Block, G.D.

Daniel, J.

Davidson, A.J.

Menaker, M.

Sellix, M.T.

Yamazaki, S.

PubMed

Elsevier - Publisher Connector 

Current Biology Vol 16 No 21
R914
already extensive evidence from 
fMRI and architectonic studies 
that the human brain contains 
many more cortical areas (possibly 
150 or more) than the brains of 
macaque monkeys. One would 
also expect areas to be more 
frequently subdivided into sets of 
modules or columns of functionally 
related neurons, such as the 
three types of bands of neurons 
subdividing the second visual area, 
V2, of primates, but there is only 
limited evidence for this. However, 
the premise that hemispheric 
asymmetries increase with 
brain size in order to reduce the 
need for costly interhemispheric 
communication is well supported 
by the extensive evidence for 
hemispheric specializations 
in the human brain related to 
handedness, language, attention, 
memory and object recognition.
In conclusion, an outline of the 
course of the evolution of the 
human brain is starting to emerge. 
Great progress in the gathering 
of relevant data has occurred 
over the last 20–30 years. A more 
complete description could easily 
occupy a series of volumes, and 
interested readers are invited to 
read further. Most importantly, 
there is much yet to be gained 
by applying current methods 
of investigation so that future 
reviews can be better informed 
and greatly enriched.
Further reading
Finlay, B.L., Darlington, R.B., and Nicastro, N. 
(2001). Developmental structure in brain 
evolution. Behav. Brain Sci. 24, 263–308.
Kaas, J.H. (2000). Why is brain size so 
important: Design problems and solutions
as neocortex gets bigger or smaller. Brain 
and Mind 1, 7–23.
J.H. Kaas, ed. (2006). Evolution of Nervous 
Systems. 4 volumes. (London: Elsevier).
Kaas, J.H. and Preuss, T.M. (2003). Human 
Brain Evolution. In Fundamental 
Neuroscience, Second Edition, L.R. 
Squire, ed. Elsevier, pp. 1147–1166.
Kielan-Jaworowska, Z., Cifelli, R.L., and Luo, 
Z.X. (2004). Mammals from the Age of 
Dinosaurs. Columbia University Press.
M.J. Ravosa and M. Dagosto, eds. 
(2006). Primate Origins: Evolution and 
Adaptations. Springer.
Striedter, G.F. (2005). Principles of Brain 
Evolution. Sinauer.
Wood, B. (2005). Human Evolution: A Very 
Short Introduction. Oxford University 
Press.
Department of Psychology, Vanderbilt 
University, 301 Wilson Hall, 111 21st 
Ave. South, Nashville, TN 37203, USA. 
E-mail: jon.h.kaas@vanderbilt.edu 
Correspondences
Chronic jet- lag 
increases 
mortality in aged 
mice
A.J. Davidson, M.T. Sellix, 
J. Daniel, S. Yamazaki, 
M. Menaker and G.D. Block
Despite the fact that 
trans- meridian travel and shift 
work are commonplace in our 
24/7 society, few controlled 
studies have addressed the 
health effects of repeated 
phase shifts of the biological 
clock. Shift work [1] and chronic 
jet- lag [2] reduce mental acuity 
and increase the risk of a 
number of medical problems, 
including cancer, peptic ulcers 
and sleep disorders. Some 
of these problems become 
more severe with the number 
of years on the job, the result 
either of cumulative damage 
or the increased age of the 
subjects [3]. In general, morbidity 
associated with many organic 
disorders is increased in the 
aged; however, the role played 
by age-associated alterations 
in the circadian clock is poorly 
understood. In particular the 
effect of repeated schedule 
changes is largely unaddressed. 
Here we report evidence that 
chronic jeg-lag increases 
mortality rates in aged mice.
We were led to the current 
experiment by an observation 
in an unrelated study where we 
found that three of eight aged 
transgenic rats exposed to a 6 
hour advance of the light cycle 
died following the light schedule 
change. In contrast, no deaths 
were observed if the light cycle 
was delayed. In order to explore 
whether the effects of light 
schedule changes on longevity 
were reproducible in a larger 
study and observable in another 
rodent species, we placed young 
(8–12 month old) and aged (27–31 
month old) C57BL/6 male mice 
on one of three lighting regimens for eight weeks. Nine young and 
30 aged mice were maintained 
on a normal 12:12 light–dark 
cycle. A second group of young 
(n = 9) and old (n = 30) mice was 
exposed to a 6 hour advance of 
the light-cycle once every seven 
days. The third group of young 
(n = 9) and old (n = 28) mice was 
phase- delayed by 6 hours once 
every 7 days. The rotating light 
schedules were chosen to effect 
large phase adjustments of the 
circadian system each week, 
such as would be expected to 
occur during flight across time 
zones or in some situations 
during rotating shift work cycles.
While younger mice fared well 
on this 8 week schedule (only 
one death occurred), we found 
that aged mice were significantly 
affected by light schedule 
changes (Figure 1A,B). At the 
end of the 8 week period of light 
schedule rotations there was 
47% survival in animals whose 
light cycle was advanced each 
week, 68% in those experiencing 
delays of the light cycle and 
83% in unshifted aged mice (chi 
square, all groups, p< 0.05 on 
Day 54). Importantly, chronic 
stress was not implicated in 
this phenomenon as total daily 
fecal corticosterone levels 
did not increase in aged mice 
undergoing phase advances or 
phase delays (see Figure S1 in 
the Supplemental data published 
with this article online). 
To determine whether the 
effects of phase advances on 
mortality might be related to 
the duration between schedule 
changes, mice were shifted 
more rapidly, every 4 days. On 
this schedule, we found that 
advancers died more quickly 
than with weekly shifts (Figure 
1C; 60% survival on Day 24). 
Delayers fared much better than 
advancers (chi square p < 0.05 
on Day 32). The data suggest 
that the asymmetry in mortality 
rates between animals exposed 
to light schedule advances and 
delays persists and is possibly 
enhanced with the shorter 
inter- shift interval of 4 days. 
Our data show that 
phase- advancing the light cycle 
hastens the death of aged mice. 
The mechanism underlying the 
Magazine
R915deleterious effects of phase 
advances of the light cycle is 
unclear. It appears that the 
mechanism is not stress-related. 
Other possibilities include sleep 
deprivation and disruption of 
the immune system. There 
is significant complexity in 
the resetting behavior of the 
mammalian timing system to 
phase advances in the light 
schedule [4] that might play a 
role in the increased mortality 
that we observed. 
In future experiments it 
will be important to explore 
how the length of the interval 
between shifts affects longevity 
and whether there is reduced 
longevity in animals that 
experience light cycle changes 
when younger.
Non-standard lighting cycles 
have repeatedly been shown to 
hasten death in animals. Fruit 
flies [5] and blowflies [6] have 
shorter lifespans when housed 
in L:D cycles with a period 
shorter than 21 hours or longer 
than 27 hours. Cardiomyopathic 
hamsters exhibited a median 
life expectancy that was 11.3% 
shorter if they were housed on a 
light schedule that was inverted 
once per week compared with a 
stationary 14:10 L:D cycle [7]. 
However, the same shifting 
schedule did not affect lifespan 
in CD2F1 mice [8]. A 6 hour 
phase- shift in the light cycle every 
two days increased the growth 
rate of Glasgow osteosarcoma in 
mice [9]. We believe that ours is 
the first study providing evidence 
that differential mortality based 
on the direction of the shift in the 
light schedule.
Endogenous circadian 
oscillations have been detected 
in nearly all mammalian tissues. 
Our results lead us to speculate 
that the internal desynchrony 
among these functional 
oscillations that accompanies 
readjustment to an advanced 
light schedule may have serious 
health consequences that are 
exacerbated in the aged. 
There is evidence that the 
circadian system of aged animals 
is altered in significant ways 
[10]. These age-related circadian 
changes may have an adverse 
effect on health during phase 0 1 2 3 4 5 6 7 8
0
7
14
21
40
60
80
100
0 4 8 12 16 20 24 28 32
40
60
80
100
B
C
Weeks/shifts
0 1 2 3 4 5 6 7 8
Weeks/shifts
 Control
 Advance
 Delay
A
Su
rv
iva
l (%
)
M
or
ta
lit
y 
(%
 / w
ee
k)
Su
rv
iva
l (%
)
Experimental days
Current Biology
Figure 1. Survival of aged mice undergoing weekly phase shifts of the light cycle.
(A) Survival curves of aged mice undergoing a weekly 6 hour advance or delay adjust-
ment of the light cycle, compared with unshifted aged controls. On Day 56 survival was 
47% in advancers, 68% in delayers, and 83% in unshifted aged mice (group sizes are 
n = 30 for controls and advancers and n = 28 for delayers). The distribution of surviv-
ing mice at the end of Week 4 (p < 0.05), Week 5 (p < 0.025), Week 6 (p < 0.01), Week 7 
(p < 0.01) and Week 8 (p < 0.05) of the protocol is significantly different than chance (chi 
square). Advancers died faster than controls (pairwise Chi square; p < 0.01, Day 54) but 
were only different from delayers at the ends of Weeks 6 (p < 0.01) and 7 (p < 0.025). 
(B) Death rate per week of the protocol. % mortality of remaining mice is plotted for 
each week in bold. Trend-lines (three-point moving average) for each dataset are shown 
with dotted lines of the same color. Advancers began dying sooner (all 3 groups chi-
square; Weeks 3–4, p < 0.025; Weeks 5–6 p <0.05) and the death rate remained higher 
than the other groups until the final week of the protocol. The death rate in unshifted 
animals was flat for the duration of the experiment. (C) Survival curves for mice shifted 
every 4 days. We found that advancers still died at a faster rate (p < 0.05 on Day 32; 
group sizes: 13 advancers, 12 delayers).advances. Alternatively, the 
general frailty of older animals 
rather than age-related changes 
in the circadian system may 
make them less able to tolerate changes in the light schedule. 
Whatever the precise mechanism, 
the dramatic differences in 
morbidity associated with phase 
advances of the biological clock 
Current Biology Vol 16 No 21
R916
The importance 
of procedural 
knowledge 
in desert-ant 
navigation 
Markus Knaden1,2, Christina 
Lange1 and Rüdiger Wehner1
Path integration enables a 
foraging animal to keep a 
continuously updated estimate 
of its direction and distance from 
some reference point — the nest 
or a frequently visited feeding 
site — and hence provide it with 
a global vector pointing from the 
animal’s current position to this 
reference point [1–5]. This global 
vector is retrieved and used 
when the animal later returns to 
the starting point. Even though 
path integration is the dominant 
mechanism in desert-ant 
navigation, the animals have been 
shown to use landmark-based 
routes as well. When following 
learned sequences of landmarks, 
the ants are guided by directional 
information gained from one 
landmark to the visual catchment 
area of the next landmark [6–9]. 
Here we report evidence that the 
procedural knowledge involved 
in route learning can dominate 
the path integrator to such an 
extent that the ants can even 
select the opposite direction 
to that represented by their 
path- integration global vector.
We trained desert ants, 
Cataglyphis fortis, within a 
two- leg, U-turn channel array and 
thus forced them to accomplish a 
180° turn when running back and 
forth between nesting and feeding 
sites. Subsequently the ants, 
after they arrived at the feeder, 
were displaced into a linear test 
channel in which their homebound 
courses were recorded (for 
a detailed description of the 
methods see the Supplemental 
data available online). 
In the first experiment, the 
ants were trained within linear 
channels first to run from the 
feeder for 6 m to the north, then to 
turn by 180°, and then to run for 
another 3 m to the south until they 
reached the nest (6U3 training 
paradigm; Figure 1). After training 
was completed, the ants were 
transferred to a linear test channel 
oriented in the same north–south 
direction. Control ants were 
trained along a linear path with 
the feeder 3 m to the north of the 
nest. After their release into the 
test channel the experimental 
ants (n = 30) ran much further 
in the northward direction than 
the control ants (n = 30) before 
they performed their first turn 
(Figure 1A, p < 0.0001). This result 
means that the 6U3 ants overshot 
the nest- to-feeder distance and 
headed for the U-turn as their first 
target. 
In a second experiment, the 
ants were trained in a reversed, 
more demanding setting (3U6; 
Figure 1); the inbound ants now 
had to decide whether they 
should head for the U-turn or 
whether they should head for the 
nest now lying in the opposite 
direction of the U-turn. Only six of 
the 30 experimental ants directly 
ran off their home vector (as all 
control ants did); the remaining 
80% of the experimental ants 
first headed for the fictive 
U-turn (Figure 1A; difference 
between control and test group, 
p < 0.0001). This clear-cut result 
again shows that even in the 
difficult 3U6 task the ants had 
acquired and used remarkable 
knowledge about their two-leg 
training path.
It is well known that C. fortis 
[6], as well as other species 
of ants [7–9], can attach local 
vectors to particular landmarks 
encountered en route. In 
an intriguing experiment, 
channel- bound flying honey bees 
were also shown to use local 
vectors attached to on-route 
visual signposts [10]. In our work, 
we tried to reduce the influence 
of landmarks by using linear 
channels. Hence, the landmark 
situation at the feeder, at the nest 
and in fact during the entire run 
was almost the same. The only 
visual irregularities were the food 
crumbs at the feeder position 
and an inconspicuous opening 
between the two channels at the 
U-turn. Both cues, of course, 
were missing in the test channel. raise important issues about 
the safety of counter- clockwise 
rotating shift work and the 
potential long-term health 
consequences for airline crews 
regularly crossing time zones.
Acknowledgments
The authors wish to thank Denise 
Holmes and Naomi Ihara for technical 
assistance and Debbie Roach for her 
helpful comments on the manuscript. 
This work was supported by NIA grant 
F32 AG22741-01 to A.J.D., NINDS 
grant RO1 NS051278 to S.Y., NSBRI 
grant NCC9-58-167 and NIMH grant 
RO1 MH56647 to M.M., and NIMH 
grant RO1 MH062517 to G.D.B.
Supplemental data
Supplemental data including  
experimental procedures are available 
at http://www.current-biology.com/cgi/
content/full/16/21/R914/DC1
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Department of Biology, University 
of Virginia, Charlottesville, Virginia 
22904-4328, USA.  
E-mail: gdb@virginia.edu


Chronic jet-lag increases mortality in aged mice 

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Chronic jet-lag increases mortality in aged mice

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