MicroRNAs hsa-miR-99b, hsa-miR-330, hsa-miR-126 and hsa-miR-30c: Potential Diagnostic Biomarkers in Natural Killer (NK) Cells of Patients with Chronic Fatigue Syndrome (CFS)/ Myalgic Encephalomyelitis (ME)

Chronic Fatigue Syndrome (CFS/ME) is a complex multisystem disease of unknown aetiology which causes debilitating symptoms in up to 1% of the global population. Although a large cohort of genes have been shown to exhibit altered expression in CFS/ME patients, it is currently unknown whether microRNA (miRNA) molecules which regulate gene translation contribute to disease pathogenesis. We hypothesized that changes in microRNA expression in patient leukocytes contribute to CFS/ME pathology, and may therefore represent useful diagnostic biomarkers that can be detected in the peripheral blood of CFS/ME patients.miRNA expression in peripheral blood mononuclear cells (PBMC) from CFS/ME patients and healthy controls was analysed using the Ambion Bioarray V1. miRNA demonstrating differential expression were validated by qRT-PCR and then replicated in fractionated blood leukocyte subsets from an independent patient cohort. The CFS/ME associated miRNA identified by these experiments were then transfected into primary NK cells and gene expression analyses conducted to identify their gene targets.Microarray analysis identified differential expression of 34 miRNA, all of which were up-regulated. Four of the 34 miRNA had confirmed expression changes by qRT-PCR. Fractionating PBMC samples by cell type from an independent patient cohort identified changes in miRNA expression in NK-cells, B-cells and monocytes with the most significant abnormalities occurring in NK cells. Transfecting primary NK cells with hsa-miR-99b or hsa-miR-330-3p, resulted in gene expression changes consistent with NK cell activation but diminished cytotoxicity, suggesting that defective NK cell function contributes to CFS/ME pathology.This study demonstrates altered microRNA expression in the peripheral blood mononuclear cells of CFS/ME patients, which are potential diagnostic biomarkers. The greatest degree of miRNA deregulation was identified in NK cells with targets consistent with cellular activation and altered effector function

A Collection of Works in Neuroergonomics

Neuroergonomics is a nascent field of study that seeks to apply knowledge and tools from neuroscience to better optimize the tracking and regulation of human factors in the everyday and working environments. Neuroergonomics emphasizes the use of naturalistic and ecologically relevant experimental tasks to make important advancements from sterile experimental settings to useful real-world scenarios. This dissertation offers two naturalistic and ecologically relevant experimental tasks, as well as innovative neuroimaging and statistical analysis techniques, to contribute to, and demonstrate the feasibility of, the growing field of neuroergonomics. For the first experimental task, we designed a three-dimensional and first-person fMRI task during which human subjects maneuvered a simulated airplane in pursuit of a target airplane along constantly changing headings. The second experiment involves recording mobile EEG from human subjects performing a working memory adaptation of the everyday task of dart throwing. We find encouraging neuroimaging results from both experiments and relate them to important cognitive neuroscience theories on human action and working memory. In so doing, we demonstrate the feasibility of neuroergonomics and how knowledge and tools from neuroscience can indeed help us understand the brain at work and in everyday life

A Collection of Works in Neuroergonomics

Neuroergonomics is a nascent field of study that seeks to apply knowledge and tools from neuroscience to better optimize the tracking and regulation of human factors in the everyday and working environments. Neuroergonomics emphasizes the use of naturalistic and ecologically relevant experimental tasks to make important advancements from sterile experimental settings to useful real-world scenarios. This dissertation offers two naturalistic and ecologically relevant experimental tasks, as well as innovative neuroimaging and statistical analysis techniques, to contribute to, and demonstrate the feasibility of, the growing field of neuroergonomics. For the first experimental task, we designed a three-dimensional and first-person fMRI task during which human subjects maneuvered a simulated airplane in pursuit of a target airplane along constantly changing headings. The second experiment involves recording mobile EEG from human subjects performing a working memory adaptation of the everyday task of dart throwing. We find encouraging neuroimaging results from both experiments and relate them to important cognitive neuroscience theories on human action and working memory. In so doing, we demonstrate the feasibility of neuroergonomics and how knowledge and tools from neuroscience can indeed help us understand the brain at work and in everyday life

The Mu Rhythm

(Statement of Responsibility) by Robert Joseph Gougelet(Thesis) Thesis (B.A.) -- New College of Florida, 2010(Electronic Access) RESTRICTED TO NCF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE(Bibliography) Includes bibliographical references.(Source of Description) This bibliographic record is available under the Creative Commons CC0 public domain dedication. The New College of Florida, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.(Local) Faculty Sponsor: Bauer, Gordo

Resting State Functional Connectivity MRI among Spectral MEG Current Sources in Children on the Autism Spectrum.

Social and communicative impairments are among the core symptoms of autism spectrum disorders (ASD), and a great deal of evidence supports the notion that these impairments are associated with aberrant functioning and connectivity of various cortical networks. The present study explored the links between sources of MEG amplitude in various frequency bands and functional connectivity MRI in the resting state. The goal of combining these modalities was to use sources of neural oscillatory activity, measured with MEG, as functionally relevant seed regions for a more traditional pairwise fMRI connectivity analysis. We performed a seed-based connectivity analysis on resting state fMRI data, using seed regions derived from frequency-specific amplitude sources in resting state MEG data in the same nine subjects with ASD (10-17 years of age). We then compared fMRI connectivity among these MEG-source-derived regions between participants with autism and typically developing, age-matched controls. We used a source modeling technique designed for MEG data to detect significant amplitude sources in six frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12-30 Hz), low gamma (30-60 Hz), and high gamma (60-120 Hz). MEG-derived source maps for each participant were co-registered in standard MNI space, and group-level source maps were obtained for each frequency. For each frequency band, the 10 largest clusters resulting from these t-tests were used as regions of interest (ROIs) for the fMRI functional connectivity analysis. Pairwise BOLD signal correlations were obtained between each pair of these ROIs for each frequency band. Each pairwise correlation was compared between the ASD and TD groups using t-tests. We also constrained these pairwise correlations to known network structures, resulting in a follow-up set of correlation matrices specific to each network we considered. Frequency-specific MEG sources had distinct patterns of fMRI resting state functional connectivity in the ASD group, but perhaps the most significant was a finding of hypoconnectivity between many sources of low and high gamma activity. These novel findings suggest that in ASD there are differences in functionally defined networks as shown in previous fMRI studies, as well as between sets of regions defined by magnetoencephalographic neural oscillatory activity

Resting State Functional Connectivity MRI among Spectral MEG Current Sources in Children on the Autism Spectrum.

Social and communicative impairments are among the core symptoms of autism spectrum disorders (ASD), and a great deal of evidence supports the notion that these impairments are associated with aberrant functioning and connectivity of various cortical networks. The present study explored the links between sources of MEG amplitude in various frequency bands and functional connectivity MRI in the resting state. The goal of combining these modalities was to use sources of neural oscillatory activity, measured with MEG, as functionally relevant seed regions for a more traditional pairwise fMRI connectivity analysis. We performed a seed-based connectivity analysis on resting state fMRI data, using seed regions derived from frequency-specific amplitude sources in resting state MEG data in the same nine subjects with ASD (10-17 years of age). We then compared fMRI connectivity among these MEG-source-derived regions between participants with autism and typically developing, age-matched controls. We used a source modeling technique designed for MEG data to detect significant amplitude sources in six frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12-30 Hz), low gamma (30-60 Hz), and high gamma (60-120 Hz). MEG-derived source maps for each participant were co-registered in standard MNI space, and group-level source maps were obtained for each frequency. For each frequency band, the 10 largest clusters resulting from these t-tests were used as regions of interest (ROIs) for the fMRI functional connectivity analysis. Pairwise BOLD signal correlations were obtained between each pair of these ROIs for each frequency band. Each pairwise correlation was compared between the ASD and TD groups using t-tests. We also constrained these pairwise correlations to known network structures, resulting in a follow-up set of correlation matrices specific to each network we considered. Frequency-specific MEG sources had distinct patterns of fMRI resting state functional connectivity in the ASD group, but perhaps the most significant was a finding of hypoconnectivity between many sources of low and high gamma activity. These novel findings suggest that in ASD there are differences in functionally defined networks as shown in previous fMRI studies, as well as between sets of regions defined by magnetoencephalographic neural oscillatory activity