shore birds (22), and interdigital webbing has
been reported in theropod dinosaurs (29).
Reduction of the pelvic girdle and hindlimb and
the concomitant enhancement of axial-powered
locomotion are common among semiaquatic
vertebrates. The flexibility of the tail and the
form of the neural spines in Spinosaurus suggest
tail-assisted swimming. Like extinct and extant
semiaquatic reptiles, Spinosaurus used lateral
undulation of the tail, in contrast to the vertical
axial undulation adopted repeatedly by semiaquatic mammals (20, 21).
The dorsal “sail” in Spinosaurus, the tallest
axial structure documented among dinosaurs,
has been argued to be a thermoregulatory surface, a muscle- or fat-lined hump (30), or a display structure. Stromer (1) drew an analogy to
the skin-covered neural spines of the crested
chameleon, Trioceros cristatus (Fig. 4E). As in
T. cristatus, the sail of Spinosaurus is centered
over the trunk (Fig. 2A). The shape and positioning of the spine are also similar, and the base of
the neural spine is expanded anteroposteriorly,
with edges marked by ligament scars (Fig. 2E).
In Trioceros, a tendon of multisegmental axial
musculature attaches to the expanded base of
the neural spine (Fig. 4E). The upper portion of
the spine has sharp anterior and posterior edges,
is marked by fine vertical striae (Figs. 2E and 4D),
and is spaced away from adjacent spines, unlike the broader, contiguous, paddle-shaped dorsal
spines of other spinosaurids (13). The striated
surface, sharp edges, and dense, poorly vascular-ized internal bone of the spines suggest that they
were wrapped snugly in skin and functioned as
a display structure that would have remained
visible while swimming.
REFERENCES AND NOTES
1. E. Stromer, Ahb. Königl. Bayer. Akad. Wissen. Math-Phys. Kl. 28,
2. E. Stromer, Abh. Königl. Bayer. Akad. Wissen. Math-Naturwissen.
Abt. 22, 1–79 (1934).
3. J. B. Smith, M. C. Lamanna, H. Mayr, K. J. Lacovara,
J. Paleontol. 80, 400–406 (2006).
4. W. Nothdurft, J. Smith, The Lost Dinosaurs of Egypt (Random
House, New York, 2002).
5. P. Taquet, D. Russell, C. R. Acad. Sci. Paris 299, 347–353 (1998).
6. C. Dal Sasso, S. Maganuco, E. Buffetaut, M. A. Mendez, J. Vert.
Paleontol. 25, 888–896 (2005).
7. P. C. Sereno et al., Science 272, 986–991 (1996).
8. See the supplementary materials on Science Online.
9. R. Lavocat, in Comptes Rendus de la 19ème Congrès
Géologique International, Alger, 1952, session XII-3, 15 (1954),
10. L. Mahler, J. Vert. Paleont. 25, 236–239 (2005).
11. D. A. Russell, Bull. Mus. Hist. Nat. Paris 18, 349–402 (1996).
12. B. McFeeters, M. J. Ryan, S. Hinic-Frlog, C. Schröder-Adams,
H. Sues, Can. J. Earth Sci. 50, 636–649 (2013).
13. P. C. Sereno et al., Science 282, 1298–1302 (1998).
14. A. J. Charig, A. C. Milner, Bull. Nat. Hist. Mus 53, 11–70 (1997).
15. C. Brochu, J. Vert. Paleontol. Mem. 7, 22 (suppl. 4), 1–138
16. D. B. Leitch, K. C. Catania, J. Exp. Biol. 215, 4217–4230 (2012).
17. F. E. Novas, F. Dalla Vecchia, D. F. Pais, Rev. Mus. Argent.
Cien. Nat. 7, 167–175 (2005).
18. F. E. Fish, G. V. Lauder, Annu. Rev. Fluid Mech. 38, 193–224
19. S. I. Madar, Adv. Vert. Paleobiol. 1, 353–378 (1998).
20. P. D. Gingerich, Paleobiology 29, 429–454 (2003).
21. F. E. Fish, IEEE J. Oceanic Eng. 29, 605–621 (2004).
22. A. Manegold, Acta Ornithol. 41, 79–82 (2006).
23. E. Amson, C. de Muizon, M. Laurin, C. Argot, V. de Buffrénil,
Proc. Biol. Sci. 281, 20140192 (2014).
24. K. T. Bates, R. B. J. Benson, P. L. Falkingham, Paleobiology 38,
25. S. M. Gatesy, M. Bäker, J. R. Hutchinson, Paleobiology 29,
26. E. Stromer, Abh. Königl. Bayer. Akad. Wissen. Math.-Naturwissen.
Abt. 33, 1–102 (1936).
27. A. J. Charig, A. C. Milner, Nature 324, 359–361 (1986).
28. E. J. Rayfield, A. C. Milner, V. B. Xuan, P. G. Young,
J. Vert. Paleontol. 27, 892–901 (2007).
29. M. L. Casanovas Cladellas et al., España Zub. Monogr. 5,
30. J. B. Bailey, J. Paleontol. 71, 1124–1146 (1997).
We thank C. Abraczinskas for final drafts of all text figures;
M. Auditore for discussions and drawings; T. Keillor, L. Conroy,
and E. Fitzgerald for image processing and modeling; R. Masek,
T. Keillor, E. Fitzgerald, and F. Bacchia for fossil preparation;
C. Straus, N. Gruszauskas, D. Klein, and the University of Chicago
Medical Center for computed tomographic scanning; M. Zilioli,
F. Marchesini, M. Pacini, E. Lamm, and P. Vignola for preparation of
histological samples; A. Di Marzio (Siemens Milano) and P. Biondetti
(Fondazione Ospedale Maggiore Istituto di Ricovero e Cura a
Carattere Scientifico, Milan) for computed tomography scanning and
rendering of MSNM V4047; and the Island Fund of the New York
Community Trust and National Geographic Society (grant
SP-13-12) for support of this research. N.I. was also supported by
NSF grant DBI-1062542. We also thank the embassy of the
Kingdom of Morocco in Washington, DC, for their continued
interest in this project. Skeletal measurements and geologic data
are included in the supplementary materials. The neotype is going to
be deposited at the Faculté des Sciences Aïn Chock (University of
Casablanca), Casablanca, Morocco.
Figs. S1 to S8
Tables S1 to S5
15 July 2014; accepted 3 September 2014
A critical time window for dopamine
actions on the structural plasticity
of dendritic spines
Sho Yagishita,1,2 Akiko Hayashi-Takagi,1,2,3 Graham C.R. Ellis-Davies,4
Hidetoshi Urakubo,5 Shin Ishii,5 Haruo Kasai1,2*
Animal behaviors are reinforced by subsequent rewards following within a narrow time
window. Such reward signals are primarily coded by dopamine, which modulates the
synaptic connections of medium spiny neurons in the striatum. The mechanisms of the
narrow timing detection, however, remain unknown. Here, we optically stimulated
dopaminergic and glutamatergic inputs separately and found that dopamine promoted
spine enlargement only during a narrow time window (0.3 to 2 seconds) after the
glutamatergic inputs. The temporal contingency was detected by rapid regulation of
adenosine 3′,5′-cyclic monophosphate in thin distal dendrites, in which protein-kinase
A was activated only within the time window because of a high phosphodiesterase
activity. Thus, we describe a molecular basis of reinforcement plasticity at the level of
single dendritic spines.
Animal behaviors are reinforced only when rewarded shortly after a motor or sensory event (1, 2). The neocortex, hippocampus, and amygdala process the sensorimotor signals andsendglutamatergic synaptic out-
put to the striatum (3), where connections can
be modified by Hebbian learning mechanisms,
(4). Animals learn to associate the sensorimotor
signals with subsequent rewards through rein-
forcement of the neuronal circuits involving do-
pamine (5–7). Despite its importance, this narrow
timing detection has never been demonstrated at
the cellular level and might be ascribed to neural
network properties (6, 8).
Dendritic spine morphology is correlated with
spine function (9), and dendritic spines enlarge
during long-term potentiation in the cortices
(10–12). We examined the effects of dopamine
on the structural plasticity in striatal medium
spiny neurons (MSNs). Results show that dopamine affected spine structural plasticity in a
narrow time window consistent with behavioral conditioning (5). Functional imaging revealed
the molecular interrelationships between the reinforcement and Hebbian plasticity.
We investigated dopamine actions on glutamatergic synapses on MSNs using optogenetics and
1616 26 SEPTEMBER 2014 • VOL 345 ISSUE 6204
1Laboratory of Structural Physiology, Center for Disease
Biology and Integrative Medicine, Faculty of Medicine, The
University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan.
2Core Research for Evolutional Science and Technology,
Japan Science and Technology Agency, Japan Science and
Technology Agency, 4-1-8 Honcho, Kawaguchi, Saitama
332-0012, Japan. 3Precursory Research for Embryonic
Science and Technology, Japan Science and Technology
Agency, Japan Science and Technology Agency, 4-1-8
Honcho, Kawaguchi, Saitama 332-0012, Japan. 4Department
of Neuroscience, Mount Sinai School of Medicine, New York,
NY 10029, USA. 5Integrated Systems Biology Laboratory,
Department of Systems Science, Graduate School of
Informatics, Kyoto University, Sakyo-ku, Kyoto 606-8501,
*Corresponding author. E-mail: firstname.lastname@example.org