34 research outputs found

    Functional Neural Correlates of Attentional Deficits in Amnestic Mild Cognitive Impairment

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    Although amnestic mild cognitive impairment (aMCI; often considered a prodromal phase of Alzheimer’s disease, AD) is most recognized by its implications for decline in memory function, research suggests that deficits in attention are present early in aMCI and may be predictive of progression to AD. The present study used functional magnetic resonance imaging to examine differences in the brain during the attention network test between 8 individuals with aMCI and 8 neurologically healthy, demographically matched controls. While there were no significant behavioral differences between groups for the alerting and orienting functions, patients with aMCI showed more activity in neural regions typically associated with the networks subserving these functions (e.g., temporoparietal junction and posterior parietal regions, respectively). More importantly, there were both behavioral (i.e., greater conflict effect) and corresponding neural deficits in executive control (e.g., less activation in the prefrontal and anterior cingulate cortices). Although based on a small number of patients, our findings suggest that deficits of attention, especially the executive control of attention, may significantly contribute to the behavioral and cognitive deficits of aMCI

    Cognitive and mood functioning in borderline and schizotypal personality disorders

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    Research suggests many shared clinical features across individuals with Schizotypal Personality Disorder (SPD) and Borderline Personality Disorder (BPD), including problems with attention/ executive functioning and mood. Therefore, aspects of these areas of functioning were compared in SPD and BPD to better characterize their respective difficulties. BPD, SPD, and healthy control (HC) participants were administered measures of cognitive and mood functioning. Compared with healthy controls, SPD patients performed significantly worse on aspects of the Delayed-Matching- to-Sample task, a measure of short-term visual memory abilities; however, the individuals with BPD did not differ from healthy controls. Neither of the patient groups differed from HC’s on measures of processing speed or planning. With regard to mood functioning, the BPD group exhibited significantly higher levels of affective disturbance (e.g., sadness, fear, anger) compared with the SPD patients and HCs. Overall, findings suggest different patterns of fronto-subcortical weakness in each patient group. While SPD patients exhibited relative weakness with short-term memory, BPD patient performance on such measures did not reveal relative weakness compared with HCs but did implicate problems with mood

    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

    Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

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    Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease

    Quantitative 18F-AV1451 Brain Tau PET Imaging in Cognitively Normal Older Adults, Mild Cognitive Impairment, and Alzheimer's Disease Patients

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    Recent developments of tau Positron Emission Tomography (PET) allows assessment of regional neurofibrillary tangles (NFTs) deposition in human brain. Among the tau PET molecular probes, 18F-AV1451 is characterized by high selectivity for pathologic tau aggregates over amyloid plaques, limited non-specific binding in white and gray matter, and confined off-target binding. The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by 18F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and 18F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on 18F-AV1451 brain uptake.Methods: The study included total 115 participants (CN = 49, MCI = 58, and AD = 8) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed 18F-AV1451 PET images, structural MRIs, and demographic and clinical assessments were downloaded from the ADNI database. A reblurred Van Cittertiteration method was used for voxelwise partial volume correction (PVC) on PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. The parametric images of 18F-AV1451 SUVR relative to cerebellum were calculated. The ROI SUVR measurements from PVC and non-PVC SUVR images were compared. The correlation between ROI 18F-AV1451 SUVR and the measurements of MMSE, CSF total tau (t-tau), and phosphorylated tau (p-tau) were also assessed.Results:18F-AV1451 prominently specific binding was found in the amygdala, entorhinal cortex, parahippocampus, fusiform, posterior cingulate, temporal, parietal, and frontal brain regions. Most regional SUVRs showed significantly higher uptake of 18F-AV1451 in AD than MCI and CN participants. SUVRs of small regions like amygdala, entorhinal cortex and parahippocampus were statistically improved by PVC in all groups (p < 0.01). Although there was an increasing tendency of 18F-AV-1451 SUVRs in MCI group compared with CN group, no significant difference of 18F-AV1451 deposition was found between CN and MCI brains with or without PVC (p > 0.05). Declined MMSE score was observed with increasing 18F-AV1451 binding in amygdala, entorhinal cortex, parahippocampus, and fusiform. CSF p-tau was positively correlated with 18F-AV1451 deposition. PVC improved the results of 18F-AV-1451 tau deposition and correlation studies in small brain regions.Conclusion: The typical deposition of 18F-AV1451 tau PET imaging in AD brain was found in amygdala, entorhinal cortex, fusiform and parahippocampus, and these regions were strongly associated with cognitive impairment and CSF biomarkers. Although more deposition was observed in MCI group, the 18F-AV-1451 PET imaging could not differentiate the MCI patients from CN population. More tau deposition related to decreased MMSE score and increased level of CSF p-tau, especially in ROIs of amygdala, entorhinal cortex and parahippocampus. PVC did improve the results of tau deposition and correlation studies in small brain regions and suggest to be routinely used in 18F-AV1451 tau PET quantification

    Blast Exposure, White Matter Integrity, and Cognitive Function in Iraq and Afghanistan Combat Veterans

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    The long-term effects of blast exposure are a major health concern for combat veterans returning from the recent conflicts in Iraq and Afghanistan. We used an optimized diffusion tensor imaging tractography algorithm to assess white matter (WM) fractional anisotropy (FA) in blast-exposed Iraq and Afghanistan veterans (n = 40) scanned on average 3.7 years after deployment/trauma exposure. Veterans diagnosed with a blast-related mild traumatic brain injury (mTBI) were compared to combat veterans with blast exposure but no TBI diagnosis. Blast exposure was associated with decreased FA in several WM tracts. However, total blast exposure did not correlate well with neuropsychological testing performance and there were no differences in FA based on mTBI diagnosis. Yet, veterans with mTBI performed worse on every neurocognitive test administered. Multiple linear regression across all blast-exposed veterans using a six-factor prediction model indicated that the amount of blast exposure accounted for 11–15% of the variability in composite FA scores such that as blast exposure increased, FA decreased. Education accounted for 10% of the variability in composite FA scores and 25–32% of FA variability in the right cingulum, such that as level of education increased, FA increased. Total blast exposure, age, and education were significant predictors of FA in the left cingulum. We did not find any effect of post-traumatic stress disorder on cognition or composite FA. In summary, our findings suggest that greater total blast exposure is a contributing factor to poor WM integrity. While FA was not associated with neurocognitive performance, we hypothesize that FA changes in the cingulum in veterans with multiple combat exposures and no head trauma prior to deployment may represent a marker of vulnerability for future deficits. Future work needs to examine this longitudinally
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