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In this study, we applied coherence to voxel-wise measurement of regional homogeneity of resting-state functional magnetic resonance imaging (RS-fMRI) signal. We compared the current method, regional homogeneity based on coherence (Cohe-ReHo), with previously proposed method, ReHo based on Kendall’s coefficient of concordance (KCC-ReHo), in terms of correlation and paired t-test in a large sample of healthy participants. We found the two measurements differed mainly in some brain regions where physiological noise is dominant. We also compared the sensitivity of these methods in detecting difference between resting-state conditions (eyes open (EO) vs. eyes closed (EC)) and in detecting abnormal local synchronization between two groups (attention deficit hyperactivity disorder (ADHD) patients vs. normal controls). Our results indicated that Cohe-ReHo is more sensitive than KCC-ReHo to the difference between two conditions (EO vs. EC) as well as that between ADHD and normal controls. These preliminary results suggest that Cohe-ReHo is superior to KCC-ReHo. A possible reason is that coherence is not susceptible to random noise induced by phase delay among the timecourses to be measured. However, further investigation is still needed to elucidate the sensitivity and specificity of these methods.

As a promising non-invasive imaging technique, functional near infrared spectroscopy (fNIRS) has recently earned increasing attention in resting-state functional connectivity (RSFC) studies. Preliminary fNIRS-based RSFC studies adopted a seed correlation approach and yielded interesting results. However, the seed correlation approach has several inherent problems, such as neglecting of interactions among multiple regions and a dependence on seed region selection. Moreover, ineffectively reduced noise and artifacts in fNIRS measurements also negatively affect RSFC results. In this study, independent component analysis (ICA) was introduced to meet these challenges in RSFC detection based on resting-state fNIRS measurements. The results of ICA on data from the sensorimotor and the visual systems both showed functional system-specific RSFC maps. Results from comparison between ICA and the conventional seed correlation approach demonstrated, both qualitatively and quantitatively, the superior performance of ICA with higher sensitivity and specificity, especially in the case of higher noise level. The capability of ICA to separate noise and artifacts from resting-state fNIRS data was also demonstrated, and the extracted noise and artifacts were illustrated. Finally, some practical issues on performing ICA on resting-state fNIRS data were discussed.

Recently, resting state functional connectivity (RSFC) studies based on fMRI and EEG/MEG have provided valuable insight into the intrinsic functional architecture of the human brain. However, whether functional near infrared spectroscopy (fNIRS), a suitable imaging method for infant and patient populations, can be used to examine RSFC remains elusive. Using an ETG-4000 Optical Topography System, the present study measured 29 adult subjects (14 females) over the sensorimotor and auditory cortexes during a resting session and a motor-localizer task session. The RSFC maps were computed by seed-based correlation analysis and data-driven cluster analysis. The results from both analyses showed robust RSFC maps, which were not only consistent with the localizer task-related activation results, but also those of previous fMRI findings. Moreover, the strong consistency between the seed-based correlation analysis and the data-driven cluster analysis further validated the use of fNIRS to assess RSFC. The potential influence of a specific low-frequency filtering range (0.04–0.15 Hz and 0.01–0.08 Hz) and three fNIRS parameters (oxy-Hb, deoxy-Hb, and total-Hb) on RSFC results were also examined.

International audience; Baseline activity of resting state brain networks (RSN) in a resting subject has become one of the fastest growing research topics in neuroimaging. It has been shown that up to 12 RSNs can be differentiated using an independent component analysis (ICA) of blood oxygen level dependent (BOLD) resting state data. In this work we investigate how many RSN signal sources can be separated from the entire brain cortex using high dimension ICA analysis from a group dataset. Group data from 55 subjects were analysed using temporal concatenation and a probabilistic ICA (PICA) algorithm. PICA estimation suggested 73 components to be calculated. ICA repeatability testing (ICASSO) verified that 60 of the 70 computed components were robustly detectable. Forty-two independent signal sources were identifiable as RSN, and 28 were related to artifacts or other non-interest sources (non-RSN). The depicted RSNs bore a closer match to functional neuroanatomy than the previously reported RSN components. The non-RSN sources have significantly lower temporal inter-source connectivity than the RSN (p< 0.0003). We conclude that the high model order ICA of group BOLD data enables functional segmentation of the brain cortex. The method enables new analysis approaches to causality and connectivity with more specific anatomical details.

We employed a sulcal geometry-based approach to investigate the morphology of the central sulcus (CS) in musicians (pianists). The anterior and posterior walls of the CS were first manually outlined from high-resolution magnetic resonance (MR) images of 41 right-handed subjects (20 musicians and 21 controls), followed by a surface reconstruction and parameterization procedure to ensure the anatomical correspondence of surface locations across subjects. The intrasulcal length, surface area, and local variability of the CS were measured. There were no significant differences in either the intrasulcal length or surface area of the anterior or posterior walls between the 2 groups. However, we observed that the controls had a pronounced left-larger-than-right asymmetry that was reduced in the musicians. Importantly, we found that the musicians showed greater local variability in the middle section (i.e., somatotopic hand area) of the right CS and the lower section of the left CS as compared with the controls. Further analysis revealed significantly negative correlations between the variability of the middle section of the right CS and the age of commencement of musical training. Our findings suggest that the musicians might be associated with plastic changes in the 3D morphology of the CS in response to long-term motor skill training.

The characterization of topological architecture of complex brain networks is one of the most challenging issues in neuroscience. Slow (

In this study, the static and dynamic characteristics of cerebral blood flow (CBF) in the resting state were investigated using an arterial spin labeling (ASL) perfusion imaging technique. Consistent with previous PET results, static CBF measured by ASL was significantly higher in the posterior cingulate cortex (PCC), thalamus, insula/superior temporal gyrus (STG) and medial prefrontal cortex (MPFC) than the average CBF of the brain. The dynamic measurement of CBF fluctuations showed high correlation (functional connectivity) between components in the default mode network. These brain regions also had high local temporal synchrony and high fluctuation amplitude, as measured by regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF) analyses. The spatial pattern of the static CBF correlated well with that of the dynamic indices. The high static and dynamic activities in the PCC, MPFC, insula/STG and thalamus suggest that these regions play a vital role in maintaining and facilitating fundamental brain functions.

The cognitive division of anterior cingulate cortex (ACC-cd) plays an important role in cognitive control via a distributed attention network. The structural hemispheric asymmetries of ACC have been revealed by several neuroimaging studies. However potential functional hemispheric asymmetries of ACC remain less clear. Investigating the functional hemispheric asymmetries of ACC helps for a better understanding of ACC function. The aim of this study was to use resting-state functional magnetic resonance imaging (fMRI) to examine hemispheric differences in the functional networks associated with ACC-cd in the two hemispheres. ROI-based functional connectivity analysis was performed on a group of 49 right-handed healthy volunteers. The left and right ACC-cd showed significant differences in their patterns of connectivity with a variety of brain regions, including the dorsolateral prefrontal cortex, inferior parietal lobule, superior parietal lobule and dorsal posterior cingulate cortex in their ipsilateral cerebral cortex, as well as cerebellar tonsil and inferior semilunar lobule in their contralateral cerebellar hemisphere. Specifically, for these areas, we found significantly greater connectivity strength with ACC-cd in the right hemisphere than the left, regardless of whether the connection was positive or negative. The current results highlight the presence of clear asymmetries in functional networks associated with ACC-cd. Future functional imaging studies are needed to give greater attention to the lateralized ACC functional networks which are observed.

Background Recent functional MRI (fMRI) studies have demonstrated that there is an intrinsically organized default mode network (DMN) in the resting brain, primarily made up of the posterior cingulate cortex (PCC) and the medial prefrontal cortex (MPFC). Several previous studies have found that the DMN is minimally disturbed during different resting-state conditions with limited cognitive demand. However, this conclusion was drawn from the visual inspection of the functional connectivity patterns within the DMN and no statistical comparison was performed. Methodology/Principal Findings Four resting-state fMRI sessions were acquired: 1) eyes-closed (EC) (used to generate the DMN mask); 2) EC; 3) eyes-open with no fixation (EO); and 4) eyes-open with a fixation (EO-F). The 2–4 sessions were counterbalanced across participants (n = 20, 10 males). We examined the statistical differences in both functional connectivity and regional amplitude of low frequency fluctuation (ALFF) within the DMN among the 2–4 resting-state conditions (i.e., EC, EO, and EO-F). Although the connectivity patterns of the DMN were visually similar across these three different conditions, we observed significantly higher functional connectivity and ALFF in both the EO and the EO-F conditions as compared to the EC condition. In addition, the first and second resting EC conditions showed significant differences within the DMN, suggesting an order effect on the DMN activity. Conclusions/Significance Our findings of the higher DMN connectivity and regional spontaneous activities in the resting state with the eyes open suggest that the participants might have more non-specific or non-goal-directed visual information gathering and evaluation, and mind wandering or daydreaming during the resting state with the eyes open as compared to that with the eyes closed, thus providing insights into the understanding of unconstrained mental activity within the DMN. Our results also suggest that it should be cautious when choosing the type of a resting condition and designating the order of the resting condition in multiple scanning sessions in experimental design.

The thalamus and visual cortex are two key components associated with the alpha power of electroencephalography. However, their functional relationship remains to be elucidated. Here, we employ resting-state functional MRI to investigate the temporal correlations of spontaneous fluctuations between the thalamus [the whole thalamus and its three largest nuclei (bilateral mediodorsal, ventrolateral and pulvinar nuclei)] and visual cortex under both eyes open and eyes closed conditions. The whole thalamus show negative correlations with the visual cortex and positive correlations with its contralateral counterpart in eyes closed condition, but which are significantly decreased in eyes open condition, consistent with previous findings of electroencephalography desynchronization during eyes open resting state. Furthermore, we find that bilateral thalamic mediodorsal nuclei and bilateral ventrolateral nuclei have remarkably similar connectivity maps, and resemble to those of the whole thalamus, suggesting their crucial contributions to the thalamus-visual correlations. The bilateral pulvinar nuclei are found to show distinct functional connectivity patterns, compatible with previous findings of the asymmetry of anatomical and functional organization in the nuclei. Our data provides evidence for the associations of intrinsic spontaneous neuronal activity between the thalamus and visual cortex under different resting conditions, which might have implications on the understanding of the generation and modulation of the alpha rhythm.

To study the changes of amplitude of low-frequency fluctuation (ALFF) of the resting-fMRI in the mesial temporal lobe epilepsy (mTLE) with bilateral hippocampal sclerosis (HS), and discussed its underlying neuro-pathophysiological mechanism.The resting-fMRI data of 20 TLE patients with HS and 20 normal volunteers were performed ALFF analysis. The amplitude of the blood oxygenation level-dependent activation of the resting-state brain was investigated. The brain structures showing increased and decreased ALFF in TLE patients were demonstrated by comparing to normal subjects with 2-sample t-test with threshold of P0.01.By comparison with that of normal subjects, the regions showing increased and decreased ALFF in TLE patients were distributed in the brain symmetrically and bilaterally. The regions showing increased ALFF were distributed with center of limbic system, such as parahippocampal gyri, amygdala, hypothalamus, dorsal anterior cingulate gyrus and part of posterior insular lobe, as well as the neocortices such as primary sensorimotor cortices, occipital cortices, inferior temporal gyri, orbital gyri, and the subcortical structures of verbal brainstem and mesial cerebellum. The point with maximal increased ALFF (T = 6.02) located in the right precentral gyru (15, - 12.51). While the regions showing decreased ALFF covered the areas of default mode, such as posterior cingulate cortex/ precuneus and medial prefrontal cortex /ventral anterior cingulate cortex, as well as other structures such as dorsal lateral prefrontal cortices, superior temporal gyri, caudate heads, dorsal brain stem and the posterior cerebellum (3, -78, -21) with the maximal decreased ALFF (T = -4.42).The method of ALFF allows the direct observation to the epileptic activation in TLE. The increased ALFF is considered the facilitation such as the epileptic activity generation and propagation; while the ALFF decrease is considered the function inhibition in these regions, especially implies the suspension in the default mode activity.

Previous studies have witnessed that complex brain networks have the properties of high global and local efficiency. In this study, we investigated the gender effect on brain functional networks measured using functional magnetic resonance imaging (fMRI). Our experimental results showed that there were no significant difference in global and local efficiency between male and female. However, the gender-related effects on nodal efficiency were found at several brain regions, including the left middle frontal gyrus, right superior temporal gyrus, left middle cingulum gyrus, left hippocampus, right hippocampus, right parahippocampal and left amygdala. These results were compatible with previous findings. To our knowledge, this study provided the first evidence of gender effect on the efficiency of brain functional networks using resting-state fMRI.

BACKGROUND: Functional connectivity magnetic resonance imaging technique has revealed the importance of distributed network structures in higher cognitive processes in the human brain. The hippocampus has a key role in a distributed network supporting memory encoding and retrieval. Hippocampal dysfunction is a recurrent finding in memory disorders of aging such as amnestic mild cognitive impairment (aMCI) in which learning- and memory-related cognitive abilities are the predominant impairment. The functional connectivity method provides a novel approach in our attempts to better understand the changes occurring in this structure in aMCI patients. METHODS: Functional connectivity analysis was used to examine episodic memory retrieval networks in vivo in twenty 28 aMCI patients and 23 well-matched control subjects, specifically between the hippocampal structures and other brain regions. RESULTS: Compared with control subjects, aMCI patients showed significantly lower hippocampus functional connectivity in a network involving prefrontal lobe, temporal lobe, parietal lobe, and cerebellum, and higher functional connectivity to more diffuse areas of the brain than normal aging control subjects. In addition, those regions associated with increased functional connectivity with the hippocampus demonstrated a significantly negative correlation to episodic memory performance. CONCLUSIONS: aMCI patients displayed altered patterns of functional connectivity during memory retrieval. The degree of this disturbance appears to be related to level of impairment of processes involved in memory function. Because aMCI is a putative prodromal syndrome to Alzheimer's disease (AD), these early changes in functional connectivity involving the hippocampus may yield important new data to predict whether a patient will eventually develop AD.

Recent neuroimaging studies have shown that several brain regions--namely, the posterior cingulate cortex (PCC), ventral medial prefrontal cortex (vmPFC), and the bilateral angular gyrus--are more active during resting states than during cognitive tasks (i.e., default mode network). Although there is evidence showing that the default mode network is associated with unconscious state, it is unclear whether this network is associated with unconscious processing when normal human subjects perform tasks without awareness. We manipulated the level of conscious processing in normal subjects by asking them to perform an implicit and an explicit memory task, and analyzed signal changes in the default mode network for the stimuli versus baseline in both tasks. The functional magnetic resonance imaging (fMRI) analysis showed that the level of activation in regions within this network during the implicit task was not significantly different from that during the baseline, except in the left angular gyrus and the insula. There was strong deactivation for the explicit task when compared with the implicit task in the default mode regions, except in the left angular gyrus and the left middle temporal gyrus. These data suggest that the activity in the default network is sustained and less disrupted when an implicit memory task is performed, but is suspended when explicit retrieval is required. These results provide evidence that the default mode network is associated with unconscious processing when human subjects perform an implicit memory task.

The current study combined structural magnetic resonance imaging (sMRI) and diffusion tensor MRI (DT-MRI) to investigate both gray matter density (GMD) and white matter integrity (WMI) in 18 pianists and 21 age-matched non-musicians. The pianists began their piano training at a mean age of 12. Voxel-based morphometry of the sMRI data showed that the pianists had higher GMD in the left primary sensorimotor cortex and right cerebellum. Voxel-based analysis of the DT-MRI data showed that pianists had higher fractional anisotropy (FA) (indicating higher WMI) in the right posterior limb of the internal capsule. The sMRI and DT-MRI results indicate that both the GMD and WMI of pianists may exhibit movement-related increases during adolescence or even early adulthood compared with non-musicians.

Attention deficit/hyperactivity disorder (ADHD) is one of the most common but poorly understood developmental disorders in childhood. Although neuropsychological studies demonstrate that children with ADHD have attentional alerting deficits, the neurobiological bases of such deficits have not been examined extensively. In this study, by using functional magnetic resonance imaging (fMRI), we explored the neural correlates of intrinsic alertness and phasic alertness deficits in ADHD by comparing twelve boys with ADHD (13.4+/-1.7 years) with 13 age-matched normal controls (13.2+/-1.2 years) in a cued target detection task. Behaviorally, compared with the controls, the ADHD group showed a higher overall error rate and a larger reaction time variability in performing the task. At the neural level, children with ADHD showed less activation than the controls in frontal (middle and superior frontal gyrus), parietal (inferior parietal lobe, precuneus) and putamen regions. These results demonstrate that children with ADHD have deficits in alerting functions and these deficits are related to the abnormal activities in frontal and parietal regions subserving top-down attention control processes.

To study the differences of brain functions between children with attention deficit hyperactivity disorder (ADHD) predominantly inattentive (ADHD-I) and combined (ADHD-C) subtypes in resting state using functional magnetic resonance imaging (fMRI).A newly reported regional homogeneity (ReHo) approach was used to analyze blood oxygen level-dependent fMRI (BOLD-fMRI) data in resting state among 6 ADHDj C, 9 ADHD-I and 15 normal control boys.The brain regions showing differences among the three groups included bilateral frontal lobe, right cuneus and right inferior temporal gyrus. Compared with the normal controls, ADHD-C showed decreased ReHo in left frontal lobe and right inferior temporal gyrus, ADHD-I showed decreased ReHo in bilateral frontal and temporal lobe and right cerebellum and increased ReHo in bilateral occipital lobe and right inferior parietal gyrus. There were no brain regions showing different ReHo between ADHD-C and ADHD-I.Although both ADHD-C and ADHD-I showed abnormal neural activity in resting state compared with the normal controls, there were no differences for brain functions in resting state between ADHD-C and ADHD-I.

Our knowledge about aging modulation of the central motor system remains sparse and contradictory. In the current study, we used functional MRI (fMRI) to study the aging influence on regional homogeneity of the motor-related brain areas in the resting state. We found that regional homogeneity in extensive motor regions, like the cingulate motor area, cerebellum, primary motor cortex, premotor area, supplementary motor area, thalamus, globus pallidus and putamen was significantly decreased in aged subjects. Our study indicates that normal aging process may disrupt the function of motor areas in the resting state, which may contribute to the declined motor ability in aged population.

In this study, a resting-state fMRI based classifier, for the first time, was proposed and applied to discriminate children with attention-deficit/hyperactivity disorder (ADHD) from normal controls. On the basis of regional homogeneity (ReHo), a mapping of brain function at resting state, PCA-based Fisher discriminative analysis (PC-FDA) was trained to build a linear classifier. Permutation test was then conducted to identify the brain areas with the most significant contribution to the final discrimination. Experimental results showed a correct classification rate of 85% using a leave-one-out cross-validation. Moreover, some highly discriminative brain regions, like the prefrontal cortex and anterior cingulate cortex, well confirmed the previous findings on ADHD. Interestingly, some important but less reported regions such as the thalamus were also identified. We conclude that the classifier, using resting-state brain function as classification feature, has potential ability to improve current diagnosis and treatment evaluation of ADHD.

We used functional MRI (fMRI) to study the aging influence on functional connectivity of the motor network in the resting state. A network model based on graph theory was used to measure functional connectivity. The total connectivity degree of each region within the motor network was calculated and compared between aged and young groups. We found that the pattern of functional connectivity was changed in aged subjects, including a significant decrease in the functional connectivity degree of the right cingulate motor area and left premotor area compared to young subjects. Our study demonstrates that normal aging modulates the functional connectivity of motor network in the resting state. We postulate that this abnormal functional connectivity of motor network in the baseline state is an important reason contributing to the deteriorated motor ability in aged subjects.

The aim of the current study was to localize the epileptic focus and characterize its causal relation with other brain regions, to understand the cognitive deficits in children with benign childhood epilepsy with centrotemporal spikes (BECTS). Resting-state functional magnetic resonance imaging (fMRI) was performed in 37 children with BECTS and 25 children matched for age, sex and educational achievement. We identified the potential epileptogenic zone (EZ) by comparing the amplitude of low frequency fluctuation (ALFF) of spontaneous blood oxygenation level dependent fMRI signals between the groups. Granger causality analysis was applied to explore the causal effect between EZ and the whole brain. Compared with controls, children with BECTS had significantly increased ALFF in the right postcentral gyrus and bilateral calcarine, and decreased ALFF in the left anterior cingulate cortex, bilateral putaman/caudate, and left cerebellum. ALFF values in the putaman/caudate were positively correlated with verbal IQ scores in patients. The ALFF values in cerebellum and performance IQ scores were negatively correlated in patients. These results suggest that ALFF disturbances in the putaman/caudate and cerebellum play an important role in BECTS cognitive dysfunction. Compared with controls, the patients showed increased driving effect from the EZ to the right medial frontal cortex and posterior cingulate cortex and decreased causal effects from the EZ to left inferior frontal gyrus. The causal effect of the left inferior frontal gyrus negatively correlated with disease duration, which suggests a relation between the epileptiform activity and language impairment. All together, these findings provide additional insight into the neurophysiological mechanisms of epilepitogenisis and cognitive dysfunction associated with BECTS.

Delusions of schizophrenia have been found to be associated with alterations of some brain regions in structure and task-induced activation. However, the relationship between spontaneously occurring symptoms and spontaneous brain activity remains unclear. In the current study, 14 schizophrenic patients with delusions and 14 healthy controls underwent a resting-state functional magnetic resonance imaging (RS-fMRI) scan. Patients with delusions of schizophrenia patients were rated with Positive and Negative Syndrome Scale (PANSS) and Characteristics of Delusional Rating Scale (CDRS). Regional homogeneity (ReHo) was calculated to measure the local synchronization of the spontaneous activity in a voxel-wise way. A two-sample t-test showed that ReHo of the right anterior cingulate gyrus and left medial superior frontal gyrus were higher in patients, and ReHo of the left superior occipital gyrus was lower, compared to healthy controls. Further, among patients, correlation analysis showed a significant difference between delusion scores of CRDS and ReHo of brain regions. ReHo of the left medial superior frontal gyrus was negatively correlated with patients' CDRS scores but not with delusional PANSS scores. These results suggested that altered local synchronization of spontaneous brain activity may be related to the pathophysiology of delusion in schizophrenia.

Most studies of resting-state functional magnetic resonance imaging (fMRI) have applied the temporal correlation in the time courses to investigate the functional connectivity between brain regions. Alternatively, the power of low frequency fluctuation (LFF) may also be used as a biomarker to assess spontaneous activity. The purpose of the current study is to evaluate whether the amplitude of the LFF (ALFF) relates to cerebral physiological states. Ten healthy subjects underwent four resting-state fMRI scanning sessions, two for eyes-open (EO) and two for eyes-closed (EC) conditions, with two sets of parameters (TR=400 ms and 2 s, respectively). After data preprocessing, ALFF was obtained by calculating the square root of the power spectrum in the frequency range of 0.01-0.08 Hz. Our results showed that the ALFF in EO was significantly higher than that in EC (P

Recent functional imaging studies have indicated that the pathophysiology of Alzheimer's disease (AD) can be associated with the changes in spontaneous low-frequency (< 0.08 Hz) blood oxygenation level-dependent fluctuations (LFBF) measured during a resting state. The purpose of this study was to examine regional LFBF coherence patterns in early AD and the impact of regional brain atrophy on the functional results. Both structural MRI and resting-state functional MRI scans were collected from 14 AD subjects and 14 age-matched normal controls. We found significant regional coherence decreases in the posterior cingulate cortex/precuneus (PCC/PCu) in the AD patients when compared with the normal controls. Moreover, the decrease in the PCC/PCu coherence was correlated with the disease progression measured by the Mini-Mental State Exam scores. The changes in LFBF in the PCC/PCu may be related to the resting hypometabolism in this region commonly detected in previous positron emission tomography studies of early AD. When the regional PCC/ PCu atrophy was controlled, these results still remained significant but with a decrease in the statistical power, suggesting that the LFBF results are at least partly explained by the regional atrophy. In addition, we also found increased LFBF coherence in the bilateral cuneus, right lingual gyrus and left fusiform gyrus in the AD patients. These regions are consistent with previous findings of AD-related increased activation during cognitive tasks explained in terms of a compensatory- recruitment hypothesis. Finally, our study indicated that regional brain atrophy could be an important consideration in functional imaging studies of neurodegenerative diseases. (c) 2006 Elsevier Inc. All rights reserved.

Dorsal anterior cingulate cortex (dACC) has been found to function abnormally in attention deficit hyperactivity disorder (ADHD) patients in several former functional MRI (fMRI) studies. Resting-state low-frequency fluctuations (LFFs) of blood oxygen level-dependent (BOLD) fMRI signals have been proved to be quite informative. This study used resting-state LFFs to investigate the resting-state functional connectivity pattern differences of dACC in adolescents with and without ADHD. As compared to the controls, the ADHD patients exhibited more significant resting-state functional connectivities with the dACC in bilateral dACC, bilateral thalamus, bilateral cerebellum, bilateral insula and bilateral brainstem (pons). No brain region in the controls was found to exhibit more significant resting-state functional connectivity with the dACC. We suggest these abnormally more significant functional connectivities in the ADHD patients may indicate the abnormality of autonomic control functions in them.

Article in Press, Corrected Proof; previous termIn childrennext term with attention deficit hyperactivity disorder (ADHD), functional neuroimaging studies have revealed abnormalities previous terminnext term various previous termbrainnext term regions, including prefrontal-striatal circuit, cerebellum, and brainstem. previous termInnext term the current study, we used a new marker of functional magnetic resonance imaging (fMRI), amplitude of low-frequency (0.01–0.08 Hz) fluctuation (ALFF) to investigate the previous termbaseline brainnext term function of this disorder. Thirteen boys with ADHD (13.0 ± 1.4 years) were examined by resting-state fMRI and compared with age-matched controls. As a result, we found that patients with ADHD had decreased ALFF previous terminnext term the right inferior frontal cortex, left sensorimotor cortex, and bilateral cerebellum and the vermis as well as increased ALFF previous terminnext term the right anterior cingulated cortex, left sensorimotor cortex, and bilateral brainstem. This resting-state fMRI study suggests that the changed spontaneous neuronal previous termactivitynext term of these regions may be implicated previous terminnext term the underlying pathophysiology previous termin childrennext term with ADHD.

Functional neuroimaging studies of handedness have traditionally focused on exploring regionally activated discrepancies, yet little is known regarding the effect of handedness on functional connections of brain regions. Here, we reported the relationship between cerebellar functional connectivity patterns and handedness by low-frequency blood oxygenation level-dependent fluctuations. Compared with the right-handers, the left-handers show higher cerebellar-prefrontal, cerebellar-parietal, and cerebellar-temporal functional connectivity, and lower cerebellar-limbic connectivity. Previous non-human primate studies have shown that these regions with known contributions to higher cognitive functions have afferent or efferent connections with the cerebellum. Our findings suggest that these observed low-frequency fluctuation correlations may reflect actually anatomic connections between the cerebellum and cerebral cortex, and the cerebellar involvement in higher function may be associated with handedness.

Recently, increasing attention has focused on exploring brain activity during rest. A current challenge is to ascertain activity patterns without using an external reference. In this paper, we propose a model-free approach based on regional homogeneity (ReHo) to identify specific network of brain regions during rest. In the context of the ReHo, it seems to be reasonable to assume that the voxels within a functional cluster have higher temporal coherence than that within a general cluster. Using this technique, a large distributed network during rest was identified and compared with previous meta-analysis studies. The proposed method shows an extensive ability in analyzing resting state data.

In this work, a discriminative model of attention deficit hyperactivity disorder (ADHD) is presented on the basis of multivariate pattern classification and functional magnetic resonance imaging (fMRI). This model consists of two parts, a classifier and an intuitive representation of discriminative pattern of brain function between patients and normal controls. Regional homogeneity (ReHo), a measure of brain function at resting-state, is used here as a feature of classification. Fisher discriminative analysis (FDA) is performed on the features of training samples and a linear classifier is generated. Our initial experimental results show a successful classification rate of 85%, using leave-one-out cross validation. The classifier is also compared with linear support vector machine (SVM) and Batch Perceptron. Our classifier outperforms the alternatives significantly. Fisher brain, the optimal projective-direction vector in FDA, is used to represent the discriminative pattern. Some abnormal brain regions identified by Fisher brain, like prefrontal cortex and anterior cingulate cortex, are well consistent with that reported in neuroimaging studies on ADHD. Moreover, some less reported but highly discriminative regions are also identified. We conclude that the discriminative model has potential ability to improve current diagnosis and treatment evaluation of ADHD.

In this article, we present some advances on medical imaging and computing at the National Laboratory of Pattern Recognition (NLPR) in the Chinese Academy of Sciences. The first part is computational neuroanatomy. Several novel methods on segmentations of brain tissue and anatomical substructures, brain image registration, and shape analysis are presented. The second part consists of brain connectivity, which includes anatomical connectivity based on diffusion tensor imaging (DTI), functional and effective connectivity with functional magnetic resonance imaging (fMRI). It focuses on abnormal patterns of brain connectivity of patients with various brain disorders compared with matched normal controls. Finally, some prospects and future research directions in this field are also given.

Current analysis of diffusion tensor imaging (DTI) is based mostly on a region of interest (ROI) in an image dataset, which is specified by users. This method is not always reliable, however, because of the uncertainty of manual specification. We introduce an improved fiber‐based scheme rather than an ROI‐based analysis to study in DTI datasets of 31 normal subjects the asymmetry of the cingulum, which is one of the most prominent white matter fiber tracts of the limbic system. The present method can automatically extract the quantitative anisotropy properties along the cingulum bundles from tractography. Moreover, statistical analysis was carried out after anatomic correspondence specific to the cingulum across subjects was established, rather than the traditional whole‐brain registration. The main merit of our method compared to existing counterparts is that to find such anatomic correspondence in cingulum, a scale‐invariant parameterization method by arc‐angle was proposed. It can give a continuous and exact description on any segment of cingulum. More interestingly, a significant left‐greater‐than‐right asymmetry pattern was obtained in most segments of cingulum bundle (−50–25 degrees), except in the most posterior portion of cingulum (25–50 degrees). Hum Brain Mapp 24:92–98, 2005. © 2004 Wiley‐Liss, Inc.

Using event-related functional magnetic resonance imaging to study the Stroop, effect on both behavioral and brain activation of ADHD children off or on methylphenidate (MPH). Nine ADHD boys (aged 9.8-14.5 years) and 9 age-matched normal controls were included. A Stroop-like paradigm was used. AFNI (Analysis of Functional Neurolmaging) and its Deconvolution Analysis were used in a descriptive comparison between ADHD and control groups. (1) Both behavioral reaction time and brain activation showed Stroop effect in controls but neither was found in ADHD children off MPH. When MPH was administered, the Stroop effect tended to appear. (2) The activation volume (AV) of prefrontal cortex (PFC) in both the neutral (NC) and interference conditions (IQ in ADHD children off MPH was smaller than in controls. AV of anterior cingulate cortex in the IC in ADHD children off MPH was smaller than that in controls, but was similar in the NC to that in controls. AV of the basal ganglia, insula and cerebellum was also smaller in the IC, but was larger in the NC for ADHD children off MPH compared with controls. These findings are consistent with prior findings of hypofrontality in ADHD children and implicate a compensatory network including basal ganglia, insula and cerebellum for relative lower cognitive load tasks. (c) 2005 Elsevier B.V. All rights reserved.

We introduce a hybrid method for functional magnetic resonance imaging (fMRI) activation detection based on the well‐developed split–merge and region‐growing techniques. The proposed method includes conjoining both of the spatio‐temporal priors inherent in split–merge and the prior information afforded by the hypothesis‐led component of region selection. Compared to the fuzzy c‐means clustering analysis, this method avoids making assumptions about the number of clusters and the computation complexity is reduced markedly. We evaluated the effectiveness of the proposed method in comparison with the general linear model and the fuzzy c‐means clustering method conducted on simulated and in vivo datasets. Experimental results show that our method successfully detected expected activated regions and has advantages over the other two methods. Hum. Brain Mapping 22:271–279, 2004. © 2004 Wiley‐Liss, Inc.

Temporal self-correlation has recently been proposed as a measure for fMRI-activation detection. In this paper, a modified temporal self-correlation method is introduced. The modified temporal self-correlation is based on the expectation value and standard deviation of the correlation coefficients between all pairs of epochs, while the original temporal self-correlation method is only based on the expectation value. Performance of the proposed method is evaluated on both simulated and in vivo fMRI data. Compared with the original temporal self-correlation method, the proposed method shows a significant improvement. In addition, a technique for quantitative comparison of different fMRI data analysis methods is proposed.

Quite a few studies in functional magnetic resonance imaging (fMRI) have tested that, even in a resting state, motor cortices constitute a network. It has never been investigated how the network modulates from the resting state to the motor task state. In this report, by a newly developed approach taking into account n‐to‐1 connectivity using 1‐to‐1 connectivity measures instead of conventional pairwise connectivity, we show the existence of a large organized functional connectivity network related to motor function in the resting brain with fMRI. More importantly, we found that such a network can be modulated from a conscious resting state to planning, initiation, coordination, guidance, and termination of voluntary movement state, exhibited by significant changes of functional connectivity of some brain regions in different brain activity. Moreover, a quantitative description of such a functional modulation has also been presented. Hum. Brain Mapp. 22:65–73, 2004. © 2004 Wiley‐Liss, Inc.

So far, resting state functional connectivity (RSFC) has been performed mainly by seed correlation analysis (SCA) on functional MRI (fMRI) studies. In previous studies, the seeds are usually selected on the basis of prior anatomical information or previously performed activation maps. In this paper, we proposed a novel way to select the desired seeds by taking the natures of resting state data into account. The proposed approach is based on the measurement of regional homogeneity (ReHo) of brain regions. Using this technique, 2 locations showing higher ReHo in the cerebellum (i.e. the bilateral anterior inferior cerebellum, AICb) were identified and used as the seeds for RSFC patterns studies. We found that the bilateral AICb show significant functional connectivity with the bilateral thalamus, the bilateral hippocampus, the precuneus, the temporal lobe and the prefrontal lobe. Further, the differences of RSFC patterns between the bilateral AICb were ascertained by a random effect paired t-test. These findings may improve our understanding of cerebellar involvement in motor and a variety of non-motor functions.

Kendall's coefficient concordance (KCC) can measure the similarity of a number of time series. It has been used for purifying a given cluster in functional MRI (fMRI). In the present study, a new method was developed based on the regional homogeneity (ReHo), in which KCC was used to measure the similarity of the time series of a given voxel to those of its nearest neighbors in a voxel-wise way. Six healthy subjects performed left and right finger movement tasks in event-related design five of them were additionally scanned in a rest condition. KCC was compared among the three conditions (left finger movement, right finger movement, and the rest). Results show that bilateral primary motor cortex (M1) had higher KCC in either left or right finger movement condition than in rest condition. Contrary to prediction and to activation pattern, KCC of ipsilateral M1 is significantly higher than contralateral M1 in unilateral finger movement conditions. These results support the previous electrophysiologic findings of increasing ipsilateral M1 excitation during unilateral movement. ReHo can consider as a complementary method to model-driven method, and it could help reveal the complexity of the human brain function. More work is needed to understand the neural mechanism underlying ReHo. (C) 2004 Elsevier Inc. All rights reserved.

Existing analytical techniques for functional magnetic resonance imaging (fMRI) data always need some specific assumptions on the time series. In this article, we present a new approach for fMRI activation detection, which can be implemented without any assumptions on the time series. Our method is based on a region growing method, which is very popular for image segmentation. A comparison of performance on fMRI activation detection is made between the proposed method and the deconvolution method and the fuzzy clustering method with receiver operating characteristic (ROC) methodology. In addition, we examine the effectiveness and usefulness of our method on real experimental data. Experimental results show that our method outperforms over the deconvolution method and the fuzzy clustering method on a number of aspects. These results suggest that our region growing method can serve as a reliable analysis of fMRI data.

Twelve previously untreated boys suffering from attention-deficit hyperactivity disorder (ADHD) were investigated by using proton magnetic resonance spectroscopy (1H MRS) before and after one dose (10 mg) of methylphenidate. Pre- and post-methylphenidate spectra were acquired bilaterally in the globus pallidus. Peaks of N-acetylaspartate (NAA), choline (Cho), myo-inositol, glutamate and creatine (Cr) were measured and the ratios of the peaks were calculated and compared with data from ten matched controls. In children having ADHD, NAA/Cr ratio decreased significantly in the bilateral striatum while Cho/Cr ratio showed a mild unilateral increase. One oral dose of methylphenidate did not affect the ratios significantly. These findings suggest that the striatum was bilaterally involved in pediatric ADHD patients. Approximately 20-25% of neurons may have died or may be severely dysfunctional. There seems to be a mild hyperactivity of the cholinergic system.

INTRODUCTION: Current pathophysiological theories of schizophrenia highlight the role of altered brain functional and anatomical connectivity. The cognitive division of anterior cingulate cortex (ACC-cd) is a commonly reported abnormal brain region in schizophrenia for its importance in cognitive control process. The aim of this study was to investigate the functional and anatomical connectivity of ACC-cd and its cognitive and clinical manifestation significance in schizophrenia by using the resting-state functional magnetic resonance imaging (fMRI) and the diffusion tensor imaging (DTI). METHODS: Thirty-three medicated schizophrenics and 30 well-matched health controls were recruited. Region-of-interest (ROI)-based resting-state functional connectivity analysis and Tract-Based Spatial Statistics (TBSS) were performed on 30 patients and 30 controls, and 24 patients and 29 controls, respectively. The Pearson correlation was performed between the imaging measures and the Stroop performance and scores of the Positive and Negative Syndrome Scale (PANSS), respectively. RESULTS: Patients with schizophrenia showed significantly abnormal in the functional connectivity and its hemispheric asymmetry of the ACC-cd with multiple brain areas, e.g., decreased positive connectivity with the bilateral putamen and caudate, increased negative connectivity with the left posterior cingulated cortex (PCC), increased asymmetry of connectivity strength with the contralateral inferior frontal gyrus (IFG). The FA of the right anterior cingulum was significantly decreased in patients group (p=0.014). The abnormal functional and structural connectivity of ACC-cd were correlated with Stroop performance and the severity of the symptoms in patients. CONCLUSIONS: Our results suggested that the abnormal connectivity of the ACC-cd might play a role in the cognitive impairment and clinical symptoms in schizophrenia.

BACKGROUND: Prior research has shown that the amygdala of carriers of the short allele (s) of the serotonin transporter (5-HTT) gene (5-HTTLPR) have a larger response to negative emotional stimuli and higher spontaneous activity during the resting state than non-carriers. However, recent studies have suggested that the effects of 5-HTTLPR may be specific to different ethnic groups. Few studies have been conducted to address this issue. METHODOLOGY/PRINCIPAL FINDINGS: Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) was conducted on thirty-eight healthy Han Chinese subjects (l/l group, n = 19; s/s group, n = 19) during the resting state and during an emotional processing task. Compared with the s/s group, the l/l group showed significantly increased regional homogeneity or local synchronization in the right amygdala during the resting state (|t|>2.028, p

0387-7604/$ see front matter 2012 The Japanese Society of Child Neuro doi:10.1016/j.braindev.2012.01.002 DOI of original article: 10.1016/j.braindev.2006.07.002. ⇑ Corresponding author. Present address: Center for Cognition and Brain Disorders, Affiliated Hospital, Hangzhou Normal University, Zhangzhou 310015, Zhejiang, China. E-mail addresses: zangyf@gmail.com, zangyf@hznu.edu.cn (Y-F. Zang). bilateral cerebellum and the vermis as well as increased ALFF in the right anterior cingulated cortex, left sensorimotor cortex, and bilateral brainstem.’ In Fig. 3, the numbers beside the blue bar (upper) should be 3.828 and 2.796, respectively. And the numbers besides the red and yellow bar (lower) should be +2.796 and +4.604, respectively.

Functional connectivity has become one of the important approaches to understanding the functional organization of the hu- man brain. Recently, functional near-infrared spectroscopy fNIRS was demonstrated as a feasible method to study resting-state func- tional connectivity RSFC in the sensory and motor systems. How- ever, whether such fNIRS-based RSFC can be revealed in high-level and complex functional systems remains unknown. In the present study, the feasibility of such an approach is tested on the language system, of which the neural substrates have been well documented in the literature. After determination of a seed channel by a language localizer task, the correlation strength between the low frequency fluctuations of the fNIRS signal at the seed channel and those at all other channels is used to evaluate the language system RSFC. Our results show a significant RSFC between the left inferior frontal cortex and superior temporal cortex, components both associated with domi- nant language regions. Moreover, the RSFC map demonstrates left lateralization of the language system. In conclusion, the present study successfully utilized fNIRS-based RSFC to study a complex and high- level neural system, and provides further evidence for the validity of the fNIRS-based RSFC approach. © 2010 Society of Photo-Optical Instrumentation