Regional homogeneity abnormalities in patients with transient ischaemic attack: A resting-state fMRI study

Clinical Neurophysiology 125 (2014) 520–525

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Regional homogeneity abnormalities in patients with transient ischaemic attack: A resting-state fMRI study Jian Guo a,1, Ning Chen a,1, Rong Li b, Qizhu Wu c, Huafu Chen b, Qiyong Gong c, Li He a,⇑ a

Department of Neurology, West China Hospital of Sichuan University, Chengdu 610041, PR China Key Laboratory for Neuroinformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610041, PR China c Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China b

a r t i c l e

i n f o

Article history: Accepted 21 August 2013 Available online 21 September 2013 Keywords: Functional MRI Regional homogeneity Resting state Transient ischaemic attack

h i g h l i g h t s  The regional homogeneity (ReHo) method was employed to investigate transient ischaemic attack

(TIA)-related modulations of neural activity in the resting state.  Altered regional spontaneous activities in dorsolateral prefrontal cortex (dlPFC) and inferior prefron-

tal cortex (iPFC) were found in TIAs, which were positively correlated with cognitive function in these patients.  ReHo could be regarded as a promising tool to better our understanding of the neurobiological consequences of TIA.

a b s t r a c t Objective: To investigate regional activity abnormalities in the resting state in patients with transient ischaemic attack (TIA) using a regional homogeneity (ReHo) method combined with functional magnetic resonance imaging (fMRI) and to examine the relationship between regional activity abnormalities and clinical variables. Methods: Resting-state fMRI was conducted in 21 patients with right-sided TIA and in 21 healthy volunteers. The ReHo was calculated to assess the strength of the local signal synchrony and was compared between the two groups. Results: Compared with the controls, the TIA patients exhibited a decreased ReHo in the right dorsolateral prefrontal cortex (dlPFC), the right inferior prefrontal cortex (iPFC), the right ventral anterior cingulate cortex (vACC) and the right dorsal posterior cingulate cortex (dPCC). In addition, the mean ReHo values in the right dlPFC and the right iPFC were significantly correlated with the Montreal Cognitive Assessment (MoCA) in TIA patients. Conclusions: Neural activities in the resting state are changed in TIA patients even without visible ischaemic lesions on conventional MRI. The positive correlation between the ReHo of resting-state fMRI and cognition suggests that ReHo could be a promising tool to observe the neurobiological consequences of TIA. Significance: The present study revealed abnormal local synchronisation of spontaneous neural activities in patients with TIA. Ó 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

1. Introduction Transient ischaemic attack (TIA) is defined as an episode of reversible neurological deficit caused by temporary focal cerebral

⇑ Corresponding author. Tel.: +86 13808185446; fax: +86 028 85423550. 1

E-mail address: [email protected] (L. He). Jian Guo and Ning Chen contributed equally to this work.

nervous system hypoperfusion, of which the clinical symptoms can be resolved within 24 h (Albers et al., 2002). Although the brain is traditionally regarded as healthy, various studies have provided supporting evidence that patients who have suffered from a TIA may exhibit different degrees of neuropsychological impairment. Many risk factors of TIA, such as hypertension, carotid stenosis and diabetes, are associated with cognitive impairment, especially difficulties with temporal orientation and verbal recall (Johnston

1388-2457/$36.00 Ó 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.clinph.2013.08.010

J. Guo et al. / Clinical Neurophysiology 125 (2014) 520–525

et al., 2004; Prencipe et al., 2003). In addition, TIA patients have been reported to have significant cognitive impairment compared with controls in recent studies (Guyomard et al., 2011). However, the mechanism of such neurocognitive dysfunction is unclear. As resting-state functional magnetic resonance imaging (fMRI) has improved, the investigation of baseline brain activity associated with neurological function has become increasingly more sensitive. It can be applied to detect low-frequency fluctuation (LFF) in various cerebral areas based on resting-state blood oxygen level dependence (BOLD) signals. Therefore, fMRI reflects the spontaneous neuronal activity of certain brain regions (Biswal et al., 1995). Resting-state fMRI signals have been suggested to be functionally meaningful and reflect the ‘intrinsic’ functional organisation of the human brain (Raichle, 2010). Unique changes in resting-state fMRI have been reported in patients with various pathological states, such as epilepsy and Alzheimer’s disease (Aghakhani et al., 2006; Liu et al., 2012). Recent studies have even demonstrated altered resting-state effective connectivity and corresponding neurological deficits in stroke patients (Park et al., 2011). However, though with similar pathophysiology, the baseline brain activity of patients with TIA has been rarely explored using resting-state fMRI. Regional homogeneity (ReHo) is a newly developed restingstate fMRI approach that analyses the similarities or coherence of intraregional spontaneous low-frequency (<0.08 Hz) BOLD signal fluctuations using voxel-wise analysis across the whole brain (Zang et al., 2004). It is assumed that the brain activity occurs more likely as clusters rather than as a single voxel, and such activity changes with different diseases (Zang et al., 2004). Since the BOLD signal of resting-state fMRI can reflect spontaneous neuronal activity, ReHo can be used to measure the regional synchrony of brain activity recorded by resting-state fMRI (Yuan et al., 2008). ReHo has been successfully used to detect local abnormalities in subjects with various neurological diseases such as neuromyelitis optica and Parkinson’s disease (Liang et al., 2011; Wu et al., 2009) and has been shown to be helpful in exploring the neurobiological consequences of these diseases. Therefore, we hypothesised that ReHo may also be a useful tool to reveal the neurobiological consequences of TIA. In this study, we employed ReHo to investigate whether the synchrony of regional spontaneous activity in resting-state fMRI is altered in TIA. Moreover, we examined whether ReHo is associated with clinical parameters in this disease.

2. Materials and methods 2.1. Subjects The study protocol was approved by the institutional ethics committee at Sichuan University. Written informed consent was obtained before each subject’s participation in the study. From June 2010 to September 2011, 21 TIA patients who had suffered from an ischaemic event in the right hemisphere were enroled in the study. According to the WHO recommendations, TIA was defined as any syndrome of focal neurological dysfunction ascribable to a vascular territory and lasting <24 h (Bejot et al., 2007). TIA was diagnosed by two senior stroke neurologists and confirmed by consensus at clinical team meetings. The study’s exclusion criteria were as follows: (1) patients younger than 40 years or older than 65 years of age; (2) posterior circulation or left-hemisphere localisation; (3) symptoms most likely related to a non-ischaemic diagnosis such as a psychiatric disorder, seizure or migraine; (4) patients with leukoaraiosis or brain lesions on fluid attenuated inversion recovery (FLAIR) images or T2-weighted images and (5) patients with pre-existing cognitive impairment or psychiatric

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diseases before TIA. The controls were healthy volunteers matched for age, sex and years of education with no history of stroke/TIA or other neurological disorders. All subjects underwent complete blood count and metabolic profile testing, and a carotid duplex ultrasound examination. The degree of carotid stenosis was calculated according to Grant’s method (Grant et al., 2003) by a consensus of two readers blinded to the clinical data using carotid duplex ultrasound or magnetic resonance angiography (MRA). To detect potential cardiac sources of emboli (including atrial fibrillation and valve diseases), 12-lead electrocardiogram, Holter monitor and transthoracic echocardiography or trans-oesophageal echocardiography were used. 2.2. Cognitive assessment Cognitive assessments of these subjects were made by two independent neuropsychologists. The Montreal Cognitive Assessment (MoCA), which assesses the general condition of cognitive function; the Auditory Verbal Memory Test (AVMT, Chinese version based on the California Verbal Learning Test), which analyses verbal memory; and the backward Digital Span Test (DST-backward), which evaluates working memory, were conducted in all subjects. 2.3. Data acquisition Imaging was performed on a 3-tesla Trio scanner (Siemens AG, Erlangen, Germany) by using an eight-channel birdcage head coil. Each subject lay supine with the head snugly fixed by a belt and foam pads. The resting-state fMRIs were obtained by using an echo-planar imaging sequence with the following protocols: TR/ TE, 2000/30; field of view, 240  240 mm2; acquisition matrix, 64  64; and slice thickness, 5 mm with no gap. This acquisition sequence generated 190 volumes in 6 min and 20 s. During the resting-state fMRI scanning, all subjects were informed to keep still with their eyes closed, think of nothing in particular and remain awake. A 3D time-of-flight MRA was performed to visualise the cerebral vasculature of the subjects, and 3D high-resolution T1and T2-weighted and FLAIR images were also acquired to detect clinically silent lesions. 2.4. Data analysis Demographic data as well as cognitive characteristics were analysed using SPSS (version 15.0). The differences in these variables between the TIA patients and the controls were calculated by the two-sample t-test and Pearson’s v2-test. Pre-processing of the resting-state fMRI data was conducted using data processing assistant for resting-state fMRI (DPARSF, http://www.restfmri.net/forum/DPARSF) v2.1 software as previously described (Chao-Gan and Yu-Feng, 2010). In brief, the first 10 volumes of each functional time series were discarded for participant adaptation to the scanning. The remaining 180 images were slice-time-corrected, realigned, normalised to the East Asian brain template provided by statistical parametric mapping (SPM8, http://www.fil.ion.ucl.ac.uk/spm/software/spm8/) and resampled to 3  3  3 mm3. Several sources of spurious variance, including estimated motion parameters, linear drift and average BOLD signals in ventricular and white matter regions, were removed from the data through linear regression. Then a temporal filter (0.01–0.08 Hz) was used to reduce the low-frequency drift and physiological high-frequency noise. Anatomical data were processed to separate the grey matter (GM) from the 3D T1-weighted structural images using voxel-based morphometry toolbox (VBM8, http://dbm.neuro. uni-jena.de/vbm.html). Briefly, images were bias corrected, tissue

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classified and registered using linear (12-parameter affine) and non-linear transformations, within a unified model (Ashburner and Friston, 2005). Subsequently, the GM partitions were modulated to preserve actual GM values locally. The segmented GM volume was then treated as an external regressor in the subsequent multiple regression analysis. Next, ReHo analysis was performed on a voxel-by-voxel basis by calculating Kendall’s coefficient of concordance (KCC) of the time series of a given voxel with its 26 neighbouring voxels using resting-state fMRI data analysis toolkit (REST, v1.7, http://restfmri.net/forum/index.php), according to the following formula:

P W¼

2

ðRi Þ2  nðRÞ

1 K 12

2

ðn3  nÞ

where W is the KCC among given voxels, ranging from 0 to 1; Ri is the rank sum of the ith time point; R ¼ ðnþ1ÞK is the mean of the Ri’s; 2 K is the number of time series within a measured cluster (here, K = 27, one given voxel plus the number of its neighbours) and n is the number of ranks (here, n = 180 time points). By calculating the KCC value of every voxel in the whole brain, individual ReHo maps were generated for each subject (Zang et al., 2004). Regions outside the brain, contributing nothing to the discrimination, were masked and removed from the ReHo maps in order to reduce feature dimensionality. The resulting data were spatially smoothed with a Gaussian kernel of 4-mm full-width at half-maximum. A second-level, random-effect, one-sample t-test was performed to show the ReHo patterns for the controls and the TIA patients, respectively. The threshold was set at P < 0.01 and corrected with the false discovery rate (FDR) criterion. To reveal if there was any change in the synchrony of regional spontaneous activity in TIA patients, a two-sample t-test was conducted to compare the ReHo values of the controls and the TIA patients. The threshold was set at P < 0.05 and corrected using a threshold cluster of 25 contiguous voxels. The threshold cluster was determined using AlphaSim and 1000 Monte Carlo simulations. Moreover, to explore whether or not ReHo correlated with neuropsychological function in TIA patients, the correlation analysis of ReHo vs. MoCA, AVMT and DST-backward adjusted for sex, age and GM volume Table 1 Baseline characteristics of the participants. Characteristics

TIA patients (n = 21)

Controls (n = 21)

Age (y), mean (SD) Sex, males (%) Education (y), mean (SD)

50.1 (6.5) 15 (71) 10.4 (2.1)

48.2 (7.9) 13 (62) 10.5 (2.8)

0.39 0.51 0.95

Risk factors (%) Hypertension Diabetes Hyperlipidemia Atrial Fibrillation Previous stroke Smoking Carotid stenosis 1–49% 50–69% >70% Intracranial arteries stenosis

8 (38) 3 (14) 7 (33) 0 0 5 (24) 16 (76) 7 (33) 6 (29) 3 (14) 3 (14)

5 1 6 0 0 2 3 3 0 0 0

(24) (5) (28)

0.32 0.27 0.74

(9) (14) (14)

0.18 <0.001

Clinical features (%) Motor symptoms Sensory symptoms

19 (90) 12 (57)

Time since latest event <7 days 7–14 days 15–30 days

3 (14) 14 (67) 4 (19)

TIA, Transient ischaemic attack; SD, standard deviation.

(0)

P-value

0.06

was performed at each voxel of the whole brain. P < 0.05 was used to determine a significant correlation. 3. Results The study population consisted of 42 subjects with a mean age of 49.2 years (standard deviation, 7.20), of whom 66.7% were male. They were all right handed and received 10.5 years of education, on average. The demographic profiles, risk factors and clinical features of all subjects are listed in Table 1. There were no significant differences in age, gender and education between the TIA group and the control group. Significantly more TIA patients had suffered from carotid artery stenosis than the subjects from the control group (16/21 TIA patients vs. 3/21 control patients, P < 0.001). None of the patients in our sample presented atrial fibrillation or other heart diseases, and no significant differences were found for the other vascular risk factors. All TIA patients experienced symptoms with acute onset of paralysis or numbness on the left side of the body, which occurred <1 month before the MRI examination. The median duration of symptoms in TIA patients was 48 min (ranging from 15 min to 1.5 h). The results of the cognitive tests are summarised in Table 2. The TIA patients tended to have poorer MoCA (24.5 ± 3.5 vs. 26.2 ± 1.6, P = 0.053), AVMT (47.9 ± 15.8 vs. 55.7 ± 19.8, P = 0.065) and DST-backward (5.1 ± 1.9 vs. 5.7 ± 3.4, P = 0.060) scores compared with the controls. 3.1. Within-group and between-group ReHo analyses The mean ReHo maps within each group are shown in Fig. 1 (one-sample t-test; P < 0.01, FDR corrected). The voxels with greater ReHo values than the global mean ReHo value were bilaterally distributed within a few of the medial and lateral brain structures, including the medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), posterior cingulate cortex (PCC)/precuneus and inferior prefrontal cortex (iPFC) in both controls (Fig. 1A) and TIA patients (Fig. 1B), whose patterns were consistent with those in previous studies (Liang et al., 2011; Wu et al., 2009; Yu et al., 2012). The differences in the ReHo values between the TIA patients and the controls are shown in Table 3. Compared with the controls, the TIA patients showed a significant ReHo decrease in the right dorsolateral prefrontal cortex (dlPFC), right iPFC, right ventral ACC (vACC) and right dorsal PCC (dPCC; P < 0.05, AlphaSim corrected; Fig. 2). No areas of significantly increased ReHo were detected in patients compared with the controls. 3.2. Correlations between ReHo values and clinical parameters Next, we examined if ReHo values in these brain areas correlated with clinical parameters. The results showed that the MoCA scores positively correlated (r = 0.5102; P = 0.0215) with the ReHo values of the right dlPFC and right iPFC in the TIA patients (Fig. 3). However, the ReHo values of other brain regions did not correlate with the tested clinical parameters.

Table 2 Cognitive test scores of participants.

MoCA, mean (SD) AVMT, mean (SD) DST-backward, mean (SD)

TIA patients (n = 21)

Controls (n = 21)

Pvalue

24.5 (3.5) 47.9 (15.8) 5.1 (1.9)

26.2 (1.6) 55.7 (19.8) 5.7 (3.4)

0.053 0.065 0.060

MoCA, Montreal Cognitive Assessment; AVMT, Auditory Verbal Memory Test; DSTbackward, Backward Digital Span Test; SD, standard deviation.

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Fig. 1. Results of regional homogeneity (ReHo) shown as the Kendall’s coefficient from the concordance map across control subjects (A) and TIA patients (B) in the resting state (one-sample t-test; P < 0.01, false discovery rate corrected). mPFC, medial prefrontal cortex; iPFC, inferior prefrontal cortex; ACC, anterior cingulate cortex; PCC, posterior cingulate gyrus.

Table 3 Brain areas with ReHo differences between the TIA and control groups. Brain area

BA

Peak correlation MNI coordinates X

R dorsolateral prefrontal cortex R inferior prefrontal gyrus R ventral anterior cingulate cortex R dorsal posterior cingulate cortex

Y

Tvalue

Voxel size

Z

46/ 9 47 24

42

36

14

4.32

68

36 6

30 6

9 36

4.20 4.40

42 30

31

3

16

48

4.07

28

Alphasim corrected; BA, Brodmann’s area; R, right.

4. Discussion The present study used ReHo to investigate the synchrony of regional spontaneous activity in resting-state fMRI among TIA patients. The results showed that compared with the controls, the TIA patients exhibited significantly reduced ReHo in dlPFC, iPFC, vACC and dPCC on the ipsilateral side of the TIA. In addition, the ReHo values in the dlPFC and iPFC significantly correlated with the global cognitive status (MoCA score) in patients with TIA. The most interesting finding of our study was that the ReHo values in the patients with TIA decreased in the dlPFC and the iPFC, compared to those of controls, which significantly correlated with cognitive performance. Altered prefrontal activity following acute and chronic ischaemic stroke – which shares a similar pathophysiology with TIA – has been suggested by fMRI in two previous studies (Puh et al., 2007; Meehan et al., 2011). Puh et al. have reported a task-related fMRI study indicating that bilateral activation of the prefrontal cortex (PFC) may participate in the recovery process after stroke (Puh et al., 2007). Meehan et al. observed an abnormal BOLD response in the dlPFC in individuals who had suffered from a stroke by using an implicit sequence-specific motor-learning fMRI task, which implicated a potential alteration in the prefrontalbased attentional network in stroke patients (Meehan et al., 2011). The present study extends these findings by demonstrating that, even without permanent cerebral infarction, TIA could also induce disrupted synchronisation of spontaneous neural activity in the PFC. Moreover, it is known that TIA patients can suffer from

executive dysfunction (Sachdev et al., 2004) and that the PFCs are critical neural substrates for execution control (Alvarez and Emory, 2006). Thus, our results of reduced ReHo in the dlPFC and the iPFC in patients are indirectly supported by the executive deficits in TIA. The significant ReHo/cognition correlation in the PFC further reinforces the significance of the role of this brain region in TIA patients’ executive performance. We also found reduced ReHo values in the right vACC and dPCC in TIA patients compared to controls. ACC and PCC are the cerebral regions with greater metabolism relative to the whole brain activity. They have been identified as being a part of the default mode network (DMN) that is highly active in the resting state (Raichle et al., 2001). These brain areas play an important role in emotion processing (Szily and Keri, 2008), executive function (Ito et al., 2003) and self-control (Allman et al., 2001). Some previous studies have shown cingulate cortex dysfunction in stroke patients, which may be a key reason of post-stroke depression and working memory damage in these patients (Terroni et al., 2011; Ziemus et al., 2007). Our results also exhibited decreased regional coherence in the cingulate cortex in TIA patients but did not reveal significant associations with the clinical scales. The possible reason might be that even the regulation of executive and cognitive functions of this brain region is emotion related (Peoples, 2002). However, psychiatric tests were not performed in this study, which prevents us from conducting a correlation analysis of psychiatric test scores with our fMRI results. Further work should be carried out to clarify the relationship between them. As far as we know, this is the first study to demonstrate that TIA can lead to abnormal coherence of spontaneous neural activity in the regional brain. One factor that must be considered is that TIA is a heterogeneous clinical entity. Therefore, in the current study, we selectively enroled the patients who suffered TIA in the same hemisphere and without visible lesions in conventional brain MRI, to minimise the heterogeneity among patient groups. In addition, we only examined patients with right-sided TIA, for the reason that all the patients included in the study were right handed; the diagnosis of left-sided TIA may be interfered with if they only had the clinical symptoms of speech disorder. In this study, we adopted ReHo to evaluate the neurological deficiency of TIA patients by observing the regional synchrony of the spontaneous neuronal activity. We found that TIA patients exhibited altered ReHo in several brain regions, and the ReHo values significantly correlated with cognitive performance in these

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Fig. 2. Brain regions with abnormal ReHo in TIA patients compared with the controls (P < 0.05, AlphaSim corrected). (A) The results of between-group ReHo analyses are shown on the projection map. The brain regions with a decreased ReHo value in TIA patients included the following: (B) the right dorsolateral prefrontal cortex and right inferior prefrontal cortex; (C) the right ventral anterior cingulate cortex and right dorsal posterior cingulate cortex.

Fig. 3. Correlation analysis between the MoCA scores (x-axis) and ReHo (y-axis) in the right dorsolateral prefrontal cortex and inferior prefrontal cortex.

patients. The neural mechanism underlying such a phenomenon is still unclear, but previous studies may provide us with some clues. The synchronous oscillation activity of the cortex has been shown to be vital to temporal and spatial coordination, which is performed as the integration of neural elements with separated anatomic properties and consistent functions (Wang et al., 2011). Previous studies also have demonstrated that the synchronous activity of neurons is conducive to the integration and coordination of information processing in the brain (Buzsaki and Draguhn, 2004). Recently, Zhang et al. further revealed that altering neuronal

synchrony may lead to the deterioration of information processing speed and efficiency, resulting in cognitive dysfunction (Zhang et al., 2012). Thus, we presume that the effects of TIA, even in the absence of overt structural damage, result in abnormally synchronised neural activities. This abnormal activity causes abnormal ReHo values and, consequently, results in cognitive dysfunction. Therefore, ReHo is possibly an early biomarker of brain injury in TIA. There were some limitations to the current study. Although it is generally accepted that cardiogenic factors can be a crucial risk for

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TIA (Rojas et al., 2007), none of the patients selected in the study had atrial fibrillation, and cardiac examinations did not reveal positive findings. There might be several reasons for that: First, the sample size is small and there might be a selection bias as only 21 patients were enroled in our study. Second, to reduce the impact of age on brain structure and function, we limited the age range of the subjects to 40–65 years. Nevertheless, some previous studies have shown that for stroke patients, the incidence of atrial fibrillation increases with ageing (Wang et al., 2011). Thus, the risk of atrial fibrillation for our TIA group was possibly less than that for real populations. Third, there is a relatively low detectable rate of atrial fibrillation among all stroke patients in our country (Lin et al., 2011). In China, the detectable rate of cardioembolism is between 5% and 13.6%, which is much less than about 20% reported from some Western countries (Lamassa et al., 2001). Therefore, our findings may mainly represent the alteration of neuronal synchrony of TIA patients with haemodynamic dysfunction caused by artery stenosis. Another limitation is that to ensure the homogeneity of the sample, we only included patients with right-sided TIA in our study. Whether or not TIA with posterior circulation or lefthemisphere involvement also displays ReHo abnormalities should be studied further. In conclusion, the presence of an abnormality in the ReHo of resting-state fMRI is a sensitive early indicator of altered brain function in TIA. The simplicity and non-invasiveness of this method make it a promising tool to better our understanding of the neurobiological consequences of TIA. However, larger sample sizes and a longer follow-up period are warranted in future studies to determine the potential of altered regional synchrony in TIA patients. Acknowledgements This work was supported by the National Natural Science Foundation (Grants Nos. 81071140 and 81300943) and China Postdoctoral Science Foundation funded project (No. 2012M521699). The authors acknowledge all participants in the study. References Aghakhani Y, Kobayashi E, Bagshaw AP, Hawco C, Benar CG, Dubeau F, et al. Cortical and thalamic fMRI responses in partial epilepsy with focal and bilateral synchronous spikes. Clin Neurophysiol 2006;117:177–91. Albers GW, Caplan LR, Easton JD, Fayad PB, Mohr JP, Saver JL, et al. Transient ischemic attack–proposal for a new definition. N Engl J Med 2002;347:1713–6. Allman JM, Hakeem A, Erwin JM, Nimchinsky E, Hof P. The anterior cingulate cortex. The evolution of an interface between emotion and cognition. Ann N Y Acad Sci 2001;935:107–17. Alvarez JA, Emory E. Executive function and the frontal lobes: a meta-analytic review. Neuropsychol Rev 2006;16:17–42. Ashburner J, Friston KJ. Unified segmentation. Neuroimage 2005;26:839–51. Bejot Y, Rouaud O, Benatru I, Durier J, Caillier M, Couvreur G, et al. Trends in the incidence of transient ischemic attacks, premorbid risk factors and the use of preventive treatments in the population of Dijon, France from 1985 to 2004. Cerebrovasc Dis 2007;23:126–31. Biswal B, Yetkin FZ, Haughton VM, Hyde JS. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 1995;34:537–41. Buzsaki G, Draguhn A. Neuronal oscillations in cortical networks. Science 2004;304:1926–9. Chao-Gan Y, Yu-Feng Z. DPARSF: a matlab toolbox for ‘‘pipeline’’ data analysis of resting-state fMRI. Front Syst Neurosci 2010;4:13.

525

Grant EG, Benson CB, Moneta GL, Alexandrov AV, Baker JD, Bluth EI, et al. Carotid artery stenosis: gray-scale and Doppler US diagnosis–society of radiologists in ultrasound consensus conference. Radiology 2003;229:340–6. Guyomard V, Metcalf AK, Naguib MF, Fulcher RA, Potter JF, Myint PK. Transient ischaemic attack, vascular risk factors and cognitive impairment: a casecontrolled study. Age Ageing 2011;40:641–4. Ito S, Stuphorn V, Brown JW, Schall JD. Performance monitoring by the anterior cingulate cortex during saccade countermanding. Science 2003;302:120–2. Johnston SC, O’Meara ES, Manolio TA, Lefkowitz D, O’Leary DH, Goldstein S, et al. Cognitive impairment and decline are associated with carotid artery disease in patients without clinically evident cerebrovascular disease. Ann Intern Med 2004;140:237–47. Lamassa M, Di Carlo A, Pracucci G, Basile AM, Trefoloni G, Vanni P, et al. Characteristics, outcome, and care of stroke associated with atrial fibrillation in Europe: data from a multicenter multinational hospital-based registry (The European Community Stroke Project). Stroke 2001;32:392–8. Liang P, Liu Y, Jia X, Duan Y, Yu C, Qin W, et al. Regional homogeneity changes in patients with neuromyelitis optica revealed by resting-state functional MRI. Clin Neurophysiol 2011;122:121–7. Lin S, Wu B, Hao ZL, Kong FY, Tao WD, Wang DR, et al. Characteristics, treatment and outcome of ischemic stroke with atrial fibrillation in a Chinese hospital-based stroke study. Cerebrovasc Dis 2011;31:419–26. Liu Z, Zhang Y, Bai L, Yan H, Dai R, Zhong C, et al. Investigation of the effective connectivity of resting state networks in Alzheimer’s disease: a functional MRI study combining independent components analysis and multivariate Granger causality analysis. NMR Biomed 2012;25:1311–20. Meehan SK, Randhawa B, Wessel B, Boyd LA. Implicit sequence-specific motor learning after subcortical stroke is associated with increased prefrontal brain activations: an fMRI study. Hum Brain Mapp 2011;32:290–303. Park CH, Chang WH, Ohn SH, Kim ST, Bang OY, Pascual-Leone A, et al. Longitudinal changes of resting-state functional connectivity during motor recovery after stroke. Stroke 2011;42:1357–62. Peoples LL. Neuroscience. Will, anterior cingulate cortex, and addiction. Science 2002;296:1623–4. Prencipe M, Santini M, Casini AR, Pezzella FR, Scaldaferri N, Culasso F. Prevalence of non-dementing cognitive disturbances and their association with vascular risk factors in an elderly population. J Neurol 2003;250:907–12. Puh U, Vovk A, Sevsek F, Suput D. Increased cognitive load during simple and complex motor tasks in acute stage after stroke. Int J Psychophysiol 2007;63:173–80. Raichle ME. Two views of brain function. Trends Cogn Sci 2010;14:180–90. Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL. A default mode of brain function. Proc Natl Acad Sci U S A 2001;98:676–82. Rojas JI, Zurru MC, Romano M, Patrucco L, Cristiano E. Acute ischemic stroke and transient ischemic attack in the very old–risk factor profile and stroke subtype between patients older than 80 years and patients aged less than 80 years. Eur J Neurol 2007;14:895–9. Sachdev PS, Brodaty H, Valenzuela MJ, Lorentz L, Looi JC, Wen W, et al. The neuropsychological profile of vascular cognitive impairment in stroke and TIA patients. Neurology 2004;62:912–9. Szily E, Keri S. Emotion-related brain regions. Ideggyogy Sz 2008;61:77–86. Terroni L, Amaro E, Iosifescu DV, Tinone G, Sato JR, Leite CC, et al. Stroke lesion in cortical neural circuits and post-stroke incidence of major depressive episode: a 4-month prospective study. World J Biol Psychiatry 2011;12:539–48. Wang L, Song M, Jiang T, Zhang Y, Yu C. Regional homogeneity of the resting-state brain activity correlates with individual intelligence. Neurosci Lett 2011;488:275–8. Wu T, Long X, Zang Y, Wang L, Hallett M, Li K, et al. Regional homogeneity changes in patients with Parkinson’s disease. Hum Brain Mapp 2009;30:1502–10. Yu D, Yuan K, Zhao L, Zhao L, Dong M, Liu P, et al. Regional homogeneity abnormalities in patients with interictal migraine without aura: a resting-state study. NMR Biomed 2012;25:806–12. Yuan Y, Zhang Z, Bai F, Yu H, Shi Y, Qian Y, et al. Abnormal neural activity in the patients with remitted geriatric depression: a resting-state functional magnetic resonance imaging study. J Affect Disord 2008;111:145–52. Zang Y, Jiang T, Lu Y, He Y, Tian L. Regional homogeneity approach to fMRI data analysis. Neuroimage 2004;22:394–400. Zhang Z, Liu Y, Jiang T, Zhou B, An N, Dai H, et al. Altered spontaneous activity in Alzheimer’s disease and mild cognitive impairment revealed by Regional Homogeneity. Neuroimage 2012;59:1429–40. Ziemus B, Baumann O, Luerding R, Schlosser R, Schuierer G, Bogdahn U, et al. Impaired working-memory after cerebellar infarcts paralleled by changes in BOLD signal of a cortico-cerebellar circuit. Neuropsychologia 2007;45:2016–24.