NeuroImage 55 (2011) 1610–1616
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j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / y n i m g
Transient haemodynamic events in neurologically compromised infants:
A simultaneous EEG and diffuse optical imaging study
R.J. Cooper a,⁎, Jeremy C. Hebden a, H. O'Reilly b, S. Mitra b, A.W. Michell c, N.L. Everdell a,
A.P. Gibson a, T. Austin b
Biomedical Optics Research Laboratory, Department of Medical Physics and Bioengineering, University College London, London, UK
The Rosie Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
Department of Clinical Neurosciences, Addenbrookes Hospital, Cambridge, UK
a r t i c l e
i n f o
Article history:
Received 5 November 2010
Revised 20 December 2010
Accepted 8 January 2011
Available online 19 January 2011
a b s t r a c t
We describe a series of novel simultaneous EEG and diffuse optical imaging studies of newborn infants. These
experiments provide evidence of large, transient haemodynamic events which occur repeatedly and
consistently within and across several infants with neurological damage, all of whom were diagnosed with
seizures. A simple but independent process of rejecting artifacts and identifying events within diffuse optical
imaging data is described, and this process is applied to data from 4 neurologically damaged neonates and
from 19 healthy, age-matched controls. This method results in the consistent identification of events in three
out of four of the neurologically damaged infant group which are dominated by a slow (N 30 s) and significant
increase in oxyhaemoglobin concentration, followed by a rapid and significant decrease before a slow return
to baseline. No comparable events are found in any of our control data sets. The importance and physiological
implications of our findings are discussed, as is the suitability of a combined EEG and diffuse optical imaging
approach to the study and monitoring of neonatal brain injury.
© 2011 Elsevier Inc. All rights reserved.
Brain injury in the perinatal period is a major cause of mortality and
life-long neurodisability. The aetiology and pathophysiology of perinatal
brain injury is complex and multifactorial. However, alterations in
cerebral haemodynamics and oxygenation are implicated in many
forms of brain injury of both preterm and term infants. Seizures are a
common symptom of many neurological disorders, both congenital and
acquired, although they are poorly classified, frequently under
diagnosed, and are difficult to treat (Rennie et al., 2008). There is also
growing evidence that seizures themselves can be damaging to the
developing brain (Thibeault-Eybalin et al., 2009; Glass et al., 2009;
Zimmermann et al., 2008; Scher, 2003).
Electroencephalography (EEG) is the gold-standard neuro-monitoring technique in cases of neonatal seizure and has many significant
advantages including portability, stability and easy application
(Boylan et al., 2002). However, the interpretation of EEG data
obtained in the perinatal period is extremely challenging because of
the high-amplitude, mixed-frequency nature of the neonatal EEG
(Vanhatalo and Kaila, 2006). There have also been many reports of
clinically observed neonatal seizure events (i.e. fitting) which do not
exhibit a simultaneous electrographic correlate (Weiner et al., 1991;
⁎ Corresponding author.
E-mail address: [email protected] (R.J. Cooper).
1053-8119/$ – see front matter © 2011 Elsevier Inc. All rights reserved.
Pinto and Giliberti, 2001). These observations can only be explained if
either the fitting events have a non-epileptic origin, or there is a
failure in the sensitivity of scalp EEG. Although it can be improved
using dense sampling and source localisation techniques, the depth
sensitivity of EEG is severely limited.
Seizures in adults and children have been shown to be associated
with significant haemodynamic responses using a variety of techniques
(Duncan, 1997; Avery et al., 2000; Salek-Haddadi et al., 2002; Gallagher
et al., 2008; Roche-Labarbe et al., 2008). A better understanding of how
the neonatal cerebral vascular system reacts during and after seizure
events, particularly in infants who have already suffered hypoxic injury,
is highly desirable and may well have an impact on treatment
(Silverstein, 2009).
The neonatal head, by virtue of its small size and thin skull, is ideally
suited for interrogation by diffuse optical imaging (DOI), and clinical
studies of the neonatal brain using diffuse optical techniques have been a
fruitful area of research for nearly 25 years. A number of studies have
successfully employed DOI as a method of imaging neonatal brain injury
(Van Houten et al., 1996; Hebden et al., 2002; Austin et al., 2006), whilst
many more have promoted the use of simpler diffuse optical techniques
for the monitoring of neonatal cerebral haemodynamics (Wyatt et al.,
1986; Cope and Delpy, 1988; Meek et al., 1999; Roche-Labarbe et al.,
2010). Although maintaining adequate cerebral perfusion and oxygenation is critical in newborn infants, limitations in quantification and
precision have prevented the routine clinical use of diffuse optical
techniques (Sorensen and Greisen, 2006).
R.J. Cooper et al. / NeuroImage 55 (2011) 1610–1616
Diffuse optical imaging can provide both excellent temporal
resolution (10 Hz is typical) and good spatial resolution (Gibson et al.,
2005). Even when a planar imaging array is employed, DOI can provide
accurate localisation of changes in haemoglobin concentration to a
depth of up to 30 mm (Correia et al., 2009; Heiskala et al., 2009).
Although combined EEG-fMRI methods have been very successful in
the study of the haemodynamics of epileptic and seizure activity in
children and adults (Gotman, 2008; Vulliemoz et al., 2010), similar
studies are almost impossible with critically ill newborns. Diffuse optical
imaging has several advantages over fMRI. It is portable and can be
brought to the cot-side of an infant in intensive care, is completely
compatible with EEG and is relatively insensitive to movement artifacts.
A simultaneous EEG and diffuse optical imaging (DOI) method is
therefore well suited to the study of the haemodynamics of neonatal
seizure, and could potentially provide an improved method of seizure
We have developed a paradigm which allows EEG, with the full
neonatal clinical montage, to be performed simultaneously with DOI
of a large proportion of the neonatal cerebral cortex. In this paper we
present the results of the application of this technique to four
newborn infants with perinatal brain injury, all of whom had been
diagnosed with seizure. We also present DOI data recorded in a large
number of age-matched controls. These EEG-DOI experiments
represent a preliminary assessment of the suitability of the technique
for the study of neurovascular coupling and neonatal seizure at the
Four infants with perinatal brain injury were recruited from the
Neonatal Intensive Care Unit of The Rosie Maternity Hospital, Cambridge, UK on the basis of a clinical diagnosis of seizure. Ethical
permission was obtained from the Cambridgeshire Research Ethics
Committee and signed informed consent was obtained from the parents
of all recruited infants. All four infants (S01–S04, median gestational
age: 40 weeks, range: 4.4 weeks) had received anticonvulsant medication at the time of the study and were not exhibiting overt clinical
seizure activity. Clinical details of these infants are given in Table 1.
Seven healthy control infants (C01–C07, median gestational age:
38.9 weeks, range: 4.3 weeks) were recruited from the neonatal unit
in Cambridge and a further 12 healthy newborns (C08–C19, all aged
N37 weeks at birth and studied within 3 days) were recruited by the
Laboratoire de Science Cognitive et Psycholinguitique (LSCP) in Paris as
part of a separate investigation.
Experimental paradigm
Studies were performed using a novel dual-modality sensing array
which includes 6 co-located, combined EEG electrodes and optical
fibre bundles. These ‘opto-electrodes’ were described previously
(Cooper et al., 2009). The sensing array consists of two sets of 5
source and 6 detector fibre bundles, providing a total of 60 DOI
channels, with 30 arranged over each temporal lobe. The 22 optical
fibre bundles are coupled to the subject using a silicone rubber cap,
which fixes source-detector separations whilst remaining relatively
flexible and naturally adhering to the scalp. The cap is held in place
using a number of Velcro® straps, which can be adjusted to suit the
individual infant. The array is designed so as to apply opto-electrodes
at locations approximately equal to the 10–20 positions T3, C3, O1, O2,
C4, and T4. The standard neonatal EEG montage is completed by
applying normal EEG electrodes at F3, F4 and Cz as well as reference
and ground electrodes. A diagram of the sensing array is shown in
Fig. 1. In the case of infant S01, a much-simplified simultaneous EEGDOI experiment was performed using two source-detector pairs and
four electrodes arranged bi-laterally over the temporal lobes.
Optical imaging was performed using the UCL Optical Topography
System as described by Everdell et al. (2005). The system can employ
up to 32 laser diode sources and 16 avalanche photodiode detectors
with a sample rate of 10 Hz. Sources are arranged in pairs, with each
pair consisting of one 690 nm source and one 850 nm source.
EEG recording was performed using a MicroMed SystemPlus
clinical system (MicroMed S.p.A, Italy), sampling at 256 Hz or greater,
with a band pass filter applied at 0.3–70 Hz. A 50 Hz notch filter was
also applied to minimise the effect of mains interference in the
electrically noisy neonatal intensive care unit. In infants S02, S03 and
S04, a single-channel electrocardiogram (ECG) was also recorded,
using a dedicated channel of the EEG amplifier system.
Simultaneous EEG-DOI recording was performed for between 45
and 100 min in each brain-injured subject. The length of recording
was determined by the clinical condition of the infant under the
supervision of the attending Neonatologist.
The control data is of three different forms. Control data sets C01 and
C02 were recorded using the same optical imaging array described
above, but without the addition of the EEG system and associated
electrodes (i.e. optical topography data only). Control data sets C03 to
C07 were recorded using a different array which interrogated the
occipital lobe, and included the simultaneous recording of a limitedchannel EEG. Control data sets C08 to C19 were recorded using a second
UCL Optical Topography System, and although the layout of optical
sources and detectors was different to that shown in Fig. 1, the
positioning on the head was very similar, covering the majority of the
temporal lobes. The duration of recording was decided by the attending
Table 1
Clinical details of infants S01–S04.
Infant Age at birth
Age at seizure Age at
(weeks + days) diagnosis
Seizure form
Related condition
4 days
9 days
Left middle and posterior Phenobarbital
cerebral artery infarct
20 h
5 days
Clonic, left-sided movements.
Left-sided seizure confirmed
by aEEG
Clonic movements of legs.
Flicking of eyelids and jaw
3 days
6 days
1 day
13 days Generalised seizures
confirmed by aEEG
Generalised seizures
confirmed by aEEG
Suspected sepsis at
Severe neonatal
encephalopathy. Right
temporal haemorrhagic
Drug regime
Phenobarbital and
clonazepam infusion
clonazepam and
midazolam infusion.
High frequency
Simplified bilateral
oscillatory ventilation NIRS and reducedelectrode EEG
Full EEG-OT with
clinical, 9-electrode
EEG montage
Full EEG-OT with
clinical, 9-electrode
EEG montage
Full EEG-OT with
clinical, 9-electrode
EEG montage
R.J. Cooper et al. / NeuroImage 55 (2011) 1610–1616
Fig. 1. The dual-modality sensing array. Red circles represent source fibre positions and blue circles detector fibres. Those positions with a yellow circle are opto-electrode positions, which
correspond approximately to the 10–20 location specified.
Neonatologist on the basis of the behavioural state of the infant.
Typically, each dataset was 20–25 min in length.
Artifact and event identification
Examination of the un-processed optical data of the neurologically
damaged infants revealed several large, unexplained deviations from
the apparent baseline, which did not appear to be artifact related. An
example of two such features is provided in Fig. 2. In order to
determine a meaningful baseline for these features (which is necessary
to convert raw attenuation data into changes in haemoglobin
concentrations), and to determine whether they were consistent and
repeated, it was necessary to develop an objective, automated approach
to the identification of these events. Such an approach would then be
applicable to age-matched control data, which would allow us to
determine whether these features are a common occurrence in this age
group or whether they are related to neuropathology.
The analysis consisted of two operations. The first was to locate
and reject periods of optical topography data which were corrupted
by movement artifact, and the second was to identify the features of
interest. Before either of these operations was performed the dataset
was pre-filtered using a band-pass Butterworth filter between 0.002
and 1.5 Hz to eliminate very slow trends in laser diode source power,
high-frequency noise, and heart rate oscillations.
In order to identify periods of movement artifact, we used the
following approach: The standard deviation (SDn (t)) of the 5 s of optical
intensity data about each data point (t) was calculated for each sourcedetector pair (n). The mean standard deviation for each source-detector
pair (SDn ) was also calculated. Changes in total haemoglobin concentration (HbT(t)) were calculated for the entire optical data set using the
mean intensity of each channel as a baseline. These data were then
differentiated to give the rate of change in total haemoglobin
concentration (HbT'(t)). If a given data point, for any channel, was
found to occupy a data window with a standard deviation greater than x
times the mean standard deviation, whilst the rate of change of total
haemoglobin exceeded a threshold of y (i.e. if SDn(t) N x × SD AND
HbT'(t) N y) then the 5 s of data before and after that data point, for all
channels, was identified as movement corrupted. By comparison with
the visual inspection of movement-corrupted data from a previous
functional activation study, the final values of x and y were selected to be
4.5 (dimensionless) and 0.3 μM/s respectively.
After periods of movement artifact had been rejected, events were
identified by using a variation in optical intensity from a mean ~DC
filtered baseline (0.002–0.005 Hz). On visual inspection the observed
features appeared large (relative to background variations), slow
(typically N30 s) and dominated by an increase in intensity. Therefore
the identification algorithm was designed to find periods where the
mean intensity over 15 s of data exceeded the baseline by 8% (of the
baseline intensity) in at least one channel at one wavelength. Once an
event was located, the following 100 s of data were skipped to prevent
a single event being identified repeatedly. Where possible, these
events were then subjected to a further rejection process based on
visual inspection of the synchronised EEG data. If excessive movement
was present in the EEG, the event was rejected. For infants S01–S04
and C01 and C02, this entire event identification process was
performed independently for data recorded over each side of the
head so that any lateralisation could be identified.
Once an event was identified, an epoch consisting of 100 s of data
before and after that event position was selected. Variations in
oxyhaemoglobin concentration [HbO2] and deoxyhaemoglobin concentration [HHb], and reconstructed optical images were then produced
using a period prior to the identified event position as a baseline. The
baseline period was selected as the average of the first 40 s of each epoch
(i.e. from ­100 to ­60 s relative to the identified event position).
Images of the change in optical absorption were produced using a
linear image reconstruction algorithm based on the Rytov approximation
to the diffusion equation (Gibson et al., 2005). These images were then
converted to changes in [HbO2] and [HHb] using the specific absorption
coefficients reported by Matcher et al. (1995).
Fig. 2. An example of a period of un-processed optical data showing two completely
lateralised features in quick succession from infant S01. The red traces correspond to
670 nm sources and the blue traces to 850 nm sources.
The results of the movement and event identification procedures
for four neurologically damaged infants (sample) and the 19 healthy
term infants (control) are as follows: An average of 1.41% and 14.9% of
DOI data were rejected due to movement artifact in the sample and
control groups respectively. The average number (and standard
deviation) of events identified per hour of accepted DOI data was 8.5
(6.7) for the sample group and 6.5 (4.8) for the control group. Note
that a significant fraction of the 90 min of optical imaging data
acquired for infant S04 was removed prior to the implementation of
the processing algorithms because of the presence of a significant
R.J. Cooper et al. / NeuroImage 55 (2011) 1610–1616
increase in background noise, believed to be related to changes in
ambient light conditions in the neonatal intensive care unit which
were beyond our control.
The percentage of the optical topography data rejected due to
movement artifact in the neurologically damaged infants is significantly
lower on average than that of the control infants (student t-test,
p b 0.05). This is very likely due to the various levels of sedation to which
the sample infants were subjected; movement was far less common.
The number of identified events per hour of non-movement-corrupted
data for the sample infants is not significantly different from those of the
control infants (student t-test, p b 0.05). The events identified in infant
S01 are completely lateralised, occurring only over the left hemisphere.
For S02, some events were identified on both sides of head individually,
and some occurred globally. Infant S03 exhibited no independent rightsided events, but several on the left and globally. Only one event was
identified in infant S04, but it was rejected on the basis of movement on
the EEG recording.
Data from a single selected channel showing haemoglobin concentration variations for the first event identified in infants S01 to S03 are
shown in Fig. 3a–c. A selection of mean defined events, for all three
infants, is shown in Fig. 4. Although the scale and duration is variable, the
form of these events, both within and across infants, is remarkably
consistent. Oxyhaemoglobin concentration increases significantly and
reaches a peak after a mean (and standard deviation) of 26.2 (12.5) s. It
then rapidly decreases, to significantly below the defined baseline,
reaching a minimum after an average of 55.5 (13.3) s before slowly
returning to baseline. The average total [HbO2] event duration is 103.4
(19.7) s. Deoxyhaemoglobin concentration follows a similar pattern,
though does not generally exhibit as significant a change. The deviations
from baseline of [HbO2] and [HHb] occur slightly out of phase, with
[HbO2] changes lagging behind those of [HHb] by an average of 3.4 (1.3) s.
Deoxyhaemoglobin concentration returns to its baseline value more
quickly than [HbO2], such that the average total [HHb] event duration is
91.6 (27.7) s. The average inter-event interval in the neurologically
damaged infants is 393.6, but varied significantly from approximately
2 min up to more than 21 min seconds, with a standard deviation of
306.0 s.
An example of a single identified event and the mean of the all
defined events in control data set C01 are shown in Figs. 3d and 4d,
respectively. These figures are representative of all control results
because the events identified within the 14 control data sets appear,
without exception, to be non-physiological. None of the events
identified in any of control infants show the slow, biphasic pattern
apparent in the data from the neurologically damaged infants. The
origin of the events that are identified in the control data sets is likely
to be either movement or other artifacts which have failed to be
Fig. 5 shows an example image series for one left-sided event
occurring in infant S02. This series of reconstructed images shows a
large, lateralised and focal increase in [HbO2] followed by a sudden,
but less focal, decrease. These changes are most significant in the
voxel layer centred at a depth of 10.5 mm. A similar pattern is
observed in [HHb]. The right side of the head exhibited no comparable
changes during this period.
The EEG data from infants S01–S04 were examined by a clinical
neurophysiologist experienced in neonatal EEG examination. Infants
S01–S03 all exhibited some suppression of EEG amplitude and S02
and S03 were discontinuous. The EEG of infant S04 was continuous
and not obviously suppressed. None of the data sets contained
evidence of electrographic seizure activity. Once the optical events
described above had been identified, the corresponding periods of
EEG were re-examined and no consistent variation in EEG pattern
could be observed in any of the infants. Where available, the ECG was
converted to a measure of heart rate, which was examined during
each defined event. Again, no consistent or significant variations were
These experiments are, to our knowledge, the first example of the
use of full montage neonatal EEG simultaneously with diffuse optical
topographic imaging. Despite failing to observe any electrographic
seizure events, we have used a simple, automated approach to identify a
repeated, transient haemodynamic event which is present in the diffuse
Fig. 3. Axes a–c show single-channel examples of one haemodynamic event identified in each of the neurologically damaged infants S01–S03. Axis d shows an event defined in
control infant C01, which is representative of all the events identified in the control group and appears to be non-physiological in origin.
R.J. Cooper et al. / NeuroImage 55 (2011) 1610–1616
Fig. 4. Examples of the average of defined events. The first column shows a left- and a right-sided channel for the mean of all the left-sided events in infant S01. The second column
shows a left and a right-sided channel for the mean of all left-sided events in infant S02 and the third column shows a left and a right-sided channel for the mean of all globally
defined events in infant S03. The fourth column shows a left and right-sided channel for all globally defined events in control infant C01, which appear to be non-physiological in
origin. The horizontal red and blue bars indicate periods of significant HbO2 and HHb change relative to the period of data from ­100 to ­60 s, using a two-tailed t-test with p b 0.05.
Fig. 5. An example of a series of reconstructed images of change in HbO2 concentration for a single event defined in infant S02. The series consists of 20 images, each reconstructed
using the mean of 10 s of data and corresponding to a depth of 9–12 mm. This was the layer of greatest HbO2 concentration change. The time position gives the time about which
each 10 s of data was centred, relative to the defined event start time.
R.J. Cooper et al. / NeuroImage 55 (2011) 1610–1616
optical data of three out of four neurologically compromised infants but
is completely absent in 19 healthy, age-matched newborns.
Data sets C01 to C19 do not constitute ideal controls. Simultaneous
EEG recording was only performed in C03 to C07, which interrogated a
different region of the brain, and the experiments which resulted in data
sets C08 to C19 were performed using a different arrangement of sources
and detectors. The control group were also not subject to mechanical
ventilation or sedation. However, these control data sets were sufficient
to establish that these large, slow variations in haemoglobin concentrations are not a common feature of neonatal cerebral haemodynamics.
These haemodynamic events appear robust and consistent within
our relatively small sample, and all evidence indicates that they are of
a physiological origin. The fact that these data can be reconstructed to
produce meaningful images, particularly ones which show a peak
change at a cortical depth, is a particularly strong indication that these
events are due to variations in cerebral haemoglobin concentrations
and not due to artifact or physiological changes in superficial tissues.
The absence of any events in infant S04, who was examined 12 days
after the initial seizure diagnosis, was only lightly sedated and
exhibited little EEG abnormality, is a further indication that these
haemodynamic events are not an artifact inherent to the paradigm.
Although these events are apparently physiological, their origin is,
as yet, undetermined. Without other physiological measures it is
impossible to know for certain whether these events represent
localised changes in cerebral blood flow and volume due to variations
in neuronal metabolism, or whether they result from a failure in the
brain's ability to insulate itself from systemic changes. The fact that
many of these events are lateralised, and even focal, and that (where
measured) there was no associated fluctuation in heart rate, does
suggest that these events have a non-systemic origin. However, it is
also possible that an inhomogeneous response of localised regions of
damaged tissue to a systemic change in blood pressure could give rise
to such focal changes.
The haemodynamic events we have identified are consistent in their
form, but they do not exhibit the variations in [HHb] which are
commonly associated with a change in regional cerebral blood flow
(rCBF) in adults. The classical response to functional stimulation consists
of increase in [HbO2] and a concurrent decrease in [HHb], producing a
positive BOLD signal (Obrig and Villringer, 2003). Studies of functional
activation using BOLD-fMRI and diffuse optical techniques have shown
the haemodynamic response in newborn infants to be highly variable.
Whilst the functional response is still associated with an increase in
rCBF, many studies have reported an increase in both oxy and
deoxyhaemoglobin concentrations (Meek et al., 1998; Hoshi et al.,
2000; Muramoto et al., 2002).
Although the aetiology of the brain injury was heterogeneous, the
diagnosis of seizure and the application of the anti-epileptic drug
phenobarbital are the only features common to all the infants in
which these haemodynamic events were identified. Studies of partial
seizure events in adults using single photon emission computed
tomography (SPECT) have consistently reported a sustained ictal
increase in rCBF followed by a decrease in rCBF relative to the interictal state (Duncan, 1997). This has been confirmed using ictal EEGfMRI (Salek-Haddadi et al., 2002). Slow changes in regional cerebral
blood flow in brain-injured adults, measured using laser Doppler
flowmetry, have been shown to be associated with cortical spreading
ischaemia (Dreier et al., 2009), but no such findings exist for infants.
The only published study which has observed the haemodynamic
response to neonatal seizure is that of Wallois et al. (2009). They used
the onsets of ‘seizure-like’ EEG discharges to isolate haemodynamic
features which consisted of an increase in [HHb] and [HbO2], followed
by an undershoot of [HHb] only, and a slow return to baseline. Twenty of
these features were observed in a 2-h recording and they lasted an
average of 171 s. We were recently made aware of earlier, unpublished
data in which EEG-informed near-infrared spectroscopy of neonatal
seizure in three infants showed a large slow increase in [HbO2] and
[HHb] followed by a significant undershoot of both, in a manner almost
identical to the haemodynamic events described here (Roche-Labarbe
and Wallois, personal communication).
The suitability of phenobarbital as a default treatment for neonatal
seizure is still the subject of debate, as it successfully controls seizure
in fewer than half of infants (Painter et al., 1999; Rennie et al., 2008).
The persistence of electrographic seizures when all clinical symptoms
have been suppressed is a common feature of treatment with
phenobarbital and suggests the preferential suppression of particular
cortical activity (Scher, 2003). In large doses, phenobarbital is known
to cause a generalised suppression of EEG activity but the effect of
phenobarbital on cerebral haemodynamics is unknown. We believe it
is possible that these transient haemodynamic events represent a
response to seizure-like activity in groups of neurons which, due to
their location or the effects of phenobarbital, do not produce
observable electrographic discharges. This would potentially explain
the form of these haemodynamic features, which seem consistent
with a sudden increase in cerebral blood flow that is insufficient to
meet a significant increase in metabolic demand. This hypothesis
does, however, remain highly speculative.
We have identified consistent, transient haemodynamic events in
term infants with perinatal brain injury, in whom the diagnosis of
seizure and the treatment with phenobarbital are the only common
factors. These events consist of an initial increase, then dramatic fall in
[HbO2] and [HHb], which can be either localised or global. Although
these features show remarkable consistency in three out of four
infants studied here, their incidence in brain-injured infants, and their
association with particular neurological conditions and medications is
beyond the limits of this study. Whether these features result from
disturbances in local autoregulatory control or from continuing
seizure-related neuronal activity, not visible to conventional EEG, is
uncertain and warrants further investigation.
We would like to thank Dr. Emmanuel Dupoux of the Laboratoire
de Science Cognitive et Psycholinguistique, Paris. This research was
supported by the Engineering and Physical Sciences Research Council.
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Transient haemodynamic events in neurologically compromised infants: