Question:
Describe about the Case Study of The Journal of Neuroscience.
Answer:
To what extent is the state instability hypothesis supported by the study?
The hypothesis postulates that state instability is associated with an increase in sleep drive and it leads to variable neurobehavioral performances. The research study largely supports the hypothesis. This study illustrated differences between neural activation during lapses in sleep deprivation and lapses after a normal night’s sleep. The study made three predictions: 1) sleep deprivation would attenuate peak signals in transient lapse, 2) SD lapses would lead to lapse related lowering of activity in the visual cortex and 3) SD lapses would change sub-cortical activation patterns (Chee et al., 2008). Brain imaging studies of the participants showed that sleep deprivation resulted in less accuracy and more variability in the performance. A prominent long right tail was observed after SD in correct trial’s distribution of response. An increase in intra-individual variability was also observed, which showed correlation with previous studies. Task related activation was found to be reduced in SD in comparison to rested wakefulness. In accordance with previous studies, it was observed that sleep deprivation did not modulate the relation between lapses and peristimulus activity reduction. The reduction in this signal was comparatively small between the difference in peak signals induced by such lapses in both the states. The study established that increased peak signals in regions that control cognition were associated with the lapses in SD. The elevation in this signal was less pronounced in SD state compared to RW. Lapses in RW in the inferior occipital regions showed no relation to any small or large peak signals. However, in SD they were found to be linked to a reduction in extrastriate peak signals. This was in accordance to the bias model of selective attention (Chua et al., 2014). On comparing cortical responses, greater bilateral intraparietal sulcus and medial frontal peak signals were found to be correlate with slow reponses. Fastest responses failed to create higher activation in the extrastriate visual cortex region (Devita et al., 2017). This was completely congruent with the hypothesis. Thus, the study found that SD attenuated activation in brain during lapses in addition to affecting the overall activation patterns related to tasks. These findings helped in differentiating SD lapse from other lapses that occur after a normal sleep. Thus, the findings were completely in line with the theory of state instability.
To what extent is the prefrontal cortex impairment hypothesis supported?
The hypothesis states that sleep deprivation creates negative effects on cognitive performance and alertness and this is related to brain activity and function decrease. This decrease in activity occurs in thalamus and the prefrontal cortex which is involved in attention and alertness and higher-order cognitive processes. The study tested 17 subjects for changes in brain activity during 85 hours of sleep deprivation (Thomas et al., 2000). During the 18FDG uptake, each of which occurred for 30 minutes, the subjects participated in SD serial addition and subtraction tasks. Polysomnographic analysis revealed that the subjects were awake. The cerebral metabolic rate for glucose showed a global decrease of 8% and 3-7% more decrease in regional values after the twenty four hour sleep deprivation stage. The decrease was observed in posterior parital cortex and the thalamus (Killgore & Weber, 2014). A decrease was also observed in the cerebellar vermis, medial temporal cortex and right ventral cerebellar hemisphere. Moreover, cognitive performance and alertness showed a decline with the deactivation of brain regions (Occhionero, Cicogna & Esposito, 2017). Thus, the study provided evidence for substantiating the relation between normal functioning of the brain and sleep. It also proved that sleep deprivation for a short period decreases brain activity. The corticothalamic network activity, which controls cognitive skills and attention, gets reduced significantly. Hence, it proved association between sleep deprivation, reduced brain activity and decline in cognition (Jackson et al., 2013).
References
Chee, M. W., Tan, J. C., Zheng, H., Parimal, S., Weissman, D. H., Zagorodnov, V., & Dinges, D. F. (2008). Lapsing during sleep deprivation is associated with distributed changes in brain activation. Journal of Neuroscience, 28(21), 5519-5528.
Chua, E. C. P., Yeo, S. C., Lee, I. T. G., Tan, L. C., Lau, P., Cai, S., … & Gooley, J. J. (2014). Sustained attention performance during sleep deprivation associates with instability in behavior and physiologic measures at baseline. Sleep, 37(1), 27-39.
Devita, M., Montemurro, S., Ramponi, S., Marvisi, M., Villani, D., Raimondi, M. C., … & Mondini, S. (2017). Obstructive sleep apnea and its controversial effects on cognition. Journal of clinical and experimental neuropsychology, 39(7), 659-669.
Jackson, M. L., Gunzelmann, G., Whitney, P., Hinson, J. M., Belenky, G., Rabat, A., & Van Dongen, H. P. (2013). Deconstructing and reconstructing cognitive performance in sleep deprivation. Sleep medicine reviews, 17(3), 215-225.
Jackson, M. L., Gunzelmann, G., Whitney, P., Hinson, J. M., Belenky, G., Rabat, A., & Van Dongen, H. P. (2013). Deconstructing and reconstructing cognitive performance in sleep deprivation. Sleep medicine reviews, 17(3), 215-225.
Killgore, W. D., & Weber, M. (2014). Sleep deprivation and cognitive performance. In Sleep Deprivation and Disease (pp. 209-229). Springer New York.
Occhionero, M., Cicogna, P., & Esposito, M. J. (2017). The Effect of Sleep Loss on Dual Time-Based Prospective Memory Tasks. American Journal of Psychology, 130(1), 93-103.
Thomas M, Sing H, Belenky G, Holcomb H, Mayberg H, Dannals R, Wagner H, Thorne D, Popp K, Rowland L, Welsh A, Balwinski S, Redmond D. (2000). Neural basis of alertness and cognitive performance impairments during sleepiness. I. Effects of 24 h of sleep deprivation on waking human regional brain activity. Journal of Sleep Research, 9(4), 335-52.
Notes for paper: Functional Imaging of Working Memory after 24 Hr of Total Sleep Deprivation (Chee & Choo, 2004).
Aim(s)
- To examine the interaction between task complexities and state that modulates cortical activation in young, healthy adults during working memory tasks.
Participant
- n= 14 right handed, young, healthy adults (mean age- 23 years).
- male-9, female- 5.
Study Design
- Volunteers with good sleep patterns.
- Average sleep of 7.2 +/- 0.9 hours per night (Chee & Choo, 2004).
- No volunteers included with history of insomnia, daytime sleepiness, psychiatric illness, narcolepsy or addicts.
Protocol
- SD and RW scanning of subjects conducted within 1 week.
- Subjects abstained from caffeine, smoking, for 24 hr before scanning. Alcohol was disallowed.
- Engaged in non-strenuous activities like conversing and video watching.
- Epworth sleepiness scale (ESS) used to rate sleepiness and simple reaction time task (SRT) performed.
- 180 trials executed.
Measures
- 3T Allegra magnetic resonance imaging
- T1-weighted three-dimensional-MPRAGE imaging
- Motion correction using PACE (Siemens)
- Mean intensity normalization
- LTRRW, LTRSD, PLUSRW, PLUSSD used for functional analysis
- Region of interest based analysis
Results
- Behavioral results-
- Increased ESS showed greater subjective sense of sleepiness after SD.
- Responses omitted after SD not for PLUS but for LTR.
- Slow RT for both PLUS and LTR.
- RW activation-
- Left hemisphere dominant activation observed in LTR in prefrontal (pre-central regions, insula, Brodman’s area and thalamus).
- Areas showed more activation in PLUS than LTR.
- These areas were left prefrontal region around left insula, left inferior parietal lobule, middle frontal gyrus and bilateral thalamus.
- No region more activated in LTR compared to PLUS.
- Cortical deactivation lesser for LTR than PLUS in RW.
- Activation after SD when compared to RW-
- PLUS and LTR showed activation in overlapping regions after SD than during RW.
- LTR and PLUS elicited smaller task related BOLD signal by Voxel-by-voxel analysis in the parietal region when compared to RW.
- Larger post SD increase in BOLD signal observed in left dorsolateral prefrontal cortex near middle frontal gyrus compared to RW (Poh & Chee, 2017).
- Prefrontal activation by LTR showed no significant difference after SD.
- Reduced deactivation after SD observed in left posterior cingulate and anterior medial frontal regions in voxel-by-voxel contrasts.
- ROI-based analyses showed effects of state and in posterior cingulated and anterior medial frontal regions. No significant state-by-task interaction found.
- RT inversely correlated with the anterior medial frontal region deactivation
- RT did not correlate with change in BOLD signal in posterior cingulated, left dorsolateral prefrontal, and thalamus or parietal regions.
Interpretation
- Greater parietal and prefrontal activation shown by PLUS than LTR in both states that matched the notion that when load of working memory is not excessive, additional processing resources are engaged by manipulation (Almklov et al., 2015).
- Left dorsomedial thalamus activation was more associated with PLUS. Previous experiments demonstrated activation of thalamus with increased working memory demand.
- The thalamic activation increase with prefrontal activation signified the existence of reciprocal connections between prefrontal cortex and dorsomedial thalamic nucleus. Sustained attention also increased thalamic activation. These mechanisms contributed to task related differences in thalamic activation (Yeo, Tandi & Chee, 2015).
- Deactivation of BOLD signal relative to baseline during task performance was pronounced with complex task in both the states. Deactivated anterior medial frontal and posterior cingulate regions were part of activated default network during passive conditions.
- Inverse relationship between RT and deactivation magnitude suggested greater deactivation is related to efficient task performance. After SD recruitment of cognitive resources are required in diminished capacity to engage in goal directed behaviours.
- Areas that showed an increase in task related activation after sleep deprivation can be considered as regions that play a compensatory role. The results of functional imaging prove that efficient processing of the brain is associated with an up-regulation in the activation of task related regions.
- The results from the study can also be used to interpret that when words are encoded without specific instructions, the respondents who belonged to old age have a tendency to show reduction or decline in activation of frontal regions of the brain. They also exhibit poor retrieval of memory. However, when environmental support that facilitates encoding was provided to them, the elderly participants displayed a bilateral or non-selective increase in activation of frontal areas. This was found to correspondingly improve mnemonic performances when the patients were compared to younger counterparts (Yeo, Tandi & Chee, 2015).
- It can also be interpreted that reduction in activation of occipital lobe is associated with impairment in sensory processing in elderly patients.
References
Almklov, E. L., Drummond, S. P., Orff, H., & Alhassoon, O. M. (2015). The effects of sleep deprivation on brain functioning in older adults. Behavioral sleep medicine, 13(4), 324-345.
Chee MW, Choo WC. (2004). Functional imaging of working memory after 24 hr of total sleep deprivation. The Journal of Neuroscience, 24(19), 4560-7.
Poh, J. H., & Chee, M. W. (2017). Degradation of cortical representations during encoding following sleep deprivation. Neuroimage, 153, 131-138.
Verweij, I. M., Romeijn, N., Smit, D. J., Piantoni, G., Van Someren, E. J., & van der Werf, Y. D. (2014). Sleep deprivation leads to a loss of functional connectivity in frontal brain regions. BMC neuroscience, 15(1), 88.
Yeo, B. T., Tandi, J., & Chee, M. W. (2015). Functional connectivity during rested wakefulness predicts vulnerability to sleep deprivation. Neuroimage, 111, 147-158.\
Behavioral/Systems/Cognitive
Functional Imaging of Working Memory after 24 Hr of Total
Sleep Deprivation
Michael W. L. Chee and Wei Chieh Choo
Cognitive Neuroscience Laboratory, SingHealth Research Laboratories, Singapore 169611, Singapore
The neurobehavioral effects of 24 hr of total sleep deprivation (SD) on working memory in young healthy adults was studied using
functional magnetic resonance imaging. Two tasks, one testing maintenance and the other manipulation and maintenance, were used.
After SD, response times for both tasks were significantly slower. Performance was better preserved in the more complex task. Both tasks
activated a bilateral, left hemisphere-dominant frontal–parietal network of brain regions reflecting the engagement of verbal working
memory. In both states, manipulation elicited more extensive and bilateral (L
R) frontal, parietal, and thalamic activation. After SD,
there was reduced blood oxygenation level-dependent signal response in the medial parietal region with both tasks. Reduced deactivation
of the anterior medial frontal and posterior cingulate regions was observed with both tasks. Finally, there was disproportionately greater
activation of the left dorsolateral prefrontal cortex and bilateral thalamus when manipulation was required. This pattern of changes in
activation and deactivation bears similarity to that observed when healthy elderly adults perform similar tasks. Our data suggest that
reduced activation and reduced deactivation could underlie cognitive impairment after SD and that increased prefrontal and thalamic
activation may represent compensatory adaptations. The additional left frontal activation elicited after SD is postulated to be task
dependent and contingent on task complexity. Our findings provide neural correlates to explain why task performance in relatively more
complex tasks is better preserved relative to simpler ones after SD.
Key words:
working memory; prefrontal cortex; cortical deactivation; sleep deprivation; functional imaging; BOLD fMRI
Introduction
Sleep deprivation (SD), even for one night, can result in dimin-
ished alertness and cognitive performance. Although the behav-
ioral changes accompanying SD have been studied extensively,
the underlying neural correlates of these changes have been less
well characterized, not the least because of the need to account for
the contributions of cognitive domain tested, task complexity,
arousal, and duration of SD (Kjellberg, 1975; Wilkinson, 1992).
In this study, we focused on how task complexity interacts with
state to modulate cortical activation as healthy young adults per-
formed working memory tasks.
We chose to study working memory because neuropsycholog-
ical (Horne, 1988; Wimmer et al., 1992; Harrison and Horne,
1998) and EEG studies (Werth et al., 1997; Cajochen et al., 1999)
suggest that physiological changes taking place in the frontal
lobes after SD contribute significantly to cognitive decline. How-
ever, frontal lobe dysfunction alone cannot account for why per-
formance is relatively preserved with moderately complex tasks
(Wilkinson, 1965; Hockey et al., 1998; Linde et al., 1999; Harrison
and Horne, 2000) but is degraded with simpler tasks (Kjellberg,
1975; Gillberg and Akerstedt, 1998). Given that SD is accompa-
nied by a lowering of arousal (Babkoff et al., 1991), higher task
complexity is thought to minimize performance decline by tem-
porarily increasing arousal or sustained attention (Wilkinson,
1965). Top-down increase in thalamic activation (Portas et al.,
1998) may be one means toward this because a reduction in tha-
lamic activation after SD has been associated with performance
decline (Thomas et al., 2000).
We chose to evaluate a single cognitive domain because diver-
gent results have been obtained from existing functional imaging
studies relating to SD, depending on the cognitive domain tested.
For example, frontal and parietal activation after SD has been
shown to increase in experiments involving verbal learning
(Drummond et al., 2000, 2001), decrease in experiments involv-
ing serial subtraction (Drummond et al., 1999; Thomas et al.,
2000), or show no change in an experiment testing attention
(Portas et al., 1998).
Even within a particular cognitive domain, frontal activation
may increase with task difficulty up to a point and then decrease
(Callicott et al., 1999), reflecting an overwhelming of processing
capacity, a loss of motivation (Jaeggi et al., 2003), or both. [Here,
the term “load” refers to the number of items that have to be
maintained in working memory (e.g., in a Sternberg-type main-
tenance task or n-back tasks). “Task complexity” refers to the
increase in types of cognitive process required to perform the task
(e.g., manipulation vs maintenance). “Difficulty” is used when
either or both of these conditions are fulfilled when similar cog-
nitive domains are tested; when comparing tasks tapping differ-
ent domains, subjective rating or response time (RT) is used to
Received Jan. 2, 2004; revised March 29, 2004; accepted March 31, 2004.
This work was supported by National Medical Research Council Grant 2000/0477, Biomedical Research Council
Grant 014, and The Shaw Foundation (4K/SIS/TFTM).
Correspondence should be addressed to Dr. Michael W. L. Chee, Cognitive Neuroscience Laboratory, 7 Hospital
Drive, #01-11, Singapore 169611, Singapore. E-mail: [email protected].
DOI:10.1523/JNEUROSCI.0007-04.2004
Copyright © 2004 Society for Neuroscience
0270-6474/04/244560-08$15.00/0
4560
•
The Journal of Neuroscience, May 12, 2004
•
24(19):4560 – 4567
gauge difficulty.] Subjective difficulty may have been excluded as
a potential source of divergent imaging results (Drummond and
Brown, 2001), but this assertion has not been tested explicitly.
To examine the interaction between state and task complexity,
we used a two-by-two experimental design to test working mem-
ory after 24 hr of total SD and rested wakefulness (RW). The less
demanding task engaged maintenance of information, whereas
the more demanding task required manipulation in addition to
maintenance. Short-term total SD, although artificial (chronic
SD is more common and has greater general relevance), affords
better experimental control. The
experiments were relatively
short because the benefit of task complexity is often tempo-
rary. Furthermore, the loss of interest with prolonged testing
results in a decline in arousal and performance (Wilkinson,
1965).
On the basis of previous work, we predicted that in both states,
manipulation would increase prefrontal (Smith et al., 1998;
D
’
Esposito et al., 1999) and parietal (Veltman et al., 2003) acti-
vation to a greater extent than maintenance. Furthermore, in
light of behavioral data showing that moderately complex tasks
are less affected than simpler tasks, we also expected that manip-
ulation would result in better preserved performance and elicit
disproportionately greater frontal lobe activation. Because sev-
eral parallels have been drawn between decline in prefrontal
function after SD and aging (Harrison et al., 2000), we used the
extensive work on aging and cognition (Reuter-Lorenz, 2002;
Cabeza et al., 2004) as a framework to in-
terpret our observations concerning the
modulation of activation after SD.
Materials and Methods
Subject characteristics.
Fourteen right-handed,
healthy undergraduate volunteers (five wom-
en; mean age, 23 years; range, 19
–
24) partici-
pated in the study after giving informed con-
sent. They were selected from a wider pool of
candidates who answered a questionnaire on
their sleeping habits and who kept a sleep diary
for 1 week. Only volunteers with habitual good
sleep, who slept no later than 1 A.M. and woke
up no later than 9 A.M., were studied. The par-
ticipants of this study slept an average of 7.2
0.9 hr per night in the week preceding SD. Vol-
unteers were screened for a history of excessive
daytime sleepiness and insomnia. None of the
volunteers had a history of psychiatric illness,
obstructive sleep apnea, narcolepsy, or periodic
leg movements in sleep, as ascertained by a
physician (W.C.C). None of the volunteers was
on medication. Alcohol and recreational drug use were excluded.
Experimental protocol.
Subjects were scanned twice, once during RW
and once after SD. The two scanning sessions were conducted 1 week
apart to minimize the possibility of residual effects of SD affecting cog-
nition of volunteers who underwent a SD scan before a RW scan (Van
Dongen et al., 2003). The order of scanning was counterbalanced across
subjects to reduce the potential influence of practice, learning, and order
effects on cortical activation. Subjects abstained from smoking, caffeine,
and other stimulants for 24 hr before being scanned. Alcohol was simi-
larly disallowed. While undergoing SD, subjects were monitored in the
laboratory from 9 P.M. onward. They were allowed to engage in non-
strenuous activities such as watching videos and conversing. They did not
interact with persons outside the laboratory. Every hour throughout the
study night and under supervision, subjects rated their sleepiness using
the Epworth sleepiness scale (ESS) and performed a simple reaction time
task (SRT). The SRT required that subjects respond by pressing the ap-
propriate key, depending on whether they saw a left- or right-pointing
arrow. Arrows appeared at random (1.0
–
5.0 sec) after the start of each
trial. One hundred eighty trials were executed during each testing ses-
sion. Scanning took place after 22.9
0.8 hr of wakefulness.
Experimental tasks.
Two working memory tasks were used (Fig. 1).
LTR evaluated maintenance and was adapted from previous work on
verbal working memory (Reuter-Lorenz et al., 2000). Four different up-
percase letters were presented for 0.5 sec, followed by a delay period of 3.0
sec, during which a fixation cross was displayed. A lowercase probe letter
was then presented for 1.5 sec, and this was followed by fixation for an
additional 0.5 sec. Subjects signaled a match or a nonmatch by pressing
one of two response buttons. Half the probes matched the target letters.
Response omissions were reported as a proportion of total possible
responses.
The control condition was designed to match for perceptual and mo-
tor responses. Four identical uppercase letters appeared for 0.5 sec. This
was followed by a shorter 0.3 sec delay period before the appearance of a
lowercase probe that matched the target in half the trials. Subjects sig-
naled a match or nonmatch using one of two response buttons.
PLUS was designed to engage manipulation of items retained in verbal
working memory. Two different letters were presented, and subjects were
instructed to shift each letter forward alphabetically and to keep in mind
the results. For example, if
“
B
”
and
“
J
”
were presented, subjects had to
remember
“
c
”
and
“
k
”
to be matched with the probe. Matches comprised
half the trials. Stimulus presentation sequence, timing, and control con-
dition were identical to that used in LTR.
Before scanning, each subject performed a practice run. Task and
control blocks each lasted 33 sec. Each block consisted of six trials (5.5 sec
Figure 1.
Schematic showing exemplars of stimuli used in LTR and PLUS and presentation timings. The control condition was
identical for both tasks.
Table 1. Behavioral data recorded during rested wakefulness and after sleep
deprivation (SD in parentheses)
Rested wakefulness
Sleep deprived
Measures of sleepiness
ESS
4.1 (4.1)
17.1 (4.0)***
Simple RT (msec)
378 (58)
394 (82)
LTR
Omitted responses (%)
0.2 (0.5)
4.0 (6.3)*
Accuracy
0.959 (0.049)
0.902 (0.097)**
RT (msec)
825 (80)
883 (110)**
PLUS
Omitted responses (%)
0.4 (1.1)
2.3 (3.8)
Accuracy
0.957 (0.055)
0.926 (0.086)
RT (msec)
786 (119)
860 (144)**
Significant differences across states using paired
t
test are indicated: *
p
0.05; **
p
0.005; ***
p
0.001.
Chee and Choo
•
fMRI of Working Memory after Sleep Deprivation
J. Neurosci., May 12, 2004
•
24(19):4560 – 4567
• 4561
derly, underscoring the need to explore a gamut of different tasks
before attempting to explain the neural basis for cognitive decline
in these states (Cabeza et al., 2004). An informative illustration:
when encoding words without specific instruction, elderly volun-
teers exhibited reduced frontal activation and poor memory re-
trieval. However, when provided with environmental support to
facilitate encoding, the elderly volunteers showed a nonselective
(bilateral) increase in frontal activation and correspondingly im-
proved mnemonic performance relative to their younger coun-
terparts (Logan et al., 2002). This suggests that the engagement of
compensatory neural responses may be contingent on the use of
specific mental operations or strategies.
A relative reduction of occipital lobe activation (Grady et al.,
1994; Madden et al., 1996; Cabeza et al., 1997) has been observed
in the elderly, and this finding appears to be task independent
(Cabeza et al., 2004). The basis for this reduction in activation is
unclear, although it has been suggested that sensory processing
might be impaired in the elderly (Li and Lindenberger, 2002). We
observed relatively trivial reduction in occipital deactivation after
SD in the present study. However, such reduction in occipital
activation has been observed (but not highlighted) in at least
three previous studies (Drummond et al., 1999, 2001; Habeck et
al., 2004).
References
Babkoff H, Caspy T, Mikulincer M (1991) Subjective sleepiness ratings: the
effects of sleep deprivation, circadian rhythmicity and cognitive perfor-
mance. Sleep 14:534
–
539.
Barch DM, Braver TS, Nystrom LE, Forman SD, Noll DC, Cohen JD (1997)
Dissociating working memory from task difficulty in human prefrontal
cortex. Neuropsychologia 35:1373
–
1380.
Cabeza R (2002) Hemispheric asymmetry reduction in older adults: the
HAROLD model. Psychol Aging 17:85
–
100.
Cabeza R, Grady CL, Nyberg L, McIntosh AR, Tulving E, Kapur S, Jennings
JM, Houle S, Craik FI (1997) Age-related differences in neural activity
during memory encoding and retrieval: a positron emission tomography
study. J Neurosci 17:391
–
400.
Cabeza R, Dolcos F, Graham R, Nyberg L (2002) Similarities and differences
in the neural correlates of episodic memory retrieval and working mem-
ory. NeuroImage 16:317
–
330.
Cabeza R, Daselaar M, Dolcos F, Prince SE, Budde M, Nyberg L (2004)
Task-independent and task-specific age effects on brain activity during
working memory, visual attention and episodic retrieval. Cereb Cortex
14:364
–
375.
Cajochen C, Foy R, Dijk DJ (1999) Frontal predominance of a relative in-
crease in sleep delta and theta EEG activity after sleep loss in humans.
Sleep Res Online 2:65
–
69.
Callicott JH, Mattay VS, Bertolino A, Finn K, Coppola R, Frank JA, Goldberg
TE, Weinberger DR (1999) Physiological characteristics of capacity
constraints in working memory as revealed by functional MRI. Cereb
Cortex 9:20
–
26.
Coull JT (1998) Neural correlates of attention and arousal: insights from
electrophysiology, functional neuroimaging and psychopharmacology.
Prog Neurobiol 55:343
–
361.
Craik FIM (1986) A functional account of age differences in memory. In:
Human memory and cognitive capabilities, mechanisms and perfor-
mances (Klix F, Hagendorf H, eds), pp 409
–
422: Amsterdam: Elsevier.
D
’
Esposito M, Postle BR, Ballard D, Lease J (1999) Maintenance versus ma-
nipulation of information held in working memory: an event-related
fMRI study. Brain Cogn 41:66
–
86.
Drummond SP, Brown GG (2001) The effects of total sleep deprivation on
cerebral responses to cognitive performance. Neuropsychopharmacology
25:S68
–
S73.
Drummond SP, Brown GG, Stricker JL, Buxton RB, Wong EC, Gillin JC
(1999) Sleep deprivation-induced reduction in cortical functional re-
sponse to serial subtraction. NeuroReport 10:3745
–
3748.
Drummond SP, Brown GG, Gillin JC, Stricker JL, Wong EC, Buxton RB
(2000) Altered brain response to verbal learning following sleep depriva-
tion. Nature 403:655
–
657.
Drummond SP, Gillin JC, Brown GG (2001) Increased cerebral response
during a divided attention task following sleep deprivation. J Sleep Res
10:85
–
92.
Esposito G, Kirkby BS, Van Horn JD, Ellmore TM, Berman KF (1999)
Context-dependent, neural system-specific neurophysiological concom-
itants of ageing: mapping PET correlates during cognitive activation.
Brain 122:963
–
979.
Gillberg M, Akerstedt T (1998) Sleep loss and performance: no
“
safe
”
dura-
tion of a monotonous task. Physiol Behav 64:599
–
604.
Grady CL, Maisog JM, Horwitz B, Ungerleider LG, Mentis MJ, Salerno JA,
Pietrini P, Wagner E, Haxby JV (1994) Age-related changes in cortical
blood flow activation during visual processing of faces and location.
J Neurosci 14:1450
–
1462.
Gray JR, Chabris CF, Braver TS (2003) Neural mechanisms of general fluid
intelligence. Nat Neurosci 6:316
–
322.
Gusnard DA, Raichle ME (2001) Searching for a baseline: functional imag-
ing and the resting human brain. Nat Rev Neurosci 2:685
–
694.
Gusnard DA, Akbudak E, Shulman GL, Raichle ME (2001) Medial prefron-
tal cortex and self-referential mental activity: relation to a default mode of
brain function. Proc Natl Acad Sci USA 98:4259
–
4264.
Habeck C, Rakitin BC, Moeller J, Scarmeas N, Zarahn E, Brown T, Stern Y
(2004) An event-related fMRI study of the neurobehavioral impact of
sleep deprivation on performance of a delayed-match-to-sample task.
Brain Res Cogn Brain Res 18:306
–
321.
Harrison Y, Horne JA (1998) Sleep loss impairs short and novel language
tasks having a prefrontal focus. J Sleep Res 7:95
–
100.
Harrison Y, Horne JA (2000) The impact of sleep deprivation on decision
making: a review. J Exp Psychol Appl 6:236
–
249.
Harrison Y, Horne JA, Rothwell A (2000) Prefrontal neuropsychological
effects of sleep deprivation in young adults
–
a model for healthy aging?
Sleep 23:1067
–
1073.
Hockey GR, Wastell DG, Sauer J (1998) Effects of sleep deprivation and user
interface on complex performance: a multilevel analysis of compensatory
control. Hum Factors 40:233
–
253.
Horne JA (1988) Sleep loss and
“
divergent
”
thinking ability. Sleep
11:528
–
536.
Jaeggi SM, Seewer R, Nirkko AC, Eckstein D, Schroth G, Groner R, Gutbrod
K (2003) Does excessive memory load attenuate activation in the pre-
frontal cortex? Load-dependent processing in single and dual tasks: func-
tional magnetic resonance imaging study. NeuroImage 19:210
–
225.
Kinomura S, Larsson J, Gulyas B, Roland PE (1996) Activation by attention
of the human reticular formation and thalamic intralaminar nuclei. Sci-
ence 271:512
–
515.
Kjellberg A (1975) Effects of sleep deprivation on performance of a
problem-solving task. Psychol Rep 37:479
–
485.
Li KZ, Lindenberger U (2002) Relations between aging sensory/sensorimo-
tor and cognitive functions. Neurosci Biobehav Rev 26:777
–
783.
Linde L, Edland A, Bergstrom M (1999) Auditory attention and multiat-
tribute decision-making during a 33 h sleep-deprivation period: mean
performance and between-subject dispersions. Ergonomics 42:696
–
713.
Logan JM, Sanders AL, Snyder AZ, Morris JC, Buckner RL (2002) Under-
recruitment and nonselective recruitment: dissociable neural mecha-
nisms associated with aging. Neuron 33:827
–
840.
Lustig C, Snyder AZ, Bhakta M, O
’
Brien KC, McAvoy M, Raichle ME, Morris
JC, Buckner RL (2003) Functional deactivations: change with age and
dementia of the Alzheimer type. Proc Natl Acad Sci USA 100:14504
–
14509.
Madden DJ, Turkington TG, Coleman RE, Provenzale JM, DeGrado TR,
Hoffman JM (1996) Adult age differences in regional cerebral blood
flow during visual world identification: evidence from H215O PET. Neu-
roImage 3:127
–
142.
Madden DJ, Turkington TG, Provenzale JM, Denny LL, Hawk TC, Gottlob
LR, Coleman RE (1999) Adult age differences in the functional neuro-
anatomy of verbal recognition memory. Hum Brain Mapp 7:115
–
135.
Manoach DS, Greve DN, Lindgren KA, Dale AM (2003) Identifying re
gional
activity associated with temporally separated components of working mem-
ory using event-related functional MRI. NeuroImage 20:1670
–
1684.
Mazoyer B, Zago L, Mellet E, Bricogne S, Etard O, Houde O, Crivello F, Joliot
M, Petit L, Tzourio-Mazoyer N (2001) Cortical networks for working
memory and executive functions sustain the conscious resting state in
man. Brain Res Bull 54:287
–
298.
McKiernan KA, Kaufman JN, Kucera-Thompson J, Binder JR (2003) A
4566
•
J. Neurosci., May 12, 2004
•
24(19):4560 – 4567
Chee and Choo
•
fMRI of Working Memory after Sleep Deprivation
parametric manipulation of factors affecting task-induced deactivation in
functional neuroimaging. J Cogn Neurosci 15:394
–
408.
Mecklinger A, Weber K, Gunter TC, Engle RW (2003) Dissociable brain
mechanisms for inhibitory control: effects of interference content and
working memory capacity. Brain Res Cogn Brain Res 18:26
–
38.
Miller MB, Van Horn JD, Wolford GL, Handy TC, Valsangkar-Smyth M,
Inati S, Grafton S, Gazzaniga MS (2002) Extensive individual differ-
ences in brain activations associated with episodic retrieval are reliable
over time. J Cogn Neurosci 14:1200
–
1214.
Owen AM, Evans AC, Petrides M (1996) Evidence for a two-stage model of
spatial working memory processing within the lateral frontal cortex: a
positron emission tomography study. Cereb Cortex 6:31
–
38.
Portas CM, Rees G, Howseman AM, Josephs O, Turner R, Frith CD (1998)
A specific role for the thalamus in mediating the interaction of attention
and arousal in humans. J Neurosci 18:8979
–
8989.
Postle BR, Berger JS, D
’
Esposito M (1999) Functional neuroanatomical
double dissociation of mnemonic and executive control processes con-
tributing to working memory performance. Proc Natl Acad Sci USA
96:12959
–
12964.
Reuter-Lorenz P (2002) New visions of the aging mind and brain. Trends
Cogn Sci 6:394
–
400.
Reuter-Lorenz PA, Jonides J, Smith EE, Hartley A, Miller A, Marshuetz C,
Koeppe RA (2000) Age differences in the frontal lateralization of verbal
and spatial working memory revealed by PET. J Cogn Neurosci 12:174
–
187.
Rypma B, D
’
Esposito M (2000) Isolating the neural mechanisms of age-
related changes in human working memory. Nat Neurosci 3:509
–
515.
Schumacher EH, Lauber E, Awh E, Jonides J, Smith EE, Koeppe RA (1996)
PET evidence for an amodal verbal working memory system. NeuroImage
3:79
–
88.
Smith EE, Jonides J, Marshuetz C, Koeppe RA (1998) Components of verbal
working memory: evidence from neuroimaging. Proc Natl Acad Sci USA
95:876
–
882.
Talairach J, Tournoux P (1988) Co-planar stereotaxic atlas of the human
brain. New York: Thieme Medical Publishers.
Thomas M, Sing H, Belenky G, Holcomb H, Mayberg H, Dannals R, Wagner
H, Thorne D, Popp K, Rowland L, Welsh A, Balwinski S, Redmond D
(2000) Neural basis of alertness and cognitive performance impairments
during sleepiness. I. Effects of 24 h of sleep deprivation on waking human
regional brain activity. J Sleep Res 9:335
–
352.
Van Dongen HP, Maislin G, Mullington JM, Dinges DF (2003) The cumu-
lative cost of additional wakefulness: dose-response effects on neurobe-
havioral functions and sleep physiology from chronic sleep restriction
and total sleep deprivation. Sleep 26:117
–
126.
Veltman DJ, Rombouts SA, Dolan RJ (2003) Maintenance versus manipu-
lation in verbal working memory revisited: an fMRI study. NeuroImage
18:247
–
256.
Wei X, Yoo SS, Dickey CC, Zou KH, Guttmann CR, Panych LP (2004)
Functional MRI of auditory verbal working memory: long-term repro-
ducibility analysis. NeuroImage 21:1000
–
1008.
Werth E, Achermann P, Borbely AA (1997) Fronto-occipital EEG power
gradients in human sleep. J Sleep Res 6:102
–
112.
Wilkinson RT (1965) Sleep deprivation. In: Physiology of human survival
(Edholm R, Bacharach A, eds), pp 399
–
430. London: Academic.
Wilkinson RT (1992) Sleep, arousal and performance. In: The measure-
ment of sleepiness (Broughton RJ, Ogilvie RD, eds), pp 254
–
265. Boston:
Birkhauser.
Wimmer F, Hoffmann RF, Bonato RA, Moffitt AR (1992) The effects of
sleep deprivation on divergent thinking and attention processes. J Sleep
Res 1:223
–
230
