Publications by Year: 2015

Soccer is played by more than 250 million people worldwide. Repeatedly heading the ball may place soccer players at high risk for repetitive subconcussive head impacts (RSHI). This study evaluates the long-term effects of RSHI on neurochemistry in athletes without a history of clinically diagnosed concussion, but with a high exposure to RSHI. Eleven former professional soccer players (mean age 52.0±6.8 years) and a comparison cohort of 14 age- and gender-matched, former non-contact sport athletes (mean age 46.9±7.9 years) underwent 3T magnetic resonance spectroscopy (MRS) and neurocognitive evaluation. In the soccer players a significant increase was observed in both choline (Cho), a membrane marker, and myo-inositol (ml), a marker of glial activation, compared with control athletes. Additionally, ml and glutathione (GSH) were significantly correlated with lifetime estimate of RSHI within the soccer group. There was no significant difference in neurocognitive tests between groups. Results of this study suggest an association between RSHI in soccer players and MRS markers of neuroinflammation, suggesting that even subconcussive head impacts affect the neurochemistry of the brain and may precede neurocognitive changes. Future studies will need to determine the role of neuroinflammation in RSHI and the effect on neurocognitive function.

BACKGROUND: Delusions of control are among the most distinctive and characteristic symptoms of schizophrenia. Several theories have been proposed that implicate aberrant communication between spatially disparate brain regions in the etiology of this symptom. Given that white matter fasciculi represent the anatomical infrastructure for long-distance communication in the brain, the present study investigated whether delusions of control were associated with structural abnormalities in four major white matter fasciculi. METHODS: Ten schizophrenia patients with current delusions of control, 13 patients with no clinical history of delusions of control, and 12 healthy controls underwent a Diffusion-Tensor Imaging (DTI) scan. Deterministic tractography was used to extract the corpus callosum, superior longitudinal fasciculus, arcuate fasciculus, and cingulum bundle. The structural integrity of these four fasciculi was quantified with fractional anisotropy (FA) and compared between groups. RESULTS: The patients with delusions of control exhibited significantly lower FA in all four fasciculi, relative to the healthy controls. Furthermore, the patients with delusions of control also exhibited significantly lower FA in the cingulum bundle relative to patients without a history of this symptom, and this difference remained significant when controlling for between-group differences in global SAPS score and medication dosage. CONCLUSIONS: The results suggest that structural damage to the cingulum bundle may be involved in the etiology of delusions of control, possibly because of its role in connecting the action initiation areas of the premotor cortex with the cingulate gyrus.

The purpose of this study is to examine the relation between the microstructural architecture of white matter, as measured by diffusion tensor imaging (DTI), and postconcussion symptom reporting 6-8 weeks following mild traumatic brain injury (MTBI). Participants were 108 patients prospectively recruited from a Level 1 Trauma Center (Vancouver, BC, Canada) following an orthopedic injury [i.e., 36 trauma controls (TCs)] or MTBI (n = 72). DTI of the whole brain was undertaken using a Phillips 3T scanner at 6-8 weeks postinjury. Participants also completed a 5 h neurocognitive test battery and a brief battery of self-report measures (e.g., depression, anxiety, and postconcussion symptoms). The MTBI sample was divided into two groups based on ICD-10 criteria for postconcussional syndrome (PCS): first, PCS-present (n = 20) and second, PCS-absent (n = 52). There were no significant differences across the three groups (i.e., TC, PCS-present, and PCS-absent) for any of the neurocognitive measures (p = .138-.810). For the self-report measures, the PCS-present group reported significantly more anxiety and depression symptoms compared with the PCS-absent and TC groups (p .001, d = 1.63-1.89, very large effect sizes). For the DTI measures, there were no significant differences in fractional anisotropy, axial diffusivity, radial diffusivity, or mean diffusivity when comparing the PCS-present and PCS-absent groups. However, there were significant differences (p .05) in MD and RD when comparing the PCS-present and TC groups. There were significant differences in white matter between TC subjects and the PCS-present MTBI group, but not the PCS-absent MTBI group. Within the MTBI group, white-matter changes were not a significant predictor of ICD-10 PCS.

The last two decades have witnessed the explosive growth in the development and use of noninvasive neuroimaging technologies that advance the research on human brain under normal and pathological conditions. Multimodal neuroimaging has become a major driver of current neuroimaging research due to the recognition of the clinical benefits of multimodal data, and the better access to hybrid devices. Multimodal neuroimaging computing is very challenging, and requires sophisticated computing to address the variations in spatiotemporal resolution and merge the biophysical/biochemical information. We review the current workflows and methods for multimodal neuroimaging computing, and also demonstrate how to conduct research using the established neuroimaging computing packages and platforms.

We present a particular formulation of optimal transport for matrix-valued density functions. Our aim is to devise a geometry which is suitable for comparing power spectral densities of multivariable time series. More specifically, the value of a power spectral density at a given frequency, which in the matricial case encodes power as well as directionality, is thought of as a proxy for a "matrix-valued mass density." Optimal transport aims at establishing a natural metric in the space of such matrix-valued densities which takes into account differences between power across frequencies as well as misalignment of the corresponding principle axes. Thus, our transportation cost includes a cost of transference of power between frequencies together with a cost of rotating the principle directions of matrix densities. The two endpoint matrix-valued densities can be thought of as marginals of a joint matrix-valued density on a tensor product space. This joint density, very much as in the classical Monge-Kantorovich setting, can be thought to specify the transportation plan. Contrary to the classical setting, the optimal transport plan for matrices is no longer supported on a thin zero-measure set.

The influence of Gaussian diffusion on the magnetic resonance signal is determined by the apparent diffusion coefficient (ADC) and tensor (ADT) of the diffusing fluid as well as the gradient waveform applied to sensitize the signal to diffusion. Estimations of ADC and ADT from diffusion-weighted acquisitions necessitate computations of, respectively, the b-value and b-matrix associated with the employed pulse sequence. We establish the relationship between these quantities and the gradient waveform by expressing the problem as a path integral and explicitly evaluating it. Further, we show that these important quantities can be conveniently computed for any gradient waveform using a simple algorithm that requires a few lines of code. With this representation, our technique complements the multiple correlation function (MCF) method commonly used to compute the effects of restricted diffusion, and provides a consistent and convenient framework for studies that aim to infer the microstructural features of the specimen.

BACKGROUND: The 22q11.2 deletion syndrome (22q11.2DS) is regarded as an etiologically homogenous model for understanding neuroanatomic disruptions associated with a high risk for schizophrenia. This study utilized diffusion tensor imaging (DTI) to analyze white matter microstructure in individuals with 22q11.2DS. We focused on the cingulum bundle (CB), previously shown to be disrupted in patients with schizophrenia and associated with symptoms of psychosis. METHODS: White matter microstructure was assessed in the anterior, superior, and posterior CB using the tractography algorithm in DTIStudio. Neuropsychological function, presence of prodromal symptoms of psychosis, and medication history were assessed in all participants. RESULTS: Relative to controls, young adults with 22q11.2DS showed alterations in most DTI metrics of the CB. Alterations were associated with positive prodromal symptoms of psychosis. However, when individuals with 22q11.2DS were divided by usage of antipsychotics/mood stabilizers, the medicated and non-medicated groups differed significantly in axial diffusivity of the anterior CB and in fractional anisotropy of the superior CB. DTI metrics did not differ between the medicated group and the control group. CONCLUSIONS: Results suggest that the microstructure of the CB is altered in individuals with 22q11.2DS, and that those alterations may underlie positive prodromal symptoms of psychosis. Our findings further provide preliminary evidence that antipsychotic/mood stabilizer usage may have a reparative effect on white matter microstructure in prodromal 22q11.2DS, independent of the potential effects of psychosis. Future studies of white matter pathology in individuals with 22q11.2DS should test for potential effects of medication on white matter microstructure.

In multiatlas segmentation, one typically registers several atlases to the novel image, and their respective segmented label images are transformed and fused to form the final segmentation. In this work, we provide a new dynamical system perspective for multiatlas segmentation, inspired by the following fact: The transformation that aligns the current atlas to the novel image can be not only computed by direct registration but also inferred from the transformation that aligns the previous atlas to the image together with the transformation between the two atlases. This process is similar to the global positioning system on a vehicle, which gets position by inquiring from the satellite and by employing the previous location and velocity-neither answer in isolation being perfect. To solve this problem, a dynamical system scheme is crucial to combine the two pieces of information; for example, a Kalman filtering scheme is used. Accordingly, in this work, a Kalman multiatlas segmentation is proposed to stabilize the global/affine registration step. The contributions of this work are twofold. First, it provides a new dynamical systematic perspective for standard independent multiatlas registrations, and it is solved by Kalman filtering. Second, with very little extra computation, it can be combined with most existing multiatlas segmentation schemes for better registration/segmentation accuracy.

Multimodal neuroimaging is increasingly used in neuroscience research, as it overcomes the limitations of individual modalities. One of the most important applications of multimodal neuroimaging is the provision of vital diagnostic data for neuropsychiatric disorders. Multimodal neuroimaging computing enables the visualization and quantitative analysis of the alterations in brain structure and function, and has reshaped how neuroscience research is carried out. Research in this area is growing exponentially, and so it is an appropriate time to review the current and future development of this emerging area. Hence, in this paper, we review the recent advances in multimodal neuroimaging (MRI, PET) and electrophysiological (EEG, MEG) technologies, and their applications to the neuropsychiatric disorders. We also outline some future directions for multimodal neuroimaging where researchers will design more advanced methods and models for neuropsychiatric research.