Much of our knowledge of the mechanisms underlying plasticity in the visual cortex in response to visual impairment, vision restoration, and environmental interactions comes from animal studies. We evaluated human brain plasticity in a group of patients with Leber’s congenital amaurosis (LCA), who regained vision through gene therapy. Using non-invasive multimodal neuroimaging methods, we demonstrated that reversing blindness with gene therapy promoted long-term structural plasticity in the visual pathways emanating from the treated retina of LCA patients. The data revealed improvements and normalization along the visual fibers corresponding to the site of retinal injection of the gene therapy vector carrying the therapeutic gene in the treated eye compared to the visual pathway for the untreated eye of LCA patients. After gene therapy, the primary visual pathways (for example, geniculostriate fibers) in the treated retina were similar to those of sighted control subjects, whereas the primary visual pathways of the untreated retina continued to deteriorate. Our results suggest that visual experience, enhanced by gene therapy, may be responsible for the reorganization and maturation of synaptic connectivity in the visual pathways of the treated eye in LCA patients. The interactions between the eye and the brain enabled improved and sustained long-term visual function in patients with LCA after gene therapy.
Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous neurodegenerative disease that can result from either frontotemporal lobar degeneration (FTLD) or Alzheimer’s disease (AD) pathology. It is critical to establish statistically powerful biomarkers that can achieve substantial cost-savings and increase feasibility of clinical trials. We assessed three broad categories of neuroimaging methods to screen underlying FTLD and AD pathology in a clinical FTD series: global measures (e.g., ventricular volume), anatomical volumes of interest (VOIs) (e.g., hippocampus) using a standard atlas, and data-driven VOIs using Eigenanatomy. We evaluated clinical FTD patients (N=93) with cerebrospinal fluid, gray matter (GM) MRI, and diffusion tensor imaging (DTI) to assess whether they had underlying FTLD or AD pathology. Linear regression was performed to identify the optimal VOIs for each method in a training dataset and then we evaluated classification sensitivity and specificity in an independent test cohort. Power was evaluated by calculating minimum sample sizes (mSS) required in the test classification analyses for each model. The data-driven VOI analysis using a multimodal combination of GM MRI and DTI achieved the greatest classification accuracy (89% SENSITIVE; 89% SPECIFIC) and required a lower minimum sample size (N=26) relative to anatomical VOI and global measures. We conclude that a data-driven VOI approach employing Eigenanatomy provides more accurate classification, benefits from increased statistical power in unseen datasets, and therefore provides a robust method for screening underlying pathology in FTD patients for entry into clinical trials.
Responses to acute stressors are determined in part by stress history. For example, a history of chronic stress results in facilitated responses to a novel stressor and this facilitation is considered to be adaptive. We previously demonstrated that repeated exposure of rats to the resident-intruder model of social stress results in the emergence of two subpopulations that are characterized by different coping responses to stress. The submissive subpopulation failed to show facilitation to a novel stressor and developed a passive strategy in the Porsolt forced swim test. Because a passive stress coping response has been implicated in the propensity to develop certain psychiatric disorders, understanding the unique circuitry engaged by exposure to a novel stressor in these subpopulations would advance our understanding of the etiology of stress-related pathology. An ex vivo functional imaging technique, manganese-enhanced magnetic resonance imaging (MEMRI), was used to identify and distinguish brain regions that are differentially activated by an acute swim stress (15 min) in rats with a history of social stress compared to controls. Specifically, Mn2+ was administered intracerebroventricularly prior to swim stress and brains were later imaged ex vivo to reveal activated structures. When compared to controls, all rats with a history of social stress showed greater activation in specific striatal, hippocampal, hypothalamic, and midbrain regions. The submissive subpopulation of rats was further distinguished by significantly greater activation in amygdala, bed nucleus of the stria terminalis, and septum, suggesting that these regions may form a circuit mediating responses to novel stress in individuals that adopt passive coping strategies. The finding that different circuits are engaged by a novel stressor in the two subpopulations of rats exposed to social stress implicates a role for these circuits in determining individual strategies for responding to stressors. Finally, these data underscore the utility of ex vivo MEMRI to identify and distinguish circuits engaged in behavioral responses.
Linking structural neuroimaging data from multiple modalities to cognitive performance is an important challenge for cognitive neuroscience. In this study we examined the relationship between verbal fluency performance and neuroanatomy in 54 patients with frontotemporal degeneration (FTD) and 15 age-matched controls, all of whom had T1- and diffusion-weighted imaging. Our goal was to incorporate measures of both gray matter (voxel-based cortical thickness) and white matter (fractional anisotropy) into a single statistical model that relates to behavioral performance. We first used eigenanatomy to define data-driven regions of interest (DD-ROIs) for both gray matter and white matter. Eigenanatomy is a multivariate dimensionality reduction approach that identifies spatially smooth, unsigned principal components that explain the maximal amount of variance across subjects. We then used a statistical model selection procedure to see which of these DD-ROIs best modeled performance on verbal fluency tasks hypothesized to rely on distinct components of a large-scale neural network that support language: category fluency requires a semantic-guided search and is hypothesized to rely primarily on temporal cortices that support lexical-semantic representations; letter-guided fluency requires a strategic mental search and is hypothesized to require executive resources to support a more demanding search process, which depends on prefrontal cortex in addition to temporal network components that support lexical representations. We observed that both types of verbal fluency performance are best described by a network that includes a combination of gray matter and white matter. For category fluency, the identified regions included bilateral temporal cortex and a white matter region including left inferior longitudinal fasciculus and frontal–occipital fasciculus. For letter fluency, a left temporal lobe region was also selected, and also regions of frontal cortex. These results are consistent with our hypothesized neuroanatomical models of language processing and its breakdown in FTD. We conclude that clustering the data with eigenanatomy before performing linear regression is a promising tool for multimodal data analysis.
Language; Verbal fluency; Multimodal; FTD
Genome-wide association studies have identified SNPs that are sensitive for tau or TDP-43 pathology in frontotemporal lobar degeneration (FTLD). Neuroimaging analyses have revealed distinct distributions of disease in FTLD patients with genetic mutations. However, genetic influences on neuroanatomical structure in sporadic FTLD have not been assessed. In this report we use novel multivariate tools, eigenanatomy and sparse canonical correlation analysis (SCCAN), to identify associations between SNPs and neuroanatomical structure in sporadic FTLD. MRI analyses revealed that rs8070723 (MAPT) was associated with grey matter variance in the temporal cortex. DTI analyses revealed that rs1768208 (MOBP), rs646776 (near SORT1) and rs5848 (PGRN) were associated with white matter variance in the midbrain and superior longitudinal fasciculus. In an independent autopsy series we observed that rs8070723 and rs1768208 conferred significant risk of tau pathology relative to TDP-43, and rs646776 conferred increased risk of TDP-43 pathology relative to tau. Identified brain regions and SNPs may help provide an in vivo screen for underlying pathology in FTLD and contribute to our understanding of sporadic FTLD.
Frontotemporal lobar degeneration; Neuroimaging; Genetics; Biomarkers
Concepts bind together the features commonly associated with objects and events to form networks in long-term semantic memory. These conceptual networks are the basis of human knowledge and underlie perception, imagination, and the ability to communicate about experiences and the contents of the environment. Although it is often assumed that this distributed semantic information is integrated in higher-level heteromodal association cortices, open questions remain about the role and anatomic basis of heteromodal representations in semantic memory. Here we used combined neuroimaging evidence from functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to characterize the cortical networks underlying concept representation. Using a lexical decision task, we examined the processing of concepts in four semantic categories that varied on their sensory-motor feature associations (sight, sound, manipulation, and abstract). We found that the angular gyrus was activated across all categories regardless of their modality-specific feature associations, consistent with a heteromodal account for the angular gyrus. Exploratory analyses suggested that categories with weighted sensory-motor features additionally recruited modality-specific association cortices. Furthermore, DTI tractography identified white matter tracts connecting these regions of modality-specific functional activation with the angular gyrus. These findings are consistent with a distributed semantic network that includes a heteromodal, integrative component in the angular gyrus in combination with sensory-motor feature representations in modality-specific association cortices.
DTI; fMRI; language; semantic memory; sensory-motor; heteromodal
We hypothesize that semantic memory for object concepts involves both representations of visual feature knowledge in modality-specific association cortex and heteromodal regions that are important for integrating and organizing this semantic knowledge so it can be used in a flexible, contextually appropriate manner. We examined this hypothesis in an fMRI study of mild Alzheimer’s disease (AD). Participants were presented with pairs of printed words and asked whether the words match on a given visual-perceptual feature (e.g. guitar, violin: SHAPE). Stimuli probed natural kinds and manufactured objects, and judgments involved shape or color. We found activation of bilateral ventral temporal cortex and left dorsolateral prefrontal cortex during semantic judgments, with AD patients showing less activation of these regions than healthy seniors. Moreover, AD patients showed less ventral temporal activation relative to healthy seniors for manufactured objects but not natural kinds. We also used diffusion-weighted MRI of white matter to examine fractional anisotropy (FA). Patients with AD showed significantly reduced FA in the superior longitudinal fasciculus and inferior frontal-occipital fasciculus that carry projections linking temporal and frontal regions of this semantic network. Our results are consistent with the hypothesis that semantic memory is supported in part by a large-scale neural network involving modality-specific association cortex, heteromodal association cortex and projections between these regions. The semantic deficit in AD thus arises from gray matter disease that affects the representation of feature knowledge and processing its content, as well as white matter disease that interrupts the integrated functioning of this large-scale network.
A disabling impairment of higher-order language function can be seen in patients with Lewy body spectrum disorders such as Parkinson's disease (PD), Parkinson's disease dementia (PDD), and dementia with Lewy bodies (DLB). We focus on script comprehension in patients with Lewy body spectrum disorders. While scripts unfold sequentially, constituent events are thought to contain an internal organization. Executive dysfunction in patients with Lewy body spectrum disorders may interfere with comprehension of this internal structure. We examined 42 patients (30 non-demented PD and 12 mildly demented PDD/DLB patients) and 12 healthy seniors. We presented 22 scripts (e.g., “going fishing”), each consisting of six events. Pilot data from young controls provided the basis for organizing associated events into clusters and arranging them hierarchically into scripts. We measured accuracy and latency to judge the order of adjacent events in the same cluster versus adjacent events in different clusters. PDD/DLB patients were less accurate in their ordering judgments than PD patients and controls. Healthy seniors and PD patients were significantly faster to judge correctly the order of highly associated within-cluster event pairs relative to less closely associated different-cluster event pairs, while PDD/DLB patients did not consistently distinguish between these event-pair types. This relative insensitivity to the clustered-hierarchical organization of events was related to executive impairment and to frontal atrophy as measured by volumetric MRI. These findings extend prior work on script processing to patients with Lewy body spectrum disorders and highlight the potential impact of frontal/executive dysfunction on the daily lives of affected patients.
Parkinson's disease; Parkinson's disease dementia; Dementia with Lewy bodies; Frontal cortex; Executive function; Scripts; Organization; Discourse; Volumetric MRI
Patients with Alzheimer’s disease have category-specific semantic memory difficulty for natural relative to manufactured objects. We assessed the basis for this deficit by asking healthy adults and patients to judge whether pairs of words share a feature (e.g. “banana:lemon – COLOR”). In an fMRI study, healthy adults showed gray matter (GM) activation of temporal-occipital cortex (TOC) where visual-perceptual features may be represented, and prefrontal cortex (PFC) which may contribute to feature selection. Tractography revealed dorsal and ventral stream white matter (WM) projections between PFC and TOC. Patients had greater difficulty with natural than manufactured objects. This was associated with greater overlap between diseased GM areas correlated with natural kinds in patients and fMRI activation in healthy adults for natural than manufactured artifacts, and the dorsal WM projection between PFC and TOC in patients correlated only with judgments of natural kinds. Patients thus remained dependent on the same neural network as controls during judgments of natural kinds, despite disease in these areas. For manufactured objects, patients’ judgments showed limited correlations with PFC and TOC GM areas activated by controls, and did not correlate with the PFC-TOC dorsal WM tract. Regions outside of the PFC–TOC network thus may help support patients’ judgments of manufactured objects. We conclude that a large-scale neural network for semantic memory implicates both feature knowledge representations in modality-specific association cortex and heteromodal regions important for accessing this knowledge, and that patients’ relative deficit for natural kinds is due in part to their dependence on this network despite disease in these areas.
semantic; fMRI; DTI; Alzheimer’s; temporal; prefrontal
Significant heterogeneity in clinical features of frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS) cases with the pathogenic C9orf72 expansion (C9P) have been described. To clarify this issue, we compared a large C9P cohort with carefully matched non-expansion (C9N) cases with a known or highly-suspected underlying TDP-43 proteinopathy.
A retrospective-cohort study using available cross-sectional and longitudinal clinical and neuropsychological data, MRI voxel-based morphometry (VBM) and neuropathological assessment from 64 C9P cases (ALS=31, FTLD=33) and 79 C9N cases (ALS=36, FTLD=43).
C9P cases had an earlier age of onset (p=0.047), and in the subset of deceased patients, an earlier age of death (p=0.014) than C9N. C9P had more rapid progression than C9N: C9P ALS cases had a shortened survival (2.6±0.3 years) compared to C9N ALS (3.8±0.4 years; log-rankλ2=4.183,p=0.041), and C9P FTLD showed a significantly greater annualized rate of decline in letter fluency (4.5±1.3words/year) than C9N FTLD (1.4±0.8words/year, p=0.023). VBM revealed greater atrophy in the right fronto-insular, thalamus, cerebellum and bilateral parietal regions for C9P FTLD relative to C9N FTLD, and regression analysis related verbal fluency scores to atrophy in frontal and parietal regions. Neuropathologic analysis found greater neuronal loss in the mid-frontal cortex in C9P FTLD, and mid-frontal cortex TDP-43 inclusion severity correlated with poor letter fluency performance.
C9P cases may have a shorter survival in ALS and more rapid rate of cognitive decline related to frontal and parietal disease in FTLD. C9orf72 genotyping may provide useful prognostic and diagnostic clinical information for ALS and FTLD patients.
Frontotemporal dementia; Amyotrophic lateral sclerosis; C9orf72; neuropsychological tests; neuroimaging
An abnormally high incidence of lung disease has been observed in the residents of Libby, Montana, which has been attributed to occupational and environmental exposure to fibrous amphiboles originating from a nearby contaminated vermiculite mine. The composition of Libby amphibole (LA) is complex and minimal toxicity data are available. In this study, we conduct a comparative particle toxicity analysis of LA compared with standard reference asbestiform amphibole samples.
Primary human airway epithelial cells (HAEC) were exposed to two different LA samples as well as standard amphibole reference samples. Analysis of the samples included a complete particle size distribution analysis, calculation of surface area by electron microscopy and by gas adsorption and quantification of surface-conjugated iron and hydroxyl radical production by the fibers. Interleukin-8 mRNA levels were quantified by qRT-PCR to measure relative pro-inflammatory response induced in HAEC in response to amphibole fiber exposure. The relative contribution of key physicochemical determinants on the observed pro-inflammatory response were also evaluated.
The RTI amosite reference sample contained the longest fibers and demonstrated the greatest potency at increasing IL-8 transcript levels when evaluated on an equal mass basis. The two LA samples and the UICC amosite reference sample consisted of similar particle numbers per milligram as well as similar particle size distributions and induced comparable levels of IL-8 mRNA. A strong correlation was observed between the elongated particle (aspect ratio ≥3:1) dose metrics of length and external surface area. Expression of the IL-8 data with respect to either of these metrics eliminated the differential response between the RTI amosite sample and the other samples that was observed when HAEC were exposed on an equal mass basis.
On an equal mass basis, LA is as potent as the UICC amosite reference sample at inducing a pro-inflammatory response in HAEC but is less potent than the RTI amosite sample. The results of this study show that the particle length and particle surface area are highly correlated metrics that contribute significantly to the toxicological potential of these amphibole samples with respect to the inflammogenic response induced in airway epithelial cells.
Libby amphibole; Airway epithelium; Relative toxicity; Inflammation; Interleukin-8; Dose metrics
Recent interest in human brain connectivity has led to the application of graph theoretical analysis to human brain structural networks, in particular white matter connectivity inferred from diffusion imaging and fiber tractography. While these methods have been used to study a variety of patient populations, there has been less examination of the reproducibility of these methods. A number of tractography algorithms exist and many of these are known to be sensitive to user-selected parameters. The methods used to derive a connectivity matrix from fiber tractography output may also influence the resulting graph metrics. Here we examine how these algorithm and parameter choices influence the reproducibility of proposed graph metrics on a publicly available test-retest dataset consisting of 21 healthy adults. The dice coefficient is used to examine topological similarity of constant density subgraphs both within and between subjects. Seven graph metrics are examined here: mean clustering coefficient, characteristic path length, largest connected component size, assortativity, global efficiency, local efficiency, and rich club coefficient. The reproducibility of these network summary measures is examined using the intraclass correlation coefficient (ICC). Graph curves are created by treating the graph metrics as functions of a parameter such as graph density. Functional data analysis techniques are used to examine differences in graph measures that result from the choice of fiber tracking algorithm. The graph metrics consistently showed good levels of reproducibility as measured with ICC, with the exception of some instability at low graph density levels. The global and local efficiency measures were the most robust to the choice of fiber tracking algorithm.
structure; tractography; connectivity; brain; network; reproducibility; graph
With costs exceeding $5.8 billion per year, violence against women has significant ramifications for victims, their families, the health care systems that treat them, and the employers who depend on their labor. Prior research has found that alcohol abuse contributes to violence against both men and women, and that stringent alcohol control policies can reduce alcohol consumption and in turn some forms of violence. In this paper, we estimate the direct relationship between an important alcohol control measure, excise taxes, and the most extreme form of violence, homicide. We use female homicide rates as our measure of severe violence, as this measure is consistently and accurately reported across multiple years. Our results provide evidence that increased alcohol taxes reduce alcohol consumption and that reductions in alcohol consumption can reduce femicide. Unfortunately, a direct test of the relationship does not have the power to determine whether alcohol taxes effectively reduce female homicide rates. We conclude that while alcohol taxes have been shown to effectively reduce other forms of violence against women, policy makers may need alternative policy levers to reduce the most severe form of violence against women.
female homicide; violence; domestic violence; intimate partner violence; alcohol use; substance use; policy; taxes; consumption
Thousands of Americans are killed by gunfire each year, and hundreds of thousands more are injured or threatened with guns in robberies and assaults. The burden of gun violence in urban areas is particularly high. Critics suggest that the results of firearm trace data and gun trafficking investigation studies cannot be used to understand the illegal supply of guns to criminals and, therefore, that regulatory and enforcement efforts designed to disrupt illegal firearms markets are futile in addressing criminal access to firearms. In this paper, we present new data to address three key arguments used by skeptics to undermine research on illegal gun market dynamics. We find that criminals rely upon a diverse set of illegal diversion pathways to acquire guns, gun traffickers usually divert small numbers of guns, newer guns are diverted through close-to-retail diversions from legal firearms commerce, and that a diverse set of gun trafficking indicators are needed to identify and shut down gun trafficking pathways.
Gun violence; Gun policy; Gun trafficking; Injury prevention
Frontotemporal lobar degeneration (FTLD) is most commonly associated with TAR-DNA binding protein (TDP-43) or tau pathology at autopsy, but there are no in vivo biomarkers reliably discriminating between sporadic cases. As disease-modifying treatments emerge, it is critical to accurately identify underlying pathology in living patients so that they can be entered into appropriate etiology-directed clinical trials. Patients with tau inclusions (FTLD-TAU) appear to have relatively greater white matter (WM) disease at autopsy than those patients with TDP-43 (FTLD-TDP). In this paper, we investigate the ability of white matter (WM) imaging to help discriminate between FTLD-TAU and FTLD-TDP during life using diffusion tensor imaging (DTI).
Patients with autopsy-confirmed disease or a genetic mutation consistent with FTLD-TDP or FTLD-TAU underwent multimodal T1 volumetric MRI and diffusion weighted imaging scans. We quantified cortical thickness in GM and fractional anisotropy (FA) in WM. We performed Eigenanatomy, a statistically robust dimensionality reduction algorithm, and used leave-one-out cross-validation to predict underlying pathology. Neuropathological assessment of GM and WM disease burden was performed in the autopsy-cases to confirm our findings of an ante-mortem GM and WM dissociation in the neuroimaging cohort.
ROC curve analyses evaluated classification accuracy in individual patients and revealed 96% sensitivity and 100% specificity for WM analyses. FTLD-TAU had significantly more WM degeneration and inclusion severity at autopsy relative to FTLD-TDP.
These neuroimaging and neuropathological investigations provide converging evidence for greater WM burden associated with FTLD-TAU, and emphasize the role of WM neuroimaging for in vivo discrimination between FTLD-TAU and FTLD-TDP.
We contribute a novel and interpretable dimensionality reduction strategy, eigenanatomy, that is tuned for neuroimaging data. The method approximates the eigendecomposition of an image set with basis functions (the eigenanatomy vectors) that are sparse, unsigned and are anatomically clustered. We employ the eigenanatomy vectors as anatomical predictors to improve detection power in morphometry. Standard voxel-based morphometry (VBM) analyzes imaging data voxel-by-voxel—and follows this with cluster-based or voxel-wise multiple comparisons correction methods to determine significance. Eigenanatomy reverses the standard order of operations by first clustering the voxel data and then using standard linear regression in this reduced dimensionality space. As with traditional region-of-interest (ROI) analysis, this strategy can greatly improve detection power. Our results show that eigenanatomy provides a principled objective function that leads to localized, data-driven regions of interest. These regions improve our ability to quantify biologically plausible rates of cortical change in two distinct forms of neurodegeneration. We detail the algorithm and show experimental evidence of its efficacy.
Prior work has related sentence processing to executive deficits in non-demented patients with Parkinson’s disease (PD). We extended this investigation to patients with dementia with Lewy bodies (DLB) and PD dementia (PDD) by examining grammatical and working memory components of sentence processing in the full range of patients with Lewy body spectrum disorder (LBSD). Thirty-three patients with LBSD were given a two-alternative, forced-choice sentence-picture matching task. Sentence type, working memory, and grammatical structure were systematically manipulated in the sentences. We found that patients with PDD and DLB were significantly impaired relative to non-demented PD patients and healthy controls. The deficit in PDD/DLB was most pronounced for sentences lengthened by the strategic placement of an additional prepositional phrase and for sentences with an additional proposition due to a center-embedded clause. However, there was no effect for subject-relative versus object-relative grammatical structure. An MRI voxel-based morphometry analysis in a subset of patients showed significant gray matter thinning in the frontal lobe bilaterally, and this extended to temporal, parietal and occipital regions. A regression analysis related sentence processing difficulty in LBSD to frontal neocortex, including inferiorprefrontal, premotor, and dorsolateral prefrontal regions, as well as right superior temporal cortex. These findings are consistent with the hypothesis that patients with PDD and DLB have difficulty processing sentences with increased working memory demands and that this deficit is related in part to their frontal disease.
Lewy body; Parkinson’s; sentence processing; working memory; MRI; prefrontal
Few studies have examined connected speech in demented and non-demented patients with Parkinson’s disease (PD). We assessed the speech production of 35 patients with Lewy body spectrum disorder (LBSD), including non-demented PD patients, patients with PD dementia (PDD), and patients with dementia with Lewy bodies (DLB), in a semi-structured narrative speech sample in order to characterize impairments of speech fluency and to determine the factors contributing to reduced speech fluency in these patients. Both demented and non-demented PD patients exhibited reduced speech fluency, characterized by reduced overall speech rate and long pauses between sentences. Reduced speech rate in LBSD correlated with measures of between-utterance pauses, executive functioning, and grammatical comprehension. Regression analyses related non-fluent speech, grammatical difficulty, and executive difficulty to atrophy in frontal brain regions. These findings indicate that multiple factors contribute to slowed speech in LBSD, and this is mediated in part by disease in frontal brain regions.
Parkinson’s disease; speech; language; fluency; dementia with Lewy bodies
While grammatical aspects of language are preserved, executive deficits are prominent in Lewy body spectrum disorder (LBSD), including Parkinson’s disease (PD), Parkinson’s dementia (PDD) and dementia with Lewy bodies (DLB). We examined executive control during sentence processing in LBSD by assessing temporary structural ambiguities. Using an on-line word detection procedure, patients heard sentences with a syntactic structure that has high-compatibility or low-compatibility with the main verb’s statistically preferred syntactic structure, and half of the sentences were lengthened strategically between the onset of the ambiguity and its resolution. We found selectively slowed processing of lengthened ambiguous sentences in the PDD/DLB subgroup. This correlated with impairments on measures of executive control. Regression analyses related the working memory deficit during ambiguous sentence processing to significant cortical thinning in frontal and parietal regions. These findings emphasize the role of prefrontal disease in the executive limitations that interfere with processing ambiguous sentences in LBSD.
Parkinson’s; Lewy body; syntactic ambiguity; working memory; frontal
Narrative discourse is an essential component of day-to-day communication, but little is known about narrative in Lewy Body spectrum disorder (LBSD), including Parkinson's disease (PD), Parkinson's disease with dementia (PDD), and dementia with Lewy bodies (DLB). We performed a detailed analysis of a semi-structured speech sample in 32 non-aphasic patients with LBSD, and we related their narrative impairments to gray matter (GM) atrophy using voxel-based morphometry. We found that patients with PDD and DLB have significant difficulty organizing their narrative speech. This was correlated with deficits on measures of executive functioning and speech fluency. Regression analyses associated this deficit with reduced cortical volume in inferior frontal and anterior cingulate regions. These findings are consistent with a model of narrative discourse that includes executive as well as language components and with an impairment of the organizational component of narrative discourse in patients with PDD and DLB.
Parkinson's disease; discourse; speech; language; Dementia with Lewy bodies
Converging lines of evidence suggest an adverse effect of heavy cannabis use on adolescent brain development, particularly on the hippocampus. In this preliminary study, we compared hippocampal morphology in 14 “treatment-seeking” adolescents (aged 18-20) with a history of prior heavy-cannabis use (5.8 joints/day) after an average of 6.7 months of drug abstinence, and 14 demographically matched normal controls. Participants underwent a high-resolution 3D MRI as well as cognitive testing including the California Verbal Learning Test (CVLT). Heavy-cannabis users showed significantly smaller volumes of the right (p< .04) and left (p< .02) hippocampus, but no significant differences in the amygdala region compared to controls. In controls, larger hippocampus volumes were observed to be significantly correlated with higher CVLT verbal learning and memory scores, but these relationships were not observed in cannabis users. In cannabis users, a smaller right hippocampus volume was correlated with a higher amount of cannabis use (r= - .57, p< .03). These data support a hypothesis that heavy-cannabis use may have an adverse effect on hippocampus development. These findings, after an average 6.7 month of supervised abstinence, lend support to a theory that cannabis use may impart long-term structural and functional damage. Alternatively, the observed hippocampal volumetric abnormalities may represent a risk factor for cannabis dependence. These data have potential significance for understanding the observed relationship between early cannabis exposure during adolescence and subsequent development of adult psychopathology reported in the literature for schizophrenia and related psychotic disorders.
hippocampus; cannabis; adolescence; magnetic resonance imaging; CVLT; learning and memory
We introduce Atropos, an ITK-based multivariate n-class open source segmentation algorithm distributed with ANTs (http://www.picsl.upenn.edu/ANTs). The Bayesian formulation of the segmentation problem is solved using the Expectation Maximization (EM) algorithm with the modeling of the class intensities based on either parametric or non-parametric finite mixtures. Atropos is capable of incorporating spatial prior probability maps (sparse), prior label maps and/or Markov Random Field (MRF) modeling. Atropos has also been efficiently implemented to handle large quantities of possible labelings (in the experimental section, we use up to 69 classes) with a minimal memory footprint. This work describes the technical and implementation aspects of Atropos and evaluates its performance on two different ground-truth datasets. First, we use the BrainWeb dataset from Montreal Neurological Institute to evaluate three-tissue segmentation performance via (1) K-means segmentation without use of template data; (2) MRF segmentation with initialization by prior probability maps derived from a group template; (3) Prior-based segmentation with use of spatial prior probability maps derived from a group template. We also evaluate Atropos performance by using spatial priors to drive a 69-class EM segmentation problem derived from the Hammers atlas from University College London. These evaluation studies, combined with illustrative examples that exercise Atropos options, demonstrate both performance and wide applicability of this new platform-independent open source segmentation tool.
Image segmentation; Open source; Multivariate; Cortical parcellation; Evaluation; BrainWeb; ITK
Much of our understanding regarding the mechanisms for induction of disease following inhalation of respirable elongated mineral particles (REMP) is based on studies involving the biological effects of asbestos fibers. The factors governing the disease potential of an exposure include duration and frequency of exposures; tissue-specific dose over time; impacts on dose persistence from in vivo REMP dissolution, comminution, and clearance; individual susceptibility; and the mineral type and surface characteristics. The mechanisms associated with asbestos particle toxicity involve two facets for each particle's contribution: (1) the physical features of the inhaled REMP, which include width, length, aspect ratio, and effective surface area available for cell contact; and (2) the surface chemical composition and reactivity of the individual fiber/elongated particle. Studies in cell-free systems and with cultured cells suggest an important way in which REMP from asbestos damage cellular molecules or influence cellular processes. This may involve an unfortunate combination of the ability of REMP to chemically generate potentially damaging reactive oxygen species, through surface iron, and the interaction of the unique surfaces with cell membranes to trigger membrane receptor activation. Together these events appear to lead to a cascade of cellular events, including the production of damaging reactive nitrogen species, which may contribute to the disease process. Thus, there is a need to be more cognizant of the potential impact that the total surface area of REMP contributes to the generation of events resulting in pathological changes in biological systems. The information presented has applicability to inhaled dusts, in general, and specifically to respirable elongated mineral particles.
We use a new, unsupervised multivariate imaging and analysis strategy to identify related patterns of reduced white matter integrity, measured with the fractional anisotropy (FA) derived from diffusion tensor imaging (DTI), and decreases in cortical thickness, measured by high resolution T1-weighted imaging, in Alzheimer's disease (AD) and frontotemporal dementia (FTD). This process is based on a novel computational model derived from sparse canonical correlation analysis (SCCA) that allows us to automatically identify mutually predictive, distributed neuroanatomical regions from different imaging modalities. We apply the SCCA model to a dataset that includes 23 control subjects that are demographically-matched to 49 subjects with autopsy or CSF-biomarker-diagnosed AD (n=24) and FTD (n=25) with both DTI and T1-weighted structural imaging. SCCA shows that the FTD-related frontal and temporal degeneration pattern is correlated across modalities with permutation corrected p < 0.0005. In AD, we find significant association between cortical thinning and reduction in white matter integrity within a distributed parietal and temporal network (p < 0.0005). Furthermore, we show that—within SCCA identified regions—significant differences exist between FTD and AD cortical-connective degeneration patterns. We validate these distinct, multimodal imaging patterns by showing unique relationships with cognitive measures in AD and FTD. We conclude that SCCA is a potentially valuable approach in image analysis that can be applied productively to distinguishing between neurodegenerative conditions.
dementia; multivariate; correlation; diffusion tensor; cortical thickness; AD; FTD; canonical correlation