11 research outputs found

    Frontotemporal networks and behavioral symptoms in primary progressive aphasia

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    OBJECTIVE: To determine if behavioral symptoms in patients with primary progressive aphasia (PPA) were associated with degeneration of a ventral frontotemporal network. METHODS: We used diffusion tensor imaging tractography to quantify abnormalities of the uncinate fasciculus that connects the anterior temporal lobe and the ventrolateral frontal cortex. Two additional ventral tracts were studied: the inferior fronto-occipital fasciculus and the inferior longitudinal fasciculus. We also measured cortical thickness of anterior temporal and orbitofrontal regions interconnected by these tracts. Thirty-three patients with PPA and 26 healthy controls were recruited. RESULTS: In keeping with the PPA diagnosis, behavioral symptoms were distinctly less prominent than the language deficits. Although all 3 tracts had structural pathology as determined by tractography, significant correlations with scores on the Frontal Behavioral Inventory were found only for the uncinate fasciculus. Cortical atrophy of the orbitofrontal and anterior temporal lobe cortex was also correlated with these scores. CONCLUSIONS: Our findings indicate that damage to a frontotemporal network mediated by the uncinate fasciculus may underlie the emergence of behavioral symptoms in patients with PPA

    Neuroimaging modality fusion in Alzheimer's classification using convolutional neural networks.

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    Automated methods for Alzheimer's disease (AD) classification have the potential for great clinical benefits and may provide insight for combating the disease. Machine learning, and more specifically deep neural networks, have been shown to have great efficacy in this domain. These algorithms often use neurological imaging data such as MRI and FDG PET, but a comprehensive and balanced comparison of the MRI and amyloid PET modalities has not been performed. In order to accurately determine the relative strength of each imaging variant, this work performs a comparison study in the context of Alzheimer's dementia classification using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset with identical neural network architectures. Furthermore, this work analyzes the benefits of using both modalities in a fusion setting and discusses how these data types may be leveraged in future AD studies using deep learning

    A novel frontal pathway underlies verbal fluency in primary progressive aphasia

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    The frontal aslant tract is a direct pathway connecting Broca’s region with the anterior cingulate and pre-supplementary motor area. This tract is left lateralized in right-handed subjects, suggesting a possible role in language. However, there are no previous studies that have reported an involvement of this tract in language disorders. In this study we used diffusion tractography to define the anatomy of the frontal aslant tract in relation to verbal fluency and grammar impairment in primary progressive aphasia. Thirty-five patients with primary progressive aphasia and 29 control subjects were recruited. Tractography was used to obtain indirect indices of microstructural organization of the frontal aslant tract. In addition, tractography analysis of the uncinate fasciculus, a tract associated with semantic processing deficits, was performed. Damage to the frontal aslant tract correlated with performance in verbal fluency as assessed by the Cinderella story test. Conversely, damage to the uncinate fasciculus correlated with deficits in semantic processing as assessed by the Peabody Picture Vocabulary Test. Neither tract correlated with grammatical or repetition deficits. Significant group differences were found in the frontal aslant tract of patients with the non-fluent/agrammatic variant and in the uncinate fasciculus of patients with the semantic variant. These findings indicate that degeneration of the frontal aslant tract underlies verbal fluency deficits in primary progressive aphasia and further confirm the role of the uncinate fasciculus in semantic processing. The lack of correlation between damage to the frontal aslant tract and grammar deficits suggests that verbal fluency and grammar processing rely on distinct anatomical networks

    A review of software inspections

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    For two decades, software inspections have proven e ective for detecting defects in software. We have reviewed the di erent ways software inspections are done, created a taxonomy of inspection methods, and examined claims about the cost-e ectiveness of di erent methods. We detect a disturbing pattern in the evaluation of inspection methods. Although there is universal agreement on the e ectiveness of software inspection, their economics are uncertain. Our examination of several empirical studies leads us to conclude that the bene ts of inspections are often overstated and the costs (especially for large software developments) are understated. Furthermore, some of the most in uential studies establishing these costs and bene ts are 20 years old now, which leads us to question their relevance to today's software development processes. Extensive work is needed to determine exactly how, why, and when software inspections work, and whether some defect detection techniques might be more cost-e ective than others. In this article we ask some questions about measuring e ectiveness of software inspections and determining how much they really cost when their e ect on the rest of the development process is considered. Finding answers to these questions will enable us to improve the e ciency of software development.
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