84 research outputs found

    Logopenic and nonfluent variants of primary progressive aphasia are differentiated by acoustic measures of speech production

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    Differentiation of logopenic (lvPPA) and nonfluent/agrammatic (nfvPPA) variants of Primary Progressive Aphasia is important yet remains challenging since it hinges on expert based evaluation of speech and language production. In this study acoustic measures of speech in conjunction with voxel-based morphometry were used to determine the success of the measures as an adjunct to diagnosis and to explore the neural basis of apraxia of speech in nfvPPA. Forty-one patients (21 lvPPA, 20 nfvPPA) were recruited from a consecutive sample with suspected frontotemporal dementia. Patients were diagnosed using the current gold-standard of expert perceptual judgment, based on presence/absence of particular speech features during speaking tasks. Seventeen healthy age-matched adults served as controls. MRI scans were available for 11 control and 37 PPA cases; 23 of the PPA cases underwent amyloid ligand PET imaging. Measures, corresponding to perceptual features of apraxia of speech, were periods of silence during reading and relative vowel duration and intensity in polysyllable word repetition. Discriminant function analyses revealed that a measure of relative vowel duration differentiated nfvPPA cases from both control and lvPPA cases (r2 = 0.47) with 88% agreement with expert judgment of presence of apraxia of speech in nfvPPA cases. VBM analysis showed that relative vowel duration covaried with grey matter intensity in areas critical for speech motor planning and programming: precentral gyrus, supplementary motor area and inferior frontal gyrus bilaterally, only affected in the nfvPPA group. This bilateral involvement of frontal speech networks in nfvPPA potentially affects access to compensatory mechanisms involving right hemisphere homologues. Measures of silences during reading also discriminated the PPA and control groups, but did not increase predictive accuracy. Findings suggest that a measure of relative vowel duration from of a polysyllable word repetition task may be sufficient for detecting most cases of apraxia of speech and distinguishing between nfvPPA and lvPPA

    Relationships between Gene Expression and Brain Wiring in the Adult Rodent Brain

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    We studied the global relationship between gene expression and neuroanatomical connectivity in the adult rodent brain. We utilized a large data set of the rat brain “connectome” from the Brain Architecture Management System (942 brain regions and over 5000 connections) and used statistical approaches to relate the data to the gene expression signatures of 17,530 genes in 142 anatomical regions from the Allen Brain Atlas. Our analysis shows that adult gene expression signatures have a statistically significant relationship to connectivity. In particular, brain regions that have similar expression profiles tend to have similar connectivity profiles, and this effect is not entirely attributable to spatial correlations. In addition, brain regions which are connected have more similar expression patterns. Using a simple optimization approach, we identified a set of genes most correlated with neuroanatomical connectivity, and find that this set is enriched for genes involved in neuronal development and axon guidance. A number of the genes have been implicated in neurodevelopmental disorders such as autistic spectrum disorder. Our results have the potential to shed light on the role of gene expression patterns in influencing neuronal activity and connectivity, with potential applications to our understanding of brain disorders. Supplementary data are available at http://www.chibi.ubc.ca/ABAMS

    Gene Expression in the Rodent Brain is Associated with Its Regional Connectivity

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    The putative link between gene expression of brain regions and their neural connectivity patterns is a fundamental question in neuroscience. Here this question is addressed in the first large scale study of a prototypical mammalian rodent brain, using a combination of rat brain regional connectivity data with gene expression of the mouse brain. Remarkably, even though this study uses data from two different rodent species (due to the data limitations), we still find that the connectivity of the majority of brain regions is highly predictable from their gene expression levels–the outgoing (incoming) connectivity is successfully predicted for 73% (56%) of brain regions, with an overall fairly marked accuracy level of 0.79 (0.83). Many genes are found to play a part in predicting both the incoming and outgoing connectivity (241 out of the 500 top selected genes, p-value<1e-5). Reassuringly, the genes previously known from the literature to be involved in axon guidance do carry significant information about regional brain connectivity. Surveying the genes known to be associated with the pathogenesis of several brain disorders, we find that those associated with schizophrenia, autism and attention deficit disorder are the most highly enriched in the connectivity-related genes identified here. Finally, we find that the profile of functional annotation groups that are associated with regional connectivity in the rodent is significantly correlated with the annotation profile of genes previously found to determine neural connectivity in C. elegans (Pearson correlation of 0.24, p<1e-6 for the outgoing connections and 0.27, p<1e-5 for the incoming). Overall, the association between connectivity and gene expression in a specific extant rodent species' brain is likely to be even stronger than found here, given the limitations of current data

    Cytoarchitectonic and chemoarchitectonic characterization of the prefrontal cortical areas in the mouse

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    This study describes cytoarchitectonic criteria to define the prefrontal cortical areas in the mouse brain (C57BL/6 strain). Currently, well-illustrated mouse brain stereotaxic atlases are available, which, however, do not provide a description of the distinctive cytoarchitectonic characteristics of individual prefrontal areas. Such a description is of importance for stereological, neuronal tracing, and physiological, molecular and neuroimaging studies in which a precise parcellation of the prefrontal cortex (PFC) is required. The present study describes and illustrates: the medial prefrontal areas, i.e., the infralimbic, prelimbic, dorsal and ventral anterior cingulate and Fr2 area; areas of the lateral PFC, i.e., the dorsal agranular insular cortical areas and areas of the ventral PFC, i.e., the lateral, ventrolateral, ventral and medial orbital areas. Each cytoarchitectonically defined boundary is corroborated by one or more chemoarchitectonic stainings, i.e., acetylcholine esterase, SMI32, SMI311, dopamine, parvalbumin, calbindin and myelin staining

    Sensory and cognitive mechanisms of change detection in the context of speech

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    The aim of this study was to dissociate the contributions of memory-based (cognitive) and adaptation-based (sensory) mechanisms underlying deviance detection in the context of natural speech. Twenty healthy right-handed native speakers of English participated in an event-related design scan in which natural speech stimuli, /de:/ (“deh”) and /deI/ (“day”); (/te:/ (“teh”) and /teI/ (“tay”) served as standards and deviants within functional magnetic resonance imaging event-related “oddball” paradigm designed to elicit the mismatch negativity component. Thus, “oddball” blocks could involve either a word deviant (“day”) resulting in a “word advantage” effect, or a non-word deviant (“deh” or “tay”). We utilized an experimental protocol controlling for refractoriness similar to that used previously when deviance detection was studied in the context of tones. Results showed that the cognitive and sensory mechanisms of deviance detection were located in the anterior and posterior auditory cortices, respectively, as was previously found in the context of tones. The cognitive effect, that was most robust for the word deviant, diminished in the “oddball” condition. In addition, the results indicated that the lexical status of the speech stimulus interacts with acoustic factors exerting a top-down modulation of the extent to which novel sounds gain access to the subject’s awareness through memory-based processes. Thus, the more salient the deviant stimulus is the more likely it is to be released from the effects of adaptation exerted by the posterior auditory cortex

    Individual Human Brain Areas Can Be Identified from Their Characteristic Spectral Activation Fingerprints

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    The human brain can be parcellated into diverse anatomical areas. We investigated whether rhythmic brain activity in these areas is characteristic and can be used for automatic classification. To this end, resting-state MEG data of 22 healthy adults was analysed. Power spectra of 1-s long data segments for atlas-defined brain areas were clustered into spectral profiles (“fingerprints”), using k-means and Gaussian mixture (GM) modelling. We demonstrate that individual areas can be identified from these spectral profiles with high accuracy. Our results suggest that each brain area engages in different spectral modes that are characteristic for individual areas. Clustering of brain areas according to similarity of spectral profiles reveals well-known brain networks. Furthermore, we demonstrate task-specific modulations of auditory spectral profiles during auditory processing. These findings have important implications for the classification of regional spectral activity and allow for novel approaches in neuroimaging and neurostimulation in health and disease
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