Fetal Neurobehavioral Development
Janet A. DiPietro, Denice M. Hodgson,
Kathleen A. Costigan, and Sterling C. Hilton
Johns Hopkins University
Timothy R. B. Johnson
University of Michigan
DIPIETRO, JANET A.; HODGSON, DENICE M.; COSTIGAN, KATHLEEN A.; HILTON, STERLING C ; and
JOHNSON, TIMOTHY R. B. Fetal Neurobehavioral Development. CHILD DEVELOPMENT, 1996, 67,
2553-2567. The ontogeny of fetal autonomic, motodc, state, and interactive functioning was investigated longitudinally in a sample of 31 healthy fetuses from 20 weeks through term. Fetal heart
rate and movement data were collected during 50 min of Doppler-based fetal monitoring at 6
gestational ages. Measures of fetal heart rate and variability, activity level and vigor, behavioral
state, and reactivity were derived from these digitized data. Weighted least squares analyses
were conducted to model the developmental patterns and to examine the role of maternal and
fetal covariates. With advancing gestation, fetuses displayed slower heart rate, increased heart
rate variability, reduced hut more vigorous motor hehavior, coalescence of heart rate and movement patterns into distinct behavioral states, and increasing cardiac responsivity to stimulation.
Male fetuses were more active than female fetuses, and greater maternal stress appraisal was
associated with reduced fetal heart rate variability. An apparent period of neurobehavioral transition exists between 28 and 32 weeks. Fetal research methods are evaluated.
We must regard our interest in the problem of
normal fetal hehavior as a direct outgrowth ofthe
widespread tendency within the past few years to
approach more nearly the beginnings of human
life in the hope of obtaining a Picture of behavior
as it emerges. (Sontag & Richards, 1938, p. 1)
'
'^ I
So began tbe introduction of one of the
earliest Monographs of this journal, reporting results of the first systematic study
of fetal behavioral development, originating
at the Fels Institute. Fetal heart rate was
measured by a stethoscope and stop watch
while fetal movement was detected using
four rubber sacks, encased in a plaster of
.
ijjxj.1
i
iv_j
paris cast molded to the maternal abdomen
fc J. s \Tir TT
inoe\ T^ -i. i.il
(Sontag & Wallace, 1935). Despite these ele-
and t h e reduction in t h e gestational age of
viability have fostered a body of research on
the development of extrauterine functioning
p^^,. to term. As a result, a more complete
^ j ^ f ^j^ Ontogeny of neural regulation
ri_ l • l
j
j -j. • l
a, t.
of behavior has emerged, and it is clear that
features of neurobebavioral functioning
which have been measured extensively in
the neonate and infant, and which are integral to current theories of development, do
not originate at birth. In fact, there appears
to be little neurobehavioral discontinuity
between the fetus and the neonate (Prechtl,
1984).
o
u
^v,
iJ
l
Research on the normative develop. r
- c r t i u
i • t: u •
ment of Specific fetal characteristics has lnl j j .
i. ^.
r r ^ l L _i ,.
mentary methods of fetal surveillance, this
fl^'^i^T^^^S^^^Tn
research provided exceptional insight on
the nature of fetal neurobehavioral devel-
i'lf'^l'T
S
lation (Dalton Phil, Dawes, &Pati:ick, 1983;
P ^ ^ ^ ^ ' Hmighton, Redman^ & Visser, 1982;
Groome, Mooney, Bentz, & Wilson, 1994);
'
qualitative and quantitative patterns of fetal
Since then, technologic advances have movement (deVries, Visser, & Prechtl, 1982;
opened a window to the fetus that was un- Nasello-Paterson, Natale, & Connors, 1988;
imaginable 60 years ago. Concurrently, the
Patrick, Campbell, Carmichael, Natale, &
increased survival rate of preterm infants
Richardson, 1982; Roberts, Griffin, Mooney,
This research was supported hy grant R29 HD27592, National Institute of Child Health
and Human Development, awarded to the first author. The investigators wish to thank the diligent and generous participation of our study families, without which this research would not
have heen possible, and Dr. Harini Narayan and Alyson Shupe for their assistance in state coding
and training. Address reprint requests to Janet DiPietro, Department of Maternal and Child
Health, Johns Hopkins University, 624 N. Broadway, Baltimore, MD 21205.
[Child Development, i996,67,2553-2567. © 1996 by the Society for Research in Child Development, Inc.
All rights reserved. 0009-3920/96/6705-0041$01.00]
2554
Child Development
Cooper, & Campbell, 1980; Robertson,
1985; Roodenburg, Wladimiroff, van Es, &
Prechtl, 1991); behavioral state (Nijhuis,
1986; Nijhuis, Prechtl, Martin, & Bots, 1982;
van Vliet, Martin, Nijhuis, ^c Prechtl, 1985a);
and responsivity to external stimuli (Kisilevsky & Muir, 1991; Kisilevsky, Muir, & Low,
1992; Leader, Baillie, Martin, & Vermeulen,
1982; Madison, Madison, & Adubato, 1986;
Sontag & Wallace, 1935). Neurobehavioral
development is atypical in fetuses that exhibit other indicators of neurologic compromise (Gagnon, Hunse, Fellows, Carmichael,
& Patrick, 1988; Horimoto et al., 1993; Snijders, Ribbert, Visser, & Mulder, 1992; van
Vliet, Martin, Nijhuis, & Prechtl, 1985b; Visser, Bekedam, Mulder, & van Ballegooie,
1985).
Unlike studies of postpartum neurobehavioral development, investigations of the
fetus have been typically limited to a single
feature of development. This article will
present the results of a comprehensive investigation of the ontogeny of fetal neurobehavioral development in a sample of normal
fetuses studied longitudinally from 20
weeks' gestation through term. Current
models of neurobehavioral development of
preterm infants include the emergence and
differentiation of autonomic, motor, state,
and interactive domains of function, both
alone and in relation to each other (Als,
1982). Neurobehaviors are typically viewed
as representing multiple expressions of underlying neural integrity (Brazelton, 1990).
Our goal was to collect normative data on
intrauterine development to describe the nature of fetal neurobehavior and its maturation over the latter half of gestation. To this
end we relied on downward extension of
concepts of neurobehavioral development
traditionally applied postnatally. Our measures are similar to those with an extensive
history of application in infants and include
activity level, behavioral state, reactivity,
and heart rate patterns. Intrinsic to this endeavor was the development of methods and
protocols for collecting and quantifying fetal
neurobehavioral data.
Fetal development occurs in the context
of the maternal environment. The effect of
maternal emotional state on the fetus has
long been a source of speculation (e.g.. Sontag & Wallace, 1934), but existing data on
the relation between maternal characteristics and the fetus are limited. Recent studies
indicate that maternal exposure to repeated
stressors during pregnancy affects postnatal
neuromotor behavior in squirrel monkeys.
and it has been suggested that this effect is
mediated by antenatal alterations in the hypothalamic-pituitary-adrenal axis (Schneider
& Coe, 1993). In women, perceived stress
during pregnancy is correlated with ACTH
levels (Sandman et al., 1994), and several
small studies and anecdotal reports suggest
that maternal emotional state is associated
with fetal behavior in a manner consistent
with activation of this axis (Van den Bergh
et al., 1989; Zimmer et al., 1982).
The hypotheses to be tested center on
the nature of the maturational function
within and across each neurobehavioral domain with advancing gestation. We expect
that increased parasympathetic control will
be manifest by increased fetal heart rate
variability and responsivity to external stimuli; cardiac and movement patterns will become integrated into specific fetal states;
and ontogenic parallels and discontinuities
will exist across domains. Finally, we propose that maternal stress will significantly
affect fetal functioning in a manner consistent with sympathetic activation and/or reduced parasympathetic control.
Method
Subjects
Subjects were 34 healthy, volunteer
pregnant women and their singleton fetuses.
The intent of recruitment was to select a
low-risk sample for study, and subjects were
enrolled if they had an unremarkable pregnancy history and were nonsmokers, high
school graduates, and at least 20 yetirs of age.
Gestational age determination criteria included one or all of the following: pregnancy
test within 2 weeks of missed period and/or
first trimester obstetric or ultrasound examination. In the final sample, actual dating criteria were more stringent than required
by the protocol: the mean gestational age
at pregnancy confirmation was 5.4 weeks.
Three of these subjects were retrospectively
excluded during study participation due to
the following maternal/fetal conditions: congenital fetal anomaly (one); gestational diabetes (one); and hydrops fetalis secondary to
infection with parvovirus B19 infection
(one). The final sample is based on the remaining 31 individuals with uncomplicated
clinical courses. Some conditions associated
with elevated antepartum or intrapartum
risk were detected as the fetuses approached
term, such as mildly elevated blood pressure
and reduced amniotic fluid level, but none
was considered serious enougb to pose a significant threat to pregnancy outcome. As
DiPietro et al.
such, the sample includes a range of conditions which are commonly encountered late
in pregnancy but often lack clinical significance.
The final sample consisted largely of
well-educated, employed women (M maternal age = 28.4 years, SD = 3.7; M years
education = 16.6, SD = 2.0). Most women
were married (90%) and primiparous (61%).
Six women (19%) were African-American,
the remainder were Caucasian. All neonates
were delivered at term (M gestational age
[GA] = 38.9 weeks, SD = 1.2), 23% by Caesarian section. Mean 1-min Apgar score was
8.3 (SD = 1.1); by 5 min all Apgar values
were 8 or greater. All infants were considered healthy upon delivery and were discharged on normal nursery schedules (M
birthweight = 3,349 grams, SD = 437). Seventeen (55%) were girls.
Materials
Fetal heart rate and movement data
were collected from a fetal actocardiograph
(Toitii, MT320, Wayne PA) using a single
wide array Doppler transducer applied externally. T'his monitor, and others of its generation, determines FHR by processing
Doppler-generated waveforms using autocon'elation techniques. This process
matches small segments of sequential waveforms to detect each serial heart beat. Because the potential error in detection of
each heart beat is 1.5 ms, temporally based
beat-to-beat vairiability cannot be reliably
computed from existing methods of transabdominal FHR recording. Altbougb Doppler-based, autocorrelated FHR data lose
some precision in ascertainment of true interbeat interval (Dawes, Redman, & Smith,
1985), technology for lengthy periods of
transabdominal monitoring of fetal ECG is
not currently available.
Tbe innovation in this and other similar
monitors is Doppler-based fetal movement
2555
detection. Higher frequency Doppler signals (150-220 hertz) are generated by motion of the fetal heart. Thus, standard FHR
monitoring requires a Doppier signal sensitive enough to detect movement changes
that are as small as 1-2 mm. Lower frequency signals, which would be produced
by maternal and fetal body activity, are typically filtered out as noise and discarded. Instead of discarding these signals, the actograph bandpasses both the highest
frequency (i.e., FHR) and the lowest frequency signals (i.e., maternal movement and
respiration). Actograph signals are generated
by a change in the returned Doppler waveform; if there is no movement, the returned
signal will retain the same frequency as the
emitted signal. If the fetus is moving, the
echo will be returned at a different frequency which is proportional to the velocity
with which the fetal body part moves toward
or away from the transducer. The resultant
signal is output in the form of spikes on a
polygraphic tracing in arbitrary voltage units
and corresponds almost exclusively to limb
and body movement of the fetus (Maeda,
Tatsumura, & Nakajima, 1991).^ Sample output from this monitor has been published
elsewhere (DiPietro, Hodgson, Costigan,
Hilton, & Johnson, 1996).
Fetal heart rate and movement output
were digitized on-line (Macintosh Ilci,
Apple Computer, Inc.) using an A-D converter board (LabVIEW NB, National Instruments Corp., Austin TX) and acquired using
a commercial data collection package (LabVIEW, National Instruments). Data were
sampled at 5-hertz. FHR and FM data were
input into two channels, and two additional
channels were used to signal events.
Procedure
Subjects were tested at the following
gestational ages: 20, 24, 28, 32, 36, and
38—39 weeks. To control for potential diur-
' There have heen several reports on the validity of actocardiographs using real-time ultrasound to verify fetal movement. The Toitu actograph has heen reported to detect 95.9% of all
movements observed on ultrasound, including 100% of all large, complex movements (Besinger
& Johnson, 1989). Similar validation of other brands of actocardiograph monitors has been reported (Melendez, Rayhum, & Smith, 1992). Both reports indicated that Fetal actographs are
somewhat better at detecting larger and longer movements than they are at smaller, more discrete
movements. Signal artifacts that do not represent actual fetal movement have been observed
occasionally hut are typically output as single spikes (Besinger & Johnson, 1989). Some of these
may he associated with sudden maternal movements that can he detected at the level of the
ahdomen (i.e., coughing), and there is evidence that better control of maternal position and
monitoring conditions decreases the amount of signal artifact (Melendez et al., 1992). Note,
however, that estimates of both false positive and false negative rates are limited hy the lack of
a true "gold standard" in ascertainment of fetal movement; ultrasound transducers can visualize
only portions ofthe fetal hody and may miss localized movements which are produced hy limbs
beyond this field and which do not affect the rest of the hody.
2556
Child Development
nal and prandial effects, subjects were tested
at the same time each visit, either at 1:00 or
3:00 P.M. Women were instructed to eat IV2
hours prior to testing. Subjects received a
brief ultrasound exam at each visit in order
to determine fetal position and to provide
photographs for parents. Fifty minutes of fetal monitoring followed. Data collection was
set at this length to maximize the likelihood
of fetal state changes while limiting both
subject burden and processing capacity required for data acquisition. Women were
monitored in the left lateral recumbent position while resting quietly, using a single
Doppler transducer applied to the maternal
abdomen. After at least 15 min of undisturbed recording, a control and actual application of a vibratory stimulus (VS) followed.
The stimulus used was a commercially available product designed for fetal stimulation
(Toitu, Fetal Stimulator TR-30) which produces a mild vibration (40—60 bertz). Following a 2-min period of low FHR variability (approximately 5—10 bpm), the fetal
stimulator was placed on the maternal abdomen near the fetal head and either activated
for 3 sec (i.e., VS) or not activated (i.e., control). Each episode was spaced at least 2 min
apart to allow return to baseline FHR, determined by visual inspection of the preceding
heart rate record. This spacing was selected
because it was long enough to allow return
to pre-stimulus levels for most fetuses at the
lower gestational ages, but not too lengthy as
to increase the possibility of a change from a
quiescent (i.e., low FHR variability) period
to a higher one. The remaining event (either
stimulus or control) did not commence until
baseline was achieved. The order of these
events was determined by a random number
table. Following the second event, fetal
monitoring continued undisturbed for tbe
remainder of the 50 min.
Fetal Data Collection and Quantification
Fetal heart rate.—Distinguishing artifactual from actual data is a difficult but critical component in quantifying FHR because
fetal movement can produce poor signal
quality if the fetal heart moves beyond the
Doppler field, although actual FHR can
change rapidly. The digital data underwent
a series of error rejection procedures based
on computation of moving averages of sequential values. The error rejection algorithm was developed after comparing the
polygraphic output of the monitor to the
computerized output of several hundred records and ultimately validated against visual
inspection of 7,500 min of collected polygraphic data. Minutes in which two-thirds of
the data (i.e., 40 sec) or more were rejected
were not included in data quantification.
Details of the error rejection program are
available upon request.
Once processed for artifact, data were
quantified in 1-min epochs. FHR variables
included mean fetal heart rate (mean of 50
1-min epochs) and mean fetal heart rate variability, computed as the standard deviation
for each 1-min epoch, again averaged over
the 50-min recording. This measure provides information concerning short-term
variability in FHR.
Fetal movement.—The actographic signal is output in arbitrary units (a.u.s.) which
range from 0 to 100. Signals of less than 25
a.u.s. may be produced by fetal breathing or
hiccups, which generate incidental fetal
movement but are not considered motor activity, or by smaller movements which may
not always be reliably detected (Maeda et
al., 1991). This threshold is also employed
when the actograph is used for clinical detection of movement during antepartum testing. A movement bout was defined as commencing each time the actograph signal
attained or exceeded 25 a.u.s. and terminatMaternal Data Collection and
ing when the signal fell below 25 a.u.s. for
Quantification
Maternal pregnancy history, demo- at least 10 consecutive seconds. Thus each
graphic data, and responses to the Social Re- bout migbt represent an isolated excursion
adjustment Scale (Holmes & Rahe, 1967) of a single limb or a more complex gross
were collected upon enrollment. At each body movement. Tbe duration of each movevisit, women completed the Hassles and Up- ment bout was calculated from the first time
lifts Scale (DeLongis, Folkman, & Lazarus, the signal reached or exceeded 25 a.u.s.
1988). This scale includes 53 items which through the last 25 a.u.s. signal. The size of
are rated on four-point Likert-type scale in each was quantified by computing the mean
terms of the degree to which they were has- of the amplitudes of all spikes occurring
sling and/or uplifting in the past 24 hours. within that movement bout, and the mean
Reliability and validity for this scale has for all movements was computed. The total
been established (DeLongis et al., 1988). number of movement bouts was multiplied
Maternal pulse rate and blood pressure were by the mean movement duration to yield a
measured at tbe beginning of each re- measure of fetal activity level. This measure
cording.
represents the total amount of time (min) the
DiPietro et al.
fetus was moving during the recording. This
measure, and that of movement bout amplitude, were the two main variables used to
analyze fetal movement.
Fetal state.—Four distinct states are
discernible in the fetus, corresponding to
quiet sleep, REM sleep, quiet awake, and
active awake. These states have been labeled IF, 2F, 3F, and 4F, respectively, in
parallel with state scoring methods developed for neonates (Prechtl, 1974). Because
of the difficulties inherent in programming
pattern recognition of complex physiologic
processes, fetal state was coded from the
polygraphic record. Fetal heart rate patterns
were coded in 3-min windows in accord
with protocols developed by other investigators (van Vliet et al., 1985a), using existing
criteria for patterns A, B, C, and D. Fetal
actograph scoring was developed by us to be
compatible with the movement categories
associated with fetal state. Four categories,
also based on 3-min epochs, were distinguished: FM 1: none or minimal isolated activity; FM 2: mostly inactive, with sporadic
gross movements; FM 3: frequent activity of
moderate amplitude; FM 4: continuous,
high amplitude movement.^
2557
A with FM 1 = quiet sleep; FHR B with
FM 1, 2, or 3 = active sleep; FHR C with
FM 1 = quiet awake; and FHR D with FM
3 or 4 = active awake. These states may not
be directly comparable with those reported
by others because fetal eye movements were
not included as criteria. The percentage of
time the fetus spent in any of these patterns
was calculated. Thus the state measure represents the amount oftimethe fetus was observed in a pattern of FHR-FM concordance
associated with distinct fetal states, in contrast to those periods in which FHR and FM
patterns did not demonstrate state concordance.
Fetal responsivity.—The change from
the 30 sec preceding and the 30 sec following the VS and control events was computed
for FHR and FHR variability. FM data were
not used in examining the effect of the VS
because a low or stable level of FM was not
a criterion for application ofthe VS. In addition, the duration of the cardiac response
(i.e., once FHR exceeded 5 bpm above baseline, the length of time it took to return to
within 5 bpm of FHR baseline for at least 5
sec) was calculated.^
Analysis Strategy
We defined the following FHR-FM patThe major fetal measures that were anaterns as representing the behavioral states lyzed included two cardiac measures (mean
previously described in the literature: FHR FHR and mean FHR variability); two mea^ Interrater reliahility information is not usually provided in investigations of fetal state;
however, we determined that valid application of the scoring criteria to actual FHR data can he
quite difficult. Training was provided hy a visiting investigator who had experience in the European state coding methods, thus helping to validate our application of these methods. Complete
50-min records of actual data were used for reliahility purposes. After training, interrater agreement (i.e., exact matching of FHR pattern score) between ourselves (two coders who coded all
suhsequent data) and that investigator was 93%, with Cohen's kappa = .85. This sampling
included coding of 60% of all 50-min recordings from the first nine subjects who had completed
data collection during that investigator's visit (total reliahility cases = 32). Interrater reliahility
was maintained during coding hy sampling one record from each ofthe next 22 subjects, stratified
hy gestational age. Ongoing interrater agreement for FHR pattern data was 95% and .83, based
on exact matching of score and kappa, respectively. Interrater reliability using this method of
categorizing FHR patterns will always he limited due to ohservations, made by ourselves and
other investigators, that some epochs do not fit well into any ofthe four patterns. Most of these
epochs are designated as FHR pattern B, which is the most hroadly defined category. Interrater
training and reliahility testing for fetal movement pattern coding, which was not based on an a
priori coding system, was limited to flie two primary coders. After training, interrater agreement
for fetal movement pattern data computed on 23 cases yielded 91% concordance of exact score,
with kappa = .84; ongoing reliahility testing of an additional sample of 22 cases, stratified hy
gestational age, was 94% with kappa = .90. By the conclusion of state coding, approximately a
third ofthe total FHR and a quarter ofthe FM records had heen scored hy both coders; disagreements were resolved through consensus.
•^ In order to partition out the effects ofthe VS from the undisturbed portion ofthe recording,
FHR and FM data collected during VS responses of >30 sec duration were excluded from the
overall 50-min means for heart rate and movement measures. The following numher of suhjects
had at least 1 min of data excluded: none at 20 weeks, one at 24 weeks, five at 28 weeks, nine
at 32 weeks, 14 at 36 weeks, and five at 38/39 weeks. However, more than half (57%) had only
1 or 2 affected min. The arithmetic contribution to the 50 min on which the means were based
is minor even for the recording with the greatest numher of deleted intervals (five, or 10% of
the recording time).
2558
Child Development
sures of fetal movement (fetal activity and
mean amplitude); one state measure (% concordance), and two measures of responsivity
to VS (changes in FHR and FHR variability).
Weighted least squares analysis was used to
model the developmental trends of these
variables over time. This method estimates
the correlation structure generated by the repeated measurements on the same fetus and
uses the estimate to weight the observations
in the regression analysis. Robustness of the
estimated correlation structure was assessed
using generalized estimating equations
methodology (Zeger & Liang, 1986). This
technique produces consistent estimates of
regression parameters and their variance,
and, unlike most repeated-measures analysis
of variance procedures, does not exclude
subjects with missing data from the final
model. Lowess, a nonparametric smoothing
technique (Cleveland, 1979), was used to
plot the raw data for each measure in order
to examine visually the shape of the developmental trend over time. If the trend appeared nonlinear, a knotted spline(s) was included in the model at the point of apparent
nonlinearity. Knotted splines allow nonlinear trends to be modeled in an otherwise
linear model by permitting the slope to
change at the "knot," thus testing for a "broken arrow" model.
The following covariates were included
in all models: gestational age (GA) quantified in weekly intervals, fetal sex, maternal
age, maternal mean arterial blood pressure
{MAP = [(2 * diastolic value) -\- systolic
value] -^ 3}, maternal heart rate, and a combined score derived from the Hassles and
Uplifts scale. The terms for maternal blood
pressure, heart rate, and hassles/uplifts were
specific to each gestational age point. Thus,
each fetal measure was modeled as follows:
over time, this approach can obscure the actual amount of fetal responsiveness to VS
(and to a control period). Additional examination of VS/control effects were conducted
to determine whether fetuses responded to
one, both, or neither of these events. In order to control for increases in heart rate predictable by normal fiuctuations of FHR over
time, each subject's pre-VS and. precontrol
heart rate and variability were used to generate 95% confidence intervals. If the post-VS
and postcontrol values were beyond (eitber
above or below) the confidence interval, the
subject was classified as being a responder;
if not, the subject was classified as a nonresponder. Logistic regression was used for
these analyses.
Resnlts
Developmental Trends
The raw mean values for fetal heart rate,
fetal movement, and state variables are presented in Table 1. Fourteen subjects delivered prior to their scheduled term visit (i.e.,
prior to 38/39 weeks); therefore, term data
are restricted to the remaining 17 subjects.
Earlier delivery was not significantly associated with the rate of development for any
neurobehavioral measure. Results of the
weighted least squares analysis for gestational age (i.e., time) effects for these fetal
measures are presented in Table 2.
Fetal heart rate.—Fetal heart rate decreased linearly from 20 weeks through
term. The magnitude of the estimated
change was small (5.9 bpm) over the 18week period of observation. FHR variability
underwent a log transformation to stabilize
its variance, thus permitting regression coefficients to be interpreted as percentage
changes. Short-term variability in heart rate
increased during gestation, at a rate of approximately 5% per week until 32 weeks (paBo (intercept) + (Bi * GA) + (Bj * fetal sex) + (B3
* maternal age) + (B4 * daily maternal heart rate) rameter estimate = .049); after this point the
+ (B5 * daily maternal MAP) + (Bg * hassles/up- rate was 1.1% per week (i.e., .049-.038). The
mean amount of FHR data rejected due to
lifls).
artifact decreased over time from 16% at 20
Nonlinear models included the additional weeks to a stabilized rate of about 5% from
28 weeks through term (see Table 1). Tbis
term for the spline function.
was anticipated due to the increase in size
In order to provide a conservative esti- of the fetal heart during this period. FHR
mate of the actual response to VS, the differ- and short-term variability were significantly
ence between tbe change from pre- to post- correlated at 24 weeks (r = .35), but not
control period was subtracted from the pre- thereafter.
to post-VS period for each cardiac measure,
and these values were used in the regresFetal activity.—The number of movesion. However, if responses to the control ment bouts discerned were 61, 59, 59, 56,
represent actual responses and not just ser- 52, and 52, respectively, at each successive
endipitous excursions of normal variability assessment point from 20 weeks. The level
DiPietro et al.
2559
TABLE 1
MEAN VALUES FOR FETAL HEART RATE, MOVEMENT, AND STATE MEASURES AT EACH GESTATIONAL AGE
(n = 31)
GESTATIONAL AGE
(Weeks)
20
24
28
32
36
38/39
146.8
(4.0)
3.1
(.6)
15.9
(8.4)
146.2
(4.9)
3.7
(.8)
8.5
(3.7)
144.4
(6.0)
4.5
(1.1)
5.1
(3.8)
142.4
(7.0)
5.5
(1.1)
5.1
(3.0)
140.6
(7.0)
5.8
(1.4)
4.7
(2.8)
140.9
(9.1)
6.0
(1.5)
4.8
(4.8)
15.2
(6.9)
36.8
(2.6)
12.0
(7.1)
37.3
(2.9)
10.1
(5.9)
38.0
(2.9)
9.9
(7.1)
37.7
(3.6)
9.1
(7.4)
38.5
(3.7)
8.6
(8.0)
39.7
(4.2)
17.0
(33.0)
51.0
(43.0)
77.0
(35.0)
93.0
89.0
(13.0)
85.0
(18.0)
Heart rate:
Mean (bpm)
Variability
% artifact
Movement:
Total movement (min) ....
Amplitude (a.u.s)
State:
% concordance
NOTE.—Numbers in parentheses are standard deviations.
of fetal activity decreased over the course of
gestation from approximately 15 min to 8
min of total fetal movement per 50-min period, although the amount of individual variability was large. The rate of the decline
slowed significantly beginning at 28 weeks.
Movement amplitude increased linearly.
weeks. Details of the proportion of time
spent in each of three states at each gestational age are presented in Figure 1. This
figure depicts the increase in concordant periods over gestation and decrease in nonconcordant epochs, as well as changes in specific states. For example, patterns consistent
with active waking were not observed at all
Fetal state.—The percentage oftimefe- at 20 weeks but represent between 11% and
tuses spent in concordant, predefined be- 16% of fetal state from 32 weeks until term.
havioral states increased nonlinearly during Quiet awake (i.e., FHR pattern C; FM patgestation. Up to week 28, there was an esti- tern 1) was observed too infrequently to be
mated weekly increase of" 8%. This increase included in the figure. Brief episodes were
slowed to an estimated 1% for subsequent observed at 32 and 36 weeks in the same
TABLE 2
RESULTS OF W E I G H T E D LEAST SQUARES ANALYSIS: DEVELOPMENTAL TRENDS DURING GESTATION
GESTATION
Heart rate
Heart rate variability''
Total movement
Movement amplitude
State concordance
SPLINE
Est.
SE
Z
p^
CA
-.328
.079
-4.14
<.OOO1
049
-.614
.004
.164
12.50
-3.74
<.OOO1
<.OO1
32
28
121
077
.047
.008
2.58
9.25
<.O1
<.OOO1
28
Est.
SE
Z
p
-.038
.550
none
.008
.244
-4.89
2.25
<.OOO1
<.O5
-.071
.013
-5.37
<.OOO1
none
NOTE.—Total model df = 164. The table columns are defined as follows: the estimated parameter (Est), the
estimated standard error ofthe parameter estimate (SE), the ratio ofthe estimate to its standard error (Z), and the p
value corresponding to the Z statistic. These statistics are computed separately for the general trend over gestation
as well as at each tested spline term.
"All p values are two-tailed.
•"Natural log transformation.
2560
Child Development
100
80
60
40
20
20
24
28
32
36
Term
LJ Quiet sleep k^ Active sleep U Active awake ^ non-concordant
FIG. 1.—Percentage of total observation time spent in each of three behavioral states at each
gestational age studied. Nonconcordant periods are those without heart rate and activity pattern coherence.
subject, and in two other cases at 24 and 28
weeks, respectively.
Fetal responsivity.—Mean data for fetal
heart rate responsivity to the VS are presented in Table 3. These values represent
the change in cardiac measures to the VS
minus any change during the control period.
Missing data for analyses involving fetal responsivity have one of two causes. Subjects
who did not display two 2-min periods of
low FHR variability could not receive both
the VS and control stimuli, and subjects for
which the VS produced significant movement artifact in the FHR signal did not have
analyzable poststimulus data. The number
in the latter category is six at 20 weeks, one
at 28 weeks, and two at 32 weeks; these
should be subtracted from the ns for the
FHR analyses. The results of the WLS analysis for FHR are as follows: compared to the
control period, FHR responsivity increased
significantly from 20 to 24 weeks (z = 2.88,
p < .01), while the rate of change slowed
significantly from 28 weeks through term
(z = -3.10, p < .01). Responsivity of FHR
variability to the stimulus also increased
over gestation (z = 3.33; p < .001) in a linear
fashion.
Analyses involving classification of responders versus nonresponders by confidence interval boundaries, as described earlier, yielded additional information. The
frequencies of both acceleratory and deceleratory FHR responses to the VS and control
periods and characteristics of the FHR response for each are presented in Table 4.
Logistic regression indicated that more fetuses were classified as responders to VS
with advancing gestation (Z = 5.40, p <
.0001), confirming the pattern reported on
the differential in FHR change. From 28
weeks on, significantly more fetuses were
classified as responders to the VS than to the
control (Cochran's Q < .01). All but one fetus
demonstrated responsivity to the VS at some
point in gestation. At the two earliest gestational ages, the direction of the response was
equally or more likely to be a decrease in
heart rate than an increase; after 28 weeks a
deceleratory response was rare. Conversely,
responsiveness to the control did not change
over gestation (Z - - .03), and the pattern
of deceleratory versus acceleratory responses over time was somewhat different.
Both the magnitude and duration of the response increased to VS during the course of
gestation (p < .001). Means for response
DiPietro et al.
2561
TABLE 3
FETAL RESPONSIVITY TO VS BASED ON COMPARISON TO CONTROL
GESTATIONAL AGE
20
28
32
38/39
36
30
30
27
28
15
29
26
27
26
27
16
25
24
14
13
-.90
(5.34)
6.08
(6.80)
7.40
(11.95)
10.73
(10.03)
7.67
(8.50)
.50
(.79)
.63
(.78)
1.05
(.81)
CO 00
CO 00
No. of subjects receiving VS .... 30
No. of subjects receiving
control
30
No. of subjects receiving both . 24
Fetal heart rate differential
(M)
-.86
(4.16)
Fetal heart rate variability^ differential (M)
26
(.86)
24
.18
(.64)
NOTE.—Numbers in parentheses are standard deviations.
"Natural log transformation.
magnitude and duration in Table 4 include
only those cases which were identified as
actual Responders. Beginning at 24 weeks,
the magnitude and duration of responses to
the control were of significantly lower amplitude and briefer than to the VS (ps < .05).
Effects of Covariates
The relation ofthe covariates to the fetal
measures are presented in Table 5. No covariate neared significance for either VS response variable, and so these are omitted
from the table.
Fetal sex.—Tbere were no significant
sex differences for either cardiac measure or
fetal state, nor was there a difference in the
gestational age at which boys and girls first
demonstrated FHR responsivity to the VS,
t(29) = .32. However, boys (n = 14) moved
significantly more than girls (n = 17)
throughout gestation. The means for each assessment by sex are: 18.1, 14.1, 10.9, 11.4,
10.8, and 11.9 min for boys and 12.9, 10.3,
9.5, 8.7, 7.7, and 4.8 min for girls. Thus, by
term, female fetuses moved only 40% as
much as male fetuses. In addition, there was
TABLE 4
PERCENT AND RESPONSE CHARACTERISTICS TO VS AND CONTROL FOR SUBJECTS CLASSIFIED
AS RESPONDERS
GESTATIONAL AGE
20
Vibratory stimulus (VS):
% responders
% acceleratory
% deceleratory
M response magnitude
(|bpm|)
25
50
50
4.0
(1.3)
M response duration (sec) .... 15.6
(10.2)
Control:
% responders
30
% acceleratory
78
% deceleratory
22
M response magnitude
(|bpm|)
5.0
(2.6)
M response duration (sec) .... 16.8
^^_^
(9.0)
24
28
32
36
34
40
60
60
100
0
80
95
5
86
100
0
80
92
8
6.3
(2.2)
27.6
(15.0)
9.6
(4.7)
51.0
(43.8)
13.3
(7.9)
139.8
(150.6)
15.2
(8.7)
157.2
(180.0)
11.8
(6.0)
55.2
(89.4)
18
60
40
33
44
56
22
75
25
36
89
11
14
100
0
4.7
(2.1)
16.8
(7.8)
6.8
(5.5)
21.0
(25.8)
9.0
(5.7)
38.4
(23.4)
8.7
(5.5)
31.2
(28.2)
6.6
(4.2)
21.6
(19.2)
NOTE.—Numbers in parentheses are standard deviations.
38/39
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DiPietro et al.
a trend for greater movement amplitude (p
< .10) by boys. Because boys tend to be
larger than girls, additional analyses were
conducted to examine whether this relation
was related to size. At birth, there were no
sex differences in weight (M boys = 3,319
grams; M for girls = 3,373 grams; t{2Q) =
-.34) or lengtb (M boys = 51.0 cm; M girls
= 51.2 cm; t(29) = - .20) in this sample.
Maternal
characteristics.—Maternal
age, pulse rate, and blood pressure were not
significantly interrelated. Maternal age was
significantly associated with the development of fetal heart rate variability: Fetuses
of older mothers had significantly lower
heart rate variability. Ad hoc analyses revealed that this association was independent
of gestational age: Zero-order correlations
between maternal age and FHR variability
were significant at each age and ranged from
r(29) = -.32 to - . 5 1 . Maternal age was not
associated with any movement or state measure. Maternal pulse rate and blood pressure
were not significantly associated with any fetal measure, with the exception of a positive
relation between blood pressure and state
concordance.
Maternal stress.—Preliminary analyses
revealed a lack of significant associations betw^een scores on the Life Events Scale and
fetal measures. This measure of stressful life
events was not included in subsequent analyses. Preliminary analyses also indicated
that maternal reports of Hassles were positively correlated with maternal reports of
Uplifts at each gestational age. Older women
reported significantly more Hassles, but not
Uplifts, at every gestational age (rs range
from .35 to .67). Because of these relations,
and because positive and negative stressors
are often considered to bave similar physiologic effects, a combined Hassles and Uplifts
score (Hassles intensity -I- Uplifts intensity
-i- frequency of each) was used as the covariate in the weighted least squares analysis.
Results of this analysis demonstrated that
greater perceived stress was significantly associated with reduced FHR variability, Z =
3.00; p < .01.
Discussion
Tbese data provide a comprehensive
description of fetal neurobehavioral development across four domains of functioning
and define the maturational course of
healthy fetuses. These developmental
trends refiect maturation of neural regulation and parallel the rapid increase in para-
2563
sympathetic control. There is also evidence
of a developmental discontinuity occurring
between 28 and 32 weeks, with considerable
consistency across domains. The rate of development of FHR variability, activity level,
state concordance, and cardiac responsivity
slows significantly within this gestational
period. We propose that substantive changes
in neural organization underlie these observations and that the functional significance
of this discontinuity is refiected in the successful developmental outcome of most preterm infants who are born at or beyond this
gestational age. That is, although development continues after 32 weeks, this gestational period marks a period of neurologic
maturity sufficient to maintain extrauterine
survival as well as developmental competence.
Fetal heart rate decreased slightly from
20 weeks through term, while short-term
variability increased: Both processes are attributed to increased parasympatbetic innervation of the heart (Dalton et al., 1983;
Dawes et al., 1982). Note that the mean FHR
values are higher than those typically reported in clinical literature, because those
reports often use a measure of FHR baseline, which is the heart rate between periods
of variability or acceleration, while the FHR
measure in this study is a mean of all data
points. Short-term FHR variability was negatively affected by reports of maternal stress,
partially confirming our hypothesis. The potential role of maternal age in this finding
is unclear, as older women reported more
stress. Variations in neuroendocrine levels
resulting from stress during pregnancy have
been implicated in other aspects of neurobehavioral development in infant monkeys
(Schneider & Coe, 1993) and in perinatal
outcome measures in humans (Sandman et
al., 1994). Maternal uterine activity was not
monitored in this study, and there is currently no available information on how episodes of antenatal contractions might affect
fetal neurobehavior.
Fetuses moved less often but witb more
vigor from mid-second trimester through
term. In general, these data indicate that fetuses move at least once, on average, per
minute during the second half of gestation
and are active about 20%—30% of tbe time.
These values are within the range of data
reported by studies using ultrasound to observe fetal bebavior (Nasello-Paterson et al.,
1988; Patrick et al., 1982; Roberts et al.,
1980; Roodenburg et al., 1991) and are consistent with reports of a cycle time of several
2564
Child Development
Fetal state became more organized with
minutes for spontaneously generated motility patterns during the same gestational pe- gestation: Progressively fewer pteriods durriod (Robertson, 1985). The decline over ing which FHR and FM patterns were nongestation may simply reflect the mechanics concordant were evident, and specific states
of increased uterine constraint as a function became more differentiated over time.^ The
of advancing fetal size. However, inhibition observed trend represents the developing
of behavior is a hallmark of neuroregulation, capacity of the fetus to regulate and integrate
and these findings are consistent with matu- multiple neural systems, and it has been
ration of the fetal nervous system. Reduced suggested that periods of disconcordancy
fetal motor behavior may also be linked to represent inadequacies in homeostatic conmaturation of state organization, which is trol mechanisms (Groome, Bentz, & Singh,
marked by tbe development of periods of 1995). States which require significant quiescence and activity in both systems develquiescence.
oped later in gestation than did the less difMale fetuses were more active than fe- ferentiated state of active sleep. Active sleep
males, and there was a trend for these move- is associated with a range of patterning of
ments to be more vigorous, even though both FHR and FM, while quiet sleep and
there were no sex differences in size at birth active awake states require either extremely
in this sample. Individual studies have not quiescent or active patterns, respectively, in
consistently documented sex differences in both. Periods of rhythmic FHR patterning
infant activity level, although a meta- without motor activity, which have been deanalysis has determined a significant effect scribed as alertness in the fetus, were rare:
for infant sex (Eaton & Enns, 1986). The Of a total 2,900 epochs in which state was
same analysis did not yield a significant ef- scored, this state was only identified in 11
fect size in the fetal period, and a subse- epochs and in three fetuses. This confirms
quent study also failed to find a sex differ- observations of others (Arabin & Riedewald,
ence using maternal report data (Eaton & 1992; Pillai & James, 1990; van Vliet et al.,
McKeen, 1987). Thus the current finding is 1985a), and it is possible that this state, if
consistent with existing data on infants, the it is indeed a state, is not available to all
inconsistency with respect to previous ante- fetuses.
natal research may be due to limitations in
methods of fetal movement ascertainment in
Data on fetal responsivity both confirms
those studies. Thisfindingis provocative be- and extends the reports of others, which
cause it suggests that boys are born with sub- have documented greater fetal responsivity
stantially more motor "experience" and sug- with advancing gestation (Leader et al.,
gests that childhood sex differences in 1982). We have replicated observations by
activity level are not solely attributable to Kisilevsky et al. (1992) that small, deceleraenvironmental influences.
tory responses to different vibratory stimuli
* The traditional orientation advanced by the investigators who codified the definition of
fetal behavioral states is that states do not exist prior to 36 weeks in fetuses or preterm infants
and that any coincidence of parameters occurs by chance (Nijhuis et al., 1982). This orientation
has been modified somewhat as investigators have concluded that integrated coordination among
state criteria may be observed earlier in gestation, although it is less frequent (Nijhuis, 1986;
Visser, Poelmann-Weesjes, Gohen, & Bekedam, 1987). At 20 weeks, we observed a small percentage of time which might be identified as a sleep state, with significant maturation in concordance
occurring at 28 weeks and later. This observation, that the percentage of time classified as
nonconcordant decreases over time, is entirely consistent with reports of others. At 36 weeks,
our estimates of the proportion of time spent in each state are very similar to those found by
others. As in this study, active sleep is reported to be the predominant state (generally between
50%-75% of the observation), while quiet wakening is rarely identified. The remaining states,
quiet sleep and active waking, vary in their incidence across studies, although there is a large
amount of individual variation. Our value for quiet sleep at 36 weeks (i.e., 5% of observation
time) is lower than that reported by others, and we have no explanation for this discrepancy. It
is possible that other definitions tolerate more motor activity in this state than does ours. However, because the FHR and activity patterns for quiet sleep are highly characteristic, and additional information concerning fetal eye movements does not aid in its attribution (Arabin, Riedewald, Zacharias, & Saling, 1988; Nijhuis & van de Pas, 1992), it is also possible that this reflects
a difference among groups studied. Finally, our finding that 11% of the observation time at term
cannot be attributed to any state is similar to reports by others (Groome, Singh, Burgard, Neely,
& Bartolucci, 1992; Nijhuis et al., 1982; van Woerden et al., 1989).
DiPietro et al.
are common responses earlier in gestation,
although deceleratory responses continued
to be observed at 28 weeks in that study, but
not in the present one. After 28 weeks, there
is agreement that most responses are acceleratory. It is unclear whether this developmental pattern reflects maturation in stimulus detection or in response systems, or both.
Our analyses also attempted to explicate
the nature of perceived responsiveness to
VS and control periods. Although other studies typically include control periods in their
investigations of responsivity, these data are
often not systematically used in analyses
otlier than to verify that responses to the actual stimuli exceed that ofthe control period.
Alithough the possibility of maternally mediated fetal responsivity to control periods has
been raised by others (Visser, Zeelenberg,
de Vries, & Dawes, 1983), it has not been
analyzed before. The current data indicate
that when precontrol heart rate patterns are
used to compute expected confidence intervals for the postcontrol period, between 14%
and 36% of fetuses "responded" to the control at each age. The responses were less intense and more often deceleratory than
those to the VS. This phenomenon raises the
inixiguing possibility that maternal anticipation alone, perhaps mediated by mild
changes in arousal, may affect fetal functioning. This finding, like the relation between
maternal stress and heart rate patterning,
points to the complex nature ofthe maternalfetal relationship and deserves further investigation.
Finally, we believe that the actograph
is a useful data source for measuring fetal
activity and inferring fetal state and will ultimately make investigation of the fetus more
accessible to the developmental community.
Existing studies of fetal movemerit and state
have relied on lengthy sessions of continuous ultrasound, requiring two transducers to
permit visualization of tibe fetal face, torso,
and limbs, and highly trained personnel to
interpret the ultrasound image. Traditional
methods of establishing interobserver reliability have generally not been used. Despite definitional and methodologic differences between this and previous
uliiasound-based studies, similarity in
movement and state results gives us confidence in the validity of our methods. Based
on this comparability, we also believe tbat
the methodologic compromise provided by
coding fetal state from FHR and actograph
data alone, without additional fetal eye
movement data, is warranted. However, ac-
2565
tocardiographic data are not useful in all situations, particularly investigations of qualitative and dynamical aspects of fetal motor
behavior, which require real-time ultrasonography. Regardless of methodology, it is
clear that the fetus provides a fertile source
of information about the nature of human development.
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