021 IEEE/CVF International Conference on Computer Vision, ICCV 2021. p. 1781-1792  Abstract [All authors]

2020

139.
Ben-Yosef G., Kreiman G. & Ullman S. (2020) Cognition. 201, 104263.  Abstract
138.
Patish U. & Ullman S. (2020) AAAI 2020 - 34th AAAI Conference on Artificial Intelligence. Vol. 34. p. 2400-2407  Abstract
137.
Vatashsky B. Z. & Ullman S. (2020) Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. p. 10373-10383 9157617.  Abstract

2019

136.
Holzinger Y., Ullman S., Harari D., Behrmann M. & Avidan G. (2019) Journal of Cognitive Neuroscience. 31, 9, p. 1354-1367  Abstract
135.
Preis S. G., Chayet H., Katz A., Yashunsky V., Kaner A., Ullman S. & Braslavsky I. (2019) Science Advances. 5, 3, 1598.  Abstract
134.
Ullman S. (2019) Science. 363, 6428, p. 692-693  Abstract

2018

133.
Ullman S., Dorfman N. & Harari D. (2018) Cognition. 183, p. 67-81  Abstract
132.
Owaki T., Vidal-Naquet M., Nam Y., Uchida G., Sato T., Cateau H., Ullman S. & Tanifuji M. (2018) PLoS ONE. 13, 9, 0201192.  Abstract
131.
Ben-Yosef G. & Ullman S. (2018) Interface Focus. 8, 4, 20180020.  Abstract
130.
Ben-Yosef G., Assif L. & Ullman S. (2018) Cognition. 171, p. 65-84  Abstract
129.
Action Classification via Concepts and Attributes
Rosenfeld A. & Ullman S. (2018) 2018 24TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR). p. 1499-1505 (trueInternational Conference on Pattern Recognition).  Abstract

2017

128.
Rosenfeld A. & Ullman S. (2017) COMPUTER VISION - ACCV 2016, PT V. Lepetit, Nishino K., Lai SH. & Sato Y.(eds.). p. 264-279 (trueLecture Notes in Computer Science).  Abstract
127.
A model for interpreting social interactions in local image regions
Ben-Yosef G., Yachin A. & Ullman S. (2017) AAAI Spring Symposium - Technical Report. p. 525-528  Abstract

2016

126.
Rosenfeld A. & Ullman S. (2016) Proceedings - 2016 13th Conference on Computer and Robot Vision, CRV 2016. Guerrero J.(eds.). p. 148-155  Abstract
125.
Lifshitz I., Fetaya E. & Ullman S. (2016) Computer Vision - 14th European Conference, ECCV 2016, Proceedings. Leibe B., Matas J., Welling M. & Sebe N.(eds.). p. 246-260  Abstract
124.
Ullman S., Assif L., Fetaya E. & Harari D. (2016) Proceedings of the National Academy of Sciences - PNAS. 113, 10, p. 2744-2749  Abstract

2015

123.
Berzak Y., Barbu A., Harari D., Katz B. & Ullman S. (2015) Conference Proceedings - EMNLP 2015. p. 1477-1487  Abstract
122.
De La Rosa L. R. S., Choudhery R. N., Curio C., Ullman S., Assif L. & Buelthoff H. H. (2015) Visual Cognition. 22, p. 1233-1271  Abstract
121.
A model for full local image interpretation
Ben-Yosef G., Assif L., Harari D. & Ullman S. (2015) Proceedings of the 37th Annual Meeting of the Cognitive Science Society, CogSci 2015. Warlaumont A., Jennings C. D., Noelle D. C., Yoshimi J., Maglio P. P., Dale R. & Matlock T.(eds.). p. 220-225  Abstract
120.
Learning local invariant mahalanobis distances
Fetaya E. & Ullman S. (2015) 32nd International Conference on Machine Learning, ICML 2015. Blei D. & Bach F.(eds.). p. 162-168  Abstract
119.
Fetaya E., Shamir O. & Ullman S. (2015) Journal of Machine Learning Research. 38, p. 241-249  Abstract
118.
A Model for Full Local Image Interpretation
Ben-Yosef, G., Assif, L., Harari, D., Ullman, S (2015) The Annual Conference of the Cognitive Science Society - CogSci.
117.
Do You See What I Mean? Visual Resolution of Linguistic Proc. Empirical Methods on Natural Language Processing
Berzak, Y., Barbu et al. (2015) [All authors]

2014

116.
Markov N. T., Vezoli J., Chameau P. et al. (2014) Journal of Comparative Neurology. 522, 1, p. 225-259  Abstract [All authors]

2013

115.
Poggio T. & Ullman S. (2013) Conference Reports: Evolutionary Dynamics And Information Hierarchies In Biological Systems: Aspen Center For Physics Workshop And Cracking The Neural Code: Third Annual Aspen Brain Forums. 1305, 1, p. 72-82  Abstract
114.
Extending recognition in a changing environment
Harari D. & Ullman S. (2013) VISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications. p. 632-640  Abstract
113.
Learning to Perceive Coherent Objects
Dorfman N., Harari D. & Ullman S. (2013) Cooperative Minds. Wachsmuth I., Knauff M., Pauen M. & Sebanz N.(eds.). p. 394-399  Abstract
112.
Learning to Perceive Coherent Objects
Dorfman, N., Harari, D. And Ullman, S. (2013) Proceedings of the Annual Meeting of the Cognitive Science Society - CogSci, pp 394-399.

[PDF]  [Slides]  [Project page]

*Winner of the 2013 Marr Prize

2012

111.
Ullman S., Harari D. & Dorfman N. (2012) Proceedings of the National Academy of Sciences of the United States of America. 109, 44, p. 18215-18220  Abstract
110.
Karlinsky L. & Ullman S. (2012) Computer Vision, ECCV 2012 - 12th European Conference on Computer Vision, Proceedings. PART 3 ed. p. 326-339  Abstract

2011

109.
Owaki T., Vidal-Naquet M., Sato T., Cateau H., Ullman S. & Tanifuji M. (2011) Neuroscience Research. 71, p. E71-E71  Abstract
108.
Harel A., Ullman S., Harari D. & Bentin S. (2011) Journal of Vision. 11, 8, p. 1-13  Abstract

2010

107.
Ullman S. (2010) Object Categorization. Leonardis A., Schiele B., J. Tarr M. & J. Dickinson S.(eds.). Vol. 9780521887380. p. 288-300  Abstract
106.
Levi D. & Ullman S. (2010) Image and Vision Computing. 28, 4, p. 715-723  Abstract
105.
Using body-anchored priors for identifying actions in single images
Karlinsky L., Dinerstein M. & Ullman S. (2010) Advances in Neural Information Processing Systems 23.  Abstract
104.
Karlinsky L., Dinerstein M., Harari D. & Ullman S. (2010) 2010 Ieee Conference On Computer Vision And Pattern Recognition (Cvpr). p. 25-32  Abstract
103.
Vidal-Naquet M. J., Tanifuji M., Maldonado P., Ullman S. & Gruen S. (2010) Neuroscience Research. 68, p. E380-E380  Abstract
102.
Using body-anchored priors for identifying actions in single images
Karlinsky, L. Dinershtein, D. Ullman, S. (2010) Neural Information Processing, 1-9, 2010..

2009

101.
Litvak S. & Ullman S. (2009) Neural Computation. 21, 11, p. 3010-3056  Abstract
100.
Ecker A. & Ullman S. (2009) Image and Vision Computing. 27, 1-2, p. 87-98  Abstract
99.
Unsupervised Feature Optimization (UFO): simultaneous selection of multiple features with their detection parameters
Karlinsky L., Dinerstein M. & Ullman S. (2009) Cvpr: 2009 Ieee Conference On Computer Vision And Pattern Recognition, Vols 1-4. p. 1263-1270  Abstract
98.
Levi D. & Ullman S. (2009) Proceedings of the 2009 Canadian Conference on Computer and Robot Vision, CRV 2009. p. 260-267  Abstract

2008

97.
Epshtein B., Lifshitz I. & Ullman S. (2008) Proceedings of the National Academy of Sciences of the United States of America. 105, 38, p. 14298-14303  Abstract
96.
Akselrod-Ballin A. & Ullman S. (2008) Image and Vision Computing. 26, 9, p. 1269-1276  Abstract
95.
Goldberg I., Ullman S. & Malach R. (2008) Consciousness and Cognition. 17, 3, p. 587-601  Abstract
94.
Bart E. & Ullman S. (2008) IEEE Transactions on Pattern Analysis and Machine Intelligence. 30, 9, p. 1618-1631  Abstract
93.
Lerner Y., Epshtein B., Ullman S. & Malach R. (2008) Journal of Cognitive Neuroscience. 20, 7, p. 1189-1206  Abstract
92.
Fink M. & Ullman S. (2008) International Journal of Computer Vision. 77, 1-3, p. 143-156  Abstract
91.
Mcmanus J. N., Ullman S. & Gilbert C. D. (2008) Journal of Neurophysiology. 99, 5, p. 2086-2100  Abstract
90.
Borenstein E. & Ullman S. (2008) IEEE Transactions on Pattern Analysis and Machine Intelligence. 30, 12, p. 2109-2125  Abstract
89.
Unsupervised Classification and Part Localization by Consistency Amplification
Karlinsky L., Dinerstein M., Levi D. & Ullman S. (2008) Computer Vision - Eccv 2008, Pt Ii, Proceedings. 5303, p. 321-335  Abstract
88.
Combined model for detecting, localizing and recognizing faces
Karlinsky, L. Dinershtein, M. Levi, D. Ullman, S. (2008) ECCV Workshop on Faces in Real-life Images, pp. 1-14..

2007

87.
Harel A., Ullman S., Epshtein B. & Bentin S. (2007) Vision Research. 47, 15, p. 2010-2020  Abstract
86.
Amit Y., Fink M., Srebro N. & Ullman S. (2007) p. 17-24  Abstract
85.
Ullman S. (2007) Trends in Cognitive Sciences. 11, 2, p. 58-64  Abstract
84.
Semantic hierarchies for recognizing objects and parts
Epshtein B. & Ullman S. (2007) 2007 Ieee Conference On Computer Vision And Pattern Recognition, Vols 1-8. p. 891-898  Abstract
83.
Uncovering Shared Structures in Multiclass Classification
Amit, Y., Srebro, N., Ullman, S. And Fink, M (2007) ICML, 227, pp. 17-24..

2006

82.
Online multiclass learning by interclass hypothesis sharing
Fink M., Shalev-Shwartz S., Singer Y. & Ullman S. (2006) ICML 2006 - Proceedings of the 23rd International Conference on Machine Learning. p. 313-320  Abstract
81.
Epshtein B. & Ullman S. (2006) Proceedings - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006. Vol. 2. p. 2079-2086  Abstract
80.
Visual classification by a hierarchy of extended fragments
Ullman S. & Epshtein B. (2006) Toward Category-Level Object Recognition. 4170, p. 321-344  Abstract
79.
Levi D. & Ullman S. (2006) Proceedings - Thirteenth International Symposium on Temporal Representation and Reasoning, TIME 2006.  Abstract
78.
Online Multiclass Learning by Interclass Hypothesis Sharing
Fink, M., Shalev-Shwartz, S., Singer, Y. And Ullman, S. (2006) ICML, pp. 313-320.
77.
Learning to classify by ongoing feature selection
Levi, D. And Ullman (2006) CRV, Recipient of Best CRV Paper Award.
76.
Satellite Features for the Classification of Visually Similar Classes
Epstein, B. And Ullman, S. (2006) CVPR, pp. 2079-2086.
75.
Object recognition by eliminating distracting information
Bart, E. And Ullman, S. (2006) ICCVG, Warsaw, Poland..

2005

74.
Calford M. B., Chino Y. M., Das A., Eysel U. T., Gilbert C. D., Heinen S. J., Kaas J. H. & Ullman S. (2005) Nature. 438, 7065, p. E3  Abstract
73.
Shmuel A., Korman M., Sterkin A., Harel M., Ullman S., Malach R. & Grinvald A. (2005) Journal of Neuroscience. 25, 8, p. 2117-2131  Abstract
72.
Bart E. & Ullman S. (2005)  Abstract
71.
Ecker A. & Ullman S. (2005) Proceedings - 2nd Canadian Conference on Computer and Robot Vision, CRV 2005. p. 50-56  Abstract
70.
Cross-generalization: learning novel classes from a single example by feature replacement
Bart E. & Ullman S. (2005) 2005 Ieee Computer Society Conference On Computer Vision And Pattern Recognition, Vol 1, Proceedings. p. 672-679  Abstract
69.
Identifying semantically equivalent object fragments
Epshtein B. & Ullman S. (2005) 2005 Ieee Computer Society Conference On Computer Vision And Pattern Recognition, Vol 1, Proceedings. p. 2-9  Abstract
68.
Feature hierarchies for object classification
Epshtein B. & Ullman S. (2005) Tenth Ieee International Conference On Computer Vision, Vols 1 And 2, Proceedings. p. 220-227  Abstract
67.
Learning a novel class from a single example by cross-generalization.
E. Bart And S. Ullman (2005) CVPR, pp. 1063-1069.
66.
A fragment based approach for the characterization of V1 receptive fields
Vidal Naquet, M. Miyakawa, N. et al. (2005) SFN Abstract. [All authors]
65.
A hierarchical non-parametric method for capturing non-rigid transformation
Ecker, A. And Ullman, S. (2005) Canadian Robotics and Vision Conference, pp. 50-56.
64.
Single-example learning of novel classes using representation by similarity
Bart, E. And Ullman, S. (2005) BMVC, Oxford, England .

2004

63.
Zur D., Ben Simon S. G., Loewenstein A., Alster Y., Moisseiev J. & Ullman S. (2004) Ophthalmic Surgery Lasers and Imaging. 35, 5, p. 395-405  Abstract
62.
Ullman S. & Bart E. (2004) Neural Networks. 17, 5-6, p. 833-848  Abstract
61.
Bart E. & Ullman S. (2004) IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. 2004-January, January, 1384972.  Abstract
60.
Borenstein E., Sharon E. & Ullman S. (2004) IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. 2004-January, January, 1384838.  Abstract
59.
Borenstein E. & Ullman S. (2004) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3023, p. 315-328  Abstract
58.
View-invariant recognition using corresponding object fragments
Bart E., Byvatov E. & Ullman S. (2004) Computer Vision - Eccv 2004, Pt 2. 3022, p. 152-165  Abstract
57.
Combining bottom-up and top-down segmentation
E. Borenstein And S. Ullman (2004) CVPR workshop on Perceptual Organization in Computer Vision.
56.
Class-based matching of object parts
E. Bart And S. Ullman (2004) CVPR Workshop on Image and Video Registration.
55.
Image normalization by mutual information
E. Bart And S. Ullman (2004) Bmvc.

2003

54.
Zur D. & Ullman S. (2003) Vision Research. 43, 9, p. 971-982  Abstract
53.
Object recognition with informative features and linear classi cation pound
Vidal-Naquet M. & Ullman S. (2003) Ninth Ieee International Conference On Computer Vision, Vols I And Ii, Proceedings. p. 281-288  Abstract
52.
Approaches to visual recognition
Ullman, S (2003) Attention and Performance XX, Oxford University Press..

2002

51.
Zur D. & Ullman S. (2002) Journal of Vision. 2, 7, p. 183a  Abstract
50.
Ullman S., Vidal-Naquet M. & Sali E. (2002) Amino Acids. 23, 4, p. 343  Abstract
49.
Ullman S., Vidal-Naquet M. & Sali E. (2002) Nature Neuroscience. 5, 7, p. 682-687  Abstract
48.
Gilaie-Dotan S., Ullman S., Kushnir T. & Malach R. (2002) Human Brain Mapping. 15, 2, p. 67-79  Abstract
47.
Class-specific, top-down segmentation
Borenstein E. & Ullman S. (2002) Computer Vision - Eccv 2002, Pt Ii. 2351, p. 109-122  Abstract

2001

46.
Ullman S., Sali E. & Vidal-Naquet M. (2001) Visual Form 2001 - 4th International Workshop on Visual Form, IWVF4, Proceedings. Arcelli C., di Baja G. S. & Cordella L. P.(eds.). p. 85-100  Abstract
45.
A fragment-based approach to object representation and classification
Ullman, S., Sali, E. & Vidal-Naquet, M (2001) International Workshop on Visual Form, Berlin: Springer, 85-100..

2000

44.
Object classification using a fragment-based representation
Ullman S. & Sali E. (2000) Biologically Motivated Computer Vision, Proceeding. 1811, p. 73-87  Abstract

1999

43.
Ullman S. & Soloviev S. (1999) Neural Networks. 12, 7-8, p. 1021-1036  Abstract
42.
Combining class-specific fragments for object classification.
Sali, E. & Ullman, S. (1999) In Proc. 10th British Machine Vision Conference, volume 1, 203 - 213..
41.
Detecting object classes by the detection of overlapping 2-D fragments.
Sali, E. & Ullman, S. In: D. Chernikov & T. Szinanyi, (Eds.) (1999) Proceedings of the Workshop on Fundamental Structural Properties in Image and Pattern Analysis, 123-132. Published by OCG, Austrian Computer Society..

1998

40.
Ullman S. (1998) Cognition. 67, 1-2, p. 21-44  Abstract
39.
Recognizing novel 3-D objects under new illumination and viewing position using a small number of example views or even a single view
Sali E. & Ullman S. (1998) p. 153-161  Abstract
38.
Brestel C. & Ullman S. (1998) European Signal Processing Conference. 1998-January,  Abstract
37.
Moses Y. & Ullman S. (1998) International Journal of Computer Vision. 29, 3, p. 233-253  Abstract

1997

36.
Ullman S., Roth A., Thomson A. & Linne M. (1997) Trends in Neurosciences. 20, 2, p. 53-54  Abstract
35.
Adini Y., Moses Y. & Ullman S. (1997) IEEE Transactions on Pattern Analysis and Machine Intelligence. 19, 7, p. 721-732  Abstract
34.
Object recognition using stochastic optimization
Ullman S. & Zeira A. (1997) Energy Minimization Methods In Computer Vision And Pattern Recognition, Proceedings. 1223, p. 329-344  Abstract

1996

33.
Kositsky M. & Ullmann S. (1996) Track D. Vol. 4. p. 750-757  Abstract
32.
Bar M. & Ullman S. (1996) Perception. 25, 3, p. 343-352  Abstract
31.
Moses Y., Ullman S. & Edelman S. (1996) Perception. 25, 4, p. 443-461  Abstract

1995

30.
Ullman S. (1995) Cerebral Cortex. 5, 1, p. 1-11  Abstract

1994

29.
Moses Y., Adini Y. & Ullman S. (1994) Computer Vision ECCV 1994 - 3rd European Conference on Computer Vision, Proceedings. Eklundh J-O(eds.). Vol. 800. p. 286-296  Abstract

1993

28.
Basri R. & Ullman S. (1993) CVGIP: Image Understanding. 57, 3, p. 331-345  Abstract
27.
Basri R. & Ullman S. (1993) Cvgip-Image Understanding. 57, 3, p. 331-345  Abstract

1992

26.
Ullman S. (1992) Philosophical Transactions of the Royal Society of London Series b-Biological Sciences. 337, 1281, p. 371-378; discussion 379  Abstract
25.
Moses Y. & Ullman S. (1992) Computer Vision - ECCV 1992 - 2nd European Conference on Computer Vision, Proceedings. Sandini G.(eds.). p. 820-828  Abstract
24.
LIMITATIONS OF NONMODEL-BASED RECOGNITION SCHEMES
Moses Y. & Ullman S. (1992) Computer Vision - Eccv 92. 588, p. 820-828  Abstract

1991

23.
Ullman S. & Basri R. (1991) IEEE Transactions on Pattern Analysis and Machine Intelligence. 13, 10, p. 992-1006  Abstract
22.
Dick M., Ullman S. & Sagi D. (1991) Vision Research. 31, 11, p. 2025-2028  Abstract
21.
Guissin R. & Ullman S. (1991) Proceedings of the IEEE Workshop on Visual Motion. p. 146-155  Abstract

1990

20.
Edelman S., Flash T. & Ullman S. (1990) International Journal of Computer Vision. 5, 3, p. 303-331  Abstract
19.
Moses Y., Schechtman G. & Ullman S. (1990) Biological Cybernetics. 63, 6, p. 463-475  Abstract
18.
BEYOND V1 - PROBLEMS IN INTERMEDIATE-LEVEL VISION
Ullman S. (1990) Signal And Sense: Local And Global Order In Perceptual Maps. p. 143-162  Abstract

1989

17.
Ullman S. (1989) Cognition. 32, 3, p. 193-254  Abstract

1988

16.
FROM PIXELS TO PREDICATES - RECENT ADVANCES IN COMPUTATIONAL AND ROBOTIC VISION - PENTLAND,AP
Ullman S. (1988) Contemporary Psychology. 33, 1, p. 48-48  Abstract

1987

15.
Dick M., Ullman S. & Sagi D. (1987) Science. 237, 4813, p. 400-402  Abstract

1986

14.
Richter J. & Ullman S. (1986) Biological Cybernetics. 54, 4-5, p. 313-317  Abstract
13.
Richter J. & Ullman S. (1986) Biological Cybernetics. 53, 3, p. 195-202  Abstract
12.
Ullman S. (1986) Trends in Neurosciences. 9, C, p. 530-533  Abstract
11.
Artificial intelligence and the brain: Computational studies of the visual system
Ullman S. (1986) Annual Review of Neuroscience. VOL. 9, p. 1-26  Abstract

1985

10.
Shifts in selective visual attention: Towards the underlying neural circuitry
Koch C. & Ullman S. (1985) Human Neurobiology. 4, 4, p. 219-227  Abstract

1984

9.
Ullman S. (1984) Perception. 13, 2, p. 219-220  Abstract
8.
Ullman S. (1984) Perception. 13, 3, p. 255-274  Abstract

1983

7.
Ullman S. (1983) Trends in Neurosciences. 6, C, p. 177-179  Abstract

1982

6.
Ullman S. & Schechtman G. (1982) Proceedings Of The Royal Society Series B-Biological Sciences. 216, 1204, p. 299-313  Abstract

1981

5.

1980

4.
Ullman S. (1980) Perception. 9, 6, p. 617-626  Abstract

1979

3.
Marr D., Ullman S. & Poggio T. (1979) Journal of the Optical Society of America. 69, 6, p. 914-916  Abstract
2.
VISUAL DETECTION OF LIGHT SOURCES.
Ullman S. (1979) Energy Technology Review. 2, p. 81-100  Abstract
1.
Ullman S. (1979) Proceedings of the Royal Society B: Biological Sciences. 203, 1153, p. 405-426  Abstract