21 research outputs found

    Running and Adult neurogenesis: Does septohippocampal sonic hedgehog play a role?

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    Ph.DDOCTOR OF PHILOSOPH

    Effect of voluntary running on adult hippocampal neurogenesis in cholinergic lesioned mice

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    <p>Abstract</p> <p>Background</p> <p>Cholinergic neuronal dysfunction of the basal forebrain is observed in patients with Alzheimer's disease and dementia, and has been linked to decreased neurogenesis in the hippocampus, a region involved in learning and memory. Running is a robust inducer of adult hippocampal neurogenesis. This study aims to address the effect of running on hippocampal neurogenesis in lesioned mice, where septohippocampal cholinergic neurones have been selectively eliminated in the medial septum and diagonal band of Broca of the basal forebrain by infusion of mu-p75-saporin immunotoxin.</p> <p>Results</p> <p>Running increased the number of newborn cells in the dentate gyrus of the hippocampus in cholinergic denervated mice compared to non-lesioned mice 24 hours after injection of bromodeoxyuridine (BrdU). Although similar levels of surviving cells were present in cholinergic depleted animals and their respective controls four weeks after injection of BrdU, the majority of progenitors that proliferate in response to the initial period of running were not able to survive beyond one month without cholinergic input. Despite this, the running-induced increase in the number of surviving neurones was not affected by cholinergic depletion.</p> <p>Conclusion</p> <p>The lesion paradigm used here models aspects of the cholinergic deficits associated with Alzheimer's Disease and aging. We showed that running still increased the number of newborn cells in the adult hippocampal dentate gyrus in this model of neurodegenerative disease.</p

    The genetic architecture of the human cerebral cortex

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    The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

    The genetic architecture of the human cerebral cortex

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    The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

    Equine-assisted learning in youths at-risk for school or social failure

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    This study examined whether a three-month equine-assisted learning program improved measures of character skills in two independent cohorts of Year 1 youths, in a specialized secondary school for youths with difficulties coping with mainstream curriculum. In 2013, 75 students underwent intervention while 82 students did not. In 2014, 58 students underwent intervention and 59 students were waitlisted in semester 1; cross-over was performed in semester 2. The students were rated a week before, mid-way and a week post-intervention. Results from multi-level modeling indicated that the intervention led to progressive improvements in character skills over the school semester, in the majority of the constructs measured in both the 2013 and 2014 cohorts. The rate of change in measures of character skills over the semester correlated with the grade point average of the students at semester-end. Implications and limitations of the findings are discussed

    Demographic, imaging and clinical information of participants in dataset 2.

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    <p>Descriptive statistics of the healthy participants (at the baseline scan) and the subgroup of ADHD participants at the follow-up scan. 10 out of 15 ADHD subjects scanned at baseline were scanned again after three months. Continuous variables are expressed as mean (standard deviation). N = number of subjects</p><p>Demographic, imaging and clinical information of participants in dataset 2.</p

    Demographic, imaging and clinical information of participants in dataset 1.

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    <p>Descriptive statistics of healthy participants and ADHD participants at the first scan. Continuous variables are expressed as mean (standard deviation). N: number of subjects. CBCL-DESR: Child Behavioral Checklist (Parent)—Deficit in Emotional Self-Regulation.</p><p>Demographic, imaging and clinical information of participants in dataset 1.</p

    Affective networks in healthy control and ADHD groups identified using independent component analysis (ICA).

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    <p>Resting-state data from all the subjects (healthy control children and children with ADHD) were aggregated into group-level ICA. The combined affective network across all the subjects was identified by visual spatial template matching with a previously identified affective/limbic network of 1000 subjects [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0139018#pone.0139018.ref041" target="_blank">41</a>]. Individual maps of the affective network were then constructed by back-projection. The group-level average affective network for healthy control children and ADHD children are presented here at p<0.05 FWE corrected. Color bar represents t-statistics.</p
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