Yihui Hao

Altered resting-state functional connectivity and anatomical connectivity of hippocampus in schizophrenia

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.

Schizophrenic Patients and Their Unaffected Siblings Share Increased Resting-State Connectivity in the Task-Negative Network but Not Its Anticorrelated Task-Positive Network

BACKGROUND 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. METHODS 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. RESULTS 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. CONCLUSION 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.

Schizophrenia patients and their healthy siblings share disruption of white matter integrity in the left prefrontal cortex and the hippocampus but not the anterior cingulate cortex

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.

Frontal and cingulate gray matter volume reduction in heroin dependence: optimized voxel-based morphometry.

Aims:  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.

Disrupted White Matter Integrity in Heroin Dependence: A Controlled Study Utilizing Diffusion Tensor Imaging

Objectives: 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. Methods: 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. Results: Reduced FA among 16 heroin dependent subjects was located in the bilateral frontal sub-gyral regionsm, right precentral and left cingulate gyrus. FA in the right frontal sub-gyral was negatively correlated with duration of heroin use. Conclusion: The disrupted white matter integrity in right frontal white matter may occur in continuous heroin abuse.

Discriminant analysis of functional connectivity patterns on Grassmann manifold

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.

Distinct neurobehavioral consequences of prenatal exposure to sulpiride (SUL) and risperidone (RIS) in rats

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.

Discriminant Analysis of Resting-state Functional Connectivity Patterns on the Grassmann Manifold

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.