fMRI during natural sleep as a method to study brain function
during early childhood
Elizabeth Redcay,a,⁎Daniel P. Kennedy,band Eric Courchesneb,c
aDepartment of Psychology, University of California, San Diego, La Jolla, CA 92037, USA
bDepartment of Neurosciences, University of California, San Diego, La Jolla, CA 92037, USA
cCenter for Autism Research, Rady Children’s Hospital San Diego, San Diego, CA 92123, USA
Received 23 March 2007; revised 30 July 2007; accepted 2 August 2007
Available online 17 August 2007
Many techniques to study early functional brain development lack the
whole-brain spatial resolution that is available with fMRI. We utilized
a relatively novel method in which fMRI data were collected from
children during natural sleep. Stimulus-evoked responses to auditory
and visual stimuli as well as stimulus-independent functional networks
were examined in typically developing 2–4-year-old children. Reliable
fMRI data were collected from 13 children during presentation of
auditory stimuli (tones, vocal sounds, and nonvocal sounds) in a block
design. Twelve children were presented with visual flashing lights at
2.5 Hz. When analyses combined all three types of auditory stimulus
conditions as compared to rest, activation included bilateral superior
temporal gyri/sulci (STG/S) and right cerebellum. Direct compar-
isons between conditions revealed significantly greater responses to
nonvocal sounds and tones than to vocal sounds in a number of brain
regions including superior temporal gyrus/sulcus, medial frontal
cortex and right lateral cerebellum. The response to visual stimuli was
localized to occipital cortex. Furthermore, stimulus-independent
functional connectivity MRI analyses (fcMRI) revealed functional
connectivity between STG and other temporal regions (including
contralateral STG) and medial and lateral prefrontal regions.
Functional connectivity with an occipital seed was localized to occipital
and parietal cortex. In sum, 2–4 year olds showed a differential fMRI
response both between stimulus modalities and between stimuli in the
auditory modality. Furthermore, superior temporal regions showed
functional connectivity with numerous higher-order regions during
sleep. We conclude that the use of sleep fMRI may be a valuable tool
for examining functional brain organization in young children.
© 2007 Elsevier Inc. All rights reserved.
Keywords: Auditory; Visual; Functional connectivity; Sounds
The transition from infancy to the preschool years is a time of
dramatic and dynamic neural and cognitive development. For
example, brain volume shows a 4-fold increase between birth and
about 4 years of age (Courchesne et al., 2000). Synapse density in
middle frontal gyrus increases nearly 70% between birth and
4 years of life when it reaches its peak (Huttenlocher and
Dabholkar, 1997). Dendritic arbors in frontal cortex grow from 3–
11% of adult length at birth to 50% of adult length by age 2 years
while arbors in visual cortex reach adult length by age 2
(Huttenlocher, 2002). Cognitive growth during this time is also
rapid. For example, children progress from only a few words in
their expressive vocabulary at 1 year to full sentences by 3 years of
Such dramatic anatomical and behavioral changes must be
reflected in changes in brain function during this time. In fact,
event-related potential (ERP) studies reveal electrophysiological
changes from infancy to the preschool years underlying behaviors
such as face processing (e.g., Carver et al., 2003) and language
(review: Friederici, 2006). However, electrophysiological methods
lack detailed anatomical information. Blood Oxygenated Level
Dependent (BOLD) fMRI is a non-invasive tool used to pinpoint
the specific brain regions underlying cognitive, social, and
perceptual processes. Few studies have directly examined brain
function in infants and young children with fMRI due to the
difficulty in acquiring such data without motion artifact. For this
reason, our knowledge of the functional brain changes seen in the
early years of life relies primarily on measures with relatively
poor spatial localization capabilities such as ERP, lesion, or
anatomy–behavior correlation studies. In order to obtain reliable
fMRI data in infants and children, a few studies have been
conducted while children were sedated (visual: Born et al., 1996;
Martin et al., 1999; Morita et al., 2000; Yamada et al., 2000; Sie
et al., 2001; Marcar et al., 2004; auditory and visual: Souweidane
et al., 1999; Altman and Bernal, 2001). Sedation is not ethical for
use with healthy, typically developing children and thus, these
past studies involved children who were clinical patients sus-
NeuroImage 38 (2007) 696–707
⁎Corresponding author. 8110 La Jolla Shores Dr., Suite 201, La Jolla, CA
92037, USA. Fax: +1 858 551 7931.
E-mail address: email@example.com (E. Redcay).
Available online on ScienceDirect (www.sciencedirect.com).
1053-8119/$ - see front matter © 2007 Elsevier Inc. All rights reserved.
pected of having brain pathology but with negative findings on
clinical MRI. Such a sample may still include children with brain
abnormalities (e.g., seizures, etc.), since structural MRI is only
sensitive enough to detect gross anatomical brain abnormalities.
An alternative is to acquire functional MRI data from children
during natural sleep. This non-invasive method allows for the
acquisition of fMRI data from healthy, typical volunteers recruited
from the community.
Two groups have previously examined BOLD fMRI response
to auditory stimulation during sleep in infants (Anderson et al.,
2001; Dehaene-Lambertz et al., 2002). In the Anderson et al.
(2001) study, BOLD activity was detected in response to tones as
compared to rest within superior temporal regions in 14 of 20
neonates. Of those 14 neonates, 9 showed BOLD signal decreases
during tone presentation. In the study by Dehaene-Lambertz et al.
(2002) twenty 2–3-month-old infants were placed in the scanner
awake. During fMRI acquisition, 5 were judged to be completely
asleep based on behavior, 9 showed ambiguous levels of
wakefulness, and 6 were awake. They found bilateral superior
temporal activation to both forward and backward speech and a
greater response to forward than backward speech in left angular
gyrus. A third group has recorded fMRI data from a 6-year-old
boy who fell asleep during a language mapping study (Wilke et
al., 2003). The authors report strikingly similar patterns of
activation in bilateral superior temporal lobes during both sleep
and wake states.
A number of basic questions remain regarding the utility of the
sleep fMRI technique in early childhood. First, to what degree is
BOLD activity differentially modulated by external stimuli during
sleep? The Anderson et al. study only presented one auditory
stimulus type and the Dehane-Lambertz et al. study contained a
majority of infants who were awake for at least portions of the
experiment. In the current study, we examined whether presenta-
tion of auditory and visual stimuli to 2–4 year olds would produce
a differential BOLD response both across and within sensory
modalities during sleep. We predicted that stimulus-evoked BOLD
response to auditory and visual stimuli would be seen within
separable auditory and visual regions, respectively, and further-
more, that the BOLD response within the auditory modality would
vary by auditory stimulus type.
A second question is whether stimulus-independent functional
networks can be examined in the sleeping young child. To address
this question, we utilized a technique called functional con-
nectivity MRI (fcMRI) to reveal the temporal correlation of
spontaneous low frequency oscillations across brain regions. The
use of fcMRI during rest has revealed correlated stimulus-
independent activity within sensory systems including sensor-
imotor, auditory, and visual regions (Biswal et al., 1995; Cordes et
al., 2000; Nir et al., 2006) and also within higher-order associative
regions including prefrontal and parietal regions (Greicius et al.,
2003; Fox et al., 2005, 2006; Fransson, 2005; Vincent et al., 2006;
Seeley et al., 2007). Examination of these networks with fcMRI
during wakeful and sleeping adults shows similar functional
network maps across states suggesting the examination of
stimulus-independent fcMRI is relatively state-independent (Fu-
kunaga et al., 2006). In the current study, we performed a
functional connectivity analysis to determine whether stimulus-
independent functional networks could be identified during sleep
in children. We predicted stimulus-independent functional con-
nectivity patterns would be similar to stimulus-evoked patterns of
Functional imaging data were collected from a total of 21
children (7F, 14M) with no known neurological or psychological
disorders. Six of the 21 children were presented with visual stimuli
only. Nine of the 21 children were presented with auditory stimuli
only. Six of the 21 children were presented with both types of
experiments (separately) This resulted in a total of 12 successful
scan acquisitions for the visual experiment (mean age=46.4±
6.7 months) and 15 successful scan acquisitions for auditory
experiments (mean age=46.9±9.7 months). Two of the 15 scans
from auditory experiments were excluded due to excessive motion
artifacts (see criterion below) (see Table 1 for participant
information). All children were recruited from magazines and
flyers in the community as part of an on-going longitudinal
structural MRI study in our laboratory. The Institutional Review
Board of Children’s Hospital and the University of California, San
Diego approved this study. Parents of the participants gave
informed written consent for their child to participate in this study
and were compensated monetarily for their time. Hearing was
reported by parents as normal for all participants on which a
Family Medical History questionnaire was obtained. This form was
Participants information for auditory and visual experiments
Sex Cognitive score
‘A’ refers to the auditory experiment; ‘V’ refers the visual experiment.
Unless otherwise noted, cognitive score refers to the Composite score from
the Mullen Scales of Early Learning.
⁎Denotes participants whose date of cognitive testing was greater than
2 months from scan acquisition
aDenotes Full Scale IQ from the Weschler Intelligence Test.
bDenotes a score taken from a child who was non-compliant at time of
testing. Follow-up testing 6 months later revealed a Composite Score within
cDenotes General Conceptual Ability from the Different Abilities Test.
Means (standarddeviations)for the auditory andvisualexperiment aregiven
at the bottom of the table.
697 E. Redcay et al. / NeuroImage 38 (2007) 696–707
revealed a greater extent and number of brain regions. This finding
suggests that functional connectivity analyses allow for identifica-
tion of whole networks while stimulus-evoked analyses show
activation in portions of the network which are differentially
engaged for the specific type of stimulus presentation. An
exception is seen in the cerebellum, two occipital regions, and
the putamen. Stimulus-evoked activations to tones and nonvocal
sounds were seen in these regions but not in the functional
connectivity analyses with left or right STG regions. Other
stimulus-evoked and fcMRI studies have shown activation of the
cerebellum during stimulus-evoked fMRI but not stimulus-
independent, resting fcMRI analyses (Cordes et al., 2000). These
findings suggest that certain regions which are active during
stimulus-evoked analyses, such as the cerebellum, may not be part
of a specific functional network, but rather may be engaged for
processing auditory or other stimulus types when needed. This
hypothesis is consistent with a proposed role of the cerebellum as a
general purpose structure whose role is to predict and strategically
prepare the necessary neural systems needed to perform a variety
of different functions (Courchesne and Allen, 1997).
The use of sleep fMRI in the study of typical and atypical
development poses several advantages over other methods of
developmental cognitive neuroscience. First, fMRI allows for the
identification of specific cortical and sub-cortical substrates with
relatively good anatomical spatial resolution. Recording during
sleep strongly minimizes artifacts or loss of participant data due to
motion artifact. Second, sleep fMRI allows for a comparable state
of eyes-closed passive perception across participants. Often studies
of children and particularly those with developmental disorders are
not only measuring stimulus specific effects but also those related
to differences in anxiety, motivation, arousal state, or attention.
When comparing typically with atypically developing children,
differences in brain activations may be due to these confounds
rather than the stimulus in question. Third, sleep fMRI allows for
the study of stimulus-independent fluctuations in BOLD signal
across different ages from infancy to adulthood which may provide
valuable insight into the development of these and other functional
networks. Further, our findings suggest stimulus-independent
functional connectivity can reveal the functional organization of
entire networks which may be missed by stimulus-evoked analyses
alone. As shown in this study, fcMRI can identify regions involved
in stimulus-evoked analyses without limiting findings to a specific
type of stimulus presentation. This method can be applied to
children with developmental disorders with known abnormalities
of functional connectivity such as autism (Horwitz et al., 1988; Just
et al., 2004; Villalobos et al., 2005). Of course, a limitation of sleep
fMRI is that the neural response to certain stimuli during sleep is
not always as predicted from the awake state. Furthermore, future
research will need to address the question of how different sleep
stages may affect different patterns of brain activations. It will also
be important to determine how these differential BOLD responses
during sleep relate to behavioral abilities in the awake child.
Converging evidence from sleep fMRI and awake behavioral
performance could enhance understanding of early functional brain
The authors are grateful to the parents and children who
participated in this study. We thank Dr. Cindy Carter for
psychological testing, Vera Grindell, Anne Erickson, Grace Kim,
Cindy Hsu, and Randy Wu for assistance with data collection, and
Dr. Saygin and colleagues for sharing their sound stimuli. This
work was supported by the National Institutes of Health grants
RO1-NS-19855 and MH-36840 and a gift from the Donald C. and
Elizabeth M. Dickinson Foundation awarded to E.C.
Appendix A. Supplementary data
Supplementary data associated with this article can be found, in
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