The longitudinal changes of BOLD response and cerebral hemodynamics from acute to subacute stroke. A fMRI and TCD study.

Abstract

By mapping the dynamics of brain reorganization, functional magnetic resonance imaging MRI (fMRI) has allowed for significant progress in understanding cerebral plasticity phenomena after a stroke. However, cerebro-vascular diseases can affect blood oxygen level dependent (BOLD) signal. Cerebral autoregulation is a primary function of cerebral hemodynamics, which allows to maintain a relatively constant blood flow despite changes in arterial blood pressure and perfusion pressure. Cerebral autoregulation is reported to become less effective in the early phases post-stroke. This study investigated whether any impairment of cerebral hemodynamics that occurs during the acute and the subacute phases of ischemic stroke is related to changes in BOLD response. We enrolled six aphasic patients affected by acute stroke. All patients underwent a Transcranial Doppler to assess cerebral autoregulation (Mx index) and fMRI to evaluate the amplitude and the peak latency (time to peak-TTP) of BOLD response in the acute (i.e., within four days of stroke occurrence) and the subacute (i.e., between five and twelve days after stroke onset) stroke phases.
As patients advanced from the acute to subacute stroke phase, the affected hemisphere presented a BOLD TTP increase (p = 0.04) and a deterioration of cerebral autoregulation (Mx index increase, p = 0.046). A similar but not significant trend was observed also in the unaffected hemisphere. When the two hemispheres were grouped together, BOLD TTP delay was significantly related to worsening cerebral autoregulation (Mx index increase) (Spearman's rho = 0.734; p = 0.01).
The hemodynamic response function subtending BOLD signal may present a delay in peak latency that arises as patients advance from the acute to the subacute stroke phase. This delay is related to the deterioration of cerebral hemodynamics. These findings suggest that remodeling the fMRI hemodynamic response function in the different phases of stroke may optimize the detection of BOLD signal changes.

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BMC Neuroscience
Open Access
Research article
The longitudinal changes of BOLD response and cerebral
hemodynamics from acute to subacute stroke. A fMRI and TCD
study
Claudia Altamura*1,2, Matthias Reinhard3, Magnus-Sebastian Vry3,
Christoph P Kaller3, Farsin Hamzei3, Fabrizio Vernieri1,2,
Paolo Maria Rossini1,4, Andreas Hetzel3, Cornelius Weiller3 and
Dorothee Saur3
Address: 1Neurologia Clinica, Università Campus Bio-Medico di Roma, Italy, 2Associazione Fatebenefratelli per la Ricerca (AFaR): Dipartimento
di Neuroscienze, Fatebenefratelli, Isola Tiberina, Rome, Italy, 3Department of Neurology, University Medical Center Freiburg, Germany and 4Casa
di Cura San Raffaele - Cassino, Cassino, Italy
Email: Claudia Altamura* - c.altamura@unicampus.it; Matthias Reinhard - matthias.reinhard@uniklinik-freiburg.de; Magnus-
Sebastian Vry - magnus-sebastian.vry@uniklinik-freiburg.de; Christoph P Kaller - christoph-p.kaller@uniklinik-freiburg.de;
Farsin Hamzei - farsin.hamzei@uniklinik-freiburg.de; Fabrizio Vernieri - f.vernieri@unicampus.it;
Paolo Maria Rossini - paolomaria.rossini@afar.it; Andreas Hetzel - andreas.hetzel@uniklinik-freiburg.de;
Cornelius Weiller - cornelius.weiller@uniklinik-freiburg.de; Dorothee Saur - dorothee.saur@uniklinik-freiburg.de
* Corresponding author
Abstract
Background: By mapping the dynamics of brain reorganization, functional magnetic resonance
imaging MRI (fMRI) has allowed for significant progress in understanding cerebral plasticity
phenomena after a stroke. However, cerebro-vascular diseases can affect blood oxygen level
dependent (BOLD) signal. Cerebral autoregulation is a primary function of cerebral hemodynamics,
which allows to maintain a relatively constant blood flow despite changes in arterial blood pressure
and perfusion pressure. Cerebral autoregulation is reported to become less effective in the early
phases post-stroke.
This study investigated whether any impairment of cerebral hemodynamics that occurs during the
acute and the subacute phases of ischemic stroke is related to changes in BOLD response.
We enrolled six aphasic patients affected by acute stroke. All patients underwent a Transcranial
Doppler to assess cerebral autoregulation (Mx index) and fMRI to evaluate the amplitude and the
peak latency (time to peak-TTP) of BOLD response in the acute (i.e., within four days of stroke
occurrence) and the subacute (i.e., between five and twelve days after stroke onset) stroke phases.
Results: As patients advanced from the acute to subacute stroke phase, the affected hemisphere
presented a BOLD TTP increase (p = 0.04) and a deterioration of cerebral autoregulation (Mx
index increase, p = 0.046). A similar but not significant trend was observed also in the unaffected
hemisphere. When the two hemispheres were grouped together, BOLD TTP delay was
significantly related to worsening cerebral autoregulation (Mx index increase) (Spearman's rho =
0.734; p = 0.01).
Published: 20 December 2009
BMC Neuroscience 2009, 10:151doi:10.1186/1471-2202-10-151
Received: 2 April 2009
Accepted: 20 December 2009
This article is available from: http://www.biomedcentral.com/1471-2202/10/151
© 2009 Altamura et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Conclusions: The hemodynamic response function subtending BOLD signal may present a delay
in peak latency that arises as patients advance from the acute to the subacute stroke phase. This
delay is related to the deterioration of cerebral hemodynamics. These findings suggest that
remodeling the fMRI hemodynamic response function in the different phases of stroke may
optimize the detection of BOLD signal changes.
Background
Neural tissue that survives the damaging effects of a stroke
can reorganize in order to recover lost functions. The dis-
inhibition of cortical activities can lead to the over-activa-
tion of areas belonging to the physiological neural
network and of areas that are recruited to replace the func-
tions of the damaged tissue. Alternatively, cerebral activa-
tion can be inhibited in brain regions that are remote
from the damaged area (i.e., diaschisis) [1-3]. The impact
of brain area over-recruitment on functional recovery was
investigated by longitudinal studies that tracked the evo-
lution of such plastic changes over time [4-6]. These stud-
ies found that there was an over-activation of certain brain
areas (including supplementary areas and contra-lesional
homologue areas) in the sub-acute phase followed by the
progressive focusing of cerebral activation associated with
clinical recovery [4-6]. In aphasic patients, this phenome-
non was reported to have a tri-phasic trend from the acute
to the chronic stage; the initially reduced cerebral activa-
tion was followed by an over-activation of the language
cortical network in the subacute phase, which was fol-
lowed by a progressive focusing of cerebral activation [7].
Although the use of fMRI allowed investigators to make
significant progresses in understanding post-stroke cere-
bral plasticity, blood oxygen level dependent (BOLD) sig-
nals may be reduced [8-13], absent [14,15] or negative
[16] in patients with cerebro-vascular disease. Cerebro-
vascular diseases may also affect the shape of the hemody-
namic response function (HRF) of BOLD signal. In partic-
ular, HRFs in such patients can have lower amplitudes,
longer latency to peak intervals (time to peak = TTP), and
deeper initial dips [9,16-19].
These findings were also reported in cases of preserved
neuronal activity [14-16] and in relation to altered cere-
bral hemodynamics [9,11,14], which suggests that
reduced BOLD signals might reflect the decrease of neuro-
nal activation or be the consequence of neurovascular
uncoupling. These results raise the question of whether
the longitudinal changes of cerebral activation that are
found during early post-stroke phases [4-7] are due in part
to cerebral hemodynamic impairment.
Cerebral hemodynamics are characterized by the follow-
ing two distinctive properties: autoregulation (i.e., the
maintenance of relatively constant blood flow despite
changes in arterial blood pressure (ABP) and perfusion
pressure) and vasomotor reactivity (i.e., the potential for
cerebral vessels to dilate subsequent to hypercapnia). The
assessment of cerebral vasomotor reactivity requires the
patient's cooperation since hypercapnia is induced by
holding one's breath or by inhaling CO2 enriched air. In
addition, this test is potentially harmful for acute stroke
patients since hypercapnia may increase ABP. By contrast,
autoregulation can be non-invasively evaluated by corre-
lating the spontaneous oscillations of ABP and cerebral
blood flow velocity (CBFV). This does not require any
cooperation from the patient [20,21]. This correlation is
measured by calculating a coefficient named Mx index
[20,21]. A high Mx index indicates a dependence of CBFV
on ABP that is attributable to autoregulatory impairment.
Cerebral autoregulation was reported to worsen between
the acute and subacute stroke phases [20,21]. This phe-
nomenon could be explained by arteriolar dysfunction
that develops at the ischemic site and spreads to remote
areas later in the post-stroke interval. It was hypothesized
that a vicious circle can start in the peri-infarct area by
spreading local acidosis, and then is amplified by reper-
fusion (either spontaneously or induced by thrombolysis)
with a consequent dysautoregulation [21,22]. In addition,
bursts of oxidative stress induced by cerebral ischemia
lead to profound alterations in cerebro-vascular regula-
tion. In particular, reactive oxygen species can impair
endothelial NO-mediated responses, vasodilation (medi-
ated by potassium channel activation), and vasoconstric-
tor mechanisms [23]. Finally, hemispheric strokes can
damage the central autonomic network thereby altering
the neural control mechanisms of cerebral vessels [24].
Despite early impairment of cerebral hemodynamics, lon-
gitudinal changes of BOLD signal HRF in the acute and
subacute stroke phases have never been explored. One
hypothesis is that the deterioration of cerebral hemody-
namics in early phases following a stroke can affect BOLD
signal HRF.
This study investigated whether the impairment of cere-
bral hemodynamics that occurs as patients advance from
the acute to the subacute stroke phase is related to changes
in the BOLD signal HRF.

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To test this hypothesis, we evaluated cerebral autoregula-
tion (Mx index) and the amplitude and peak latency
(TTP) of BOLD responses to auditory stimuli in the audi-
tory cortex of 6 aphasic patients during the acute and the
subacute phases of stroke. At the time of recruitment, the
patients were taking part in two ongoing longitudinal
fMRI studies on language recovery.
Results
Clinical findings
Table 1 summarizes our patients' clinical characteristics.
Figure 1 shows diffusion-weighted MRIs at the maximum
infarct volume level.
Clinical status significantly improved between the first (Ex
1) the second (Ex 2) examination (Wilcoxon test, p =
0.04). None of the parameters examined in the fMRI or
TCD studies was related to vascular risk factors or clinical
outcome (Spearman's rho, consistently p > 0.2).
Ultrasound findings
Cerebral hemodynamic parameters are listed in Table 2.
CBVF did not differ significantly between the two hemi-
spheres in either the acute (Wilcoxon test, p = 0.3) or in
subacute stroke phase (p = 0.2). No variation of CBVF was
observed between Ex 1 and Ex 2 in the two hemispheres
(affected hemisphere (AH), p = 0.17; unaffected hemi-
sphere (UH), p = 0.11).
At Ex 1, the Mx index did not differ between the hemi-
spheres (Wilcoxon test, p = 0.8), though the Mx index was
higher at Ex 2 (i.e., worse cerebral autoregulation) in the
AH as compared with the UH (p = 0.027). The Mx index
increased between examinations in the AH (Wilcoxon
test, p = 0.046) and not significantly in UH (p = 0.09)
fMRI findings
Table 3 shows TTP and amplitude values that were meas-
ured in both hemispheres of the control subjects. Table 2
shows TTP and amplitude values that were measured in
the AH and UH of stroke patients at Ex 1 and Ex 2. Because
of an internal carotid occlusion, the fMRI failed to detect
auditory cortical activation in the AH of patient 4.
TTP measurements did not reveal differences between the
two hemispheres at Ex 1 (Wilcoxon test, p = 0.9) or Ex 2
(p = 0.18). At Ex 2 TTP was delayed (p = 0.04) in the AH
and in the UH with a trend toward significance (p =
0.059).
At both examination times, amplitude measurements did
not reveal differences between hemispheres (Wilcoxon
test, p > 0.2). Between Ex 1 and Ex 2, amplitude did not
change in the UH (p > 0.4), while it tended to decrease
with a trend toward significance in the AH (p = 0.06).
Figures 2 and 3 contain estimations of the hemodynamic
response function (HRF) in six healthy subjects (panel A)
and one representative patient (panel B) for language par-
adigms 1 and 2, respectively.
To analyze a possible correlation between TTP elongation
and Mx increase, we first calculated the variation between
Ex 1 and Ex 2 for each parameter. We found that BOLD
peak delays correlated with worsening cerebral auto-regu-
lation (Spearman's rho = 0.734; p = 0.01). This result was
obtained after taking into consideration, through the use
Table 1: Patients' clinical characteristics.
PtAgeAHClinical
Symptoms
NIHSS
Exp 0
Lesion siteStenosis ICA (%)Vessel
Occlusion
TrombolysisRisk factors
AH UH
1, ?
66LAphasia8PC00MCA-branchYHypert, smoke
2, ?
69LAphasia/Hemiparesis FB14 FC, PC00MCA-branch YAF
3, ?
63L Aphasia6 FC, PC00MCA-branchYHypert, AF
4, ?
46LAphasia6PC1000 M2NHypert, smoke
5, ?
72LAphasia3TC00 MCA-branchYHypert, Chol
6, ?
44LAphasia7FC00MCA-branchYHypert
Pt:patient; ?: man, ?: woman; AH: affected hemisphere, UH: unaffected hemisphere; L = left, R = right; Clinical Symptoms: FBC = facial/brachial/
crural; NIHSS Exp 0: NIH stroke scale at emergency room admission; Lesion site: BG = basal ganglia, IC = internal capsula, PC = parietal cortex, FC
= frontal cortex, TC = Temporal Cortex; Stenosis ICA = internal carotid artery; Vessel Occlusion: MCA = Middle Cerebral Artery, M2 = M2 segment
of middle cerebral artery, Trombolysis: Y = yes, N = no; Risk factors: hypert = Hypertension, AF = atrial fibrillation, Smoke = cigarette smoking, Chol
= hypercholesterolemia.

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of a Generalized Estimating Equations model, both hem-
ispheres and the within-subject dependence.
Discussion
Our main finding is that the progressive worsening of cer-
ebral hemodynamics is related to an increased latency of
the BOLD signal HRF from the acute to the subacute
stroke phase.
Increases in BOLD peak latency were previously observed
in patients with cerebro-vascular stenotic disease [18,25]
and in patients with chronic aphasia [19]. BOLD peak
latency increases were also analyzed in relation to clinical
outcome [17]. Different hypotheses can explain the find-
ings in these studies. During activation tasks, delayed
BOLD peak latency can be the effect of initial oxidative
metabolism wherein an increase in deoxy-hemoglobin is
followed by a slower increase in oxy-hemoglobin and
regional cerebral blood flow. In patients suffering from
internal carotid or intracranial steno-occlusive disease,
this phenomenon could be due to the vasodilatation of
the arterioles down-stream from the stenosis, which
increases the regional cortical blood volume at rest. In this
condition, an additional increase of blood flow during
neural activation is necessary for the detection of a BOLD
response. When evaluating fMRI activation in a damaged
cortex, the TTP increase might depend on the increased
oxygen extraction fraction due to decreased oxygen deliv-
ery during activation [26,27].
In contrast to previous studies reporting a TTP increase in
the damaged cortex of chronic patients [17,19] or in
asymptomatic patients with vascular steno-occlusive dis-
ease [18,25], we found increases in BOLD peak latency in
Ischemic Lesions
Figure 1
Ischemic Lesions. Axial Diffusion Weighted MR images of enrolled patients. The left side of the figure corresponds to the
left side of the brain.

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Table 2: fMRI and Cerebral hemodynamics parameters from the acute to the subacute phase of stroke
PtEx 1Ex 2NIHSS AH UH
TTPAmplCBFVMx index TTPAmpl CBFVMx index
Ex 1Ex 2Ex 1Ex 2Ex 1Ex 2 Ex 1Ex 2 Ex 1Ex 2Ex 1 Ex 2 Ex 1Ex 2 Ex 1 Ex 2Ex 1 Ex 2
Parad 1
11563 5.48 6.570.860.56 48.6 56.90.01 0.54 5.486.570.89 0.5050.1 45.9-0.15 0.52
2281413 5.486.570.560.4239.533.10.040.415.486.570.580.4843.227.1-0.050.28
325425.487.670.620.5241.830.6-0.120.425.486.570.890.49 47.735.8-0.100.36
Parad 2
43 1054----50.353.80.140.275.525.520.250.3351.443.7 0.420.09
54 12315.52 6.440.450.17 57.8 46.2 0.260.25 5.525.52 0.190.3236.145.6 0.120.23
619335.526.44 0.530.3462.753.1 0.140.665.526.44 0.44 0.5377.955.40.210.57
Mean
(SD)
2.2
(1.2)
8.2
(2.8)
5.8
(4.2)
4.3
(4.4)
5.50
(0.02)
6.74
(0.53)
0.60
(0.16)
0.40
(0.16)
50.12
(8.96)
45.62
(11.25)
0.08
(0.13)
0.43
(0.16)
5.50
(0.02)
6.20
(0.53)
0.54
(0.30)
0.44
(0.09)
51.07
(14.27)
42.25
(9.70)
0.08
(0.22)
0.34
(0.18)
p = 0.04p = 0.04
p = 0.06p = 0.17
p = 0.046
p = 0.059p = 0.46p = 0.11p = 0.09
Parad 1 and 2: Language paradigm 1 and 2 respectively; Ex 1 and Ex 2: days from stroke onset; NIHSS NIH stroke scale at the first examination time (Ex 1) and at the second examination time
(Ex 2); TTP: time to peak expressed in seconds and Ampl: Peak Amplitude of BOLD.; AH: affected hemisphere, UH: unaffected hemisphere; CBFV: mean MCA cerebral blood flow velocity
expressed in cm/s; Mx index: correlation coefficient between CBFV and arterial blood pressure; Mean (SD): mean values (Standard deviation); in the bottom raw p values for comparison of each
measure from Ex 1 to Ex 2 are reported, and evidenced in bold in case of statistical significance.

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preserved cerebral cortices (i.e., perilesional or those
remote from the infarction) and in absence of steno-
occlusive diseases. In our patients, a longer peak latency of
BOLD HRF could be the consequence of a general deteri-
oration of arteriolar endothelial/smooth muscle cell func-
tion, which impairs cerebral auto-regulation [21-23] and
limits the increase of regional blood flow (and oxy-hemo-
globin) produced by functional activation [26].
On the other hand, neither BOLD HRF nor cerebral auto-
regulation was altered in the acute stroke phase. This sug-
gests that an alteration of cerebral hemodynamics alone
cannot explain the impairment of BOLD signal in acute
stroke patients. Decreased fMRI activation, which was pre-
viously reported in the acute stroke phase [2,6,7], could
actually reflect lower levels of neuronal firing also in cor-
tical areas distant from the ischemic lesion. The following
potential reasons for such reduced neuronal function can
be hypothesized: an initial "stunned" brain phenomenon
that is functioning as a protective mechanism [28]; cellu-
lar and metabolic changes; prolonged hypoperfusion
despite recanalization; and incomplete infarction with
neuronal dysfunction after critical hypoperfusion [29,30].
An alternative explanation may involve the functional-
anatomic location of the lesion and its participation in a
neuronal network (i.e., "diaschisis") [31].
Previous studies have reported that hemodynamic impair-
ment can affect fMRI signal detection [9,11,14]. In the
chronic stroke phase, BOLD HRFs can have decreased
amplitudes and longer latencies to peak [17,19]. The
present study confirms these findings and reports for the
first time the dynamic variations of BOLD signals from
the acute to the subacute stroke phase as they relate to cer-
ebral hemodynamic deterioration. This may provide addi-
tional knowledge for the interpretation of early changes in
post-stroke fMRI activation.
New fMRI studies are targeting early cerebral reorganiza-
tion within the acute and sub acute stroke phases, proba-
bly responsible for initial clinical recovery and for long-
term outcome. However, our findings recommend cau-
tion when interpreting results from longitudinal studies.
Changes in BOLD activation could be either the result of
cerebral reorganization or the effects of hemodynamic
impairment over time. In particular, if the HRF of BOLD
signal detected in stroke patients has a TTP different from
that normally assumed, the analysis fMRI data might be
invalidated. The main limitation of our study is the small
number of patients enrolled. In fact, this may have lead to
an underestimation of other longitudinal changes of
BOLD HRF (i.e., amplitude). In addition, since hyperten-
sion and other vascular factors can influence cerebral
hemodynamics and thereby affect BOLD signals [32], a
control population with vascular factors comparable to
our patients would allow us to better compare TTP values
between the two groups. We cannot exclude the possibil-
ity that the observed increases in TTP in our patients were
Table 3: Parameters of Hemodynamic Response Function of BOLD signal in controls
TTPAmplTTP Ampl
SbAgeRLRL Sb AgeRLRL
Paradigm 1
1605.485.48 0.72 0.52
Paradigm 2
7 665.52 5.52 0.310.28
2695.485.480.620.588 455.525.520.310.42
3 715.485.480.57 0.859595.525.520.490.41
4 56 5.485.480.59 0.68 10 415.52 5.520.44 0.49
5 585.48 5.480.88 0.9311576.446.440.500.67
6 465.485.48 0.240.22 12 525.52 5.520.310.37
Mean
(SD)
60
(9)
5.485.480.60
(0.19)
0.63
(0.23)
53
(9)
5.675.670.39
(0.09)
0.44
(0.13)
Paradigm 1 and 2: Language paradigm 1 and 2 respectively; TTP: time to peak expressed in seconds and Ampl: Peak Amplitude of BOLD; R: right
hemisphere; L: left hemisphere. Please note that differences in the mean amplitude values between table 3 and figures 2 and 3 are due to the fact,
that in the table values were extracted from individual peak voxels, while in the figures they were extracted from the group peak voxel.

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the consequence of their additional vascular ailments
rather than the result of the stroke itself. Similarly, in
order to assess whether TTP could be considered a stable
measure in different examinations, control subjects
should have undergone fMRI at two different times.
Conclusions
Our data demonstrate a longitudinal change in BOLD
HRF that is possibly due to the sub-acute impairment of
cerebral hemodynamics. Our findings suggest that remod-
eling the fMRI HRF and adapting other parameters (e.g.,
stimulus duration or signal acquisition time) for different
stroke phases may optimize the detection of BOLD signal
changes. In addition, an integrated analysis that includes
neurophysiological techniques or hemodynamic evalua-
tion should be used also in longitudinal studies that
investigate cerebral plastic reorganization via metabolic
signal based imaging methods.
BOLD signal in controls and patient 2 performing language paradigm 1
Figure 2
BOLD signal in controls and patient 2 performing language paradigm 1. (A) HRF extracted from the peak voxel in
the bilateral auditory cortex of six healthy control subjects performing language paradigm 1. Plots represent the mean contrast
estimate across subjects (y-axis) within each time bin (x-axis). The dark grey bar indicates the time bin with the highest con-
trast estimate as an estimation of the TTP latency. (B) HRF extracted from the peak voxel in the bilateral auditory cortex of
patient 2 at day 2 (upper row) and day 8 (lower row). Plots represent mean contrast estimate across stimuli (x-axis) within
each time bin (y-axis). From day 1 to day 8, TTP latency increased (from time bin 5 to time bin 6) and amplitude decreased
slightly in both hemispheres.

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Further studies are needed to confirm our findings for dif-
ferent stroke types and vascular territories and to assess
the extent the mean TTP delay in the sub-acute stroke
phase in a larger population. This would be useful for
adapting the hemodynamic function that underlies the
BOLD-signal in the analysis of cerebral activation data
from patients in the subacute post-stroke phase.
Methods
Patients
Six patients (4 men; mean age 60.0 ± 12.0 years) with
acute ischemic stroke within the middle cerebral artery
(MCA) territory presenting with aphasia were enrolled in
this study. The diagnosis of ischemic stroke was based on
clinical criteria and on the results of diffusion weighted
MRI at admission (figure 1). The site of vessel occlusion
BOLD signal in controls and patient 6 performing language paradigm 2
Figure 3
BOLD signal in controls and patient 6 performing language paradigm 2. (A) HRF extracted from the peak voxel in
the bilateral auditory cortex of six healthy control subjects performing language paradigm 2. Plots represent the mean contrast
estimate across subjects (y-axis) within each time bin (y-axis). The dark grey bar indicates the time bin with the highest con-
trast estimate as an estimation of the TTP latency. (B) HRF extracted from the peak voxel in the bilateral auditory cortex of
patient 6 at day 1 (upper row) and day 9 (lower row). Plots represent mean contrast estimate across stimuli (x-axis) within
each time bin (y-axis). From day 1 to day 9, TTP latency increased in both hemispheres (from time bin 6 to time bin 7) and
amplitude decreased in the lesioned hemisphere.

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was demonstrated using Time-of-Flight MR angiography.
Vascular risk factors and carotid ultrasound findings were
assessed for each patient by reviewing their clinical charts.
Tables 1 and 3 detail the patients 'clinical data and the
examination times. Since leukoencephalopathy may
affect BOLD signals [32], we excluded patients whose MRI
rated >4 for the "Age Related White Matter Changes" score
[33]. Patients with a poor insonation of MCAs at the tem-
poral bone windows were excluded since TCD examina-
tions could not be performed.
Controls
The hemodynamic response function (HRF) was esti-
mated in 12 healthy, age-matched control subjects (8
men, mean age of 57 ± 9.4 years). Reference values for
hemodynamic parameters were derived from a previously
analyzed older adult control population (mean age 63 ± 9
years) [34].
The local ethics committee approved the study (267/05),
and informed consent was obtained from all subjects.
Experimental design
Experimental examinations were carried out at the acute
phase (Ex 1; i.e., within four days of stroke occurrence)
and the subacute phase (Ex 2; i.e., between five and twelve
days after stroke occurrence and at least two days after Ex
1). The examinations included:
1. Transcranial Doppler (TCD) to evaluate (i) patency and
blood flow velocity of middle cerebral arteries (MCAs)
and (ii) cerebral autoregulation.
2. fMRI study to assess BOLD signal HRF in bilateral audi-
tory cortices in response to two language paradigms.
The autoregulation and fMRI sessions were performed
within six hours of each other.
Neurological status was assessed with the NIH stroke scale
(NIHSS) at admission (Ex 0) and before each measure-
ment (Ex 1 and Ex 2).
Cerebral hemodynamics evaluation
Measurements were performed with subjects in a supine
position with slight to moderate elevation of the upper
body. CBFV in both MCAs was measured by TCD with 2
MHz transducers attached to a head frame (TC2-64, EME,
Germany). Continuous ABP recording was achieved via a
servocontrolled finger plethysmograph (Finapres, USA).
End-tidal CO2 partial pressure was measured in mm Hg
with an infrared capnometer (Normocap Datex, Finland)
during nasal expiration. After establishing stable values, a
data segment of ten minutes was recorded as patients
breathed spontaneously.
Cerebral autoregulation
In order to grade cerebral autoregulation, we used the pre-
viously described correlation coefficient method, which
makes use of spontaneously occurring fluctuations in ABP
and CBFV [20]. This approach is well established in neur-
ocritical care and has been validated against static autoreg-
ulation measurements [35]. It is based on the simple
assumption that decreasing cerebral autoregulation leads
to an increasing correlation between fluctuations in CBFV
and ABP (i.e., CBFV depends increasingly on fluctuations
in ABP). To quantify this correlation, mean values of ABP
and CBFV raw data were first averaged over three seconds.
For 20 of these three-second averages (i.e., for one-minute
periods), Pearson's correlation coefficients between the
mean ABP and CBFV were calculated. The resulting sets of
one-minute correlation coefficients gained from the entire
time series were then averaged, yielding the autoregula-
tory index Mx. Mx increases with decreasing dynamic
autoregulatory capacity. According to reference ranges
defined in an elder population [34], Mx ≥ 0.46 corre-
sponds to exhausted cerebral autoregulation.
fMRI paradigms
In both paradigms, stimuli were spoken by a female voice
and recorded by Cool Edit software. Stimuli were pre-
sented binaurally through MR compatible headphones.
Patients were asked to listen carefully and press a button
at the end of each stimulus to ensure alert listening. In the
present study, we were only interested in auditory cortex
activation in response to speech stimuli as compared with
background noise. Since our Department of Neurology
enrolled stroke patients in different fMRI studies, the six
patients included in this study underwent two different
fMRI language paradigms. However, both paradigms were
event-related experiments that differed only in the
number of stimuli and sessions.
Language paradigm 1
In an auditory comprehension task, we presented 30 nor-
mal speech stimuli (German sentences, e.g., "Der Pilot
fliegt das Flugzeug" [English translation: "The pilot flies
the plane"]), 30 stimuli of pseudo speech, which was
derived from normal speech stimuli by exchanging pho-
nemes (e.g., "Ren simot plieft mas kugireug", [English
translation is not possible]), and 30 stimuli of reversed
speech (e.g., "guezgulf sad tgeilf tolip red", [English trans-
lation is not possible]). The reversed speech stimuli were
using the Cool Edit software. Stimuli duration ranged
between 1730 and 2720 ms. Stimuli were presented bin-
aurally in a pseudo randomized order with an inter-stim-
ulus interval that varied between 3000 and 6000 ms.
Stimuli were assigned to a single nine minute long ses-
sion.

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Language paradigm 2
In a modified version of paradigm 1, we presented 92
stimuli of normal speech (German sentences, e.g., "Der
Pilot fliegt das Flugzeug" [English translation. "The pilot
flies the plane"]) and of reversed speech (e.g., "guezgulf
sad tgeilf tolip red", [English translation is not possible]).
Stimuli were presented binaurally in a pseudo rand-
omized order with an inter-stimulus interval that varied
between of 3000 and 6000 ms. Stimuli were assigned to
six sessions, resulting in a total scanning time of 21 min-
utes (for details see ref 7).
MRI data acquisition
Functional and structural MRI data from all subjects were
acquired on a 3 T Siemens TIM Trio scanner with a stand-
ard head coil.
Diffusion weighted imaging (DWI)
Scans were obtained using a standard in-house stroke
DWI sequence (23 slices, matrix 128 × 128 pixel2, voxel
size 1.8 × 1.8 × 6 mm3, TR = 3.1 s, TE = 79 ms, flip angle
= 90°).
Functional MRI
In cases where the sequence specifications differ between
paradigms, values for language task 1 and 2 are given in
parentheses. A total of 1 × 260 (6 × 115) scans per exami-
nation with 36 (32) axial slices covering the whole brain
was acquired in interleaved (descending) order using a
gradient echo echo-planar (EPI) T2*-sensitive sequence
[resolution = 3 × 3 × 3 mm3, TR = 2.19 (1.83) s, TE = 30
(25) ms, flip angle = 75° (70°), matrix = 64 × 64 pixel2].
During reconstruction, scans were corrected for motion
and distortion artifacts based on a reference measure-
ment.
MP-RAGE
A high-resolution T1 anatomical scan was obtained (160
slices, voxel size = 1 × 1 × 1 mm3, TR = 2.2 s, TE = 2.6 ms,
FOV = 160 × 240 × 240 mm3) for spatial processing of the
fMRI data.
fMRI Data analysis
fMRI data
www.fil.ion.ucl.ac.uk/spm).
were analyzed with SPM5 (http://
Preprocessing
Data were pre-processed using standard routines imple-
mented in SPM5. In both experiments, slices were first
corrected for different signals acquisition times by shifting
the signal measured in each slice relative to the acquisi-
tion of the middle slice. Volumes were then spatially nor-
malized to the Montreal Neurological Institute (MNI)
reference brain using non-linear normalization parame-
ters that were estimated during segmentation of the coreg-
istered T1 anatomical scan [36]. All normalized images
were then smoothed using an isotropic 9-mm Gaussian
kernel to account for inter-subject differences. Data were
motion corrected during acquisition using the method
introduced by Zaitsev et al. [37]
Finite impulse response (FIR) analysis
The time course of the hemodynamic BOLD response in
both hemispheres was estimated using FIR analyses as
implemented in SPM5. Onsets of auditory stimuli were
convolved with a set of ten successive basis functions,
which resulted in ten temporally aligned regressors for
each condition. Each single basis function estimated the
size of the BOLD signal for a specific time window of
length TR/2. Altogether, the condition-specific sets of the
ten basis functions covered a total post stimulus time of
10.95 s and 9.2 s for paradigms 1 and 2, respectively (see
Figure 2 and 3). F-contrasts were computed across all ten
basis functions. In the peak voxels within both hemi-
spheres, parameter estimates were extracted for each basis
function. In single subject analyses on study patients,
parameter estimates represent the averaged effect size
across stimuli, while in random effects group analyses on
controls, parameter estimates represent the averaged con-
trast estimate across subjects. Since parameter estimates
resembled normalized values, comparisons across sub-
jects were valid. For comparison across paradigms, con-
trast estimates were divided by the number of sessions
(i.e. in case of paradigm 2 by factor 6). The time bin with
the highest contrast estimate was used as an approxima-
tion of the TTP, and the contrast estimate itself reflects the
amplitude of the HRF.
Statistical analysis
Statistical analysis was carried out using SPSS 17.0 soft-
ware. Nonparametric tests (e.g., Wilcoxon signed-rank test
for paired data, Spearman test) were used to compare a
patient's data from the two hemispheres, to evaluate their
variations over time, and to assess possible correlations.
Since the sample size was small, we grouped data from
both hemispheres in order to assess the correlation
between TTP and Mx index. This was done using General-
ized Estimating Equations (GEE) models, which allowed
us to account for repeated measurements within subjects
(in this case, the measurements from two hemispheres).
We reported nominal p values and considered p values of
p < 0.05 to be statistically significant. We did not adjust p
values for multiple comparison adjustments since they
would have significantly reduced the ability to detect
interesting correlations within this small sample.
List of abbreviations
BOLD: blood oxygenated level dependent, fMRI: func-
tional magnetic resonance imaging, TCD: Transcranial
Doppler, TTP: time to peak, Ex 1: examination in the

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Page 11 of 12
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acute phase, Ex 2: examination at the subacute phase,
NIHSSri: National Institute of Health Stroke Scale recov-
ery index, AH: affected hemisphere, UH: unaffected hem-
isphere, HRF: hemodynamic response function, MCA:
middle cerebral artery, CBFV: Cerebral blood flow veloc-
ity, ABP: arterial blood pressure, FIR: finite impulse
response.
Authors' contributions
CA designed the research, carried out ultrasound exami-
nations, and wrote the manuscript. MR designed the
research, analyzed the data, and was involved with inter-
preting the data and revising the manuscript. MSV carried
out motor fMRI studies and analyzed fMRI data. CPK ana-
lyzed HRF fMRI data, FH designed the research, CW, AH,
FV and PMR interpreted the data and made critical revi-
sion of the manuscript, and finally, DS carried out lan-
guage fMRI, analyzed fMRI data, and wrote the
manuscript. All the authors erad and approved the final
manuscript.
Acknowledgements
The authors would like to thank Dr. Patrizio Pasqualetti and Dr. Gaetano
Gorgone for their statistical advice.
References
1. Johansen-Berg H: Functional imaging of stroke recovery: what
have we learnt and where do we go from here? Int J Stroke
2007, 2:7-16.
2.Rossini PM, Altamura C, Ferreri F, Melgari JM, Tecchio F, Tombini M,
Pasqualetti P, Vernieri F: Neuroimaging experimental studies
on brain plasticity in recovery from stroke. Eura Medicophys
2007, 43:241-54.
3. Ward NS: Future perspectives in functional neuroimaging in
stroke recovery. Eura Medicophys 2007, 43:285-94.
4.Feydy A, Carlier R, Roby-Brami A, Bussel B, Cazalis F, Pierot L,
Burnod Y, Maier MA: Longitudinal study of motor recovery
after stroke: recruitment and focusing of brain activation.
Stroke 2002, 33:1610-7.
5.Jaillard A, Martin CD, Garambois K, Lebas JF, Hommel M: Vicarious
function within the human primary motor cortex? A longitu-
dinal fMRI stroke study. Brain 2005, 128:1122-38.
6. Ward NS, Brown MM, Thompson AJ, Frackowiak RS: Longitudinal
changes in cerebral response to proprioceptive input in indi-
vidual patients after stroke: an fMRI study. Neurorehabil Neural
Repair 2006, 20:398-405.
7. Saur D, Lange R, Baumgaertner A, Schraknepper V, Willmes K,
Rijntjes M, Weiller C: Dynamics of language reorganization
after stroke. Brain 2006, 129:1371-84.
8. Pineiro R, Pendlebury S, Johansen-Berg H, Matthews PM: Altered
hemodynamic responses in patients after subcortical stroke
measured by functional MRI. Stroke 2002, 33:103-9.
9.Hamzei F, Knab R, Weiller C, Rother J: The influence of extra-
and intracranial artery disease on the BOLD signal in fMRI.
Neuroimage 2003, 20:1393-9.
10.Hund-Georgiadis M, Mildner T, Georgiadis D, Weih K, von Cramon
DY: Impaired hemodynamics and neural activation? A fMRI
study of major cerebral artery stenosis. Neurology 2003,
61:1276-9.
11.Krainik A, Hund-Georgiadis M, Zysset S, von Cramon DY: Regional
impairment of cerebrovascular reactivity and BOLD signal
in adults after stroke. Stroke 2005, 36:1146-52.
12.Fridriksson J, Rorden C, Morgan PS, Morrow KL, Baylis GC: Meas-
uring the hemodynamic response in chronic hypoperfusion.
Neurocase 2006, 12:146-50.
13.Prabhakaran V, Raman SP, Grunwald MR, Mahadevia A, Hussain N, Lu
H, Van Zijl PC, Hillis AE: Neural substrates of word generation
during stroke recovery: the influence of cortical hypoper-
fusion. Behav Neurol 2007, 18:45-52.
Rossini PM, Altamura C, Ferretti A, Vernieri F, Zappasodi F, Caulo M,
Pizzella V, Del Gratta C, Romani GL, Tecchio F: Does cerebrovas-
cular disease affect the coupling between neuronal activity
and local haemodynamics? Brain 2004, 127:99-110.
Binkofsk F, Seitz RJ: Modulation of the BOLD-response in early
recovery from sensorimotor stroke. Neurology 2004, 63:1223-9.
Röther J, Knab R, Hamzei F, Fiehler J, Reichenbach JR, Büchel C,
Weiller C: Negative dip in BOLD fMRI is caused by blood flow
oxygen consumption uncoupling in humans. Neuroimage 2002,
15:98-102.
Peck KK, Moore AB, Crosson BA, Gaiefsky M, Gopinath KS, White
K, Briggs RW: Functional magnetic resonance imaging before
and after aphasia therapy: shifts in hemodynamic time to
peak during an overt language task. Stroke 2004, 35:554-9.
Roc AC, Wang J, Ances BM, Liebeskind DS, Kasner SE, Detre JA:
Altered hemodynamics and regional cerebral blood flow in
patients with hemodynamically significant stenoses. Stroke
2006, 37:382-7.
Bonakdarpour B, Parrish TB, Thompson CK: Hemodynamic
response function in patients with stroke-induced aphasia:
implications for fMRI data analysis. Neuroimage 2007,
36:322-31.
Reinhard M, Roth M, Guschlbauer B, Harloff A, Timmer J, Czosnyka
M, Hetzel A: Dynamic cerebral autoregulation in acute
ischemic stroke assessed from spontaneous blood pressure
fluctuations. Stroke 2005, 36:1684-9.
Reinhard M, Wihler C, Roth M, Harloff A, Niesen WD, Timmer J,
Weiller C, Hetzel A: Cerebral Autoregulation Dynamics in
Acute Ischemic Stroke after rtPA Thrombolysis. Cerebrovasc
Dis 2008, 26:147-155.
Dohmen C, Bosche B, Graf R, Reithmeier T, Ernestus RI, Brinker G,
Sobesky J, Heiss WD: Identification and clinical impact of
impaired cerebrovascular autoregulation in patients with
malignant middle cerebral artery infarction. Stroke 2007,
38:56-61.
Faraci FM: Oxidative stress: the curse that underlies cerebral
vascular dysfunction? Stroke 2005, 36:186-188.
Korpelainen JT, Sotaniemi KA, Myllylä VV: Autonomic nervous
system disorders in stroke. Clin Auton Res 1999, 9:325-33.
Carusone LM, Srinivasan J, Gitelman DR, Mesulam MM, Parrish TB:
Hemodynamic response changes in cerebrovascular disease:
implications for functional MR imaging. Am J Neuroradiol 2002,
23:1222-8.
Iadecola C: Cerebral circulatory dysregulation in ischemia. In
Cerebrovascular Diseases Edited by: Ginsberg M, Bogousslavsky J. Cam-
bridge UK: Blackwell; 1998:319-332.
Murata Y, Sakatani K, Hoshino T, Fujiwara N, Kano T, Nakamura S,
Katayama Y: Effects of cerebral ischemia on evoked cerebral
blood oxygenation responses and BOLD contrast functional
MRI in stroke patients. Stroke 2006, 37:2514-20.
Alexandrov AV, Hall CE, Labiche LA, Wojner AW, Grotta JC:
Ischemic stunning of the brain: early recanalization without
immediate clinical improvement in acute ischemic stroke.
Stroke 2004, 35:449-52.
Weiller C, Willmes K, Reiche W, Thron A, Isensee C, Buell U, Rin-
gelstein EB: The case of aphasia or neglect after striatocapsu-
lar infarction. Brain 1993, 116:1509-25.
Saur D, Buchert R, Knab R, Weiller C, Rother J: Iomazenil-single-
photon emission tomography reveals selective neuronal loss
in magnetic resonance-defined mismtach areas. Stroke 2006,
37:2713-2719.
Feeney DM, Baron JC: Diaschisis. Stroke 1986, 17:817-30.
D'Esposito M, Deouell LY, Gazzaley A: Alterations in the BOLD
fMRI signal with ageing and disease: a challenge for neuroim-
aging. Nat Rev Neurosci 2003, 4:863-72.
Kapeller P, Barber R, Vermeulen RJ, Adèr H, Scheltens P, Freidl W,
Almkvist O, Moretti M, del Ser T, Vaghfeldt P, Enzinger C, Barkhof F,
Inzitari D, Erkinjunti T, Schmidt R, Fazekas F: European Task Force
of Age Related White Matter Changes. Stroke 2003, 34:441-5.
Reinhard M, Gerds TA, Grabiak D, Zimmermann PR, Roth M, Guschl-
bauer B, Timmer J, Czosnyka M, Weiller C, Hetzel A: Cerebral dys-
autoregulation and the risk of ischemic events in occlusive
carotid artery disease. J Neurol 2008, 255:1182-9.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.

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BMC Neuroscience 2009, 10:151http://www.biomedcentral.com/1471-2202/10/151
Page 12 of 12
(page number not for citation purposes)
35.Lang EW, Mehdorn HM, Dorsch NW, Czosnyka M: Continuous
monitoring of cerebrovascular autoregulation: a validation
study. J Neurol Neurosurg Psychiatry 2002, 72:583-6.
Ashburner J, Friston KJ: Unified segmentation. NeuroImage 2005,
26:839-851.
Zaitsev M, Hennig J, Speck O: Point spread function mapping
with parallel imaging techniques and high acceleration fac-
tors: fast, robust, and flexible method for echo-planar imag-
ing distortion correction. Magn Reson Med 2004, 52:1156-1166.
36.
37.