Emotional instability is a hallmark feature of borderline personality disorder (BPD), yet its biological underpinnings are poorly understood. We employed functional MRI to compare patterns of regional brain activation in BPD patients and healthy volunteers as they process positive and negative social emotional stimuli. fMRI images were acquired while 19 BPD patients and 17 healthy controls (HC) viewed emotion-inducing pictures from the IAPS set. Activation data were analyzed with SPM5 ANCOVA models to derive the effects of diagnosis and stimulus type. BPD patients demonstrated greater differences in activation than controls, when viewing negative pictures compared to rest, in the amygdala, fusiform gyrus, primary visual areas, superior temporal gyrus (STG), and premotor areas, while healthy controls showed greater differences than BPD’s in the insula, middle temporal gyrus and dorsolateral prefrontal cortex (BA46). When viewing positive pictures compared to rest, BPD patients showed greater differences in the STG, premotor cortex, and ventrolateral prefrontal cortex. These findings suggest that BPD patients show greater amygdala activity and heightened activity of visual processing regions than HC’s, when processing negative social emotional pictures compared to rest. They activate neural networks in emotion processing that are phylogenetically older and more reflexive than healthy controls.

Structural brain networks were constructed based on diffusion tensor imaging (DTI) data of 59 young healthy male adults. The networks had 68 nodes, derived from FreeSurfer parcellation of the cortical surface. By means of streamline tractography, the edge weight was defined as the number of streamlines between two nodes normalized by their mean volume. Specifically, two weighting schemes were adopted by considering various biases from fiber tracking. The weighting schemes were tested for possible bias toward the physical size of the nodes. A novel thresholding method was proposed using the variance of number of streamlines in fiber tracking. The backbone networks were extracted and various network analyses were applied to investigate the features of the binary and weighted backbone networks. For weighted networks, a high correlation was observed between nodal strength and betweenness centrality. Despite similar small-worldness features, binary networks and weighted networks are distinctive in many aspects, such as modularity and nodal betweenness centrality. Inter-subject variability was examined for the weighted networks, along with the test–retest reliability from two repeated scans on 44 of the 59 subjects. The inter-/intra-subject variability of weighted networks was discussed in three levels — edge weights, local metrics, and global metrics. The variance of edge weights can be very large. Although local metrics show less variability than the edge weights, they still have considerable amounts of variability. Weighting scheme one, which scales the number of streamlines by their lengths, demonstrates stable intra-class correlation coefficients against thresholding for global efficiency, clustering coefficient and diversity. The intra-class correlation analysis suggests the current approach of constructing weighted network has a reasonably high reproducibility for most global metrics.

This article demonstrates the encapsulation of cubic iron oxide NPs by Brome mosaic virus capsid shells and the formation, for the first time, of virus-based nanoparticles (VNPs) with cubic cores. Cubic iron oxide nanoparticles (NPs) functionalized with phospholipids containing poly(ethylene glycol) tails and terminal carboxyl groups exhibited exceptional relaxivity in magnetic resonance imaging experiments, which opens the way for in vivo MRI studies of systemic virus movement in plants. Preliminary data on cell-to-cell and long-distance transit behavior of cubic iron oxide NPs and VNPs in N. benthamiana leaves indicate that VNPs have specific transit properties, i.e., penetration into tissue and long-distance transfer through the vasculature in N. Benthamiana plants, even at low temperature (6° C), while NPs devoid of virus protein coats exhibit limited transport by comparison. These particles potentially open new opportunities for the high contrast functional imaging in plants and for the delivery of therapeutic anti-microbial cores into plants.

A disturbance in the integration of information during mental processing has been implicated in schizophrenia, possibly due to faulty communication within and between brain regions. Graph theoretic measures allow quantification of functional brain networks. Functional networks are derived from correlations between time courses of brain regions. Group differences between SZ and control groups have been reported for functional network properties, but the potential of such measures to classify individual cases has been little explored. We tested whether the network measure of betweenness centrality could classify persons with schizophrenia and normal controls. Functional networks were constructed for 19 schizophrenic patients and 29 non-psychiatric controls based on resting state functional MRI scans. The betweenness centrality of each node, or fraction of shortest-paths that pass through it, was calculated in order to characterize the centrality of the different regions. The nodes with high betweenness centrality agreed well with hub nodes reported in previous studies of structural and functional networks. Using a linear support vector machine algorithm, the schizophrenia group was differentiated from non-psychiatric controls using the ten nodes with highest betweenness centrality. The classification accuracy was around 80%, and stable against connectivity thresholding. Better performance was achieved when using the ranks as feature space as opposed to the actual values of betweenness centrality. Overall, our findings suggest that changes in functional hubs are associated with schizophrenia, reflecting a variation of the underlying functional network and neuronal communications. In addition, a specific network property, betweenness centrality, can classify persons with SZ with a high level of accuracy.

After giving birth, women typically experience decreased sexual desire and increased responsiveness to infant stimuli. These postpartum changes may be viewed as a trade-off in reproductive interests, which could be due to alterations in brain activity including areas associated with reward. The goal of this study was to describe the roles of oxytocin and parity on reward area activation in response to reproductive stimuli, specifically infant and sexual images. Because they have been shown to be associated with reward, the ventral tegmental area (VTA) and nucleus accumbens (NAc) were targeted as areas of expected alterations in activity. Oxytocin was chosen as a potential mediator of reproductive trade-offs because of its relationship to both mother–infant interactions, including breastfeeding and bonding, and sexual responses. We predicted that postpartum women would show higher reward area activation to infant stimuli and nulliparous women would show higher activation to sexual stimuli and that oxytocin would increase activation to infant stimuli in nulliparous women. To test this, we measured VTA and NAc activation using fMRI in response to infant photos, sexual photos, and neutral photos in 29 postpartum and 30 nulliparous women. Participants completed the Sexual Inhibition (SIS) and Sexual Excitation (SES) Scales and the Brief Index of Sexual Function for Women (BISF-W), which includes a sexual desire dimension, and received either oxytocin or placebo nasal spray before viewing crying and smiling infant and sexual images in an fMRI scanner. For both groups of women, intranasal oxytocin administration increased VTA activation to both crying infant and sexual images but not to smiling infant images. We found that postpartum women showed lower SES, higher SIS, and lower sexual desire compared to nulliparous women. Across parity groups, SES scores were correlated with VTA activation and subjective arousal ratings to sexual images. In postpartum women, sexual desire was positively correlated with VTA activation to sexual images and with SES. Our findings show that postpartum decreases in sexual desire may in part be mediated by VTA activation, and oxytocin increased activation of the VTA but not NAc in response to sexual and infant stimuli. Oxytocin may contribute to the altered reproductive priorities in postpartum women by increasing VTA activation to salient infant stimuli.

Diffusion tensor imaging (DTI) has been used for mapping the structural network of the human brain. The network can be constructed by choosing various brain regions as nodes and fiber tracts connecting those regions as links. The structural network generated from DTI data can be affected by noise in the scans and the choice of tractography algorithm. This study aimed to examine the effect of the number of seeds in tractography on the variance of structural networks. The variance of the network was characterized using an approach similar to the National Electrical Manufacturers Association (NEMA) standards for measurement of image noise. It was shown that the variance of the network is inversely related to the square root of seed density. Consequently, the number of seeds has a large impact on local characteristics and metrics of the network architecture. As the number of seeds increased, increased stability of structural network metrics was observed. However, more seeds can also lead to more spurious fibers and thus affect nodal degrees and edge weights, and proper thresholding may be necessary to create an appropriate weighted network. Because the variance of the network is also influenced by other imaging factors, further increase in the number of seeds has little effect in reducing the network variance. The selection of the seed number should be a balance between the network variance and computational effort.

Recent studies of schizophrenia have revealed cognitive and memory deficits that are accompanied by disruptions of neuronal connectivity in cortical and subcortical brain regions. More recently, alterations of topological organization of structural networks in schizophrenia are also being identified using graph theoretical analysis. However, the role of the cerebellum in this network structure remains largely unknown. In this study, global network measures obtained from diffusion tensor imaging were computed in the cerebella of 25 patients with schizophrenia and 36 healthy volunteers. While cerebellar global network characteristics were slightly altered in schizophrenia patients compared with healthy controls, the patients showed a retained small-world network organization. The modular architecture, however, was changed mainly in crus II. Furthermore, schizophrenia patients had reduced correlations between modularity and microstructural integrity, as measured by fractional anisotropy (FA) in lobules I-IV and X. Finally, FA alterations were significantly correlated with the Positive and Negative Syndrome Scale symptom scores in schizophrenia patients. Taken together, our data suggest that schizophrenia patients have altered network architecture in the cerebellum with reduced local microstructural connectivity and that cerebellar structural abnormalities are associated symptoms of the disorder.

Highlights This work reviews different methods for studying brain microstructure using dMRI. Sensitivity to microstructural differences and experimental factors is investigated. Signal representation-based methods and multi-compartment models are explained.