Zhiliang Long

Abnormal amplitude low-frequency oscillations in medication-naive, first-episode patients with major depressive disorder: A resting-state fMRI study

BACKGROUND Recent resting-state fMRI studies on major depressive disorder (MDD) have found altered temporal correlation between low-frequency oscillations (LFOs). However, changes on the amplitudes of these LFOs remain largely unknown. METHODS Twenty-two medication-naive, first-episode patients with MDD and 19 age-, sex-, education-matched healthy controls were recruited. Resting-state fMRI was obtained by using an echo-planar imaging sequence and the fractional amplitude of low-frequency fluctuations (fALFF) was calculated to investigate the amplitude of LFOs in the resting state. RESULTS Compared with control subjects, patients with MDD showed significantly decreased fALFF in right cerebellum posterior lobe, left parahippocampal gyrus and right middle frontal gyrus and increased fALFF in left superior occipital gyrus/cuneus (p<0.05, corrected for multiple comparisons). Further receiver operating characteristic curves (ROC) analyses suggested that the alterations of fALFF in these regions might be used as markers to classify patients with MDD from healthy controls. CONCLUSIONS These findings indicated LFOs abnormalities in MDD and the fALFF analysis might be a potential approach in further exploration of this disorder.

Abnormal regional spontaneous neural activity in first-episode, treatment-naive patients with late-life depression: a resting-state fMRI study.

BACKGROUND The previous resting perfusion or task-based studies have provided evidence of functional changes in the brains of patients with late-life depression (LLD). Little is known, so far, about the changes in the spontaneous brain activity in LLD during the resting state. The aim of this study was to investigate the spontaneous neural activity in first-episode, treatment-naive patients with LLD by using resting-state functional magnetic resonance imaging (fMRI). METHODS A novel analytical method, coherence-based regional homogeneity (Cohe-ReHo), was used to assess regional spontaneous neural activity during the resting state in 15 first-episode, treatment-naive patients with LLD and 15 age- and gender-matched healthy controls. RESULTS Compared to the healthy controls, the LLD group showed significantly decreased Cohe-ReHo in left caudate nucleus, right anterior cingulate gyrus, left dorsolateral prefrontal cortex, right angular gyrus, bilateral medial prefrontal cortex, and right precuneus, while significantly increased Cohe-ReHo in left cerebellum posterior lobe, left superior temporal gyrus, bilateral supplementary motor area, and right postcentral gyrus (p<0.005, corrected for multiple comparisons). CONCLUSIONS These findings indicated abnormal spontaneous neural activity was distributed extensively in first-episode, treatment-naive patients with LLD during the resting state. Our results might supply a novel way to look into the underlying pathophysiology mechanisms of patients with LLD.

Resting-State Functional Connectivity Bias of Middle Temporal Gyrus and Caudate with Altered Gray Matter Volume in Major Depression

Magnetic resonance imaging (MRI) studies have indicated that the structure deficits and resting-state functional connectivity (FC) imbalances in cortico-limbic circuitry might underline the pathophysiology of MDD. Using structure and functional MRI, our aim is to investigate gray matter abnormalities in patients with treatment-resistant depression (TRD) and treatment-responsive depression (TSD), and test whether the altered gray matter is associated with altered FC. Voxel-based morphometry was used to investigate the regions with gray matter abnormality and FC analysis was further conducted between each gray matter abnormal region and the remaining voxels in the brain. Using one-way analysis of variance, we found significant gray matter abnormalities in the right middle temporal cortex (MTG) and bilateral caudate among the TRD, TSD and healthy controls. For the FC of the right MTG, we found that both the patients with TRD and TSD showed altered connectivity mainly in the default-mode network (DMN). For the FC of the right caudate, both patient groups showed altered connectivity in the frontal regions. Our results revealed the gray matter reduction of right MTG and bilateral caudate, and disrupted functional connection to widely distributed circuitry in DMN and frontal regions, respectively. These results suggest that the abnormal DMN and reward circuit activity might be biomarkers of depression trait.

Disrupted cortical hubs in functional brain networks in social anxiety disorder

OBJECTIVE The network hubs, characterized by the large number of connections to other regions, play important roles in the proper and effective transfer of information. Previous functional neuroimaging studies have demonstrated that patients with social anxiety disorder (SAD) have aberrant functional connectivity. The changing pattern in functional network hubs in SAD, however, remains incompletely understood. METHODS Twenty SAD patients and 20 matched healthy controls were recruited. Resting-state fMRI data were obtained using a gradient-recalled echo-planar imaging sequence. Whole-brain voxel-wise functional networks were constructed by measuring the temporal correlations of each pair of brain voxels and then hubs were identified by using the graph theory method. Specifically, a functional connectivity strength (FCS) map was computed in each subject and the regions with higher FCS value were considered as functional network hubs. RESULTS Compared with healthy controls, SAD patients showed significantly decreased FCS in the bilateral precuneus and significantly increased FCS in the right fusiform gyrus. Furthermore, a significantly negative correlation was observed between the FCS value in the precuneus and the illness duration. CONCLUSION The present study demonstrated for the first time that disrupted cortical hubs existed in patients with SAD during resting state. SIGNIFICANCE These findings may provide novel insight into understanding of pathophysiological mechanisms underlying SAD.

Relationship between Personality and Gray Matter Volume in Healthy Young Adults: A Voxel-Based Morphometric Study

This study aims to investigate the neurostructural foundations of the human personality in young adults. High-resolution structural T1-weighted MR images of 71 healthy young individuals were processed using voxel-based morphometric (VBM) approach. Multiple regression analyses were performed to identify the associations between personality traits and gray matter volume (GMV). The Eysenck Personality Questionnaire-Revised, Short Scale for Chinese was chosen to assess the personality traits. This scale includes four dimensions, namely, extraversion, neuroticism, psychoticism, and lie. Particularly, we studied on two dimensions (extraversion and neuroticism) of Eysenck’s personality. Our results showed that extraversion was negatively correlated with GMV of the bilateral amygdala, the bilateral parahippocampal gyrus, the right middle temporal gyrus, and the left superior frontal gyrus, all of which are involved in emotional and social cognitive processes. These results might suggest an association between extraversion and affective processing. In addition, a positive correlation was detected between neuroticism and GMV of the right cerebellum, a key brain region for negative affect coordination. Meanwhile, a negative association was revealed between GMV of the left superior frontal gyrus and neuroticism. These results may prove that neuroticism is related to several brain regions involved in regulating negative emotions. Based on those findings, we concluded that brain regions involved in social cognition and affective process accounted for modulation and shaping of personality traits among young individuals. Results of this study may serve as a basis for elucidating the anatomical factors of personality.

Altered brain structural connectivity in post-traumatic stress disorder: a diffusion tensor imaging tractography study.

BACKGROUND Post-traumatic stress disorder (PTSD) is characterized by dysfunction of several discrete brain regions such as medial prefrontal gyrus with hypoactivation and amygdala with hyperactivation. However, alterations of large-scale whole brain topological organization of structural networks remain unclear. METHODS Seventeen patients with PTSD in motor vehicle accident survivors and 15 normal controls were enrolled in our study. Large-scale structural connectivity network (SCN) was constructed using diffusion tensor tractography, followed by thresholding the mean factional anisotropy matrix of 90 brain regions. Graph theory analysis was then employed to investigate their aberrant topological properties. RESULTS Both patient and control group showed small-world topology in their SCNs. However, patients with PTSD exhibited abnormal global properties characterized by significantly decreased characteristic shortest path length and normalized characteristic shortest path length. Furthermore, the patient group showed enhanced nodal centralities predominately in salience network including bilateral anterior cingulate and pallidum, and hippocampus/parahippocamus gyrus, and decreased nodal centralities mainly in medial orbital part of superior frontal gyrus. LIMITATIONS The main limitation of this study is the small sample of PTSD patients, which may lead to decrease the statistic power. Consequently, this study should be considered an exploratory analysis. CONCLUSIONS These results are consistent with the notion that PTSD can be understood by investigating the dysfunction of large-scale, spatially distributed neural networks, and also provide structural evidences for further exploration of neurocircuitry models in PTSD.

Disrupted structural connectivity network in treatment-naive depression.

BACKGROUND Neuroimaging studies suggest that treatment-naive depression (TD) is characterized by abnormal functional connectivity between specific brain regions. However, the question surrounding the structural basis of functional aberrations in TD patients still remains. METHODS In the present study, diffusion tensor imaging tractography was employed to construct structural connectivity networks in 22 early adult-onset, first-episode TD patients and 19 healthy controls (HC). Graph theory and network-based statistic (NBS) were then employed to investigate systematically the alteration of whole brain structural topological organization and structural connectivity in TD patients. RESULTS Graph theoretical analysis revealed that, compared with HC, TD patients exhibited altered structural topological measures, including decreased shortest path length, normalized clustering coefficient, normalized shortest path length, and small-worldness, as well as increased global and local efficiency. NBS results further revealed that TD patients showed two altered structural sub-networks. One sub-network mainly involved connections between the right orbitofrontal cortex (OFC) and the right insula, putamen, caudate, hippocampus, fusiform gyrus, inferior temporal gyrus and lingual gyrus. The other sub-network mainly included connections between the left OFC and the left gyrus rectus, insula, putamen, caudate, thalamus, pallidum and middle occipital gyrus. CONCLUSIONS The findings suggest that TD patients exhibit a disruption in the topological organization of structural brain networks. The altered orbitofrontal connectivity may particularly contribute to the manifestation of symptoms in TD patients. The abnormalities may facilitate understanding of the functional disturbances of mood and cognition in the disease.

Handedness-and hemisphere-related differences in small-world brain networks: a diffusion tensor imaging tractography study

Previous behavioral and scanning studies have suggested that handedness is associated with differences in brain morphology as well as in anatomical and functional lateralization. However, little is known about the topological organization of the white matter (WM) structural networks related to handedness. We employed diffusion tensor imaging tractography to investigate handedness- and hemisphere-related differences in the topological organization of the human cortical anatomical network. After constructing left hemispheric/right hemispheric weighted structural networks in 32 right-handed and 24 left-handed healthy individuals, we analyzed the networks by graph theoretic analysis. We found that both the right and left hemispheric WM structural networks in the two groups possessed small-world attributes (high local clustering and short paths between nodes), findings which are consistent with recent results from whole-brain structural networks. In addition, the right hemisphere tended to be more efficient than the left hemisphere, suggesting a high efficiency of general information processing in the right hemisphere. Finally, we found that the right-handed subjects had significant asymmetries in small-world properties (normalized clustering coefficient γ, normalized path length λ, and small-worldness σ), while left-handed subjects had fewer asymmetries. Our findings from large-scale brain networks aid in understanding the structural substrates underlying handedness-related and hemisphere-related differences in cognition and behavior.

Alteration of functional connectivity in autism spectrum disorder: effect of age and anatomical distance

Autism spectrum disorder (ASD) is associated with disruption of local- and long-range functional connectivity (FC). The direction of those changes in FC (increase or decrease), however, is inconsistent across studies. Further, age-dependent changes of distance-specific FC in ASD remain unclear. In this study, we used resting-state functional magnetic resonance imaging data from sixty-four typical controls (TC) and sixty-four patients with ASD, whom we further classified into child (<11 years), adolescent (11–18 years) and adult cohorts (>18 years). Functional connectivity (FC) analysis was conducted at voxel level. We employed a three-way analysis of covariance on FC to conduct statistical analyses. Results revealed that patients with ASD had lower FC than TC in cerebellum, fusiform gyrus, inferior occipital gyrus and posterior inferior temporal gyrus. Significant diagnosis-by-distance interaction was observed in ASD patients with reduced short-range and long-range FC in posterior cingulate cortex and medial prefrontal cortex. Importantly, we found significant diagnosis-by-age-by-distance interaction in orbitofrontal cortex with short-range FC being lower in autistic children, but –to a less extent– higher in autistic adults. Our findings suggest a major role of connection length in development changes of FC in ASD. We hope our study will facilitate deeper understanding of the neural mechanisms underlying ASD.

Steady-State BOLD Response Modulates Low Frequency Neural Oscillations

Neural oscillations are the intrinsic characteristics of brain activities. Traditional electrophysiological techniques (e.g., the steady-state evoked potential, SSEP) have provided important insights into the mechanisms of neural oscillations in the high frequency ranges (>1 Hz). However, the neural oscillations within the low frequency ranges (<1 Hz) and deep brain areas are rarely examined. Based on the advantages of the low frequency blood oxygen level dependent (BOLD) fluctuations, we expected that the steady-state BOLD responses (SSBRs) would be elicited and modulate low frequency neural oscillations. Twenty six participants completed a simple reaction time task with the constant stimuli frequencies of 0.0625 Hz and 0.125 Hz. Power analysis and hemodynamic response function deconvolution method were used to extract SSBRs and recover neural level signals. The SSEP-like waveforms were observed at the whole brain level and at several task-related brain regions. Specifically, the harmonic phenomenon of SSBR was task-related and independent of the neurovascular coupling. These findings suggested that the SSBRs represent non-linear neural oscillations but not brain activations. In comparison with the conventional general linear model, the SSBRs provide us novel insights into the non-linear brain activities, low frequency neural oscillations, and neuroplasticity of brain training and cognitive activities.