J. Sleep Res. (2000) 9, 335±352
Neural basis of alertness and cognitive performance impairments
during sleepiness. I. Eects of 24 h of sleep deprivation on
waking human regional brain activity
MARIA THOMAS1, HELEN SING1, GREGORY BELENKY1,
HENRY HOLCOMB2, HELEN MAYBERG3, ROBERT DANNALS4,
HENRY WAGNER, JR.4, DAVID THORNE1, KATHRYN POPP1,
L A U R A R O W L A N D 1 , A M Y W E L S H 1 , S H A R O N B A L W I N S K I 1 and
DANIEL REDMOND1
1
Division of Neuropsychiatry, Walter Reed Army Institute of Research, Silver Spring, MD, USA, 2Maryland Psychiatric Research Center,
Department of Psychiatry, University of Maryland, and Department of Radiology, School of Medicine, Johns Hopkins Medical Institutions,
Baltimore, MD, USA, 3Rotman Research Institute and the University of Toronto, Toronto, Ontario, Canada, 4Department of Environmental
Health Sciences, School of Hygiene and Public Health, Johns Hopkins Medical Institutions, Baltimore, MD, USA
Accepted in revised form 27 June 2000; received 23 November 1999
SUMMARY
The negative eects of sleep deprivation on alertness and cognitive performance suggest
decreases in brain activity and function, primarily in the thalamus, a subcortical
structure involved in alertness and attention, and in the prefrontal cortex, a region
subserving alertness, attention, and higher-order cognitive processes. To test this
hypothesis, 17 normal subjects were scanned for quanti®able brain activity changes
during 85 h of sleep deprivation using positron emission tomography (PET) and
18
Fluorine-2-deoxyglucose (18FDG), a marker for regional cerebral metabolic rate for
glucose (CMRglu) and neuronal synaptic activity. Subjects were scanned prior to and at
24-h intervals during the sleep deprivation period, for a total of four scans per subject.
During each 30 min 18FDG uptake, subjects performed a sleep deprivation-sensitive
Serial Addition/Subtraction task. Polysomnographic monitoring con®rmed that
subjects were awake. Twenty-four hours of sleep deprivation, reported here, resulted
in a signi®cant decrease in global CMRglu, and signi®cant decreases in absolute
regional CMRglu in several cortical and subcortical structures. No areas of the brain
evidenced a signi®cant increase in absolute regional CMRglu. Signi®cant decreases in
relative regional CMRglu, re¯ecting regional brain reductions greater than the global
decrease, occurred predominantly in the thalamus and prefrontal and posterior parietal
cortices. Alertness and cognitive performance declined in association with these brain
deactivations. This study provides evidence that short-term sleep deprivation produces
global decreases in brain activity, with larger reductions in activity in the distributed
cortico-thalamic network mediating attention and higher-order cognitive processes, and
is complementary to studies demonstrating deactivation of these cortical regions during
NREM and REM sleep.
KEYWORDS
alertness, cognitive performance, prefrontal cortex, regional brain
activity, sleep deprivation, thalamus
Correspondence: Maria L. Thomas, Ph.D., Department of Biomedical
Assessment, Division of Neuropsychiatry (ATTN: MCMR-UWI-C),
Walter Reed Army Institute of Research, 503 Robert Grant Avenue,
Room 2W88, Silver Spring, MD 20910±7500, USA, Tel.: 1 301 319
9146; fax: 1 301 3199979; e-mail: maria.thomas@na.amedd.army.mil
Ó 2000 US Government
INTRODUCTION
Lack of adequate sleep, or sleep deprivation, reduces workplace productivity, public safety, and personal well being
(Dement and Vaughan 1999). Sleep deprivation is one cause of
335
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M. L. Thomas et al.
accidents and catastrophic failures in real-world situations
(Mitler et al. 1988), including military friendly ®re incidents
1 (Belenky et al. 1994) and vehicular accidents (Horne and
Reyner 1995). Short periods of total sleep deprivation (i.e.
24 h) typically occur in instances where individuals or groups
undergo extended wakefulness to meet deadlines. Longer
periods of sleep deprivation (i.e. greater than 40 h) can occur
during atypical sustained work conditions (Kroemer et al.
1990), such as in some military training exercises and combat
operation missions (Haslam 1982; Krueger 1991; Belenky et al.
2 1994) and civilian emergency work situations (Krueger 1989).
Substantial sleep deprivation can also occur in individuals
suering from sleep disorders (Kelly 1991), in those with
suspected neurologic dysfunction (Williams et al. 1996), and in
the elderly (Reynolds et al. 1987).
Two cardinal features of sleep deprivation are diminished
alertness and cognitive performance. These neurobehavioral
de®cits are well established, beginning with the ®rst published
study of long-term human sleep deprivation over 100 years ago
(Patrick and Gilbert 1896). Reduced alertness has been shown
in short- as well as long-term sleep deprivation studies using
objective and/or subjective measures of sleepiness (e.g. Carskadon and Dement 1979; Mikulincer et al. 1989; Newhouse
et al. 1989; Penetar et al. 1993; Harma et al. 1998). Decrements
in cognitive performance, often independent of loss of alertness
or lapses in attention, are also produced by both short- and
long-term sleep deprivation. Simple task performance is
impaired, as re¯ected by tests of reaction time, vigilance, and
attention (e.g. Horne 1988a; Dinges and Kribbs 1991; Koslowsky and Babko 1992; Gillberg and Akerstedt 1998). Similarly,
complex task performance is impaired, as re¯ected by tests of
working memory, verbal ¯uency and speech articulation,
language, logical reasoning, creative and ¯exible thinking and
planning, decision making, and judgment (e.g. Banderet et al.
1981; Horne 1988a; Newhouse et al. 1989; Harrison and Horne
1997, 1998, 1999). Performance de®cits can occur as early as
during the ®rst night without sleep (Angus and Heslegrave
1985; Monk and Carrier 1997) and are ampli®ed after two-tothree nights without sleep (e.g. Horne and Pettit 1985;
Koslowsky and Babko 1992; How et al. 1994).
The degrading eects of sleep deprivation on alertness and
cognitive performance suggest alterations in underlying brain
physiology and function. To date, however, only a few studies
have investigated in vivo brain activity changes mediating sleep
deprivation-induced neurobehavioral impairment in normal
volunteers. In the ®rst study, Wu et al. (1991) quanti®ed
absolute changes in regional cerebral glucose metabolic rate
(CMRglu), a marker for neuronal activity, using 18Fluorine2-deoxyglucose (18FDG) (Reivich et al. 1979) and positron
emission tomography (PET) (Cherry and Phelps 1996) during a
Continuous Performance Test, a visual vigilance task. At 32 h
of sleep deprivation, signi®cant decreases in absolute regional
CMRglu were found in thalamus and cerebellum along with
signi®cant decreases in relative regional CMRglu (absolute
regional CMRglu normalized to the whole brain) in these same
regions and temporal cortex. These brain deactivations were
accompanied by a concomitant decrease in task performance.
In another study, Drummond et al. (1999a, 2000) evaluated
alterations in the cerebral hemodynamic response using bloodoxygen-level-dependent functional magnetic resonance imaging (BOLD-fMRI) during both a Serial Subtraction task and a
Verbal Learning task. The Serial Subtraction task, a variant of
3 the Serial Addition/Subtraction task (Thorne et al. 1985),
involved attention, working memory, and arithmetic subtraction, while the Verbal Learning task involved recognition and
recall. Statistical comparisons between normal wakefulness and
35 h of sleep deprivation revealed decreased BOLD responses,
associated with impaired arithmetic performance, in the
prefrontal anterior cingulate gyrus, lateral posterior parietal
lobules, pulvinar thalamus, and visual cortices (Drummond
et al. 1999a). With impaired verbal recall performance (Drummond et al. 2000), decreased BOLD responses were found in
the prefrontal anterior cingulate and temporal lobes, and
increased BOLD responses were noted in both the prefrontal
and lateral posterior parietal regions.
Although the Wu et al. (1991) study provided the ®rst
quantitative assessment of absolute human brain activity
changes and cognitive function during extended wakefulness,
longer periods of sleep deprivation beyond 32 h, i.e. the eects
of more than one night of sleep deprivation, were not
evaluated. Moreover, the regions of interest analysis used
(e.g. single activity measure over an entire cortical lobe) was
not as sensitive as the more recent voxel-based method of
analysis (e.g. statistical parametric mapping [SPM]; Friston
et al. 1995a,b). This latter analysis allows assessment of
multiple, smaller functional areas of cortex. Either of these
factors may have minimized other signi®cant regional eects of
sleep deprivation.
The Drummond et al. (1999a, 2000) sleep deprivation
®ndings were based on the BOLD-fMRI technique that
evaluates the hemodynamic response to neuronal activation
using high spatial resolution scanning. Because the technique
does not utilize radiotracers and long scanning periods, several
tasks can be evaluated in an experimental session. While a
sensitive indicator of relative cerebral activation, the BOLD
signal as currently applied is not a quanti®able measure of
neural activity (Howseman and Bowtell 1999). Relative
changes in the regional hemodynamic response are obtained
by comparing the BOLD signal during the task of interest to
the BOLD signal during a baseline or control task (Ogawa
et al. 1998). The ability to quantify absolute brain activity in
investigations of sleep deprivation may be important, however,
when global activity is aected, as changes based on relative
brain activity alone cannot characterize with certainty the
magnitude or the direction of changes in regional brain activity
response. On the other hand, when absolute quanti®cation of
brain activity has been accomplished and a whole brain or
global change has occurred, the normalization procedure (e.g.
transforming the data to z scores or ratios, or removing the
global eect with analysis of covariance [ANCOVA]), can
exclude some regions in terms of statistical signi®cance.
Also, other regions may appear activated or deactivated,
Ó 2000 US Government, J. Sleep Res., 9, 335±352
Neural basis of short-term sleep deprivation
depending on the direction of the global change, when in
fact a real change has not occurred (see Braun et al. 1997
and Kajimura et al. 1999 for related discussions). These
aspects of brain imaging data acquisition and analysis ± lack
of absolute quanti®cation and the statistical analysis of
normalized (i.e. relative) values without concomitant analysis of absolute values ± may obscure the extent and/or
interpretation of regional brain activity changes.
In the present study, we quanti®ed absolute regional
CMRglu with 18FDG and PET four times each in 17 normal
volunteers during 85 h of sleep deprivation and utilized the
SPM method for analysis of the absolute and relative
neuroimaging data. During the four-day experimental phase,
subjects were scanned after a night of normal sleep and then
serially after 24, 48, and 72 h without sleep. During each
18
FDG uptake, and at 2-h intervals between PET scans
(Fig. 1), subjects performed a computer-based Serial Addition/
Subtraction task (Thorne et al. 1985). As shown in Fig. 1 and
by other sleep deprivation studies (e.g. Thorne et al. 1983;
Newhouse et al. 1989; Penetar et al. 1994; Drummond et al.
1999a), Serial Addition/Subtraction is sensitive to the eects of
sleep deprivation, even when performed for short durations.
This task is more complex than tests of simple reaction time or
vigilance and involves not only sustained attention, but also
working memory and arithmetic processing. All of these
mental processes have been attributed, in large part, to the
prefrontal cortex (e.g. Cohen et al. 1988; Coull et al. 1996,
1998; Dolan et al. 1997; Roland and Friberg 1985; Dahaene
et al. 1996; Dehaene et al. 1999).
The main purpose of our experiment was to quantify and
characterize global and regional brain activity changes implicated in sleep deprivation-induced neurobehavioral impairment during cumulative, extended sleep loss. We endeavored
to model real-world sustained operations requiring wakeful-
337
ness and near continuous task performance across four
consecutive days. Based on previous behavioral research, we
expected `dose-dependent' decreases in alertness and cognitive
performance with cumulative sleep deprivation. We hypothesized that sleep deprivation would result in dose-dependent
deactivation of the thalamus, a subcortical structure involved
in alertness and attention (Mesulam 1985). Additionally, we
hypothesized that sleep deprivation would produce dosedependent deactivation of the prefrontal cortex, a region that
subserves higher order cognitive processes (Fuster 1989; Frith
and Dolan 1996) along with alertness and attention (Posner
and Tudela 1997). Prefrontal cortical vulnerability to sleep
deprivation has been suggested previously by Horne (1988b,
1993). We extended our prefrontal cortical deactivation
hypothesis during sleep deprivation to include the anterior
cingulate gyrus because of its participation in attentional
processes (Vogt et al. 1992).
This is the ®rst of a series of reports examining progressive
changes in regional CMRglu with increasing sleep deprivation.
We describe here the results of 24 h of sleep deprivation
compared to rested baseline. These results have been published
previously in preliminary form (Thomas et al. 1998a,b).
METHOD
Subjects
The 17 volunteers participating in the study were right-handed
civilian males, between the ages of 21±29 years (mean 24.7
2.8 years), with no history of medical, neurological, psychiatric,
or sleep disorder conditions. Their histories also included 7±8 h
of nightly sleep on a regular basis, no nicotine use, and low
caeine use (less than 100 mg/day). Subjects passed a physical
examination, including CBC and electrocardiography (EKG)
tests and a narcotics screening test. Subjects were within normal
range on mental states exams (Beck Depression Inventory, Beck
et al. 1961; and Leeds Anxiety-Depression Scales, Snaith et al.
1976) and a cognitive test (WonderlicÒ Personnel Test,
Wonderlic, Inc., Libertyville, Illinois, USA).
Informed, written consent was obtained from all subjects.
Subjects were paid for their participation in the study.
Experimental design and methodological considerations
Figure 1. Graph of the cognitive performance decline, modulated by
the circadian rhythm, for the Serial Addition/Subtraction task during
the 85 h of sleep deprivation. Data points are associated with
performance measurements collected approximately every 2 h between
PET scans, where Serial Addition/Subtraction task duration was
2±3 min. Hatched arrows indicate temporal occurrence of long-term
sleep deprivation 18FDG-PET scans, which will be reported separately.
Ó 2000 US Government, J. Sleep Res., 9, 335±352
A time series design was used, with progressive sleep deprivation as the independent variable. Repeated measures of
absolute regional CMRglu, cognitive performance, alertness,
mood, and subjective experiences were collected after 0, 24, 48,
and 72 h of sleep deprivation. Additional measures of alertness, cognitive performance, and mood were collected at ®xed
intervals throughout the sleep deprivation period. These
measures were included to place the performance results
associated with the PET scans in the context of the circadian
rhythm of cognitive performance, as well as to impose a
moderate-to-heavy near continuous workload on the subjects
as might be anticipated in a real-world sustained operation.
338
M. L. Thomas et al.
Ideally, the evaluation of a rested control group of subjects,
for whom nightly sleep occurred for three days in place of sleep
deprivation, would have been helpful to account for potential
nonspeci®c eects on brain activity (e.g. regional CMRglu
eects that may be produced by task habituation, by dayto-day variability in regional brain activity, by unbalanced
order of scans, or by learning and/or task tedium eects).
Additionally, a sleep deprived control group, in which a
performance de®cit did not occur, may have been useful to
possibly delineate primary or ®rst-order eects of sleepiness on
regional brain activity; e.g. perhaps indicating just one or two
brain areas directly aected by sleepiness and therefore
responsible, via their connectivity, for remote areas of deactivation. Also of interest would have been the addition of a ®fth
PET scan at the end of the study to assess recovery sleep eects
on brain activity and task performance as well as to have
compared several tasks within the same study to address the
issue of task speci®city and regional brain activity response to
sleep deprivation.
In our four-consecutive day 18FDG-PET scanning study,
which included a pre-experiment day where subjects underwent a simulation PET scan, the addition of an extra PET scan
to assess recovery sleep eects on subsequent wakefulness and
the addition of a rested control group were precluded because
of cost and logistical constraints. Given this circumstance, the
comparison of the sleep deprivation scans to the baseline
rested scans was a reasonable alternative to using a rested
control group. For similar reasons, we were not able to include
a sleep deprived-control group where performance did not
vary. Even so, stable performance levels, in terms of both
accuracy and reaction times, would have been impractical to
accomplish out to 72 h of sleep deprivation, without either
changing the task itself (i.e. making it considerably easier) or
adding further ®nancial incentives. Implementing these
manipulations may not have proven successful, though, as in
a previous study where substantial monetary rewards were
given for maintaining performance at rested baseline values,
intact performance could not be achieved on a simple vigilance
test at 48±72 h of sleep deprivation (Horne and Pettitt 1985).
Consequently, we focused our investigation on the underlying
brain physiology of performance de®cit, rather than intact
performance, because we were most interested in delineating
the regional brain pattern associated with the behavioral
impairments. The use in our study of two additional days of
sleep deprivation was a viable approach to discerning brain
areas that might be more sensitive (i.e. show greater deactivation than other regions) to sleep deprivation. With respect to
the eect of the speci®c task and brain activity response to
sleep deprivation, a radiotracer with quanti®cation capability,
a very short half life, and low radiation exposure would have
been required to allow evaluation of absolute brain activity
responses during multiple task performances within a brief
time window. The tracer H15
2 O, which measures cerebral blood
¯ow (a correlate of cerebral glucose metabolism) and allows up
to 12 PET scans per subject, meets these criteria. However,
because of its short half life, quantifying absolute blood ¯ow
by the H15
2 O±PET method necessitates automatic arterial
sampling. Inserting an arterial line in the same subject in his
one available wrist on four contiguous days would have been
technically unfeasible in our study.
We did attempt within our experimental design to minimize
scan order and other nonspeci®c eects. Firstly, we included a
realistic simulation (except for injection of actual radioisotope)
of the 18FDG uptake and PET scan procedure prior to the ®rst
experimental PET scan. This was done to avoid possible
novelty, anxiety, or excitement eects due to the introduction
of the imaging procedure (Roland 1993) during the rested
baseline scan. Subjective measures of tension and calmness
showed that anxiety and excitement levels were not signi®cantly dierent between the rested baseline and 24 h sleep
deprivation scans (see Results). Secondly, we tested our
subjects during performance of the same complex cognitive
task in the four 18FDG uptake periods. It has been shown in
test-retest neuroimaging studies that the use of a standard task
(vs. a `rest' task) reduces inherent between-subject and dayto-day regional CMRglu variability (Duara et al. 1987; Holcomb et al. 1993). Thirdly, we included training and practice
on the Serial Addition/Subtraction task prior to the baseline
PET scan to preclude the situation of comparing learning and
novelty eects of the task at the baseline scan vs. practice
eects at the 24 h, and subsequent, sleep deprivation scans.
Finally, we gave feedback of performance to subjects at 5-min
intervals throughout the 30 min Serial Addition/Subtraction
task and 18FDG uptake to assist in sustaining eort and
motivation levels (Wilkinson 1961). With sleep deprivation, we
observed a signi®cant increase in subjectively rated eort and a
trend for increased motivation to perform the task (see
Results) indicating that the cognitive performance de®cits
were most likely due to a direct eect of sleep deprivation on
attention and cognition and not to an indirect eect of
decreased eort and motivation produced by task repetitionor task duration-induced tedium.
Procedures
Pre-study phase
Each volunteer wore a Precision Control Design (PCD Inc.,
Fort Walton Beach, Florida, USA) BMA-32 wrist-worn
movement activity device or actigraph (Redmond and Hegge
1985), 7±10 days prior to entering the study to document his
adherence to a 22.00 to 05.45 h nightly sleep schedule, the sleep
schedule prescribed in the nighttime sleep portion of the study.
Subjects were advised to refrain from caeine intake for the
three days before the start of the study.
Acclimation and training phase
Each in-residence session lasted eight days. Subjects arrived on
Day 1 in groups of three or four at the Division of
Neuropsychiatry, WRAIR. Their pre-study actigraph data
were assessed, and they were briefed on all study procedures.
Afterwards, subjects were instrumented for continuous
Ó 2000 US Government, J. Sleep Res., 9, 335±352
Neural basis of short-term sleep deprivation
recording of electroencephalography (EEG), electrooculography (EOG), and electromyography (EMG) and were trained
on two dierent cognitive test batteries, each of which took
approximately 25 min to complete. The ®rst test battery
consisted of the Wisconsin Card Sort Test, Thurstone's Word
Fluency Test, and the Benton's Verbal Fluency Test, while the
second test battery consisted of several cognitive and reaction
time tasks, including a 2±3 min Serial Addition/Subtraction
task, from the Walter Reed Performance Assessment Battery.
Subjects were then transported to the General Clinical
Research Center (GCRC), Johns Hopkins Bayview Medical
Center, Baltimore, Maryland, where they began the residential
portion of the study and continued to practice the cognitive
tests. Subjects retired for sleep at 22.00 h and were awakened
at 05.45 h on Day 2, and the same sleep schedule was followed
for Days 2 and 3. Throughout Days 2 and 3, subjects practiced
the cognitive performance tests, including the 2±3 min Serial
Addition/Subtraction test (12 sessions total prior to the
baseline PET scan). They were pretrained on the Serial
Addition/Subtraction task and the other performance tests
prior to the experimental sleep deprivation phase to hold
learning constant. Also during Days 2 and 3, subjects took
modi®ed Multiple Sleep Latency Tests (MSLTs) and other
physiological tests (e.g. oculomotor and vital signs monitoring). On the afternoon of Day 3, subjects attended the Johns
Hopkins Radiochemistry and PET Scanning Facility at the
Johns Hopkins Medical Institutions (JHMI) where they
underwent a simulation PET scan procedure. This procedure
included insertion of an antecubal IV catheter (which remained
in-place and patent for the next four days), individual plastic
face mask ®tting, rehearsal of radiotracer injection, practice of
the Serial Addition/Subtraction task for 30 min and subjective
scales, and simulated PET scanning.
Experimental phase
On the morning of Day 4, after a night of normal sleep,
subjects donned thermal underwear tops and bottoms, which
were worn beneath their clothing, to keep them warm in order
to facilitate the arterialization of venous blood ¯ow through
their hands for later venous blood draws (thermal clothing was
then doed after PET scanning and donned again the morning
of the next PET scan). They took one modi®ed MSLT between
07.00 and 08.00 h and ate a light breakfast, timed to maintain
a 3-h fast prior to their designated 18FDG injection. Subjects
were next transported to the JHMI Radiochemistry and PET
Facility for their baseline 18FDG-PET scans.
Each 30-min 18FDG injection and uptake occurred in the
same room and in an enclosed tent-like structure that was
erected to shield personnel associated with blood drawing and
monitoring from the subjects' view. Prior to the 18FDG
uptake, subjects had a butter¯y IV catheter inserted in the
volar side of the left hand for blood drawing pre, during, and
post18FDG injection and uptake. Their left hands were
warmed with a heating pad to enhance blood ¯ow and
arterialize the venous blood. Thereafter, subjects took the
Ó 2000 US Government, J. Sleep Res., 9, 335±352
339
Stanford Sleepiness Scale (SSS) and the Global Vigor and
Aect (GVA) scales (the latter included mood scales). Headphones were worn to attenuate transient background noise
while they performed 5 min of the Serial Addition/Subtraction
task as a `warm up' to the uptake. Immediately prior to each
18
FDG injection, subjects were instructed to maintain wakefulness and to perform the task as quickly and accurately as
possible. During and post 18FDG injection, performance on
the cognitive task continued for the 30 min of the uptake
period. Task performance compliance was ascertained by
monitoring subjects via video camera and wakefulness by
monitoring their EEG via computer-based polygraph. Upon
concluding the 18FDG uptake, subjects completed another set
of GVA scales and other visual analogue scales relating to
sleep deprivation experiences. Afterwards, they relieved their
bladders (to reduce radiation exposure to this target organ)
and were carefully positioned in the PET scanner with their
heads immobilized by an individually molded plastic face
mask. Scanning then commenced for 30 min. Subjects began
the 85 h of sleep deprivation following the baseline PET scans.
They were scanned the following three days at the same time as
their baseline scan (either 09.30, 10.30, 11.30, or 12.30 h).
During the time when subjects were not at the PET facility,
they performed two cognitive test batteries (previously
described) at alternate hours during the 85-h sleep deprivation
period. As part of one of these cognitive test batteries, subjects
performed a total of 8 sessions of the short-duration Serial/
Subtraction task after the baseline PET scan and prior to the
24-h PET scan. Subjects continued to perform the cognitive
test batteries after the fourth PET scan to preclude potential
end spurt eects during the last 18FDG uptake. Throughout
the entire study, subjects were closely monitored by sta
members, who administered test procedures and assisted in
keeping them awake. Caeine and other stimulants were not
available to subjects during the study.
Recovery phase
Subjects received approximately 12 h of recovery sleep at the
end of the 85-h sleep deprivation phase (19.00 to 06.45 h). On
the morning of the last day, subjects took a modi®ed MSLT,
performed a set of the two cognitive test batteries, and
completed the other physiological tests. At 10.00 h they were
tested for 30 min on the Serial Addition/Subtraction task to
assess recovery sleep eects on this performance measure.
Following this, the subjects' electrodes were removed, and they
were allowed to shower. They were then clinically assessed and
de-briefed prior to departure from the study.
Measures
Polysomnography (PSG)
Scalp and facial electrodes were applied to: C3, C4, F3, F4, P3,
P4, O1, O2, T3, and T4 for EEG; outer canthus of each eye for
EOG; and submental for EMG. These signals were recorded
continuously on Oxford Medilog 9000-II ambulatory recor-
340
M. L. Thomas et al.
ders (Oxford Medical Instruments, Hawthorne, New York,
USA). Oxford Mentor laptop computers provided on-line,
real-time output of PSG signals for monitoring sleep latency
tests and verifying wakefulness during the 18FDG uptake
periods. Sleep periods during the study were scored in 30-sec
epochs according to standard PSG criteria (Rechtschaen and
Kales 1968). Microsleep during the 18FDG uptake was scored
as theta, or stage 1 sleep, in the absence of artifact, with a
duration of 1 to 15 sec. EEG from C3 was used for scoring
theta events, and left and right EOG and EMG were used for
assessing the presence of artifacts.
Neuroimage acquisition
Measurement of CMRglu was implemented according to
standard practice and procedure (Reivich et al. 1979). Subjects
were infused with a slow bolus, intravenous injection of
18
FDG (5 mCi per injection) in a right forearm vein. During
the infusion and 30-min 18FDG uptake period, subjects
performed the Serial Addition/Subtraction task (see below).
PET scanning then commenced (45 min post 18FDG injection)
and continued for a duration of 30 min. A GE 4096+ PET
scanner (General Electric Medical Systems, Milwaukee,
4 Wisconsin, USA) with an axial and in-plane resolution of
6.5 mm at full-width-half-maximum (FWHM) and a 15-cm
®eld of view was used to acquire the distribution of radioactivity in the brain. Emission data were corrected for attenuation using a transmission scan obtained at the same levels.
Attenuation-corrected data were reconstructed into 15 image
planes. As indicated above, a heating pad was used to warm
the subject's left hand to 44 °C to transform the pH, PO2, PCO2,
and glucose levels in the venous blood to values more nearly
resembling those of arterial blood. Samples of arterializedvenous blood were drawn at ®xed intervals throughout each
uptake and imaging procedure and were used to transform
radioactivity counts to CMRglu (Phelps et al. 1979). Repositioning of the subjects on the PET scanner between the
experimental days was accurate to within 2 mm.
Alertness test
Objective alertness was assessed using a modi®ed version of the
MSLT (Carskadon et al. 1986). Subjects were allowed to sleep
in a quiet, darkened bedroom until they reached stage 2 sleep
or after 20 min had elapsed. Sleep latency was de®ned as the
elapsed time to the ®rst 30 sec of stage 2 sleep.
Self-reports
Subjects' self-ratings of sleepiness were assessed with a
computerized version of the Stanford Sleepiness Scale (SSS)
(Hoddes et al. 1973). The SSS is a one-item choice scale
consisting of seven numbered statements that describe alertness states ranging from 1 (`feeling active and vital; alert; wide
awake') to 7 (`almost in reverie; sleep onset soon; losing
struggle to remain awake'). Self-rated levels of eort and
motivation in Serial Addition/Subtraction performance were
assessed using visual analogue scales (single straight 10 cm
horizontal lines scored between 0 and 100). Visual analogue
scales relating to vigor and aect (Monk 1989), and sleep
deprivation experiences (data not reported) were also acquired
near the 18FDG uptake periods.
Cognitive task
The Serial Addition/Subtraction task (Thorne et al. 1985)
consists of two randomly selected single digits (0±9) and an
operator (either + or ) sign) displayed sequentially in the same
center-screen location, followed by a `?' prompt. The subject
performs the indicated addition or subtraction and, if the result
is positive, enters the least signi®cant digit of the result. If the
result is negative, the subject adds 10 and enters the positive
single digit result. The digits and operator are each presented for
250 msec, with a 200 msec interdigit/operator interval. The
next trial begins 300 msec after a key entry, or response, is made
by the subject. Consequently, there is no opportunity for an
omission, or lack of response. The 200 possible combinations of
two digits with two operators were randomly sampled several
times during each 18FDG uptake, and hence, were essentially of
equal diculty. Consistent for each uptake period, the task was
divided into six, 5-min segments, to document time-on-task
eects as well as to provide periodic feedback of performance
results to the subjects (visually on the computer monitor).
Data analysis
PET data
Statistical parametric mapping (SPM) software (SPM95,
Wellcome Department of Cognitive Neurology, London,
UK) was used for registering and statistically analysing the
PET data (Friston et al. 1995, 1996). The 15 original axial PET
planes were trilinearly interpolated to yield 43 planes in which
voxels (3-D picture elements [pixels] in neuroanatomical space)
were approximately cubic. To minimize the eects of head
displacement, the scans of each subject were realigned to the
®rst PET scan on a voxel-by-voxel basis using the SPM routine
employing a rigid body spatial transformation. Next, the PET
scans of all of the subjects were transformed into standard
stereotaxic space using both linear and nonlinear three-dimensional transformation methods to allow for voxel-by-voxel
averaging across subjects. The stereotaxically normalized scans
consisted of 26 planes (voxel size 2 ´ 2 ´ 4 mm) corresponding
to the brain atlas of Talairach and Tournoux (1988). Images
were smoothed using a 12 mm Gaussian ®lter to accommodate
intersubject dierences in gyral and functional anatomy and to
increase the signal-to-noise in the images. This produced a ®nal
image resolution of 19 ´ 20 ´ 17 mm.
To evaluate quanti®able changes in regional CMRglu that
occurred during the progression of sleep deprivation, the
absolute rates of regional CMRglu during sleep deprivation
and the rested baseline were analysed and compared. The
global normalization parameter was not used in the absolute
regional CMRglu analysis. Global CMRglu values (i.e. means)
Ó 2000 US Government, J. Sleep Res., 9, 335±352
Neural basis of short-term sleep deprivation
were obtained for each subject's PET scans from the absolute
regional CMRglu analysis. The dierence between days was
analysed using a one-tailed paired t-test, with a Bonferonni
adjustment applied based on the number of comparisons across
the entire experimental sleep deprivation phase. Absolute
regional CMRglu eects were obtained from the transformation of one-tailed t-tests to the Z probability distribution. Also,
relative regional CMRglu eects were analysed in the same way
after covarying out the eect of global CMRglu using ANCOVA
and normalization of the values relative to 5.4 mg/100 g á min.
The resulting Z-values comprised a statistical parametric
map SPM(Z). For both absolute and relative regional
CMRglu comparisons, the SPM was thresholded for statistical signi®cance at P 6 0.001, uncorrected for multiple
comparisons (Z P 3.09), for regions predicted to change a
priori (thalamus and prefrontal cortex) or which had been
shown to signi®cantly change in the Wu et al. (1991) sleep
deprivation study of CMRglu (temporal cortex, thalamus,
and cerebellum). A threshold of P 6 0.05 corrected for
multiple comparisons (Z P 4.16) was used for nonhypothesized regions. Individually acquired MRI scans showed that
each subject's neuroanatomy was normal (i.e. without signs
of disease or atrophy). The high resolution MRI scan of a
normal male brain provided in the SPM program was
subsequently used to identify neuroanatomical locations of
functional change for the group.
341
during the 18FDG uptake and not brain activity during image
acquisition. The amount of sleep acquired on the scanner
represents 1% of the total 24 h sleep deprivation period. The
resultant sleep consisted primarily of stage 1 and occurred
approximately 24 h prior to the 24-h sleep deprivation 18FDG
uptake.
Wakefulness during
18
FDG uptakes
Post hoc analysis of the recorded polysomnographic signals
showed that all subjects were awake during the 30-min 18FDG
uptake period by polysomnographic criteria. The amount of
microsleep was negligible and occurred during both the rested
(mean 2 sec) and 24-h sleep deprivation (mean 5 sec)
18
FDG measurements.
Brain Activity
Global CMRglu
Global CMRglu, expressed as the average of all voxels
(excluding white matter), decreased by approximately 8%
(actual 7.76%) after 24 h of sleep deprivation [5.67 milligrams/
100 g á min (31.4 lmol/100 g á min), rested PET scans vs.
5.23 milligrams/100 g á min (29.0 lmol/100 g á min), 24-h
sleep deprived PET scans; t 3.78, P £ 0.001].
Decreases in regional CMRglu
Behavioral data
Sleep latency, self-report, and cognitive performance data were
analysed using one-tailed paired t-tests, with the exception that
subjectively rated mood data were analysed using two-tailed
paired t-tests. Bonferonni adjustments were applied to the
behavioral data. Self-report data were log transformed prior to
statistical analysis. Correlation analyses between behavioral
measures and regional CMRglu are planned for a future report.
RESULTS
Polysomnography
Scheduled sleep
Subjects obtained an average of 396 min (6 h and 36 min) of
sleep the night before the baseline PET scan. This amount is
equivalent to that obtained for each adaptation night. Sleep
stage distribution was consistent for all nights prior to the
sleep deprivation period. The sleep parameters for all nights
were within the range for normal sleep (sleep onset £ 30 min,
sleep eciency ³ 90%, and number of arousals £ 30).
Unscheduled sleep on PET scanner
Subjects obtained an average of 14 min of unscheduled sleep
during the baseline rested PET scan. The sleep occurred when
subjects were required to remain motionless on the scanner for
30 min to ensure successful image acquisition. The regional
CMRglu activity imaged by the scanner re¯ects brain activity
Ó 2000 US Government, J. Sleep Res., 9, 335±352
Following 24 h of sleep deprivation, signi®cant decreases in
absolute regional CMRglu were observed for numerous brain
regions (Fig. 2). As revealed by signi®cant decreases in relative
regional CMRglu (Fig. 3), there was heterogeneity in regional
brain activity response during sleep deprivation. Table 1 shows
that at the same voxel location for relative regional CMRglu,
the decreases in absolute regional CMRglu were approximately
3±7% greater than the 8% decrease in global CMRglu. This
indicates that regions that signi®cantly decreased in relative
regional CMRglu were more aected than those which
decreased at the global or whole brain level. Hemispheric
analyses revealed no statistically signi®cant laterality dierences in either absolute or relative regional CMRglu with 24 h
of sleep deprivation.
For hypothesized regions, decreases in absolute regional
CMRglu occurred bilaterally throughout the prefrontal cortex
(including dorsal and ventral anterior cingulate gyri), and in
the dorsal and ventral thalami after 24 h of sleep deprivation.
Additionally, absolute decreases occurred bilaterally in the
temporal lobes and parahippocampal gyri, as well as the
cerebellar hemispheres and vermis. Decreases in relative
regional CMRglu occurred bilaterally in the prefrontal cortex
(including dorsal anterior cingulate gyrus) and in the thalamus.
Also, decreased regional CMRglu was observed in the middle
and inferior temporal gyri, in medial temporal cortex consisting of the right fusiform and parahippocampal gyri, in the
cerebellar vermis, and in a small area in the right ventral
cerebellar hemisphere.
342
M. L. Thomas et al.
Figure 2. Signi®cant decreases from baseline in absolute regional CMRglu during wakefulness and cognitive task performance after 24 h of sleep
deprivation across 17 subjects. Deactivations are superimposed on a single subject's magnetic resonance imaging (MRI) template. Axial images are
oriented in millimeters relative to the anterior commissure-posterior commissure (AC-PC) plane. The left/right hemispheres appear as the left/right
sides of each image. Signi®cant regions are color coded to re¯ect thresholds for statistical probability levels: 5.02 0.001 corrected, 4.57 0.01
corrected, 4.16 0.05 corrected, 3.09 0.001 uncorrected. Thresholds for statistical signi®cance are Z P 3.09 for regions predicted to decrease
a priori (thalamus and prefrontal cortex) and/or previously published for short-term sleep deprivation eects on regional CMRglu (temporal
cortex, thalamus, and cerebellum [Wu et al. 1991]), and Z P 4.16 for nonhypothesized regions. Statistically signi®cant regions are
neuroanatomically labeled and approximate Brodmann areas (BAs) are noted in parenthesis ( ).
Ó 2000 US Government, J. Sleep Res., 9, 335±352
Neural basis of short-term sleep deprivation
343
Figure 3. Signi®cant decreases from baseline in relative regional CMRglu during wakefulness and cognitive task performance after 24 h of sleep
deprivation across 17 subjects. Details are the same as for Fig. 2. Decreases in relative regional CMRglu resulting from sleepiness, while spatially
smaller, actually represent the areas with the largest reductions in absolute regional CMRglu (i.e. 3±7% greater decreases in absolute regional
CMRglu than the global CMRglu decrease of approximately 8%; see Table 1 for direct comparison of voxel locations and percent decreases
between relative and absolute regional CMRglu).
Several nonhypothesized regions also evidenced decreases
in absolute regional CMRglu, such as the lateral posterior
parietal (both inferior and superior lobules) and the medial
parietal cortices (including posterior cingulate gyrus and
precuneus), the right anterior and left posterior insula,
Ó 2000 US Government, J. Sleep Res., 9, 335±352
caudate, putamen, globus pallidus, basal forebrain-hypothalamus, midbrain tegmentum, and mesopontine and pontine
tegmentums. Signi®cant decreases in relative regional CMRglu were also apparent throughout the posterior parietal
lobes.
344
Left Hemisphere
Right Hemisphere
Relative Regional
CMRglu
Absolute Regional
CMRglu
Relative Regional
CMRglu
Absolute Regional
CMRglu
Region
BAà
x, y, z coordinates§
Z±
%D
Z
%D
x, y, z coordinates
Z
%D
Z
%D
Frontal Cortex ± Lateral
Middle Frontal Gyrus
Superior Frontal Gyrus
Middle Frontal Gyrus
Superior Frontal Gyrus
Middle Frontal Gyrus
Inferior Frontal Gyrus
Inferior Frontal Gyrus
Middle Frontal Gyrus
Middle Frontal Gyrus
Middle Frontal Gyrus
Orbitofrontal Gyrus
6
8
8
9
9
44
45
46
10
47
11
)38, 10, 44
)16, 32, 44
4.99
6.03
5.65
5.05
5.53
5.47
12.83
12.61
36, 10, 44
6.25
5.38
5.57
12.94
34, 16, 44
7.26
5.02
5.46
13.03
)16, 40, 36
5.72
3.85
5.14
11.31
)50,
)46,
)34,
)34,
)40,
)34,
8, 28
34, 0
48, 4
48, 8
38, )8
38, )12
4.18
2.99àà
4.96
4.89
5.15
5.16
2.90
2.14
3.18
3.07
4.71
6.36
4.74
4.44
4.88
4.85
5.37
5.74
10.69
9.89
10.86
10.75
11.82
13.22
32,
46,
50,
40,
34,
38,
36,
14,
16,
16,
42,
46,
44,
40,
40
24
20
0
)4
)4
)12
5.52
5.90
5.57
6.58
6.84
7.14
5.50
4.05
3.73
4.78
5.96
6.92
7.22
7.30
5.12
5.08
5.35
5.78
6.07
6.13
5.76
12.00
11.47
12.44
13.34
14.14
14.61
15.52
8
9
10
11
)12,
)16,
)14,
)12,
38,
42,
58,
24,
40
32
12
)20
4.76
4.87
4.53
4.36
3.11
3.14
3.88
6.26
4.84
4.88
4.99
5.44
10.88
10.71
11.91
13.72
10,
14,
16,
12,
38,
44,
56,
16,
40
32
0
)20
6.19
4.54
4.31
4.04
4.47
3.11
3.22
5.01
5.29
4.78
4.81
5.12
12.30
11.33
11.28
13.11
7
)36, )74, 32
6.02
5.08
5.50
12.52
38, )62, 40
5.49
5.72
5.56
13.33
40
39
)50, )50, 40
)42, )68, 32
6.11
6.14
6.88
5.07
5.87
5.46
14.57
12.78
44, )58, 32
42, )58, 36
5.55
6.05
4.72
5.74
5.26
5.61
12.86
13.51
7
31
)10, )56, 32
)4, )54, 24
5.97
5.41
4.17
4.61
5.19
5.35
12.04
11.85
2, )44, 32
6, )54, 24
5.73
5.44
4.35
4.23
5.28
5.24
11.81
11.64
42
22
38
39
21
37
20
)36,
)58,
)22,
)44,
)58,
)58,
)56,
)26, 12
)48, 20
4, )24
)70, 24
)44, )16
)46, )16
)24, )28
§§
2.76àà
§§
5.53
3.74
3.79
4.06
§§
2.32
§§
3.56
4.76
4.97
3.81
4.05
4.45
3.95
5.00
4.95
5.00
4.94
8.78
10.21
11.43
11.40
13.62
13.69
11.56
36,
56,
22,
40,
54,
52,
54,
§§
2.94àà
§§
4.89
4.29
4.44
4.65
§§
2.29
§§
3.16
5.32
5.53
6.02
4.20
4.43
3.41
4.89
5.29
5.32
5.39
9.43
10.81
10.54
10.71
12.78
13.29
14.26
37
20
36
)52, )44, )24
)42, )32, )28
)34, )32, )4
2.62àà
3.28
2.92àà
3.53
5.26
3.51
4.52
4.92
4.62
12.53
13.41
11.93
48, )44, )24
42, )40, )28
26, )30, )28
3.76
3.79
4.61
5.36
5.21
6.46
5.10
5.07
5.59
13.37
13.51
13.41
Frontal Cortex ± Medial
Medial Frontal Gyrus
Rectus Gyrus
Ó 2000 US Government, J. Sleep Res., 9, 335±352
Parietal Cortex ± Lateral
Superior Parietal Lobule
Inferior Parietal Lobule
Supramarginal Gyrus
Angular Gyrus
Parietal Cortex ± Medial
Precuneus
Temporal Cortex ± Lateral
Transverse Temporal Gyrus
Superior Temporal Gyrus
Middle Temporal Gyrus
Inferior Temporal Gyrus
Temporal Cortex ± Medial
Fusiform Gyrus
Parahippocampal Gyrus
)26, 12
)50, 20
4, )24
)70, 24
)48, )16
)46, )20
)26, )28
M. L. Thomas et al.
Table 1 Signi®cant decreases from baseline in regional CMRglu during wakefulness and cognitive task performance after 24 h of sleep deprivation (n = 17*)
Ó 2000 US Government, J. Sleep Res., 9, 335±352
Cingulate Cortex
Anterior Cingulate Gyrus
)4, 20, 40
)2, )24, 36
)12, )54, 28
)2, )52, 20
)2, )50, 20
3.49
4.71
5.85
5.36
5.29
2.89
3.93
3.96
4.91
5.09
4.67
5.12
5.12
5.43
5.45
10.70
11.31
11.87
12.07
12.32
Insular Cortex
Anterior Insula
Posterior Insula
)38, 10, 0
)34, )18, 12
2.40àà
2.44àà
1.51
2.15
4.22
4.38
9.76
9.45
Subcortical Structures
Caudate
Putamen
Globus Pallidus
Thalamus (Dorsal)
Thalamus (Ventral)
Basal Forebrain (Hypothalamus)
Midbrain Tegmentum
Mesopontine Tegmentum
Pontine Tegmentum
)16, 4, 12
)28, )6, 0
)20, )8, 0
)8, )16, 8
)2, )26, )4
)2, )12, )4
)2, )30, )12
)2, )32, )16
)2, )40, )20
4.68
2.40àà
3.41àà
6.68
1.43àà
2.64àà
3.80àà
3.39àà
2.58àà
3.65
1.45
2.54
7.21
1.19
2.60
2.66
2.61
3.03
5.12
4.23
4.59
5.98
4.03
4.48
4.83
4.74
4.54
Cerebellar Vermis
Anterior Lobe
Posterior Lobe
)6, )50, )16
)2, )56, )24
3.63
4.69
4.22
4.73
Cerebellar Hemispheres
Anterior Lobe
Posterior Lobe
)8, )48, )16
)26, )74, )24
3.57
1.13àà
4.22
0.91
Posterior Cingulate Gyrus
8,
2,
6,
2,
2,
22, 28
)24, 36
)54, 28
)46, 24
)46, 20
5.11
4.69
5.52
5.42
5.11
3.13
3.94
4.12
5.36
5.63
4.86
5.10
5.20
5.54
5.53
10.96
11.28
11.62
12.54
12.89
38, 10, 0
NS**
3.38àà
1.98
4.39
10.57
10.32
9.12
10.16
15.07
7.84
10.26
8.60
8.70
9.66
10, 2, 12
28, )4, 0
22, )8, 0
10, )18, 8
10, )26, )4
2, )12, )4
2, )28, )12
2, )32, )16
2, )40, )20
3.30àà
2.42àà
2.56àà
6.08
3.62
2.54àà
3.87àà
3.18àà
2.48àà
3.43
1.80
2.53
5.80
2.89
2.25
2.78
2.20
2.79
4.78
4.29
4.45
5.61
4.78
4.40
4.85
4.59
4.49
10.61
9.90
10.13
13.64
9.62
10.09
8.97
8.50
9.30
4.99
5.29
11.33
11.99
2, )46, )16
2, )50, )20
2.99àà
3.94
3.43
3.76
4.69
4.96
10.45
11.02
5.00
3.93
11.04
9.26
12, )44, )16
26, )68, )28
1.64àà
3.54
1.33
3.82
4.09
4.84
8.99
11.79
Z-score statistic, voxel location in Talairach space, and percent decrease in relative and absolute regional CMRglu for each region/Brodmann area by hemisphere. For relative regional CMRglu,
Z-score maxima are given. For absolute regional CMRglu, Z scores (and percent decreases) are shown at the same voxel location as shown for relative regional CMRglu as a direct comparison, and
consequently may not re¯ect the Z-score maxima for absolute regional CMRglu for that region. Regional CMRglu decreases in frontal cortex were extensive; therefore, only frontal regions
associated with the Z-score maxima for signi®cant Brodmann areas are listed. àApproximate location. §Talairach coordinates: ´ is the lateral distance from the midline (positive = right); y is the
anteroposterior distance from the anterior commissure (positive = anterior); z is the rostrocaudal distance from the bicommissural plane (positive = rostral). ±Thresholds for statistical signi®cance
are Z ³ 3.09 (P £ 0.001 uncorrected) for regions predicted to decrease a priori (thalamus and prefrontal cortex) and/or previously published for regional CMRglu (temporal cortex, thalamus, and
cerebellum [Wu et al. 1991]), and Z ³ 4.16 (P £ 0.05 corrected) for all others. **NS = not signi®cant for both relative and absolute regional CMRglu. Some subcortical regions listed are small
relative to the spatial resolution of the PET scanner used in this study (i.e. basal forebrain-hypothalamus, midbrain/pontine tegmentums). They are important to cerebral activation but must await
con®rmation of involvement in sleepiness by future studies using higher spatial resolution scanners. ààNot signi®cant by Z-score threshold criteria. §§Data not available: A voxel was not retained for
further analysis if the F ratio for that voxel did not reach signi®cance (P £ 0.05 uncorrected) or if the activity of the voxel was not of a reasonably high activity, e.g. in the range of grey matter
activity.
Neural basis of short-term sleep deprivation
*
32
24
31
23
30
345
346
M. L. Thomas et al.
Test
Rested
Baseline
24 h of Sleep
Deprivation
Modi®ed Multiple Sleep Latency Test
Elapsed time to stage 2 (min:sec)
18:12 (04:46)
03:26 (01:39)
Stanford Sleepiness Scale (1)7)
1.8 (1.0)
2.9 (1.2)
t
Table 2 Alertness, self-assessments, and
cognitive performance during wakefulness
after a night of normal sleep (rested baseline)
and 24 h of sleep deprivation (n=17)
P
11.41
0.000
) 3.04
0.004
Global Vigor and Aect Scales (0±100)
Pre-18FDG Uptake
Vigor ± Alert
Vigor ± Eort
Vigor ± Weary
Vigor ± Sleepy
Aect ± Sad
Aect ± Tense
Aect ± Happy
Aect ± Calm
88.7
11.5
13.3
10.9
12.8
38.4
63.5
60.7
(17.8)
(13.8)
(18.0)
(15.9)
(24.8)
(36.8)
(27.3)
(28.1)
62.9
33.5
40.1
46.1
5.7
41.3
62.1
60.8
(24.7)
(24.3)
(25.2)
(26.6)
(10.7)
(36.4)
(19.6)
(31.0)
4.27
) 4.22
) 4.54
) 5.50
0.83
) 0.19
0.20
0.45
0.000
0.000
0.000
0.000
0.42
0.85
0.85
0.66
Post-18FDG Uptake
Vigor ± Alert
Vigor ± Eort
Vigor ± Weary
Vigor ± Sleepy
Aect ± Sad
Aect ± Tense
Aect ± Happy
Aect ± Calm
71.8
23.4
22.6
22.0
2.2
23.5
64.0
60.5
(21.9)
(24.9)
(27.0)
(23.4)
(4.6)
(34.0)
(28.9)
(33.4)
44.1
53.7
50.6
68.1
5.2
27.3
54.8
64.7
(23.3)
(29.3)
(35.6)
(23.3)
(8.6)
(32.1)
(28.6)
(27.1)
)
)
)
)
)
3.71
4.86
3.30
6.03
1.66
1.65
0.95
0.70
0.001
0.000
0.002
0.000
0.12
0.12
0.36
0.50
Post-18FDG/Cognitive Performance
Scales (0±100)
Eort
Motivation
54.7 (32.0)
78.7 (30.5)
74.7 (26.6)
82.0 (28.4)
) 3.06
) 1.04
0.004
0.16
Serial Addition/Subtraction Task
during 18FDG Uptake (30 min total)
Accuracy (% correct)
Speed (responses/min)
Throughput (correct responses/min)
95.5 (5.2)
71.0 (27.2)
68.3 (27.3)
92.3 (6.4)
61.4 (24.6)
57.5 (25.2)
2.97
3.48
3.54
0.005
0.002
0.001
Values are mean standard deviation.
Increases in regional CMRglu
No signi®cant increases in absolute regional CMRglu, nor
trends for signi®cant increases, were noted with 24 h of sleep
deprivation. Therefore, increases in relative regional CMRglu
(data not shown), which were evident after covarying out the
global CMRglu decrease, re¯ected either a lack of statistically
signi®cant decrease in absolute regional CMRglu or invariance
in regional CMRglu: left postcentral gyrus (BAs 3, 4); left/
right lateral occipital cortices (BAs 18, 19); left superior
temporal cortex (BA 22); left/right lingual and fusiform gyri
(BAs 18, 19); right mesial temporal lobe (amygdala area, BA
28); and right dorsal cerebellar lobe.
Behavior
After 24 h of sleep deprivation, objective and subjective
alertness declined but mood remained constant (Table 2):
latency to stage 2 sleep signi®cantly decreased on the modi®ed
MSLT, sleepiness ratings on the SSS signi®cantly increased,
and signi®cant changes were found for all vigor-related scales
of the GVA instrument indicating increased sleepiness and
eort to remain awake and perform. Signi®cant changes,
however, were not found for any of the mood-related scales of
the GVA instrument after sleep deprivation. Analysis of other
visual analogue scales revealed that after sleep deprivation,
subject-perceived eort to perform the Serial Addition/Subtraction task during the 18FDG uptake increased signi®cantly,
while subjective ratings of motivation to perform the task
remained consistently high (Table 2).
A signi®cant reduction was observed after sleep deprivation in
cognitive performance on the Serial Addition/Subtraction task
during the 18FDG uptake with respect to accuracy, speed, and
throughput (Table 2): accuracy decreased by 3%, speed by 13%,
and throughput, a speed-accuracy product and index of overall
productivity (Thorne et al. 1983), by 16%. Table 3 shows that
within the 30-min Serial Addition/Subtraction task during the
rested baseline 18FDG uptake, there was no signi®cant time-ontask decrease in performance when each subsequent 5 min
segment was compared with the ®rst segment. In the 24-h sleep
deprivation session, each subsequent segment was signi®cantly
dierent than the ®rst segment for all three performance
measures. This time-on-task eect was linear over the ®rst
15 min and then remained stable for the remaining 15 min.
Ó 2000 US Government, J. Sleep Res., 9, 335±352
Neural basis of short-term sleep deprivation
Table 3 Time-on-task 30 min performance
during18FDG uptake periods (5 min
segments) after a night of normal sleep (rested
baseline) and 24 h of sleep deprivation
(n=17)*
347
Serial Addition/
Subtraction Task
Rested
Baseline
t
P
24 h of Sleep
Deprivation
t
P
Accuracy (% correct)
1st 5 min
2nd 5 min
3rd 5 min
4th 5 min
5th 5 min
6th 5 min
95.5
96.5
95.4
94.3
95.6
95.9
(4.7)
(3.4)
(4.2)
(9.7)
(7.4)
(5.6)
) 1.50
0.13
0.67
) 0.08
) 0.31
0.08
0.45
0.26
0.47
0.38
96.1
93.9
92.2
90.9
90.5
90.1
(3.0)
(5.4)
(7.4)
(8.7)
(8.7)
(8.9)
2.41
2.98
3.31
3.30
3.27
0.01
0.004
0.002
0.002
0.002
Speed (response/min)
1st 5 min
2nd 5 min
3rd 5 min
4th 5 min
5th 5 min
6th 5 min
72.2
69.3
72.4
68.9
70.7
72.7
(28.4)
(25.3)
(32.3)
(28.2)
(25.2)
(28.4)
1.29
) 0.07
1.45
0.58
) 0.25
0.11
0.47
0.08
0.28
0.41
71.6
63.3
59.5
57.9
57.6
58.7
(29.2)
(27.9)
(28.5)
(26.4)
(20.3)
(23.9)
2.95
3.10
3.30
3.05
3.41
0.005
0.003
0.002
0.004
0.002
Throughput (correct
responses/min)
1st 5 min
2nd 5 min
3rd 5 min
4th 5 min
5th 5 min
6th 5 min
69.3
67.2
69.7
65.7
67.9
70.0
(28.5)
(25.9)
(32.3)
(28.7)
(25.1)
(28.4)
0.94
) 0.14
1.69
0.54
) 0.35
0.18
0.46
0.05
0.30
0.37
69.3
60.1
55.7
53.6
52.5
53.8
(29.3)
(28.0)
(29.0)
(27.4)
(20.7)
(25.2)
3.20
3.42
3.69
3.83
3.99
0.003
0.002
0.001
0.001
0.001
* Statistical comparisons are between the ®rst 5-min segment and each of the last ®ve 5-min
segments within each day.
Values are mean standard deviation.
DISCUSSION
Implications for sleep deprivation-induced alertness
and cognitive performance decrements
Concurrent with impaired alertness and cognitive performance, 24 h of sleep deprivation produced a decrease in global
CMRglu during polysomnographically de®ned wakefulness,
and decreased absolute regional CMRglu in several cortical
and subcortical regions. Increases in absolute regional CMRglu were not observed in any region. Decreases in relative
regional CMRglu ± indicating areas more deactivated than the
global decrease ± were found throughout the thalamus and
prefrontal cortex. These brain regions subserve alertness and
attention, while the prefrontal cortex also mediates the highestorder cognitive processes, the mental abilities most impaired
by sleep deprivation. Extensive decreases in absolute and
relative regional CMRglu were found throughout another
cortical region, the posterior parietal lobes, following sleep
deprivation. The vast deactivations in the prefrontal and
posterior parietal cortices included the heteromodal association areas (BAs 8, 32, 45, 46, 9, 10, 11 in the prefrontal cortex
and BAs 7, 40, 39 in the posterior parietal cortex), which are
involved in the higher-order analysis and integration of
sensory-motor information and cognition (Mesulam 1985).
The ®nding of thalamic deactivation after 24 h of sleep
deprivation in the present study is highly consistent with this
structure's role in cerebral activation and alertness (Roland
1993) and with the measured decrease in sleep latency and
increase in subjective sleepiness. Decreased regional CMRglu
Ó 2000 US Government, J. Sleep Res., 9, 335±352
in the thalamus has also been observed following extreme
sleepiness in rats (Everson et al. 1994) and has been found to
negatively correlate with benzodiazepine-induced sleepiness
during wakefulness (Volkow et al. 1995). Moreover, the
thalamus is important to task performance requiring attention
5 and alertness (Kinomura et al. 1996; Shulman et al. 1997), and
reduced activity of this region following sleep deprivation may
have contributed to de®cits in attention during Serial Addition/Subtraction performance. Other evidence supporting this
view is that thalamic deactivation has been found in previous
studies of sleep deprivation and impaired attentional performance (Wu et al. 1991; Drummond et al. 1999a) and has been
shown to coincide with attention and vigilance de®cits in
patients with fatal familial insomnia, a disease characterized by
thalamic lesions and intractable insomnia (Perani et al. 1993).
Anatomically, the thalamus has known bi-directional connections with the prefrontal-posterior parietal cortical association areas, which were also substantially deactivated by sleep
deprivation. The thalamus and these cortical regions are
considered to be part of a distributed neural network for
directed attention (Mesulam 1990), and studies have demonstrated coactivation of these three areas during tasks requiring
sustained attention (Coull et al. 1996, 1998) and intrinsic
alertness (Sturm et al. 1999). Of particular relevance is that
decreased activity in these structures has been found for
degraded time-on-task vigilance performance during normal
alertness (Paus et al. 1997). Time-on-task impairments in
performance are well-documented in sleep deprivation studies
(Johnson 1982) and were found with sleep deprivation in the
current study.
348
M. L. Thomas et al.
In addition to contributing to attentional processes, cerebral
activation studies show that under normal alertness conditions
the prefrontal and posterior parietal cortices are recruited
during tasks requiring visual verbal working memory (Coull
et al. 1996; Dolan et al. 1997) and arithmetic calculations
(Roland and Friberg 1985; Dahaene et al. 1996, 1999).
Behaviorally, these cognitive functions are also necessary for
Serial Addition/Subtraction performance, which decreased in
conjunction with deactivation of these cortical areas after 24 h
of sleep deprivation. Due to the long half life (110 min) of
18
FDG, a control task was not evaluated to directly discern the
functional brain components of the Serial Addition/Subtraction task. A control task was evaluated in the Drummond
et al. (1999a) sleep deprivation study using a similar arithmetic
task, which revealed task-related relative activations in localized areas of the prefrontal and posterior parietal regions
during rested arithmetic performance. The deactivations in the
prefrontal cortex in the present study were more extensive than
those observed in that sleep deprivation study, however, and
therefore may have functional implications beyond simply
re¯ecting the cognitive task used. The prefrontal cortex
mediates other higher-order mental abilities impaired by sleep
deprivation (see Introduction), such as verbal ¯uency, speech,
¯exible and innovative thinking, and planning, judgment, and
decision making based on new or updated information (Fuster
1989; Roland 1993; Damasio 1994; Frith and Dolan 1996).
The magnitude and amount of reduced activity found in this
region suggest that other higher-order cognitive impairments
proposed by Horne (1988b, 1993) and noted in various sleep
deprivation experiments could be a consequence of, and
explained by, declines in prefrontal cortical functioning.
Reconciliation with other brain activity ®ndings
of human sleep deprivation
Our brain activity results for sleep deprivation con®rm several
®ndings from a previous study of absolute and relative
regional CMRglu changes of short-term sleep deprivation
and visual attention de®cits (Wu et al. 1991). We found a
decrease in global CMRglu of approximately 8% compared
with a 7% decrease observed by Wu et al. (1991), albeit theirs
did not reach statistical signi®cance. We also found deactivation of the temporal lobes, thalamus, and cerebellum. Likewise, we noted increases in relative regional CMRglu in
occipital cortex, which re¯ected nonsigni®cant decreases in
absolute regional CMRglu. In contrast, we found signi®cant
decreases in absolute and relative regional CMRglu throughout
the prefrontal cortices, including anterior cingulate gyrus, and
the posterior parietal cortices, including posterior cingulate
gyrus and precuneus. Decreases in absolute regional CMRglu
in basal ganglia, basal forebrain, and midbrain and pontine
tegmentum brainstem areas were also apparent. Incongruity in
®ndings between the two investigations may be explained in
part by dierences in the image analysis procedures used as
already described. Evidence of this is given by a recent report
(Wu et al. 1999), where the authors applied a more sensitive
analysis to their data and showed decreases in regional
CMRglu in right dorsolateral prefrontal cortex (BA 46).
Apart from the analysis procedure, the dierences in
regional brain activity results between the studies might be
explained by apparent dierences in task demands (i.e. level of
diculty related to rate of stimulus presentation and cognitive
processing) and complexity (i.e. type of mental processing,
such as memory and arithmetic processing) necessitated by the
two dierent tasks used to probe brain function during sleep
deprivation. In the present study, Serial Addition/Subtraction
performance involved sustained attention, working memory
and arithmetic calculations of all fast-paced stimulus presentations, whereas in the Wu et al. (1991) study, Continuous
Performance Test performance required sustained attention
and a vigilance component, necessitating identi®cation
responses when an infrequently occurring target stimulus
appeared (Mesulam 1985). While both sleep deprivation
studies produced performance impairments, the rate and
nature of task requirements imposed by the Serial Addition/
Subtraction task is arguably more dicult and complex than
those imposed by the Continuous Performance Test. Subjects
in our study reported not only a moderate amount of eort to
perform this task when well-rested but also signi®cant
increases in eort over baseline with sleep deprivation,
substantiating that the task became more dicult to perform
when sleepy.
The idea that brain activity response to sleep deprivation
could be task and/or task outcome speci®c has been noted
previously (Thomas 1997; Drummond et al. 2000). In fact, our
®ndings of decreased activity in prefrontal anterior cingulate
cortex, lateral posterior parietal cortices, and thalamus during
sleep deprivation and decreased Serial Addition/Subtraction
task performance are in agreement with ®ndings on a similar,
but of shorter-duration, complex cognitive task resulting in
performance impairment (Drummond et al. 1999a). Support
for task-speci®c neural responses, with and without performance impairment, has been demonstrated in other short-term
6 sleep deprivation studies (Portas et al. 1998; Smith et al. 1999;
Drummond et al. 1999b; 2000). The results of studies where
performance was held constant revealed either no change or
primarily increases in regional brain activity. However, the
tasks used may not have been of sucient cognitive load or
challenge to evoke diminished neural responses. This concept
was evaluated in a study where dierences in dorsolateral
prefrontal cortical activation between schizophrenic patients
and controls became apparent only after diculty on a memory
task increased and performance impairment occurred (Fletcher
et al. 1998). Nonetheless, in addition to task diculty and task
complexity characteristics, task duration characteristics may
play an important role in delineating brain activity responses
during sleep deprivation. Dierences in time-on-task performance are likely to occur between studies using dierent
designs and scanning methods (and hence dierent task
durations) to assess sleep deprivation brain activity eects;
for example, temporal dierences between a 30-min 18FDG
uptake acquisition, in which the ®rst 10 min accounts for a
Ó 2000 US Government, J. Sleep Res., 9, 335±352
Neural basis of short-term sleep deprivation
majority of the regional brain activity response, vs. multiple,
40-sec scans for a BOLD-fMRI response acquisition.
Based on the results of the above studies of sleep deprivation,
these brain imaging data suggest that following one night of
sleep deprivation, neurons have the capacity to respond
normally when the brain is presented with a nonchallenging
task, or may be able to temporarily increase their response in
speci®c regions in an attempt to meet the demands of simple
short-term task performance. In the case of complex task
performance and/or sustained task performance during sleep
deprivation, the ®ndings of decreased regional brain activity
suggest that neurons cannot keep pace with high task load
requirements and/or neuronal responsivity is diminished or
fatigued after a certain period of performance (i.e. a timeon-task eect) thereby resulting in a decrement in task outcome.
Comparisons with regional brain activity alterations
observed during human sleep
An intriguing implication of the results from the current
functional neuroimaging study of sleep deprivation, when
compared with results for sleep, is that the larger decreases in
activity in the prefrontal and posterior parietal heteromodal
association cortices may indicate a greater biological vulnerability of these areas to extended wakefulness. Other work
from our laboratory (Balkin et al. 1992; Braun et al. 1997) has
shown absolute and relative decreases in dorsolateral prefrontal and inferior parietal cortical activity (as measured by
cerebral blood ¯ow) during light sleep, slow wave sleep and
REM sleep, which has also been reported by others (e.g.
Buchsbaum et al. 1989; Andersson et al. 1998; Maquet et al.
1996; Kajimura et al. 1999). Thus, the same higher-order
cognitive areas dierentially aected by sleep deprivation are
also dierentially aected by sleep indicating that these areas
may be more susceptible to sleep deprivation and consequently
have a greater need for the recuperative processes underlying
sleep. Such homeostatic processes may include brain energy
substrate and neuromodulator replenishment (Benington and
Heller 1995; Newhouse et al. 1989; McCann et al. 1992, 1993,
1995) and/or adjustment of ionic currents and reorganization
of network patterns of synaptic activity as a consequence of
learning (Steriade et al. 1993).
Neuroimaging studies of sleep have also uniformly revealed
decreased activity in the thalamus when measured during light
and/or deep NREM sleep (e.g. Buchsbaum et al. 1989; Balkin
et al. 1992; Maquet et al. 1990, 1992, 1997; Braun et al. 1997;
Ho¯e et al. 1997; Andersson et al. 1998; Kajimura et al. 1999).
Complementary to this, we showed that the largest subcortical
deactivation in waking regional CMRglu after one night of
sleep deprivation occurred in the thalamus, and this has been a
relatively consistent result in other neuroimaging studies of
sleep deprivation (Wu et al. 1991; Everson et al. 1994; Drummond et al. 1999a). Taken together, these ®ndings suggest that
a progressively deactivated thalamus may be necessary for the
transition from waking to sleep and for the occurrence of
deeper stages of sleep.
Ó 2000 US Government, J. Sleep Res., 9, 335±352
349
Temporal occurrence of sleep deprivation-induced
deactivations
Given the limited temporal resolution of PET-based brain
imaging, we cannot determine the source of our sleep
deprivation-induced brain deactivation. Deactivation could
have originated in the thalamus, in the cortex, or in other more
caudal brain regions known to be involved in thalamic and
cortical activation (McCormick and Bal 1997). Thus far,
decreased corticothalamic activity is the most marked brain
alteration seen with human sleep deprivation, whereas activity
in the areas of the basal forebrain and mesencenphalon and
pontine tegmentums is either less aected as in the current
study or observed not to change signi®cantly (Wu et al. 1991;
Drummond et al. 1999a,b; 2000). These latter areas, speci®cally the small nuclei associated with promoting thalamic and
cortical activation and those associated with promoting sleep
7 in animals (Steriade and McCarley 1990; Szymusiak 1995), will
require higher spatial, as well as temporal, resolution scanners
to accurately identify their involvement in human sleepiness.
Further data analyses of the present study, to include
correlation analysis of alertness and cognitive performance
alterations with the changes in regional brain activity, as well
as the neuroimaging measures associated with the 48 and 72 h
sleep deprivation time points, may shed light on regions which
may be aected directly or might be most sensitive to sleep
deprivation.
CONCLUSIONS
One night of sleep deprivation in humans diminishes waking
regional brain activity predominantly in a bilateral prefrontalposterior parietal-thalamic network mediating alertness attention and higher-order cognitive processes. The cortical association ®ndings are complementary to studies of slow wave and
REM sleep demonstrating deactivation of these same cortical
regions, with the implication that the need for recuperation
during sleep may be greater in these areas relative to other brain
regions. Our results of brain activity, alertness, and cognitive
performance impairments following one night of sleep deprivation suggests that the neurobehavioral function of sleep in
humans is to restore and sustain normal waking brain activity
and behavior. These ®ndings substantiate the biological necessity of sleep to normal brain functioning and are particularly
powerful in underscoring the importance of adequate sleep for
workplace productivity, public safety, and personal well being.
ACKNOWLEDGEMENTS
Funding was provided by the Military Operational Medicine
Program, Project #S15 Q, U.S. Army Medical Research and
Materiel Command, Ft. Detrick, Maryland, and by the
GCRC/Johns Hopkins Bayview Medical Center, Grant
#M01RR02719, Baltimore, Maryland. Technical support was
also provided by Science Applications International, Inc.
(SAIC) through Contract #MDA903±92±0068 with the
350
M. L. Thomas et al.
Human Research and Engineering Directorate, US Army
Research Laboratory, Aberdeen Proving Ground, Maryland.
We thank our anonymous reviewers for their thoughtful
comments and suggestions. We also thank our volunteers for
their participation. For technical assistance, we thank the
following: Johns Hopkins Radiochemistry and PET sta,
Walter Reed enlisted military and student contract sta,
GCRC/Johns Hopkins Bayview research nursing sta
(J. Wright, Nursing Supervisor; P. Knighton, Study Manager),
and sta at Henry M. Jackson Foundation (J. Williams),
SAIC (J. Zurer), Walter Reed Army Medical Center
(P. Peller), Johns Hopkins Medical Institutions (M. Murrell
and J. Leal), and Maryland Psychiatric Research Center
(M. Zhao). Additionally, we thank Dr Karl Friston (Wellcome
Department of Cognitive Neurology, London) for Statistical
Parametric Mapping software.
This study was done in partial ful®llment of the ®rst author's
doctoral degree in Applied-Experimental Psychology at
George Mason University, Fairfax, Virginia (Advisor:
R. Smith. Committee Members: R. Holt and D. BoehmDavis, Department of Psychology; and H. Morowitz,
Krasnow Institute for Advanced Study).
DEPARTMENT OF DEFENSE DISCLAIMER
Human volunteers participated in this study after giving their
free and informed consent. Investigators adhered to AR 70±25
and USAMRDC Reg 70±50 on the use of volunteers in
research. The opinions or assertions contained herein are the
private views of the authors and are not to be construed as
ocial or as re¯ecting the views of the Department of the
Army or the Department of Defense.
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