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Clinical Neurophysiology 125 (2014) 675–684
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Clinical Neurophysiology
journal homepage: www.elsevier.com/locate/clinph
Electroencephalographic activity of preterm infants is increased
by Family Nurture Intervention: A randomized controlled trial
in the NICU
Martha G. Welch a,b,c,d,⇑,1, Michael M. Myers a,b,d,1, Philip G. Grieve b,e, Joseph R. Isler b, William P. Fifer a,b,d,
Rakesh Sahni b, Myron A. Hofer a,d, Judy Austin f, Robert J. Ludwig a, Raymond I. Stark b, the FNI Trial Group2
a
Department of Psychiatry, Columbia University College of Physicians & Surgeons, New York, NY 10032, USA
Department of Pediatrics, Columbia University College of Physicians & Surgeons, New York, NY 10032, USA
c
Department of Pathology & Cell Biology, Columbia University College of Physicians & Surgeons, New York, NY 10032, USA
d
Department of Developmental Neuroscience, New York State Psychiatric Institute, New York, NY 10032, USA
e
Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA
f
Mailman School of Public Health, Columbia University, New York, NY 10032, USA
b
a r t i c l e
i n f o
Article history:
Accepted 17 August 2013
Available online 17 October 2013
Keywords:
Maternal separation
Mother–infant intervention
EEG
Premature birth
Brain maturation
h i g h l i g h t s
Family Nurture Intervention (FNI) is designed to facilitate affective connections between prematurely
born infants and their mothers.
At term age, prematurely born infants with FNI had robust increases in frontal brain activity.
Promoting early nurturing interactions may improve neurobehavioral outcomes of preterm infants.
a b s t r a c t
Objective: To assess the impact of Family Nurture Intervention (FNI) on electroencephalogram (EEG)
activity in preterm infants (26–34 weeks gestation).
Methods: Two groups were tested in a single, level IV neonatal intensive care unit (NICU; standard care or
standard care plus FNI) using a randomized controlled trial design. The intervention consists of sessions
designed to achieve mutual calm and promote communication of affect between infants and their mothers throughout the NICU stay. EEG recordings were obtained from 134 infants during sleep at 35 and
40 weeks postmenstrual age (PMA). Regional brain activity (power) was computed for 10 frequency
bands between 1 and 48 Hz in each of 125 electrodes.
Results: Near to term age, compared to standard care infants, FNI infants showed robust increases in EEG
power in the frontal polar region at frequencies 10 to 48 Hz (20% to 36% with p-values <0.0004). Effects
were significant in both quiet and active sleep, regardless of gender, singleton-twin status, gestational
age (26–30 or 30–35 weeks) or birth weight (<1500 or >1500 g).
Conclusion: FNI leads to increased frontal brain activity during sleep, which other investigators find predictive of better neurobehavioral outcomes.
Significance: FNI may be a practicable means of improving outcomes in preterm infants.
Ó 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights
reserved.
1. Introduction
⇑ Corresponding author. Address: New York State Psychiatric Institute, 1051
Riverside Drive, Unit 40, New York, NY 10032, USA. Tel.: +1 212 543 5101; fax: +1
212 253 4234.
E-mail address: [email protected] (M.G. Welch).
1
These authors contributed equally to the work.
2
The FNI Trial Group members: Ladan Afifi, Howard F. Andrews, David A. Bateman,
Amy Bechar, Beatrice S. Beebe, Susan A. Brunelli, Kathryn E. Carnazza, Christine Y.
Chang, Patricia A. Farrell, Ewelina S. Fiedor, Amie A. Hane, Qais Karim, Shanna
Kofman, Yasmine A. Koukaz, John M. Lorenz, Mary T. McKiernan, David P. Merle,
Richard A. Polin, Sorana Sopterian.
Preterm birth at <37 weeks gestational age (GA) in the United
States has an incidence of 12% (Hamilton et al., 2013). The problem
addressed by this current study is that accompanying early
preterm birth is a period of prolonged physical and emotional
separation of mothers and infants during neonatal care with
increased risk for adverse outcomes during subsequent growth
and development. This vulnerability manifests as neurobehavioral
disorders that include attention deficits (Johnson and Marlow,
1388-2457/$36.00 Ó 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
http://dx.doi.org/10.1016/j.clinph.2013.08.021
676
M.G. Welch et al. / Clinical Neurophysiology 125 (2014) 675–684
2011), executive dysfunction (Baron et al., 2012; Peterson et al.,
2000), depression and psychotic disorders (Nosarti et al., 2012),
and autism spectrum disorder (Pinto-Martin et al., 2011). Numerous preclinical and clinical studies over the course of the past fifty
years have confirmed that early mother infant separation leads to a
wide array of adverse physiological and behavioral consequences
that persist throughout life (Coe et al., 1988; Hofer, 1996; Sanchez
et al., 2001). However, other preclinical studies indicate that
increasing mother/infant interactions, such as buffered stress responses, can have positive effects on outcome (Meaney et al.,
1996). Over the past two decades, specific interventions directed
at premature infant care in Neonatal Intensive Care Units (NICU),
such as Newborn Developmental Care and Assessment Program
(NIDCAP) (Als et al., 1994, 2012), skin-to-skin care (Conde-Agudelo
et al., 2011, Feldman et al., 2002) and massage therapy (Field et al.,
2006, 2010, Vickers et al., 2004), have shown significant effects on
outcomes. However, these interventions are not universally accepted
and further studies are necessary to document efficacy in preterm infants (Conde-Agudelo et al., 2011, Ohlsson and Jacobs, 2013).
This research study tests a new approach for improving development of preterm infants, Family Nurture Intervention (FNI). The distinguishing feature of FNI is that the intervention staff facilitates
communication of affect and physiologic co-regulation between
mother and infant. The intervention starts early and continues over
the full course of hospitalization, thereby minimizing the effects of
mother–infant separation in the Neonatal Intensive Care Unit
(NICU). The intervention includes mother and infant scent cloth exchange, sustained touch and vocal soothing in the isolette with eye
contact, wrapped or skin-to-skin holding and family-based support
sessions (Welch et al., 2012) (see Methods below).
FNI was based both on a method used to treat emotional,
behavioral and developmental disorders in older children (Welch
et al., 2006) and on basic research in animal models that revealed
sensorimotor, olfactory and nurture-based activities within normal mother–infant relationships (Hofer, 1975, 1994, 1996; Myers
et al., 1989a,b). In recent laboratory studies, central neural mechanisms have been found for these effects, involving epigenetic
regulation of gene expression patterns in specific brain regions,
from infancy to adulthood, as a result of variations in early
mother-infant interactions (Meaney et al., 1996; Meaney, 2001;
Jensen and Champagne, 2012; Zhang et al., 2013; Caldji et al.,
2011). FNI can be safely and feasibly implemented in a level IV
NICU without any negative impact on length of stay (Welch
et al., 2013).
Quantitative characterization of features of the EEG unique to
early development provides state-dependent indices for tracking
changes in specific neurophysiologic mechanisms critical for normal development of cortical function (Grieve et al., 2005, 2007,
2008; Isler et al., 2005; Myers et al., 1997, 1993, 2012; Sahni
et al., 1995, 2005). The impact of prior NICU interventions on brain
development has been assessed using electroencephalogram (EEG)
measures of complexity and coherence of brain activity during
sleep (Als et al., 2012; Kaffashi et al., 2012; Ludington-Hoe et al.,
2006). Prior studies have found that preterm infants suffer from
functional abnormalities mediated by the frontal cortex, including
attention, emotion regulation, language and cognition (Baron et al.,
2012; Johnson and Marlow, 2011; Nosarti et al., 2012; Peterson
et al., 2000; Pinto-Martin et al., 2011). Other studies have found
that activity (power) at higher frequencies measured during sleep
in preterm and term infants is predictive of Bayley neurobehavioral
scores later in development (Scher et al., 1996). This current study
obtained high-density, 124-lead, EEG recordings as a novel means
to assess changes in brain activity from a NICU intervention. The
current findings show near term age that the FNI group shows
highly significant increases in EEG power in high frequency bands
in the frontal cortex.
2. Methods
2.1. FNI trial design
Data for this study were obtained in a single-center, parallel
group, randomized controlled trial (RCT) in the level IV NICU at
Morgan Stanley Children’s Hospital of New York at Columbia University Medical Center. ClinicalTrials.gov has registered this trial
(#NCT01439269). Columbia University Medical Center Institutional Review Board approved all recruitment, consent, and study
procedures. The target enrollment for this study was 150 infants.
The original protocol restricted the gestational ages of the infants
to 26 to 32 weeks 6 days. After eight months of enrollment, we obtained approval to increase the age to 34 weeks 6 days in order to
increase the rate of enrollment, but the target enrollment of 150
infants was not changed. Excluded were mothers that did not
understand and speak English, or had a history of drug addiction
or severe mental illness. Entry into the study required that families
have at least one adult other than the mother in the home. Excluded infants were those with a birth weight below the third percentile for gestational age or significant congenital defects. Shown
in the consort chart (Supplementary Figure S1) are the number of
eligible infants and consents obtained.
2.2. FNI activities and procedures
Following consent, mothers assigned to the FNI group met with
Nurture Specialists who worked with the mothers and their families throughout the study to facilitate all aspects of the intervention. Mothers of infants assigned to the SC condition received the
care that is standard for infants admitted to the NICU. The timeline
of the intervention and the sequence of mother-infant interactions
are depicted in Fig. 1.
The first FNI activities took place with the infant confined to isolette care. As soon as possible after birth, the mothers started reciprocal scent cloth exchanges. Two small cotton scent cloths were
given to the mothers, one to wear in their bra and the other to
place under the head of their infant. Mothers were encouraged to
repeat this cycle at each visit to the NICU. As infants became more
stable, Nurture Specialists facilitated FNI mothers in making affective contact with their infants through the ports of the isolette,
using firm and sustained touch and ‘containment’, speaking emotionally to their infants in their native language and when possible,
making eye contact. When infants were medically able to leave the
incubator, Nurture Specialists helped FNI mothers to engage in
skin-to-skin, or non-skin-to-skin holding to continue vocal
soothing and eye to eye contact. Mothers were facilitated in engaging regularly in these activities for a minimum of 1 h at a time.
When family members were available, the Nurture Specialist
Fig. 1. FNI Timeline. (A) Scent Cloth exchange began immediately after enrollment.
(B) Sustained Touch and Vocal Soothing began in the isolette as soon as infant was
clinically stable and continued throughout stay. (C) Wrapped and Skin to Skin
Holding took place as soon as it was clinically appropriate for the infant to come out
of the incubator. (D) Family sessions occurred mainly near the end of the NICU stay.
M.G. Welch et al. / Clinical Neurophysiology 125 (2014) 675–684
engaged them in sessions that discussed the importance of the FNI
activities between mother and infant, and offered support to the
families with ongoing problems and with their needs arising from
the arrival of their new infant.
2.3. EEG acquisition and sleep state coding
EEG recording used 128-electrode data acquisition systems
(EGI, Inc., Eugene, Oregon); however, only 124 leads are used in infants. Data were obtained between 11 am and 4 pm within
30 min after a normally scheduled feeding. A study session of
90 min duration was required to acquire 60 min of EEG data.
The details of EEG acquisition are described in prior work (Grieve
et al., 2008) Following consultation with the manufacturer of the
EEG system, we used special methods to maintain electrode/scalp
contact, including covering the electrode net with plastic wrap to
diminish evaporation of the saline in the electrode sponges and
covering the net and plastic wrap with an elastic material (Surgilast). Application of the net and these extra measures usually took
about 5 min. These procedures generally allowed impedances to be
kept below 50 kilo ohms per manufacturer’s recommendation. The
EEG was sampled at 1000 samples/s using a vertex reference. The
voltage from each lead was band-pass filtered from 0.1 to 400 Hz
and then digitized with 16 bits per sample at the rate of 1000 samples per second. Then, in software, data were re-referenced to the
average of the 124 lead EEG montage and processed to obtain measures of power (lV2) at specific frequencies for each electrode. The
negative of the average reference approximates the voltage at the
vertex lead as referenced to a point at infinity, thus producing
the 125th lead.
Research assistants performed visual coding of quiet and active
sleep, indeterminate, awake and crying states once each minute.
This coding was done continuously throughout the EEG study with
behavioral criteria previously shown to be appropriate for preterm
infants (Stefanski et al., 1984).
2.4. EEG signal artifact rejection
677
power in the highest frequency band (37–48 Hz), then data for
all frequency bands for that lead were set to missing.
With elimination of outliers and acceptance of a minimum of
3 min of EEG data within each sleep state to increase the stability
of measures of EEG power, the median power for all epochs of active sleep and quiet sleep for each lead and frequency band was
determined. This allowed the inclusion of 293 early and near term
studies (129 SC, 164 FNI) for AS analyses and 290 early and late
term studies (127 SC, 163 FNI) in the QS analyses. In both AS and
QS, there was a trend for a greater fraction of SC studies to be excluded as compared with the fraction of FNI studies that were excluded. However, in neither state were these group differences in
exclusions significantly different (AS: X2 = 2.52, p = 0.11; QS:
X2 = 3.04, p = 0.08).
EEG studies were divided into 2 age groups; preterm age (33.8–
36.9 weeks PMA) and a near term age (37.2–44.4 weeks PMA). 80%
of the preterm age studies and 25% of the near term age studies
were conducted in the NICU. The remaining studies were done in
the follow-up clinic. These percentages did not differ between
the study groups. For overall descriptive purposes, the first phase
of the analyses performed t-tests to characterize differences between FNI and SC for each lead, for each frequency band, for each
sleep state, and for each of the two study ages.
To determine whether group differences were statistically significant, ANOVAs of log EEG power for each study age group
were conducted for each of the five regions (frontal polar, frontal, temporal, parietal, occipital) (Fig. 2) for each of the 10 frequency bands and for each sleep state. These analyses had one
between-subjects factor (FNI vs. SC) and one within-subjects factor (left hemisphere, right hemisphere). Gestational age at birth
and PMA at the time of the EEG studies were included as
covariates.
When a given subject had more than one study within an age
range, results were averaged over the multiple studies within that
range. Approximately one third of the infants had multiple studies
within the early range and another third within the near to term
age range. The distribution of multiple versus single studies was
not significantly different between the two groups.
Multiple steps were taken to diminish inclusion of EEG data
contaminated by movement-related or other sources of non-cortical electrical activity. The standard deviation of voltage was computed for each 30-s epoch of each lead. Individual lead data were
excluded if the standard deviation of the lead exceeded 50 lV.
Epochs were excluded if more than 20 of the 125 leads exceeded
the standard deviation criterion and entire studies were excluded
if more than 80% of their epochs were excluded.
2.5. EEG power analysis, outlier rejection and statistical analyses
After dropping all defined artifacts, data were available from at
least one EEG study for each of 134 infants (63 SC, 71 FNI). From
these data, EEG power was computed using 1 s FFTs for each of
the 125 leads. Average power for each of 10 frequency bands (1–
3 , 4–6, 7–9, 10–12, 13–15, 16–18, 19–21, 22–24, 25–36 and 37–
48 Hz) was computed for 30-s epochs throughout the session.
To define outliers in the power data, regression analyses of log
power versus PMA at the time of the recording were conducted for
each lead, frequency band and sleep state (2500 total analyses; 125
leads 10 bands 2 states). Outliers from the regression line were
defined when residuals with Studentized value exceeded 1.98 (i.e.
p 0.05 with df 300). These values were set to missing. Finally,
muscle activity can contribute to outlier values of power in a lead
at nearly all frequencies. As a percentage of EEG power in a band,
these outliers are larger in high frequency bands (Shackman
et al., 2009). Accordingly, to limit the contribution of muscle activity, if data from a lead were set to missing because of excessive
Fig. 2. Schematic of high density EEG net. The 124 electrodes in the EEG net are
distributed within ten standard brain regions for the regional analyses of the study.
Note 10 midline leads (open circles) were excluded from statistical analyses by
region.
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M.G. Welch et al. / Clinical Neurophysiology 125 (2014) 675–684
Within each age group 100 tests were conducted (10 frequency
bands 5 regions 2 sleep states), producing p-values that reflected the main effects of treatment. To control for multiple testing, we employed the False Discovery Rate procedure (Benjamini
and Hochberg, 1995) with a threshold set at 10%. We performed
additional analyses on subsets of infants with EEG studies who
had EEG studies at both ages (33 SC, 43 FNI). These were group
by repeated measures (age) ANOVAs and were limited to left frontal polar power in the 19–21 Hz band.
the early and near term studies. Results obtained at the near to
term age range indicate there were highly significant effects of
the intervention (red to dark brown electrodes, lower sets of electrodes in Figs 3 and 4). In both sleep states, the intervention led to
regional increases in power, particularly in the most frontal electrodes at frequencies above 10 Hz. At the early study age range,
there were no robust differences in power between the two groups.
3. Results
To test whether the individual electrode differences in Figs 3
and 4 were regionally significant, we conducted a series of ANOVAs
in which the main effect of FNI vs. SC was determined across ten
regions (Fig. 2), ten frequency bands, two sleep states, and both
age ranges. Data from left and right hemispheres were included
as a within-subjects factor in these analyses and gestational age
at birth and PMA at the time of EEG study were covariates.
ANOVAS found no significant intervention group by hemisphere
interactions (Supplementary Tables S5–S8). Thus, results only focus on the main effect of intervention group. Identification of the
subset of p-values that passed the 10% False Discovery Rate threshold revealed that near to term age, power above 10 Hz in the leads
over the frontal polar cortex was significantly affected by the intervention. As shown in Table 1, there was increased power in this region in FNI infants that ranged from 19% to 36% greater than that in
SC infants. The effects of FNI appeared to be more pronounced in
QS, although robust changes were found in both sleep states. At
frequencies above 10 Hz, seven of the QS and six of the AS ANOVA
tests passed the 10% FDR threshold.
3.1. Demographics and clinical characteristics
There were no significant differences between SC and FNI
groups with regard to parent demographics, maternal or infant
birth or clinical conditions (Supplementary Tables S1–S3).
3.2. EEG study characteristics
One hundred thirty-four infants (63 SC, 71 FNI) from 105 (51 SC,
54 FNI) pregnancies including singletons and twins provided EEG
data for these analyses (Supplementary Table S4). The recordings
were 1 h in duration in both study groups and in both age groups.
In the early EEG studies, FNI infants had fewer epochs identified as
outliers in both active sleep (AS) and quiet sleep (QS) states than
did SC infants.
3.3. Electrode by electrode differences in EEG power at the two age
ranges
To evaluate the effect of FNI on EEG power, we conducted ttests for each electrode, within each sleep state and PMA range
and for each of 10 frequency bands. Electrode maps of the p-values
from these t-tests are shown in Fig. 3 for quiet sleep and in Fig. 4
for active sleep. Included in the maps are data for each of 10 frequency bands across the spectral range from 1 to 48 Hz for both
3.4. Regional effects of FNI on EEG power
3.5. FNI increased EEG power in both the first and second half of study
period
To test whether the effects of FNI were consistent over the
course of the trial, we divided the data into the first half and second
half of the study period for enrollment in the RCT. We focused on
the data obtained at near to term age in QS. Although multiple
Fig. 3. EEG power during quiet sleep. In quiet sleep FNI had effects on EEG power at the older age range (after 6 weeks of FNI) but not the early range. These effects were
most apparent in frontal regions. Shown are electrode maps of the p-values for the differences in power between FNI and SC infants in t-tests for each electrode, across the
spectral frequency range from 1 to 48 Hz and PMA range for each of 10 frequency bands across all 30 s epochs that were behaviorally coded as quiet sleep.
M.G. Welch et al. / Clinical Neurophysiology 125 (2014) 675–684
679
Fig. 4. EEG power during active sleep. In active sleep FNI had effects on EEG power at the older age range (after 6 weeks of FNI) but not the early range. These effects were
most apparent in frontal regions. Shown are electrode maps of the p-value for the differences in power between FNI and SC infants in t-tests for each electrode, across the
spectral frequency range from 1 to 48 Hz and PMA range for each of 10 frequency bands across all 30 s epochs that were behaviorally coded as active sleep.
Table 1
Results from analyses of Frontal Polar EEG power from the near to term studies (PMA
37–44.4 weeks). For each sleep state (active and quiet) analyses were repeated
measures ANOVAs of log EEG power for each of 10 frequency bands. These analyses
had one between subjects factor (Group: FNI vs. SC) and one within subjects factor
(hemisphere). The p-values shown are for the main effect by Group. Note the number
of subjects across frequency bands and states was not constant because outliers were
set to missing for individual cells in these analyses. There were no significant
interactions between treatment group and hemisphere. In both quiet and active sleep
in all frequency bands, the power was greater in FNI than in SC infants. Presented in
bold are the p-values which passed a 10% False Discovery Rate threshold based on p
values from 200 tests (5 regions 10 frequency bands 2 ages 2 states).
Active sleep
3.6. FNI increased EEG power in both males and females
A gender by group comparison determined whether the effects
of FNI treatment on EEG power were similar in males and females.
The ANOVA showed a robust main effect of group with FNI greater
than SC (F(1, 92) = 20.17, p < 0.00003), but no significant interaction between group and sex (p = 0.60). The mean power for males
and females in each group is shown (Fig. 5A). Post-hoc t-tests
showed a significant effect of FNI in both males and females
(p < 0.001(SC/FNI,
n = 20/28)
and
p < 0.007
(n = 25/25),
respectively).
Frequency
band (Hz)
Quiet sleep
FNI vs.
SC (%)
p (Group Ns)
FNI vs.
SC (%)
p (Group Ns)
3.7. FNI increased EEG power in both singletons and twins
1–3
4–6
7–9
10–12
13–15
16–18
19–21
22–24
25–36
37–48
+8
+16
+19
+21
+21
+30
+32
+32
+36
+31
0.26438 (44/51)
0.07060 (44/53)
0.03022 (44/52)
0.00364 (44/53)
0.00501 (44/50)
0.00018 (44/52)
0.00003 (44/52)
0.00006 (44/52)
0.00007 (44/53)
0.00121 (44/53)
+11
+5
+12
+20
+20
+20
+19
+20
+23
+20
0.19612 (44/50)
0.38996 (44/50)
0.10840 (44/50)
0.00360 (44/51)
0.00459 (44/49)
0.00351 (44/50)
0.00375 (44/49)
0.00525 (44/49)
0.00307 (44/51)
0.01474 (44/51)
We also conducted an ANOVA to determine if the effects of FNI
were similar in singletons and twins (Fig. 5B). There was a highly
significant effect of group with FNI greater than SC (F(1,
92) = 21.19, p < 0.00002) but there was also a significant interaction between twin/singleton status and group (F(1, 92) = 6.18,
p < 0.02). Post-hoc tests showed that the effects of FNI were significant in both singletons and twins (p < 0.03 (SC/FNI, n = 27/29) and
p < 0.01 (n = 18/24), respectively).
3.8. FNI increased EEG power independent of age or weight at birth
frequency bands showed highly significant differences, we focused
on the band that had the most robust results (19–21 Hz). Inspection of the electrode by electrode results in Figs. 3 and 4 suggested
somewhat more robust results on the left side. Thus, we conducted
these post hoc tests using data from the left frontal polar region. An
ANOVA for effects of group (FNI vs. SC) and study period half
showed there was a highly significant difference between groups
with FNI greater than SC (F(1, 92 = 20.06, p < 0.00003), but no significant group by study half interaction (p = 0.99). Post-hoc t-tests
showed a significant effect of group in both halves of the intervention (p < 0.007 (SC/FNI, n = 24/26) and p < 0.001 (n = 21/27),
respectively).
Next, we divided the infants into two groups based on gestational age at birth. There were 28 infants born 630 weeks (12 SC,
16 FNI) and 70 infants born >30 weeks (33 SC, 37 FNI). There was
a significant main effect of age group with FNI greater than SC
(F(1, 94) = 14.43, p < 0.0003) but no significant interaction between
intervention group and birth age group (p = 0.48). The mean power
for each birth age group is shown in Fig. 5C. Post-hoc t-tests
showed there was significantly greater power in the FNI group in
both age groups (630 weeks PMA, p < 0.03;>30 weeks PMA,
p < 0.001). The effect of the intervention in the left frontal polar region at 19–21 Hz was also significant for infants born <1500 g
(p < 0.005(SC/FNI, n = 18/32)) as well as infants born P1500 g
(p < 0.001(n = 27/21)) with greater power in the FNI group.
680
M.G. Welch et al. / Clinical Neurophysiology 125 (2014) 675–684
Fig. 5. Effects of FNI on EEG power are found in multiple subsets of infants. EEG power (mean ± SE) in electrodes located over the left frontal cortex in the frequency band
from 19 to 21 Hz for subgroups of SC and FNI infants. Results are presented for comparisons of subjects grouped by (A) gender, (B) birth status, twin vs. singleton, (C)
gestational age (GA) at birth, (D) Pre- or post-discharge EEG obtained near to term age.
3.9. FNI increased EEG power independent of testing before or after
discharge
The majority of near to term EEG studies were conducted postdischarge in our follow-up clinic (34 SC, 34 FNI) while a few were
obtained in the NICU prior to discharge (10 SC, 12 FNI). Analyses
showed a main effect of group with FNI greater than SC (F(1,
86) = 14.54, p < 0.0003) but no significant interaction between
group and discharge status (p = 0.56) (Fig. 5D). Moreover, there
was a significant effect of FNI in both of these subsets (tested in
NICU p < 0.02; tested in follow-up clinic p < 0.001).
3.10. FNI alters developmental trajectories of EEG power
Next, we examined developmental trajectories of EEG power by
analyzing changes in power with age (controlling for gestational
age at birth and PMA at testing). Repeated measures ANOVAs were
conducted using data from subjects with measurements both early
at 33.8–36.9 PMA and near-term at 37.2–44.4 PMA (43 FNI, 33 SC).
The developmental trajectories for EEG power in the 19–21 Hz
band during QS for the left and right sides of five brain regions
are shown in Fig. 6. Results showed that left frontal polar power increased in FNI infants with PMA, whereas SC infants showed no
significant change with PMA (Fig. 6A). This pattern of change with
age resulted in a significant age by group interaction (p < 0.0001). A
significant age by group interaction was also found for right frontal
polar power (p < 0.001). Even though the differences in frontal
power at term age were not significant, the change from the early
PMA studies to the near to term age studies was greater in FNI infants in both hemispheres (interaction term left frontal p < 0.0005,
right frontal p < 0.008; Fig. 6B). Significant age by group interactions were also found for the left temporal (p < 0.03; Fig. 6C), as
well as for the left and right parietal regions (p < 0.008, p < 0.005,
respectively; Fig. 6D), and for the right occipital region (p < 0.01;
Fig. 6E). Post-hoc tests showed that power increased significantly
(p < 0.02 to p < 0.00001) in FNI in all but the left temporal region.
In contrast, power increased in SC infants only in the left occipital
region (p < 0.05). Moreover, in SC, EEG power in the left frontal region decreased with age (p < 0.02).
4. Discussion
Preterm infants are a growing segment of the population. These
infants are taken from their uterine environment before fetal
development is complete and are exposed to an artificial environment. Advances in technology have made it possible to reduce
mortality at early gestational ages. However, adverse outcomes
in preterm infants remain high.
There are several reports of positive impact of non-medical
interventions on outcomes following neonatal intensive care (Als
et al., 1994, 2012, Conde-Agudelo et al., 2011, Feldman et al.,
2002, 2006, 2010, Vickers et al., 2004), although comprehensive
assessments of these interventions suggest that they have limited
usefulness in resolving problems of long-term outcome (Ohlsson
and Jacobs, 2013, Symington and Pinelli, 2006). The Newborn Individualized Developmental Care and Assessment Program (NIDCAP)
focuses on providing care of NICU infants tailored to their observed
neurobehavioral characteristics (Als et al., 1994). NIDCAP results in
improved medical and neurobehavioral outcomes (Als et al., 2004;
Buehler et al., 1995; McAnulty et al., 2009). These effects are correlated with MRI- and EEG-based evidence of increased connectivity
between frontal and occipital brain regions following NIDCAP
intervention (Als et al., 2004). Encouraging mothers to engage in
skin-to-skin care of their preterm infants has positive effects upon
growth and clinical course in the NICU (Conde-Agudelo et al.,
2011), as well as longer term neurobehavioral outcomes (Feldman
et al., 2002). Skin-to-skin care has also been reported to increase
EEG-based measures of complexity, interpreted as enhanced maturation of brain function (Kaffashi et al., 2012; Scher et al., 2009).
Massage intervention in preterm infants has been shown to increase growth rates and reduce length of stay in the NICU (Field
et al., 2010; Field et al., 2006, Vickers et al., 2004). Two reports
M.G. Welch et al. / Clinical Neurophysiology 125 (2014) 675–684
681
Fig. 6. Developmental trajectories of EEG power are altered by FNI. EEG power (loge 19–21 Hz (lV2/Hz); mean ± SE) for left and right sides of the (A) frontal polar, (B) frontal,
(C) temporal, (D) parietal and (E) occipital brain regions recorded during quiet sleep for SC (circles/dashed line) and FNI (Square/ solid line) infants measured between 34 and
<37 weeks PMA vs. P37 to 44 weeks PMA. The p-values are from ANOVAs and reflect the significance level of the interaction between age and intervention group controlling
for gestational age at birth and PMA at testing.
from a small trial (N = 10/group) found that massage therapy accelerated developmental decreases in inter-burst intervals in EEG
activity, shortened latencies in visual evoked responses, and
caused a transient enhancement of visual acuity at three months
of age (Guzzetta et al., 2009, 2011). These studies also showed that
massage therapy led to higher levels of EEG power during active
sleep.
Although FNI incorporates some aspects of the above interventions, it differs in central focus. FNI specifically facilitates
the pairing of mother’s communication of emotion with exchange of scent, comforting touch, vocal soothing, holding and
the experience of mutual calming. This pairing of affect communication and sensory interaction may underlie another mechanism that could explain the effects of FNI on brain function;
namely, learning. The neural substrates for learning exist very
early in development and have been demonstrated in early motor learning paradigms in rat fetuses (Robinson et al., 2008).
Other studies have demonstrated that the human fetus learns
to recognize the mother’s voice (DeCasper and Fifer, 1980; Fifer
and Moon, 1994; Moon and Fifer, 2000) and scent (Marlier et al.,
1997; Schaal et al., 2000). New learning from olfactory stimuli
(Sullivan et al., 1986a,b) guides behavior during the early postnatal period, with temperature and touch being key determinants of affiliative learning (Kojima and Alberts, 2011).
Learning in infants can occur during a wide range of circumstances, such as feeding (Delaunay-El Allam et al., 2006) and
even during sleep (Fifer et al., 2010). Based on this body of early
learning studies and on the design of our intervention, it seems
682
M.G. Welch et al. / Clinical Neurophysiology 125 (2014) 675–684
very likely that some form of learning may underlie the effects
on brain development of infants following FNI.
Indeed, our results show that near to term age infants who receive facilitated FNI exhibit robust differences in brain activity
(EEG power), when compared to infants receiving standard care.
The increases in EEG power in FNI infants ranged from 19% to
36% in frequencies from 10 to 48 Hz. The greatest percent change
(+36%) occurred during quiet sleep in the low gamma frequency
range (25–36 Hz). These findings are particularly convincing because they were obtained in a large randomized controlled trial
that employed fine grained high density EEG records with repeated
measurements over early development, and held true regardless of
gender, singleton or twin status, gestational age at birth, or birth
weight. Further, they held for infants enrolled in the first or second
half of the study, as well as for infants studied near to term age
while still in the NICU or after discharge.
FNI exerts its most highly significant effects in the frontal polar
regions at beta and low gamma frequencies. Results from other
studies have shown that increased high frequency power predicts
better developmental outcomes at later ages. Results from our
prior study in term infants with cardiac anomalies showed a positive correlation between left frontal beta power, during sleep, and
Bayley scores at 18 months (Williams et al., 2012). This is consistent with prior work in both term and preterm infants (Scher
et al., 1996; Tarullo et al., 2012). In older awake infants, frontal
gamma power, thought to be related to level of arousal and attention, was correlated with cognitive abilities (Benasich et al., 2008).
Resting frontal EEG gamma power measured in awake infants at
16 months of age predicted language capabilities at 3 years of
age (Gou et al., 2011). These studies support the hypothesis that
the increases in high frequency power we demonstrated in preterm infants following FNI presage improved neurobehavioral outcomes at later stages of development.
Based on studies in older infants, one might have expected to
find effects of FNI on the early development of EEG power left/right
asymmetry in our subjects in the 7–9 Hz frequency range. These
studies showed asymmetry in EEG power in frontal areas, particularly at frequencies between 6 and 9 Hz in association with maternal depression (Dawson et al., 1999a,b), responses to fearful
stimuli (Diaz and Bell, 2012), orphanage rearing (McLaughlin
et al., 2011), and quality of maternal care (Hane and Fox, 2006;
Hane et al., 2010). In contrast to all of the prior published asymmetry work, our data was obtained during sleep. In our study, we did
not find significant left/right group differences in power, or any
group by hemisphere interactions in the 7–9 Hz band, in postmenstrual age group, sleep state, or brain region. It is possible that
left/right differences will emerge at later ages, but we did not record EEG beyond the near to term age range or in the awake state.
Although we found that main developmental effects of FNI were
localized to frontal polar power, we also found significant groupby-age interactions in multiple brain regions. These results suggest
that there are widespread changes in developmental trajectories of
brain activity that could be mediated by FNI. Since this study was
limited to a specific age range during sleep, it is also conceivable
that increases in EEG power might be seen in the FNI group in
other brain regions and/or at earlier ages under other test conditions, such as during the awake state or following stimuli that
evoke EEG responses.
It is important to note that the effects of FNI on infant brain
activation occurred with an apparently small ‘‘dose’’ of the intervention. Scent cloth exchange was made approximately 2–3 times
per week, and Vocal Soothing and Sustained Touch with Eye Contact sessions took place approximately three times per week. Skin
to Skin Holding sessions took place an average of two times per
week for at least one hour each time. In total, Nurture Specialistfacilitated intervention sessions occurred on average approxi-
mately 4 h per week. This relatively small amount of time spent
in nurturing activities, however, may not be an accurate indicator
of the intervention effect. In other words, dose and effect may not
be directly correlated. Behavioral and emotional effects might have
been sustained in both mother and infant beyond each session.
Sensory stimulation and associated brain activation during early
development can elicit cascades of hormone and neurochemical
events that can shape infant brain development (Johnston et al.,
2001; Kuhn and Schanberg, 1998; Park and Poo, 2013). Thus, in
addition to learning mechanisms, we speculate that the increased
brain activity we see following FNI may serve to shape activitydependent aspects of brain development and plasticity. In replication studies we plan to adapt EEG-based measures (Clapp et al.,
2012) to track changes in brain plasticity as both markers and
mechanisms for the effects of FNI.
Our ongoing clinical research will assess the proximal physiological and behavioral effects of paired nurturing activities, and explore underlying developmental mechanisms. In follow-up of this
study cohort extending to two years of age and longer, we will
determine the effects of FNI on cognition, language, attention,
and emotion regulation.
5. Conclusions
Family Nurture Intervention is a novel intervention strategy for
the neonatal intensive care unit that pairs communication of affect
and interactions designed to calm both mother and infant. Compared to the SC group, the FNI group showed robust increases in
high frequency EEG brain power in the frontal polar region at near
to term age. These effects were independent of gestational age or
weight at birth, gender, twin status, or discharge status when assessed. Such region and frequency-specific increases have been
shown by others to correlate with better neurodevelopment at later ages. Results from this study support the importance of early
mother–infant nurture and of facilitating family nurture in the
NICU and suggest that FNI may provide an effective and practicable
approach to improving outcomes in preterm infants.
6. Financial disclosures
Funding for this project was provided by the Einhorn Family
Charitable Trust and the Fleur Fairman Family to the BrainGut Initiative at Columbia University Medical Center. Funding in part was
also provided by Columbia University’s CTSA from NCRR/NIH
(UL1RR024156). Author MMM received salary support from the
New York State Office of Mental Health Research Scientist position.
The authors have no competing financial interests.
Acknowledgments
We would like to thank the NICU staff at the Morgan Stanley
Children’s Hospital of New York as well as the participating families for their invaluable assistance to our program of research.
We are grateful for the support of the Columbia University Irving
Institute for Clinical and Translational Research, where the bulk
of EEG recordings were performed. We also want to acknowledge
and thank our Performance and Safety Monitoring Board for their
thoughtful contributions to the conduct of this study (Bruce Levin,
Ph.D., Michael Weitzman, M.D. and Deborah E. Campbell, M.D.).
Appendix A. Supplementary data
Supplementary data associated with this article can be found, in
the online version, at http://dx.doi.org/10.1016/j.clinph.2013.
08.021.
M.G. Welch et al. / Clinical Neurophysiology 125 (2014) 675–684
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