Altered Functional Connectivity in the Motor and Prefrontal Cortex for Children With Down's Syndrome: An fNIRS Study.

Children with Down's syndrome (DS) might exhibit disrupted brain functional connectivity in the motor and prefrontal cortex. To inspect the alterations in brain activation and functional connectivity for children with DS, the functional near-infrared spectroscopy (fNIRS) method was applied to examine the brain activation difference in the motor and prefrontal cortex between the DS and typically developing (TD) groups during a fine motor task. In addition, small-world analysis based on graph theory was also carried out to characterize the topological organization of functional brain networks. Interestingly, behavior data demonstrated that the DS group showed significantly long reaction time and low accuracy as compared to the TD group (p < 0.05). More importantly, significantly reduced brain activations in the frontopolar area, the pre-motor, and the supplementary motor cortex (p < 0.05) were identified in the DS group compared with the TD group. Meanwhile, significantly high global efficiency (E g ) and short average path length (L p ) were also detected for the DS group. This pilot study illustrated that the disrupted connectivity of frontopolar area, pre-motor, and supplementary motor cortex might be one of the core mechanisms associated with motor and cognitive impairments for children with DS. Therefore, the combination of the fNIRS technique with functional network analysis may pave a new avenue for improving our understanding of the neural mechanisms of DS.

Reduced gray matter volume in male adolescent violent offenders.

BACKGROUND: Previous studies reported that reduced gray matter volume (GMV) was associated with violent-related behaviors. However, the previous studies were conducted on adults and no study has studied the association between GMV and violent behaviors on adolescents. The purpose of the study was to investigate GMV's effects in adolescent violent offenders based on a Chinese Han population, which can address the problem of possible confounding factors in adult studies. METHODS: We recruited 30 male adolescent violent offenders and 29 age- and sex-matched healthy controls (HCs). Differences in both whole-brain and GMV were evaluated using voxel-based morphometry (VBM). We assessed the accuracy of VBM using the receiver operating characteristic curve (ROC) and discriminant analysis. RESULTS: Compared with HCs, the male adolescent offenders showed significantly reduced GMV in five cortical and subcortical brain regions, including the olfactory cortex, amygdala, middle temporal gyrus and inferior parietal lobe in the left hemisphere, as well as the right superior temporal gyrus. Both ROC curve and discriminate analyses showed that these regions had relatively high sensitivities (58.6%-89.7%) and specificities (58.1%-74.2%) with 76.7% classification accuracy. CONCLUSIONS: Our results indicated that reduced volume in the frontal-temporal-parietal-subcortical circuit may be closely related to violent behaviors in male adolescents, which might be an important biomarker for detecting violent behaviors in male adolescents.

Neuroticism and conscientiousness respectively positively and negatively correlated with the network characteristic path length in dorsal lateral prefrontal cortex: A resting-state fNIRS study.

BACKGROUND: Accumulating evidence shows that the dorsal lateral prefrontal cortex (dlPFC) is implicated in personality traits. In this study, resting-state functional near infrared spectroscopy (fNIRS) combined with small-world analysis was utilized to examine the relationship between the network properties of dlPFC and personality traits. METHODS: Thirty college students (aged between 20 and 29) were recruited from the University of Macau campus, whose personality scores were accessed with the NEO-FFT questionnaire. Graph theory combined with resting-state fNIRS data was used to quantify the network properties of dlPFC, whereas Pearson correlation analysis was performed to generate the relationship between the small-world indicators and personality scores. RESULTS: Compared to matched random networks, the resting-state brain networks exhibited a larger clustering coefficient (Cp , 0.1-0.66), shorter characteristic path length (Lp , 0.1-0.66), and higher global (Eg , 0.1-0.66) and local efficiency (Eloc , 0.1-0.65). In particular, conscientiousness (r = -0.63) and neuroticism (r = 0.40) respectively showed negative and positive correlation with the Lp . CONCLUSIONS: The resting-state functional brain networks in dlPFC exhibited the small-world properties. In addition, participants with higher conscientiousness scores showed a shorter Lp .

Optical mapping of prefrontal brain connectivity and activation during emotion anticipation.

Accumulated neuroimaging evidence shows that the dorsal lateral prefrontal cortex (dlPFC) is activated during emotion anticipation. The aim of this work is to examine the brain connectivity and activation differences in dlPFC between the positive, neutral and negative emotion anticipation by using functional near-infrared spectroscopy (fNIRS). The hemodynamic responses were first assessed for all subjects during the performance of various emotion anticipation tasks. And then small-world analysis was performed, in which the small-world network indicators including the clustering coefficient, average path length, average node degree, and measure of small-world index were calculated for the functional brain networks associated with the positive, neutral and negative emotion anticipation, respectively. We discovered that compared to negative and neutral emotion anticipation, the positive one exhibited enhanced brain activation in the left dlPFC. Although the functional brain networks for the three emotion anticipation cases manifested the small-world properties regarding the clustering coefficient, average path length, average node degree, and measure of small-world index, the positive one showed significantly higher clustering coefficient and shorter average path length than those from the neutral and negative cases. Consequently, the small-world network indicators and brain activation in dlPPC were able to distinguish well between the positive, neutral and negative emotion anticipation.

Diffusion Tensor Imaging Tractography Reveals Disrupted White Matter Structural Connectivity Network in Healthy Adults with Insomnia Symptoms.

Neuroimaging studies have revealed that insomnia is characterized by aberrant neuronal connectivity in specific brain regions, but the topological disruptions in the white matter (WM) structural connectivity networks remain largely unknown in insomnia. The current study uses diffusion tensor imaging (DTI) tractography to construct the WM structural networks and graph theory analysis to detect alterations of the brain structural networks. The study participants comprised 30 healthy subjects with insomnia symptoms (IS) and 62 healthy subjects without IS. Both the two groups showed small-world properties regarding their WM structural connectivity networks. By contrast, increased local efficiency and decreased global efficiency were identified in the IS group, indicating an insomnia-related shift in topology away from regular networks. In addition, the IS group exhibited disrupted nodal topological characteristics in regions involving the fronto-limbic and the default-mode systems. To our knowledge, this is the first study to explore the topological organization of WM structural network connectivity in insomnia. More importantly, the dysfunctions of large-scale brain systems including the fronto-limbic pathways, salience network and default-mode network in insomnia were identified, which provides new insights into the insomnia connectome. Topology-based brain network analysis thus could be a potential biomarker for IS.

Optical mapping of the dominant frequency of brain signal oscillations in motor systems.

Recent neuroimaging studies revealed that the dominant frequency of neural oscillations is brain-region-specific and can vary with frequency-specific reorganization of brain networks during cognition. In this study, we examined the dominant frequency in low-frequency neural oscillations represented by oxygenated hemoglobin measurements after the hemodynamic response function (HRF) deconvolution. Twenty-nine healthy college subjects were recruited to perform a serial finger tapping task at the frequency of 0.2 Hz. Functional near-infrared spectroscopy (fNIRS) was applied to record the hemodynamic signals over the primary motor cortex, supplementary motor area (SMA), premotor cortex, and prefrontal area. We then explored the low frequency steady-state brain response (lfSSBR), which was evoked in the motor systems at the fundamental frequency (0.2 Hz) and its harmonics (0.4, 0.6, and 0.8 Hz). In particular, after HRF deconvolution, the lfSSBR at the frequency of 0.4 Hz in the SMA was identified as the dominant frequency. Interestingly, the domain frequency exhibited the correlation with behavior data such as reaction time, indicating that the physiological implication of lfSSBR is related to the brain anatomy, stimulus frequency and cognition. More importantly, the HRF deconvolution showed its capability for recovering signals probably reflecting neural-level events and revealing the physiological meaning of lfSSBR.

Disrupted small-world brain network topology in pure conduct disorder.

OBJECTIVES: Conduct disorder (CD) is characterized by the violation of the rights of others or basic social rules and a repetitive, persistent pattern of antisocial and aggressive behaviors. A large number of functional and structural neuroimaging studies have identified widely abnormalities in specific brain regions in CD, but the alterations in the topological organization of functional networks among them remain largely unknown. METHODS: Resting-state functional magnetic resonance imaging was applied to investigate the intrinsic functional connectivity in 18 pure CD patients and eighteen typically developing healthy controls. We first constructed the functional networks and then examined the CD-related alteration in topology properties using graph theoretical analysis. RESULTS: Both the CD group and healthy controls exhibited small-world topology. However, the CD group showed decreased global and local efficiency. Changes in the nodal characteristics in CD group were found predominantly in the default-mode network, visual, and striatum regions. In addition, altered fronto-limbic-striatum network topology was found to have a relationship with clinical scores. CONCLUSIONS: Our findings indicate the altered nodal topology of brain functional connectivity networks in CD. SIGNIFICANCE: The results provide unequivocal evidence of a topological disruption in the brain networks that suggest some possible pathophysiological mechanisms underlying CD.

Disrupted Topology of Frontostriatal Circuits Is Linked to the Severity of Insomnia.

Insomnia is one of the most common health complaints, with a high prevalence of 30~50% in the general population. In particular, neuroimaging research has revealed that widespread dysfunctions in brain regions involved in hyperarousal are strongly correlated with insomnia. However, whether the topology of the intrinsic connectivity is aberrant in insomnia remains largely unknown. In this study, resting-state functional magnetic resonance imaging (rsfMRI) in conjunction with graph theoretical analysis, was used to construct functional connectivity matrices and to extract the attribute features of the small-world networks in insomnia. We examined the alterations in global and local small-world network properties of the distributed brain regions that are predominantly implicated in the frontostriatal network between 30 healthy subjects with insomnia symptoms (IS) and 62 healthy subjects without insomnia symptoms (NIS). Correlations between the small-world properties and clinical measurements were also generated to identify the differences between the two groups. Both the IS group and the NIS group exhibited a small-worldness topology. Meanwhile, the global topological properties didn't show significant difference between the two groups. By contrast, participants in the IS group showed decreased regional degree and efficiency in the left inferior frontal gyrus (IFG) compared with subjects in the NIS group. More specifically, significantly decreased nodal efficiency in the IFG was found to be negatively associated with insomnia scores, whereas the abnormal changes in nodal betweenness centrality of the right putamen were positively correlated with insomnia scores. Our findings suggested that the aberrant topology of the salience network and frontostriatal connectivity is linked to insomnia, which can serve as an important biomarker for insomnia.

Short- and long-range functional connectivity density alterations in adolescents with pure conduct disorder at resting-state.

Conduct disorder (CD) is a developmental disorder defined by a repetitive and persistent display of antisocial and aggressive behaviors that violates the rights of others or basic social rules. Recently, resting-state functional magnetic resonance imaging (rsfMRI) has been widely adopted to investigate the altered intrinsic neural activities and the disrupted endogenous brain connectivity of CD. In this study, functional connectivity density (FCD) mapping, a newly developed ultrafast voxel-wise method based on rsfMRI, was applied for the first time to examine the changes in the brain functional connectivity in CD at the voxel level. We assessed the differences in FCD between eighteen male adolescents with CD and eighteen typically-developing (TD) individuals. Then, the identified brain regions in which CD patients and healthy controls exhibited significant difference in FCD were extracted to calculate the correlations between measures of FCD values and clinical data. We discovered that compared to healthy controls, CD patients showed increased short-range FCD in the default-mode network including the bilateral posterior cingulate cortex (PCC) and the bilateral precuneus (PCUN). More importantly, increased short-range FCD values in the bilateral PCC, the bilateral PCUN, and increased long-range FCD values in the left MCC showed significant correlations with the impulsivity. Overall, these results suggested that the FCD abnormalities in CD patients occurred in brain regions known to be involved in cognition, emotion and visual perception.

Functional Connectivity Estimated from Resting-State fMRI Reveals Selective Alterations in Male Adolescents with Pure Conduct Disorder.

Conduct disorder (CD) is characterized by a persistent pattern of antisocial behavior and aggression in childhood and adolescence. Previous task-based and resting-state functional magnetic resonance imaging (fMRI) studies have revealed widespread brain regional abnormalities in adolescents with CD. However, whether the resting-state networks (RSNs) are altered in adolescents with CD remains unknown. In this study, resting-state fMRI data were first acquired from eighteen male adolescents with pure CD and eighteen age- and gender-matched typically developing (TD) individuals. Independent component analysis (ICA) was implemented to extract nine representative RSNs, and the generated RSNs were then compared to show the differences between the CD and TD groups. Interestingly, it was observed from the brain mapping results that compared with the TD group, the CD group manifested decreased functional connectivity in four representative RSNs: the anterior default mode network (left middle frontal gyrus), which is considered to be correlated with impaired social cognition, the somatosensory network (bilateral supplementary motor area and right postcentral gyrus), the lateral visual network (left superior occipital gyrus), and the medial visual network (right fusiform, left lingual gyrus and right calcarine), which are expected to be relevant to the perceptual systems responsible for perceptual dysfunction in male adolescents with CD. Importantly, the novel findings suggested that male adolescents with pure CD were identified to have dysfunctions in both low-level perceptual networks (the somatosensory network and visual network) and a high-order cognitive network (the default mode network). Revealing the changes in the functional connectivity of these RSNs enhances our understanding of the neural mechanisms underlying the modulation of emotion and social cognition and the regulation of perception in adolescents with CD.

PET/SPECT molecular imaging in clinical neuroscience: recent advances in the investigation of CNS diseases.

Molecular imaging is an attractive technology widely used in clinical practice that greatly enhances our understanding of the pathophysiology and treatment in central nervous system (CNS) diseases. It is a novel multidisciplinary technique that can be defined as real-time visualization, in vivo characterization and qualification of biological processes at the molecular and cellular level. It involves the imaging modalities and the corresponding imaging agents. Nowadays, molecular imaging in neuroscience has provided tremendous insights into disturbed human brain function. Among all of the molecular imaging modalities, positron emission tomography (PET) and single photon emission computed tomography (SPECT) have occupied a particular position that visualize and measure the physiological processes using high-affinity and high-specificity molecular radioactive tracers as imaging probes in intact living brain. In this review, we will put emphasis on the PET/SPECT applications in Alzheimer's disease (AD) and Parkinson's disease (PD) as major CNS disorders. We will first give an overview of the main classical molecular neuroimaging modalities. Then, the major clinical applications of PET and SPECT along with molecular probes in the fields of psychiatry and neurology will be discussed.

A new method for computing attention network scores and relationships between attention networks.

The attention network test (ANT) is a reliable tool to detect the efficiency of alerting, orienting, and executive control networks. However, studies using the ANT obtained inconsistent relationships between attention networks due to two reasons: on the one hand, the inter-network relationships of attention subsystems were far from clear; on the other hand, ANT scores in previous studies were disturbed by possible inter-network interactions. Here we proposed a new computing method by dissecting cue-target conditions to estimate ANT scores and relationships between attention networks as pure as possible. The method was tested in 36 participants. Comparing to the original method, the new method showed a larger alerting score and a smaller executive control score, and revealed interactions between alerting and executive control and between orienting and executive control. More interestingly, the new method revealed unidirectional influences from alerting to executive control and from executive control to orienting. These findings provided useful information for better understanding attention networks and their relationships in the ANT. Finally, the relationships of attention networks should be considered with more experimental paradigms and techniques.