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patients_ lesions overlap (15). Our findings are
similar to those obtained in nonhuman primates.
Monkeys showed persistent signs of neglect after
unilateral section of the white matter between the
fundus of the intraparietal sulcus and the lateral
ventricle (24). The greater effect of subcortical
inactivation, as compared to cortical inactivation,
is consistent with the idea that symmetrical space
processing requires the integrity of a parietal-
frontal network (1, 15). Damage to restricted
regions of the white matter can cause the dys-
function of large-scale neurocognitive networks.
Accordingtoaninfluentialmodel(1), signs of left
neglect result from impairment of a right-
hemisphere network, including prefrontal, parie-
tal, and cingulate components. The parietal
component of the network could be especially
important for the perceptual salience of extra-
personal objects, whereas the frontal component
might be implicated in the production of an
appropriate response to behaviorally relevant
stimuli (1), in the online retention of spatial
information (1, 25), or in the focusing of attention
on salient items through reciprocal connections to
more posterior regions (20).
Models of line bisection postulate a compe-
tition between the relative salience of the two
lateral segments (6). The bisection mark is drawn
at the point of subjective equality between the
two segments (5). Bisection-related tasks acti-
vate the IPL in humans (26). Transcranial
magnetic stimulation over the right posterior
parietal cortex, but not over the STG, was found
to bias the comparison of the lengths of the
component segments of pretransected lines in a
direction coherent with rightward shifts in line
bisection (27). In the monkey, regions adjacent
to the intraparietal sulcus, such as the lateral
intraparietal area, are related to visual perceptu-
al salience (11) and can reinforce the stimulus
attentional priority (10). Parietal inactivation
may thus bias the perceptual decision by mod-
ulating the salience of the line segments (6).
The assessment of spatial cognition during
intraoperative stimulation offers the double op-
portunity of preserving spatial processing
functions during brain surgery and of pinpoint-
ing the neurocognitive systems devoted to spa-
tial processing in humans. Spatial awareness is
dependent not only on the cortical areas of the
temporal-parietal junction, but also on a larger
parietal-frontal network communicating via the
superior occipitofrontal fasciculus.
References and Notes
1. M. M. Mesulam, Philos. Trans. R. Soc. London Ser. B
354, 1325 (1999).
2. P. Azouvi et al., J. Neurol. Neurosurg. Psychiatry 73,
160 (2002).
3. P. Bartolomeo, S. Chokron, Neurosci. Biobehav. Rev.
26, 217 (2002).
4. T. Schenkenberg, D. C. Bradford, E. T. Ajax, Neurology
30, 509 (1980).
5. J. C. Marshall, P. W. Halligan, Cognit. Neuropsychol.
7, 107 (1990).
6. B. Anderson, Brain 119, 841 (1996).
7. G. Vallar, Neuroimage 14, S52 (2001).
8. D. J. Mort et al., Brain 126, 1986 (2003).
9. M. Corbetta, G. L. Shulman, Nat. Rev. Neurosci. 3,
201 (2002).
10. J. W. Bisley, M. E. Goldberg, Science 299, 81 (2003).
11. J. P. Gottlieb, M. Kusunoki, M. E. Goldberg, Nature
391, 481 (1998).
12. H. O. Karnath, M. Fruhmann Berger, W. Kuker, C.
Rorden, Cereb. Cortex 14, 1164 (2004).
13. A. D. Milner, M. A. Goodale, The Visual Brain in Action
(Oxford Univ. Press, Oxford, 1995).
14. H. O. Karnath, Nat. Rev. Neurosci. 2, 568 (2001).
15. F. Doricchi, F. Tomaiuolo, Neuroreport 14, 2239 (2003).
16. H. Duffau et al., Brain 128, 797 (2005).
17. CAL and SB attended clinical observation because of
epileptic seizures. They showed no abnormality on
preoperative neurological and neuropsychological ex-
amination, consistent with the slowly infiltrative
character of low-grade gliomas, whose clinical presen-
tation rarely includes signs of focal brain disease other
than epilepsy. In particular, there were no signs of
neglect on paper-and-pencil tests (table S1). Intra-
operative electrical stimulation was well tolerated, and
the patients reported no abnormal visual sensations.
They bisected horizontal lines with their left, dominant
hand during brain surgery (28). Eight healthy left-
handed subjects (mean age, 31 years; SD, 5.3; range, 26
to 38) served as controls. They performed 30 line bi-
sections each, with the same test material and in a body
position similar to that of the patients. Our patients’
baseline performance was well within the range of the
controls’ performance (mean T SD, 0.28 T 2.39 mm) as
well as that of 10 strongly left-handed normal
individuals tested in another study (29)(meanT SD,
–1.50 T 3.66 mm). In an unselected population of 204
patients with right brain damage (2), 5 of the 10
patients with the strongest left-handedness deviated
rightward on 20-cm lines as compared to controls (29),
a frequency of impairment similar to that showed by
right-handed patients (2).
18. M. Catani, R. J. Howard, S. Pajevic, D. K. Jones,
Neuroimage 17, 77 (2002).
19. The neurosurgeon stopped the resection after stimu-
lation of the region labeled as 42 (Fig. 2A). As a
consequence, region 42 corresponded to the deepest
point on the floor of the rostral-superior part of the
surgical cavity, and was thus easily identified on
postoperative anatomical MRI scans. The white
matter tract underlying region 42 was identified by
overlapping the MRI scans with the DTI scans (fig.
S1) (Fig. 2, C and D).
20. M. Petrides, D. N. Pandya, in Principles of Frontal
Lobe Function, D. T. Stuss, R. T. Knight, Eds. (Oxford
Univ. Press, Oxford, 2002), pp. 31–50.
21. The superior occipitofrontal fasciculus is a poorly
known long association pathway. It terminates
rostrally in the lateral prefrontal cortex of the
inferior and middle frontal gyri (18). Its caudal
terminations are less known (18, 30), but despite its
name, derived from early descriptions (31), the superior
occipitofrontal fasciculus seems to terminate caudally
in the superior parietal gyrus (18)andinthe
intraparietal sulcus [(30), p. 367].
22. We used line bisection because it is an easy task for
patients to perform and allows repeated assessments
in the time scale required by intraoperative testing.
Bisection of centrally presented 20-cm lines corre-
lates positively and significantly with cancellation
tests and is a good predictor of clinical neglect as
assessed by standardized scales (2, 28).
23. C. Rorden, M. Fruhmann Berger, H.-O. Karnath, Cognit.
Brain Res., published online 19 February 2005 (10.1016/
j.cogbrainres.2004.10.022).
24. D. Gaffan, J. Hornak, Brain 120, 1647 (1997).
25. M. Husain, C. Rorden, Nat. Rev. Neurosci. 4, 26 (2003).
26. G. R. Fink, J. C. Marshall, P. H. Weiss, I. Toni, K. Zilles,
Neuropsychologia 40, 119 (2002).
27. A. Ellison, I. Schindler, L. L. Pattison, A. D. Milner,
Brain 127, 2307 (2004).
28. See supporting data on Science Online.
29. M. Rousseaux et al., Rev. Neurol. (Paris) 157, 1385
(2001).
30. R. Nieuwenhuys, J. Voogd, C. van Huijzen, The Human
Central Nervous System: A Synopsis and Atlas (Springer-
Verlag, New York, 1988).
31. M. J. De
´
jerine, Anatomie des Centres Nerveux (Rueff,
Paris, 1895).
32. J. R. Crawford, P. H. Garthwaite, Neuropsychologia
40, 1196 (2002).
33. We thank the patients for their cooperation; P. Gatignol
for help with intraoperative testing; J. Chiras and the
Department of Neuroradiology of the Salpe
ˆ
trie
`
re Hos-
pital for MRI acquisitions; S. Kinkingnehun, C. Delmaire,
J. B. Pochon, L. Thivard, and the staff of BrainVISA
software for technical support for image analysis; and P.
Azouvi and the members of the Groupe d’Etude sur la
Re
´
e
´
ducation et l’Evaluation de la Ne
´
gligence (GEREN) for
permission to use data from GEREN studies (2, 29).
Supporting Online Material
www.sciencemag.org/cgi/content/full/309/5744/2226/
DC1
Materials and Methods
SOM Text
Tables S1 and S2
Figs. S1 and S2
References
17 June 2005; accepted 26 August 2005
10.1126/science.1116251
Breakdown of Cortical Effective
Connectivity During Sleep
Marcello Massimini,
1,2
Fabio Ferrarelli,
1
Reto Huber,
1
Steve K. Esser,
1
Harpreet Singh,
1
Giulio Tononi
1
*
When we fall asleep, consciousness fades yet the brain remains active. Why is
this so? To investigate whether changes in cortical information transmission
play a role, we used transcranial magnetic stimulation together with high-
density electroencephalography and asked how the activation of one cortical
area (the premotor area) is transmitted to the rest of the brain. During quiet
wakefulness, an initial response (È15 milliseconds) at the stimulation site was
followed by a sequence of waves that moved to connected cortical areas
several centimeters away. During non–rapid eye movement sleep, the initial
response was stronger but was rapidly extinguished and did not propagate
beyond the stimulation site. Thus, the fading of consciousness during certain
stages of sleep may be related to a breakdown in cortical effective connectivity.
When awakened early in the night from non–
rapid eye movement (NREM) sleep, people
often report little or no conscious experience
(1). It was first thought that this fading of con-
sciousness was due to the brain shutting down.
However, although brain metabolism is re-
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30 SEPTEMBER 2005 VOL 309 SCIENCE www.sciencemag.org
2228
duced, the thalamocortical system remains ac-
tive, with mean firing rates close to those that
occur during quiet wakefulness (2). Moreover,
coherent or synchronized activity continues to
be detected among distant cortical areas (3–5),
and sensory signals still reach the cerebral cor-
tex (6). Why, then, does consciousness fade?
Recently we have proposed that conscious-
ness depends critically not so much on firing
rates, synchronization at specific frequency
bands, or sensory input per se, but rather on the
brain_s ability to integrate information, which is
contingent on the effective connectivity among
functionally specialized regions of the thalamo-
cortical system (7). Effective connectivity re-
fers to the ability of a set of neuronal groups
to causally affect the firing of other neuronal
groups within a system (8). The fading of con-
sciousness during NREM sleep episodes early in
the night, evidenced by short or blank reports of
cognitive activity upon awakening (1), would
then be associated with an impairment of cor-
tical effective connectivity.
To test this prediction, we used a combination
of navigated transcranial magnetic stimulation
(TMS) and high-density electroencephalography
(HD-EEG) to measure the brain response to the
direct perturbation of a chosen cortical region
noninvasively and with good spatiotemporal
resolution (9, 10). Using TMS/EEG to investi-
gate critical differences in the functioning of the
waking and sleeping brain offers several advan-
tages. Unlike sensory stimulation, direct cortical
stimulation does not activate the reticular
formation and bypasses the thalamic gate. Thus,
it directly probes the ability of cortical areas to
interact, unconfounded by peripheral effects.
Also, since study subjects reported that they
were not aware of the TMS pulse, neural
responses are not contaminated by reactions
that may result from becoming aware of the
stimulation. Most important, the combination of
TMS and HD-EEG dissociates effective con-
nectivity (causal interactions) from functional
connectivity Etemporal correlations (8)^.
Using a 60-channel TMS-compatible EEG
amplifier, we recorded TMS-evoked brain
responses while six subjects, lying with eyes
closed on a reclining chair, progressed from
wakefulness to NREM sleep. By means of mag-
netic resonance image (MRI)–guided estimation
of the electric field induced on the surface of the
brain (Fig. 1A), we targeted TMS to the rostral
portion of the right premotor cortex. This is an
area with extensive corticocortical connections
that can be conveniently stimulated without
eliciting muscle artifacts. Stimuli were de-
livered at random intervals (between 2 and
2.3 s) with intensity below the motor threshold
(90%), resulting in a maximum electric field at
the cortical target of between 75 and 84 V/m.
We took special care to reduce the amount of
auditory and somatosensory stimulation asso-
ciated with each TMS pulse (11).
As shown in Fig. 1B, TMS did not interfere
conspicuously with ongoing wake or sleep
EEG patterns nor did it cause visible artifacts.
However, TMS elicited a time-locked re-
sponse that was visible on a single-trial basis
1
Department of Psychiatry, University of Wisconsin,
Madison, 6001 Research Park Boulevard, Madison, WI
53719, USA.
2
Department of Clinical Sciences, Univer-
sity of Milan, via G. B. Grassi 74, Milan 20157, Italy.
*To whom correspondence should be addressed.
E-mail: gtononi@wisc.edu
Fig. 1. Navigated
brain stimulation and
EEG recordings during
TMS. (A) The esti-
mated electric field
induced by TMS on
the cortical surface in
one subject is color-
coded. The red area
indicates the location
of the maximal elec-
tric field strength (in
this case, 81 V/m) and
corresponds to the co-
ordinates of the rostral
premotor cortex, as
identified on the three
orthogonal projections
of the subject’s MRI.
The brown pins repre-
sent the digitized elec-
trodes. (B)Multichannel
EEG recorded during
wakefulness and NREM
sleep while TMS
(red) was delivered.
Fig. 2. Changes in the TMS-evoked response during shifts in the state of vigilance. (A) Single trials
recorded from one channel located under the stimulator while the subject (the same as in Fig. 1)
transitioned from wakefulness through stage 1 to NREM sleep. Single-trial EEG data (filtered from 4 to
100 Hz) are color-coded for voltage. (B)AveragedTMS-evokedresponses(filteredfrom1to100Hz)
obtained during the three states of vigilance. The horizontal pink bands indicate the significance level
(3 SD from the mean prestimulus voltage).
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www.sciencemag.org SCIENCE VOL 309 30 SEPTEMBER 2005
2229
and that changed markedly from wakefulness
to sleep. Figure 2A displays the single-trial
responses recorded from one electrode located
under the stimulator during a transition from
wakefulness through stage 1 to NREM (stages
2 and 3) sleep (in the same subject as in Fig.
1). Figure 2B shows the averages calculated
from the single trials collected in these three
vigilance states. During wakefulness, TMS
induced a sustained response made of recurrent
waves of activity. Specifically, a sequence of
time-locked high-frequency (20 to 35 Hz)
oscillations occurred in the first 100 ms and
wasfollowedbyafewslower(8to12Hz)
components that persisted until 300 ms. As
soon as the subjects transitioned into stage 1
sleep, the TMS-evoked response grew stronger
at early latencies but became shorter in
duration: The amplitude of the initial compo-
nents increased by 50 to 85% between 0 and
40 ms, whereas the subsequent waves were
markedly dampened and fell below prestimu-
lus noise levels (3 SD from the prestimulus
baseline mean) within the first 150 to 200 ms.
With the onset of NREM sleep, the brain
response to TMS changed markedly. The ini-
tial wave doubled in amplitude and lasted
longer. After this large wave, no further TMS-
locked activity could be detected, except for a
slight negative rebound between 80 and 140
ms. Specifically, fast waves, still visible during
stage 1, were completely obliterated, and all
TMS-evoked activity had ceased by 150 ms.
To better characterize the underlying neural
events, we calculated the spatiotemporal dy-
namics of the currents induced by TMS in the
cerebral cortex. We digitized and coregistered
electrode positions to each subject_sMRI,and
we constructed a realistic head model. We then
estimated current density on the cortical sur-
face by using the weighted minimum norm
least-squares method (11). Figure 3 shows the
average responses recorded from all channels
during wakefulness and NREM sleep in the
same subject shown in Figs. 1 and 2. At early
latencies, during both wakefulness and NREM
sleep, TMS induced a clear dipolar voltage
configuration that was centered under the coil
and corresponded to maximum cortical activa-
tion in ipsilateral area 6. During wakefulness,
this initial response was followed for about
300 ms by multiple waves of activity asso-
ciated with rapidly changing configurations of
scalp potentials. Current maxima shifted over
time from the stimulation target to contra-
lateral area 6, bilateral area 9, contralateral
area 8, and ipsilateral area 7. The rostral
premotor cortex has extensive transcallosal
connections (12) and is linked to prefrontal
areas (13). Thus, during wakefulness, the
perturbation of the rostral premotor cortex
was followed by spatially and temporally dif-
ferentiated patterns of activation that appeared
to propagate along its anatomical connections.
In striking contrast, during NREM sleep the
location of maximum current density remained
confined to the stimulated area.
As shown in Fig. 4, this breakdown in
effective connectivity during sleep was evident
and reproducible in all six subjects. We
estimated current density whenever the global
power of the evoked field was higher (96SD)
than mean prestimulus levels and plotted the
location of the strongest TMS-evoked activa-
tiononeachsubject_s cortical surface, color-
coded according to its latency (11). During
wakefulness, the site of maximum activation
moved back and forth among premotor and
prefrontal areas in both hemispheres and, in
some subjects, it also involved the motor and
posterior parietal cortex. During NREM sleep,
by contrast, the activity evoked by TMS did not
propagate in space and time in any of the
subjects. In two subjects, we were also able to
stimulate the parietal cortex (area 5), and we
found a similar impairment of intracortical in-
formation transmission during NREM sleep
(fig. S2). Thus, although TMS during sleep
elicits an initial response that is even stronger
than during wakefulness, this response remains
localized, does not propagate to connected
Fig. 3. Spatiotemporal dynamics of scalp voltages and cortical currents evoked by TMS during
wakefulness and sleep. (A and A¶¶¶¶¶¶¶ ) Averaged TMS-evoked potentials recorded at all electrodes,
superimposed in a butterfly diagram (black traces; the horizontal red line indicates the average
reference), for the same subject as in Figs. 1 and 2. The time of TMS is marked by a vertical red bar.
The red portions of the traces indicate the times at which TMS induced a significant response (see
supporting online material for calculation details). Source modeling was performed at the local maxima
of field power within periods of significant activity. (B and B¶¶¶¶¶¶¶ ) Three-dimensional contour voltage maps
(red, positive; blue, negative; step 0 0.6 mVforwakefulnessand1mVforNREMsleep).(C and C¶¶¶¶¶¶¶ )
Corresponding current density distributions plotted on the cortical surface. At each time point, the
results of the L2 Norm (see methods) were auto-scaled and thresholded at 80% to highlight maximum
current sources (CDR, current density reconstruction).
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30 SEPTEMBER 2005 VOL 309 SCIENCE www.sciencemag.org
2230
brain regions, dissipates rapidly, lacks high-
frequency components, and is stereotypical
regardless of stimulation site.
Various mechanisms could account for the
enhancement of early TMS-EEG responses in
sleep, including a stronger driving force in
hyperpolarized postsynaptic neurons (14), an
increased discharge synchrony of cortical pop-
ulations (15), a reduction in synaptic depression
(16, 17), and thalamic bursting triggered by
the TMS-induced corticothalamic volley (18).
These mechanisms may also produce the en-
hancement of cortical components of visual,
auditory, and somatosensory evoked potentials
that has been reported during NREM sleep (6).
What causes the dramatic breakdown in
cortical effective connectivity during sleep?
During NREM sleep, cortical neurons are de-
polarized and fire tonically just as in quiet
wakefulness, but these depolarized up-states
are interrupted by short hyperpolarized down-
states when neurons remain silent (19). The
transition from up- to down-states appears to
be due to depolarization-dependent potassium
currents that increase with the amount of prior
activation (19). Perhaps because of this bi-
stability of cortical networks during NREM
sleep (16, 17), any local activation, whether
occurring spontaneously or induced by TMS,
will eventually trigger a local down-state that
prevents further propagation of activity. Al-
ternatively, the block may occur in the thal-
amus, whose neurons, when hyperpolarized,
fire a single burst in response to corticotha-
lamic volleys and then enter a prolonged in-
hibitory rebound (20). Finally, there may be
sleep-related changes in the balance between
excitation and inhibition (21), as suggested by
paired-pulse TMS studies (22).
Whatever the precise mechanisms, they are
most likely engaged by the progressive reduc-
tion of the firing of diffuse neuromodulatory
systems that occurs when we fall asleep (23).
Indeed, the blockade of intracortical signaling
did not begin suddenly, and the spatiotemporal
pattern of cortical activation during stage 1
sleep was intermediate between those of wake-
fulness and NREM sleep (fig. S3). Specifically,
during stage 1 sleep, the TMS-evoked response
propagated from the right premotor cortex to
the homotopic contralateral site within the first
few tens of milliseconds; however, this initial
activation was not sustained nor did it reach
prefrontal or parietal areas.
By using a combination of TMS and HD-
EEG, we have found evidence for a breakdown
of transcallosal and long-range effective con-
nectivity during NREM sleep. This breakdown
in the ability of cortical areas to interact ef-
fectively contrasts with the persistence or in-
crease in interhemispheric and interareal
broadband coherence that can be observed in
EEG studies of sleep (3, 24). Thus, an impair-
ment in the ability to integrate information
among specialized thalamocortical modules—a
proposed theoretical requirement for conscious-
ness (7)—may underlie the fading of con-
sciousness in NREM sleep early in the night.
It will be important to see whether cortical
effective connectivity recovers in part during
late-night sleep, especially during REM sleep, a
time at which conscious reports become long
and vivid (1). More generally, probing the
brain_s effective connectivity directly may
prove useful in pharmacologically induced un-
consciousness and in several psychiatric and
neurological conditions in which consciousness
is affected and neural interactivity may be com-
promised above and beyond neural activity and
neural synchrony (25).
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Fig. 4. Spatiotemporal
cortical current maps
during wakefulness
and NREM sleep in all
six subjects. Black
traces represent the
global mean field pow-
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yellow lines indicate
significance levels.
For each significant
time sample, max-
imum current sources
were plotted and color-
coded according to
their latency of activa-
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red, 300 ms). The yel-
low cross marks the
TMS target on the
cortical surface.
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Supporting Online Material
www.sciencemag.org/cgi/content/full/309/5744/2228/
DC1
Materials and Methods
Figs. S1 to S3
References and Notes
11 July 2005; accepted 29 August 2005
10.1126/science.1117256
IP
3
Receptor Types 2 and 3
Mediate Exocrine Secretion
Underlying Energy Metabolism
Akira Futatsugi,
1,2
*
Takeshi Nakamura,
1,3
Maki K. Yamada,
3
Etsuko Ebisui,
1,2
Kyoko Nakamura,
1,3
Keiko Uchida,
3
Tetsuya Kitaguchi,
2
Hiromi Takahashi-Iwanaga,
4
Tetsuo Noda,
5
Jun Aruga,
2
Katsuhiko Mikoshiba
1,2,3
*
Type 2 and type 3 inositol 1,4,5-trisphosphate receptors (IP
3
R2 and IP
3
R3) are
intracellular calcium-release channels whose physiological roles are unknown.
We show exocrine dysfunction in IP
3
R2 and IP
3
R3 double knock-out mice, which
caused difficulties in nutrient digestion. Severely impaired calcium signaling in
acinar cells of the salivary glands and the pancreas in the double mutants
ascribed the secretion deficits to a lack of intracellular calcium release. Despite a
normal caloric intake, the double mutants were hypoglycemic and lean. These
results reveal IP
3
R2 and IP
3
R3 as key molecules in exocrine physiology
underlying energy metabolism and animal growth.
Inositol 1,4,5-trisphosphate receptors (IP
3
Rs)
are intracellular Ca
2þ
release channels located
on the endoplasmic reticulum (ER) that
mediate Ca
2þ
mobilization from the ER to
the cytoplasm in response to the binding of a
second messenger, inositol 1,4,5-trisphosphate
(IP
3
)(1). IP
3
-induced Ca
2þ
release is triggered
by various external stimuli, and most non-
excitable cells use this mechanism as the
primary Ca
2þ
signaling pathway. IP
3
Rs are
therefore thought to have important physiolog-
ical roles in various cell types and tissues (2).
Three subtypes of IP
3
Rs, derived from three
distinct genes, have been identified in mam-
mals (3). Type 1 IP
3
R(IP
3
R1) is predominant-
ly expressed in brain tissue and plays a critical
role in the regulation of motor and learning
systems (4–7 ). The other two subtypes, type 2
and 3 IP
3
Rs (IP
3
R2 and IP
3
R3), are expressed
in various tissues and cell lines (8–11); how-
ever, the importance of these subtypes in vivo
has been difficult to assess because of their co-
expression in tissues and the lack of selective
inhibitors. In this study, we examined mice
lacking both IP
3
R2 and IP
3
R3 and observed
defects in the digestive system resulting from
the lack of Ca
2þ
signaling in exocrine tissues.
In such exocrine tissues, secretagogue-induced
increases in intracellular Ca
2þ
concentra-
tion (ECa
2þ
^
i
) trigger the secretion of enzymes
or water by acting on the Ca
2þ
-dependent
exocytotic machinery or ion channels, respec-
tively (12–16 ). A crucial physiological role of
IP
3
Rs in exocrine Ca
2þ
signaling was demon-
strated (15, 17 ); however, the relative impor-
tance of the three different IP
3
R subtypes has
been unclear.
We generated mice lacking either IP
3
R2 or
IP
3
R3 by disrupting the corresponding genes
within their first coding exons (figs. S1A and
S1B). The single-gene mutants were viable
and showed no distinct abnormalities in ap-
pearance, at least for several months after
birth. Mutant mice lacking both of these IP
3
R
subtypes were also viable during the embry-
onic period. Immunoblot analysis of the sub-
mandibular glands and the pancreas, where
IP
3
R2 and IP
3
R3 are expressed (fig. S1C),
showed that expression of IP
3
R2 and IP
3
R3
was abolished in the mutants (Fig. 1A). At
birth, the appearance of double homozygotes
was indistinguishable from that of nonhomo-
zygous littermates, but double homozygotes
had gained less body weight after birth. After
the weaning period, around postnatal day 20
(P20), the homozygotes began losing weight
anddiedwithinthe4thweekofage(Fig.1B).
We suspected that an incapability of the
double mutants to eat dry food after weaning
might have caused body weight loss and even-
tual death. Indeed, double mutants did not
consume dry food at all. When the double
mutants were fed wet mash food beginning at
P20, they consumed this type of food and
survived thereafter. Body weight increases of
the double mutants, however, were still smaller
than those of nondouble mutant littermates
equally fed with wet mash food (Fig. 1C).
Interestingly, despite their reduced body
weights, the double mutants consumed no less
wet mash food than did the control mice (Fig.
2A and fig. S2A). The double mutants also
took as much milk as did control mice when
they were fed milk instead of wet mash food
after weaning (fig. S2B). Thus, the caloric
intake of the IP
3
R2
j/j
-IP
3
R3
j/j
double
mutants appeared to be slightly greater than
that of the control mice. In addition, the
amount of feces produced by adult mice fed
wet mash food was higher in the double
mutants (Fig. 2B). The total amount of proteins
and lipids in the feces were higher in the
double mutants (Fig. 2C and fig. S2C).
Furthermore, blood glucose concentrations
were significantly lower in the double mutants
(86.1 T 5.3 mg/dl, n 0 11) than those in control
mice (156.1 T 6.5 mg/dl, n 0 14). Altogether,
these results suggest that digestive system
dysfunction causes the malnutrition phenotype
of the double mutants. Actually, when the
double mutants were fed a predigested diet
containing glucose and amino acids for a
week, they gained weight (1.7 T 0.7 g, n 0
8), whereas those fed wet mash food did not
(–0.5 T 0.3 g, n 0 5).
Because the lethal double mutant pheno-
type was partially rescued by macerating the
food with water, we hypothesized that the
double mutants might be deficient in saliva
production. We therefore examined saliva secre-
tion in adult mice stimulated by subcutaneous
1
Calcium Oscillation, International Cooperative Re-
search Project, Japan Science and Technology Agency,
Tokyo 108-0071, Japan.
2
Laboratory for Developmental
Neurobiology, Brain Development Research Group,
Brain Science Institute, RIKEN, Saitama 351-0198,
Japan.
3
Division of Molecular Neurobiology, Institute
of Medical Science, University of Tokyo, Tokyo 108-
8639, Japan.
4
Department of Anatomy, School of
Medicine, Hokkaido University, Sapporo 060-8638,
Japan.
5
Department of Cell Biology, Japanese Founda-
tion for Cancer Research, Cancer Institute, Tokyo 170-
8455, Japan.
*To whom correspondence should be addressed.
E-mail: afutatsu@brain.riken.jp (A.F.); mikosiba@
ims.u-tokyo.ac.jp (K.M.)
R EPORTS
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