[show abstract][hide abstract] ABSTRACT: Abnormal connectivity of the anticorrelated intrinsic networks, the task-negative network (TNN), and the task-positive network (TPN) is implicated in schizophrenia. Comparisons between schizophrenic patients and their unaffected siblings enable further understanding of illness susceptibility and pathophysiology. We examined the resting-state connectivity differences in the intrinsic networks between schizophrenic patients, their unaffected siblings, and healthy controls.
Resting-state functional magnetic resonance images were obtained from 25 individuals in each subject group. The posterior cingulate cortex/precuneus and right dorsolateral prefrontal cortex were used as seed regions to identify the TNN and TPN through functional connectivity analysis. Interregional connectivity strengths were analyzed using overlapped intrinsic networks composed of regions common to all subject groups.
Schizophrenic patients and their unaffected siblings showed increased connectivity in the TNN between the bilateral inferior temporal gyri. By contrast, schizophrenic patients alone demonstrated increased connectivity between the posterior cingulate cortex/precuneus and left inferior temporal gyrus and between the ventral medial prefrontal cortex and right lateral parietal cortex in the TNN. Schizophrenic patients exhibited increased connectivity between the left dorsolateral prefrontal cortex and right inferior frontal gyrus in the TPN relative to their unaffected siblings, though this trend only approached statistical significance in comparison to healthy controls.
Resting-state hyperconnectivity of the intrinsic networks may disrupt network coordination and thereby contribute to the pathophysiology of schizophrenia. Similar, though milder, hyperconnectivity of the TNN in unaffected siblings of schizophrenic patients may contribute to the identification of schizophrenia endophenotypes and ultimately to the determination of schizophrenia risk genes.
[show abstract][hide abstract] ABSTRACT: The functional brain networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive function and brain disorders. Rather than analyzing each network encoded by a spatial independent component separately, we propose a novel algorithm for discriminant analysis of functional brain networks jointly at an individual level. The functional brain networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based Riemannian distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional brain networks that are informative for schizophrenia diagnosis.
[show abstract][hide abstract] ABSTRACT: The functional networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive functions and neurological diseases. In this paper, we propose a novel algorithm for discriminant analysis of functional networks encoded by spatial independent components. The functional networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of temporal signals of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based subspace distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional networks that are informative for schizophrenia diagnosis.
[show abstract][hide abstract] ABSTRACT: Healthy siblings of schizophrenia patients have an almost 9-fold higher risk for developing the illness than the general population. Disruption of white matter (WM) integrity as indicated by reduced fractional anisotropy (FA) derived from diffusion tensor imaging (DTI), is believed to be the key substrate of schizophrenia. However, it remains unclear whether schizophrenia patients and their healthy siblings share a specific pattern of disruption of WM integrity that may be related to the disease risk. The objective of this study is to determine whether a specific brain regional pattern of disruption of WM integrity is shared by schizophrenia patients and their healthy siblings. We investigated brain white matter abnormalities by voxel-based analysis of white matter FA data acquired from diffusion tensor imaging in 34 pairs of schizophrenia patients and their healthy siblings, as well as in 32 healthy controls. Both schizophrenia patients and their healthy siblings showed reduced white matter FA in the left prefrontal cortex and the hippocampus in comparison to healthy controls, without significant difference between patients and siblings. In marked contrast, only schizophrenia patients exhibited reduced white matter FA in the left anterior cingulate cortex in comparison to both siblings and controls, without significant difference between siblings and controls. Thus, schizophrenia patients and their healthy siblings share disruption of WM integrity in the left prefrontal cortex and the hippocampus that may be related to higher risk of healthy siblings to develop schizophrenia, which may be eventually attributed to additional disruption of WM integrity in the left anterior cingulate cortex.
Schizophrenia Research 08/2009; 114(1-3):128-35. · 4.59 Impact Factor
[show abstract][hide abstract] ABSTRACT: Repeated exposure to heroin, a typical opiate, causes neuronal adaptation and may result in anatomical changes in specific brain regions, particularly the frontal and limbic cortices. The volume changes of gray matter (GM) of these brain regions, however, have not been identified in heroin addiction.
Using structural magnetic resonance imaging and an optimized voxel-based morphometry approach, the GM volume difference between 15 Chinese heroin-dependent and 15 healthy subjects was tested.
Compared to healthy subjects, the heroin-dependent subjects had reduced GM volume in the right prefrontal cortex, left supplementary motor cortex and bilateral cingulate cortices.
Frontal and cingulate atrophy may be involved in the neuropathology of heroin dependence.
Psychiatry and Clinical Neurosciences 07/2009; 63(4):563-8. · 2.04 Impact Factor
[show abstract][hide abstract] ABSTRACT: Fractional anisotropy (FA) via diffusion tensor imaging (DTI) can quantify the white matter integrity. Exposure to addictive drugs, such as alcohol, cocaine, methamphetamine, marijuana, and nicotine has been shown to alter FA. White matter abnormalities have been shown, but it remains unclear whether the white matter FA is altered in heroin dependence.
Utilizing DTI, we investigated the FA difference between heroin-dependent and control subjects by a voxel-based strategy. The FA values of the identified regions were calculated from the FA image of each subject and were correlated with clinical features including months of heroin use, age, education, and dose of methadone.
Reduced FA among 16 heroin dependent subjects was located in the bilateral frontal sub-gyral regions, right precentral and left cingulate gyrus. FA in the right frontal sub-gyral was negatively correlated with duration of heroin use.
The disrupted white matter integrity in right frontal white matter may occur in continuous heroin abuse.
The American Journal of Drug and Alcohol Abuse 09/2008; 34(5):562-75. · 1.55 Impact Factor
[show abstract][hide abstract] ABSTRACT: The human brain has been described as a large, sparse, complex network characterized by efficient small-world properties, which assure that the brain generates and integrates information with high efficiency. Many previous neuroimaging studies have provided consistent evidence of 'dysfunctional connectivity' among the brain regions in schizophrenia; however, little is known about whether or not this dysfunctional connectivity causes disruption of the topological properties of brain functional networks. To this end, we investigated the topological properties of human brain functional networks derived from resting-state functional magnetic resonance imaging (fMRI). Data was obtained from 31 schizophrenia patients and 31 healthy subjects; then functional connectivity between 90 cortical and sub-cortical regions was estimated by partial correlation analysis and thresholded to construct a set of undirected graphs. Our findings demonstrated that the brain functional networks had efficient small-world properties in the healthy subjects; whereas these properties were disrupted in the patients with schizophrenia. Brain functional networks have efficient small-world properties which support efficient parallel information transfer at a relatively low cost. More importantly, in patients with schizophrenia the small-world topological properties are significantly altered in many brain regions in the prefrontal, parietal and temporal lobes. These findings are consistent with a hypothesis of dysfunctional integration of the brain in this illness. Specifically, we found that these altered topological measurements correlate with illness duration in schizophrenia. Detection and estimation of these alterations could prove helpful for understanding the pathophysiological mechanism as well as for evaluation of the severity of schizophrenia.
[show abstract][hide abstract] ABSTRACT: Hippocampus has been implicated in participating in the pathophysiology of schizophrenia. However, the functional and anatomical connectivities between hippocampus and other regions are rarely concurrently investigated in schizophrenia. In the present study, both functional magnetic resonance imaging (fMRI) during rest and diffusion tensor imaging (DTI) were performed on 17 patients with paranoid schizophrenia and 14 healthy subjects. Resting-state functional connectivities of the bilateral hippocampi were separately analyzed by selecting the anterior hippocampus as region of interest. The fornix body was reconstructed by diffusion tensor tractography, and the integrity of this tract was evaluated using fractional anisotropy (FA). In patients with schizophrenia, the bilateral hippocampi showed reduced functional connectivities to some regions which have been reported to be involved in episodic memory, such as posterior cingulate cortex, extrastriate cortex, medial prefrontal cortex, and parahippocampus gyrus. We speculated that these reduced connectivity may reflect the disconnectivity within a neural network related to the anterior hippocampus in schizophrenia. Meanwhile the mean FA of the fornix body was significantly reduced in patients, indicating the damage in the hippocampal anatomical connectivity in schizophrenia. The concurrence of the functional disconnectivity and damaged anatomical connectivity between the hippocampus and other regions in schizophrenia suggest that the functional-anatomical relationship need to be further investigated.
Schizophrenia Research 04/2008; 100(1-3):120-32. · 4.59 Impact Factor
[show abstract][hide abstract] ABSTRACT: Antipsychotic treatment during pregnancy is indicated when risk of drug exposure to the fetus is outweighed by the untreated psychosis in the mother. Although increased risk of congenital malformation has not been associated with most available antipsychotic drugs, there is a paucity of knowledge on the subtle neurodevelopmental and behavioral consequences of prenatal receptor blockade by these drugs. In the present study, antipsychotic drugs, sulpiride (SUL, a selective D2 receptor antagonist) and risperidone (RIS, a D2/5HT2 receptor antagonist) were administered to pregnant Sprague-Dawley dams from gestational day 6 to 18. Both RIS and SUL prenatal exposed rats had lower birth body weights compared to controls. RIS exposure had a significant main effect to retard body weight growth in male offspring until postnatal day (PND) 60. Importantly, water maze tests revealed that SUL prenatal exposure impaired visual cue response in visual task performance (stimulus-response, S-R memory), but not place response as reflected in hidden platform task (spatial memory acquisition and retention). In addition, prenatal SUL treatment reduced spontaneous activity as measured in open field. Both behavioral deficits suggest that SUL prenatal exposure may lead to subtle disruption of striatum development and related learning and motor systems. RIS exposure failed to elicit deficits in both water maze tasks and increased rearing in open field test. These results suggest prenatal exposure to SUL and RIS may produce lasting effects on growth, locomotion and memory in rat offspring. And the differences may exist in the effects of antipsychotic drugs which selectively block dopamine D2 receptors (SUL) as compared to second generation drugs (RIS) that potently antagonize serotonin and dopamine receptors.
Progress in Neuro-Psychopharmacology and Biological Psychiatry 03/2008; 32(2):387-97. · 3.55 Impact Factor
[show abstract][hide abstract] ABSTRACT: Functional disintegration has been observed in schizophrenia during task performance. We sought to investigate functional disintegration during rest because an intrinsic functional brain organization, including both "task-negative" (i.e., "default mode") and "task-positive" networks, has been suggested to play an important role in integrating ongoing information processing. Additionally, the brain regions that are involved in the intrinsic organization are believed to be abnormal in schizophrenia. Patients with paranoid schizophrenia (N=18) and healthy volunteers (N=18) underwent a resting-state fMRI scan. Functional connectivity analysis was used to identify the connectivity between each pair of brain regions within this intrinsic organization, and differences were examined in patients versus healthy volunteers. Compared to healthy volunteers, patients showed significant differences in connectivity within networks and between networks, most notably in the connectivities associated with the bilateral dorsal medial prefrontal cortex, the lateral parietal region, the inferior temporal gyrus of the "task-negative" network and with the right dorsolateral prefrontal cortex and the right dorsal premotor cortex of the "task-positive" network. These results suggested that the interregional functional connectivities in the intrinsic organization are altered in patients with paranoid schizophrenia. These abnormalities could be the source of abnormalities in the coordination of and competition between information processing activities in the resting brain of paranoid patients.
Schizophrenia Research 01/2008; 97(1-3):194-205. · 4.59 Impact Factor
[show abstract][hide abstract] ABSTRACT: Using resting-state functional magnetic resonance imaging, we examined the functional connectivity throughout the entire brain in schizophrenia. The abnormalities in functional connectivity were identified by comparing the correlation coefficients of each pair of 116 brain regions between 15 patients and 15 controls. Then, the global distribution of the abnormal functional connectivities was examined. Experimental results indicated, in general, a decreased functional connectivity in schizophrenia during rest, and such abnormalities were widely distributed throughout the entire brain rather than restricted to a few specific brain regions. The results provide a quantitative support for the hypothesis that schizophrenia may arise from the disrupted functional integration of widespread brain areas.
[show abstract][hide abstract] ABSTRACT: Diffusion tensor imaging studies in schizophrenia have demonstrated lower diffusion anisotropy within white matter that provides information about brain white matter integrity. We have examined whether white matter is abnormal in first-episode schizophrenia by using diffusion tensor imaging. Twenty-one schizophrenic patients and healthy controls underwent diffusion tensor imaging scans that analyzed by using a rigorous voxel-based approach. We found that fractional anisotropy in white matter of the patients was lower than that in controls at the cerebral peduncle, frontal regions, inferior temporal gyrus, medial parietal lobes, hippocampal gyrus, insula, right anterior cingulum bundle and right corona radiata. These results suggested that white matter integrity of the whole brain was disrupted in early illness onset of schizophrenia.
[show abstract][hide abstract] ABSTRACT: We used a newly reported regional homogeneity approach to measure the temporal homogeneity of blood oxygen level-dependent signal for exploring the brain activity of schizophrenia in a resting state. The results showed decreased regional homogeneity in schizophrenia, which distributed over the bilateral frontal, temporal, occipital, cerebellar posterior, right parietal and left limbic lobes, similar to the findings reported in previous resting state functional studies. The brain regions that showed decreased regional homogeneity are believed to be involved in the psychopathology and pathophysiology of schizophrenia. Our results indicate that abnormal brain activity of schizophrenia may exist in a resting state and the regional homogeneity may be potentially helpful in understanding the resting state of schizophrenia.