18 resultados para FALSE VOCAL CORDS

em Duke University


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Perceiving or producing complex vocalizations such as speech and birdsongs require the coordinated activity of neuronal populations, and these activity patterns can vary over space and time. How learned communication signals are represented by populations of sensorimotor neurons essential to vocal perception and production remains poorly understood. Using a combination of two-photon calcium imaging, intracellular electrophysiological recording and retrograde tracing methods in anesthetized adult male zebra finches (Taeniopygia guttata), I addressed how the bird's own song and its component syllables are represented by the spatiotemporal patterns of activity of two spatially intermingled populations of projection neurons (PNs) in HVC, a sensorimotor area required for song perception and production. These experiments revealed that neighboring PNs can respond at markedly different times to song playback and that different syllables activate spatially intermingled HVC PNs within a small region. Moreover, noise correlation analysis reveals enhanced functional connectivity between PNs that respond most strongly to the same syllable and also provides evidence of a spatial gradient of functional connectivity specific to PNs that project to song motor nucleus (i.e. HVCRA cells). These findings support a model in which syllabic and temporal features of song are represented by spatially intermingled PNs functionally organized into cell- and syllable-type networks.

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Spoken language and learned song are complex communication behaviors found in only a few species, including humans and three groups of distantly related birds--songbirds, parrots, and hummingbirds. Despite their large phylogenetic distances, these vocal learners show convergent behaviors and associated brain pathways for vocal communication. However, it is not clear whether this behavioral and anatomical convergence is associated with molecular convergence. Here we used oligo microarrays to screen for genes differentially regulated in brain nuclei necessary for producing learned vocalizations relative to adjacent brain areas that control other behaviors in avian vocal learners versus vocal non-learners. A top candidate gene in our screen was a calcium-binding protein, parvalbumin (PV). In situ hybridization verification revealed that PV was expressed significantly higher throughout the song motor pathway, including brainstem vocal motor neurons relative to the surrounding brain regions of all distantly related avian vocal learners. This differential expression was specific to PV and vocal learners, as it was not found in avian vocal non-learners nor for control genes in learners and non-learners. Similar to the vocal learning birds, higher PV up-regulation was found in the brainstem tongue motor neurons used for speech production in humans relative to a non-human primate, macaques. These results suggest repeated convergent evolution of differential PV up-regulation in the brains of vocal learners separated by more than 65-300 million years from a common ancestor and that the specialized behaviors of learned song and speech may require extra calcium buffering and signaling.

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Vocal learning is a critical behavioral substrate for spoken human language. It is a rare trait found in three distantly related groups of birds-songbirds, hummingbirds, and parrots. These avian groups have remarkably similar systems of cerebral vocal nuclei for the control of learned vocalizations that are not found in their more closely related vocal non-learning relatives. These findings led to the hypothesis that brain pathways for vocal learning in different groups evolved independently from a common ancestor but under pre-existing constraints. Here, we suggest one constraint, a pre-existing system for movement control. Using behavioral molecular mapping, we discovered that in songbirds, parrots, and hummingbirds, all cerebral vocal learning nuclei are adjacent to discrete brain areas active during limb and body movements. Similar to the relationships between vocal nuclei activation and singing, activation in the adjacent areas correlated with the amount of movement performed and was independent of auditory and visual input. These same movement-associated brain areas were also present in female songbirds that do not learn vocalizations and have atrophied cerebral vocal nuclei, and in ring doves that are vocal non-learners and do not have cerebral vocal nuclei. A compilation of previous neural tracing experiments in songbirds suggests that the movement-associated areas are connected in a network that is in parallel with the adjacent vocal learning system. This study is the first global mapping that we are aware for movement-associated areas of the avian cerebrum and it indicates that brain systems that control vocal learning in distantly related birds are directly adjacent to brain systems involved in movement control. Based upon these findings, we propose a motor theory for the origin of vocal learning, this being that the brain areas specialized for vocal learning in vocal learners evolved as a specialization of a pre-existing motor pathway that controls movement.

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Mechanisms for the evolution of convergent behavioral traits are largely unknown. Vocal learning is one such trait that evolved multiple times and is necessary in humans for the acquisition of spoken language. Among birds, vocal learning is evolved in songbirds, parrots, and hummingbirds. Each time similar forebrain song nuclei specialized for vocal learning and production have evolved. This finding led to the hypothesis that the behavioral and neuroanatomical convergences for vocal learning could be associated with molecular convergence. We previously found that the neural activity-induced gene dual specificity phosphatase 1 (dusp1) was up-regulated in non-vocal circuits, specifically in sensory-input neurons of the thalamus and telencephalon; however, dusp1 was not up-regulated in higher order sensory neurons or motor circuits. Here we show that song motor nuclei are an exception to this pattern. The song nuclei of species from all known vocal learning avian lineages showed motor-driven up-regulation of dusp1 expression induced by singing. There was no detectable motor-driven dusp1 expression throughout the rest of the forebrain after non-vocal motor performance. This pattern contrasts with expression of the commonly studied activity-induced gene egr1, which shows motor-driven expression in song nuclei induced by singing, but also motor-driven expression in adjacent brain regions after non-vocal motor behaviors. In the vocal non-learning avian species, we found no detectable vocalizing-driven dusp1 expression in the forebrain. These findings suggest that independent evolutions of neural systems for vocal learning were accompanied by selection for specialized motor-driven expression of the dusp1 gene in those circuits. This specialized expression of dusp1 could potentially lead to differential regulation of dusp1-modulated molecular cascades in vocal learning circuits.

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MOTIVATION: Technological advances that allow routine identification of high-dimensional risk factors have led to high demand for statistical techniques that enable full utilization of these rich sources of information for genetics studies. Variable selection for censored outcome data as well as control of false discoveries (i.e. inclusion of irrelevant variables) in the presence of high-dimensional predictors present serious challenges. This article develops a computationally feasible method based on boosting and stability selection. Specifically, we modified the component-wise gradient boosting to improve the computational feasibility and introduced random permutation in stability selection for controlling false discoveries. RESULTS: We have proposed a high-dimensional variable selection method by incorporating stability selection to control false discovery. Comparisons between the proposed method and the commonly used univariate and Lasso approaches for variable selection reveal that the proposed method yields fewer false discoveries. The proposed method is applied to study the associations of 2339 common single-nucleotide polymorphisms (SNPs) with overall survival among cutaneous melanoma (CM) patients. The results have confirmed that BRCA2 pathway SNPs are likely to be associated with overall survival, as reported by previous literature. Moreover, we have identified several new Fanconi anemia (FA) pathway SNPs that are likely to modulate survival of CM patients. AVAILABILITY AND IMPLEMENTATION: The related source code and documents are freely available at https://sites.google.com/site/bestumich/issues. CONTACT: yili@umich.edu.

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In a stochastic environment, long-term fitness can be influenced by variation, covariation, and serial correlation in vital rates (survival and fertility). Yet no study of an animal population has parsed the contributions of these three aspects of variability to long-term fitness. We do so using a unique database that includes complete life-history information for wild-living individuals of seven primate species that have been the subjects of long-term (22-45 years) behavioral studies. Overall, the estimated levels of vital rate variation had only minor effects on long-term fitness, and the effects of vital rate covariation and serial correlation were even weaker. To explore why, we compared estimated variances of adult survival in primates with values for other vertebrates in the literature and found that adult survival is significantly less variable in primates than it is in the other vertebrates. Finally, we tested the prediction that adult survival, because it more strongly influences fitness in a constant environment, will be less variable than newborn survival, and we found only mixed support for the prediction. Our results suggest that wild primates may be buffered against detrimental fitness effects of environmental stochasticity by their highly developed cognitive abilities, social networks, and broad, flexible diets.

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The objective of spatial downscaling strategies is to increase the information content of coarse datasets at smaller scales. In the case of quantitative precipitation estimation (QPE) for hydrological applications, the goal is to close the scale gap between the spatial resolution of coarse datasets (e.g., gridded satellite precipitation products at resolution L × L) and the high resolution (l × l; L»l) necessary to capture the spatial features that determine spatial variability of water flows and water stores in the landscape. In essence, the downscaling process consists of weaving subgrid-scale heterogeneity over a desired range of wavelengths in the original field. The defining question is, which properties, statistical and otherwise, of the target field (the known observable at the desired spatial resolution) should be matched, with the caveat that downscaling methods be as a general as possible and therefore ideally without case-specific constraints and/or calibration requirements? Here, the attention is focused on two simple fractal downscaling methods using iterated functions systems (IFS) and fractal Brownian surfaces (FBS) that meet this requirement. The two methods were applied to disaggregate spatially 27 summertime convective storms in the central United States during 2007 at three consecutive times (1800, 2100, and 0000 UTC, thus 81 fields overall) from the Tropical Rainfall Measuring Mission (TRMM) version 6 (V6) 3B42 precipitation product (~25-km grid spacing) to the same resolution as the NCEP stage IV products (~4-km grid spacing). Results from bilinear interpolation are used as the control. A fundamental distinction between IFS and FBS is that the latter implies a distribution of downscaled fields and thus an ensemble solution, whereas the former provides a single solution. The downscaling effectiveness is assessed using fractal measures (the spectral exponent β, fractal dimension D, Hurst coefficient H, and roughness amplitude R) and traditional operational scores statistics scores [false alarm rate (FR), probability of detection (PD), threat score (TS), and Heidke skill score (HSS)], as well as bias and the root-mean-square error (RMSE). The results show that both IFS and FBS fractal interpolation perform well with regard to operational skill scores, and they meet the additional requirement of generating structurally consistent fields. Furthermore, confidence intervals can be directly generated from the FBS ensemble. The results were used to diagnose errors relevant for hydrometeorological applications, in particular a spatial displacement with characteristic length of at least 50 km (2500 km2) in the location of peak rainfall intensities for the cases studied. © 2010 American Meteorological Society.

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BACKGROUND: There is considerable interest in the development of methods to efficiently identify all coding variants present in large sample sets of humans. There are three approaches possible: whole-genome sequencing, whole-exome sequencing using exon capture methods, and RNA-Seq. While whole-genome sequencing is the most complete, it remains sufficiently expensive that cost effective alternatives are important. RESULTS: Here we provide a systematic exploration of how well RNA-Seq can identify human coding variants by comparing variants identified through high coverage whole-genome sequencing to those identified by high coverage RNA-Seq in the same individual. This comparison allowed us to directly evaluate the sensitivity and specificity of RNA-Seq in identifying coding variants, and to evaluate how key parameters such as the degree of coverage and the expression levels of genes interact to influence performance. We find that although only 40% of exonic variants identified by whole genome sequencing were captured using RNA-Seq; this number rose to 81% when concentrating on genes known to be well-expressed in the source tissue. We also find that a high false positive rate can be problematic when working with RNA-Seq data, especially at higher levels of coverage. CONCLUSIONS: We conclude that as long as a tissue relevant to the trait under study is available and suitable quality control screens are implemented, RNA-Seq is a fast and inexpensive alternative approach for finding coding variants in genes with sufficiently high expression levels.

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People often do not realize they are being influenced by an incidental emotional state. As a result, decisions based on a fleeting incidental emotion can become the basis for future decisions and hence outlive the original cause for the behavior (i.e., the emotion itself). Using a sequence of ultimatum and dictator games, we provide empirical evidence for the enduring impact of transient emotions on economic decision making. Behavioral consistency and false consensus are presented as potential underlying processes. © 2009 Elsevier Inc. All rights reserved.

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© 2013 The Association for the Study of Animal Behaviour.Social complexity, often estimated by group size, is seen as driving the complexity of vocal signals, but its relation to olfactory signals, which arguably arose to function in nonsocial realms, remains underappreciated. That olfactory signals also may mediate within-group interaction, vary with social complexity and promote social cohesion underscores a potentially crucial link with sociality. To examine that link, we integrated chemical and behavioural analyses to ask whether olfactory signals facilitate reproductive coordination in a strepsirrhine primate, the Coquerel's sifaka, Propithecus coquereli. Belonging to a clade comprising primarily solitary, nocturnal species, the diurnal, group-living sifaka represents an interesting test case. Convergent with diurnal, group-living lemurids, sifakas expressed chemically rich scent signals, consistent with the social complexity hypothesis for communication. These signals minimally encoded the sex of the signaller and varied with female reproductive state. Likewise, sex and female fertility were reflected in within-group scent investigation, scent marking and overmarking. We further asked whether, within breeding pairs, the stability or quality of the pair's bond influences the composition of glandular signals and patterns of investigatory or scent-marking behaviour. Indeed, reproductively successful pairs tended to show greater similarity in their scent signals than did reproductively unsuccessful pairs, potentially through chemical convergence. Moreover, scent marking was temporally coordinated within breeding pairs and was influenced by past reproductive success. That olfactory signalling reflects social bondedness or reproductive history lends support to recent suggestions that the quality of relationships may be a more valuable proxy than group size for estimating social complexity. We suggest that olfactory signalling in sifakas is more complex than previously recognized and, as in other socially integrated species, can be a crucial mechanism for promoting group cohesion and maintaining social bonds. Thus, the evolution of sociality may well be reflected in the complexity of olfactory signalling.

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Technological advances in genotyping have given rise to hypothesis-based association studies of increasing scope. As a result, the scientific hypotheses addressed by these studies have become more complex and more difficult to address using existing analytic methodologies. Obstacles to analysis include inference in the face of multiple comparisons, complications arising from correlations among the SNPs (single nucleotide polymorphisms), choice of their genetic parametrization and missing data. In this paper we present an efficient Bayesian model search strategy that searches over the space of genetic markers and their genetic parametrization. The resulting method for Multilevel Inference of SNP Associations, MISA, allows computation of multilevel posterior probabilities and Bayes factors at the global, gene and SNP level, with the prior distribution on SNP inclusion in the model providing an intrinsic multiplicity correction. We use simulated data sets to characterize MISA's statistical power, and show that MISA has higher power to detect association than standard procedures. Using data from the North Carolina Ovarian Cancer Study (NCOCS), MISA identifies variants that were not identified by standard methods and have been externally "validated" in independent studies. We examine sensitivity of the NCOCS results to prior choice and method for imputing missing data. MISA is available in an R package on CRAN.

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Like humans, birds that exhibit vocal learning have relatively delayed telencephalon maturation, resulting in a disproportionately smaller brain prenatally but enlarged telencephalon in adulthood relative to vocal non-learning birds. To determine if this size difference results from evolutionary changes in cell-autonomous or cell-interdependent developmental processes, we transplanted telencephala from zebra finch donors (a vocal-learning species) into Japanese quail hosts (a vocal non-learning species) during the early neural tube stage (day 2 of incubation), and harvested the chimeras at later embryonic stages (between 9-12 days of incubation). The donor and host tissues fused well with each other, with known major fiber pathways connecting the zebra finch and quail parts of the brain. However, the overall sizes of chimeric finch telencephala were larger than non-transplanted finch telencephala at the same developmental stages, even though the proportional sizes of telencephalic subregions and fiber tracts were similar to normal finches. There were no significant changes in the size of chimeric quail host midbrains, even though they were innervated by the physically smaller zebra finch brain, including the smaller retinae of the finch eyes. Chimeric zebra finch telencephala had a decreased cell density relative to normal finches. However, cell nucleus size differences between each species were maintained as in normal birds. These results suggest that telencephalic size development is partially cell-interdependent, and that the mechanisms controlling the size of different brain regions may be functionally independent.

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Humans and song-learning birds communicate acoustically using learned vocalizations. The characteristic features of this social communication behavior include vocal control by forebrain motor areas, a direct cortical projection to brainstem vocal motor neurons, and dependence on auditory feedback to develop and maintain learned vocalizations. These features have so far not been found in closely related primate and avian species that do not learn vocalizations. Male mice produce courtship ultrasonic vocalizations with acoustic features similar to songs of song-learning birds. However, it is assumed that mice lack a forebrain system for vocal modification and that their ultrasonic vocalizations are innate. Here we investigated the mouse song system and discovered that it includes a motor cortex region active during singing, that projects directly to brainstem vocal motor neurons and is necessary for keeping song more stereotyped and on pitch. We also discovered that male mice depend on auditory feedback to maintain some ultrasonic song features, and that sub-strains with differences in their songs can match each other's pitch when cross-housed under competitive social conditions. We conclude that male mice have some limited vocal modification abilities with at least some neuroanatomical features thought to be unique to humans and song-learning birds. To explain our findings, we propose a continuum hypothesis of vocal learning.

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BACKGROUND: A public that is an informed partner in clinical research is important for ethical, methodological, and operational reasons. There are indications that the public is unaware or misinformed, and not sufficiently engaged in clinical research but studies on the topic are lacking. PARTAKE - Public Awareness of Research for Therapeutic Advancements through Knowledge and Empowerment is a program aimed at increasing public awareness and partnership in clinical research. The PARTAKE Survey is a component of the program. OBJECTIVE: To study public knowledge and perceptions of clinical research. METHODS: A 40-item questionnaire combining multiple-choice and open-ended questions was administered to 175 English- or Hindi-speaking individuals in 8 public locations representing various socioeconomic strata in New Delhi, India. RESULTS: Interviewees were 18-84 old (mean: 39.6, SD ± 16.6), 23.6% female, 68.6% employed, 7.3% illiterate, 26.3% had heard of research, 2.9% had participated and 58.9% expressed willingness to participate in clinical research. The following perceptions were reported (% true/% false/% not aware): 'research benefits society' (94.1%/3.5%/2.3%), 'the government protects against unethical clinical research' (56.7%/26.3%/16.9%), 'research hospitals provide better care' (67.2%/8.7%/23.9%), 'confidentiality is adequately protected' (54.1%/12.3%/33.5%), 'participation in research is voluntary' (85.3%/5.8%/8.7%); 'participants treated like 'guinea pigs'' (20.7%/53.2%/26.0%), and 'compensation for participation is adequate' (24.7%/12.9%/62.3%). CONCLUSIONS: Results suggest the Indian public is aware of some key features of clinical research (e.g., purpose, value, voluntary nature of participation), and supports clinical research in general but is unaware of other key features (e.g., compensation, confidentiality, protection of human participants) and exhibits some distrust in the conduct and reporting of clinical trials. Larger, cross-cultural surveys are required to inform educational programs addressing these issues.

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In 2005, Holy and Guo advanced the idea that male mice produce ultrasonic vocalizations (USV) with some features similar to courtship songs of songbirds. Since then, studies showed that male mice emit USV songs in different contexts (sexual and other) and possess a multisyllabic repertoire. Debate still exists for and against plasticity in their vocalizations. But the use of a multisyllabic repertoire can increase potential flexibility and information, in how elements are organized and recombined, namely syntax. In many bird species, modulating song syntax has ethological relevance for sexual behavior and mate preferences. In this study we exposed adult male mice to different social contexts and developed a new approach of analyzing their USVs based on songbird syntax analysis. We found that male mice modify their syntax, including specific sequences, length of sequence, repertoire composition, and spectral features, according to stimulus and social context. Males emit longer and simpler syllables and sequences when singing to females, but more complex syllables and sequences in response to fresh female urine. Playback experiments show that the females prefer the complex songs over the simpler ones. We propose the complex songs are to lure females in, whereas the directed simpler sequences are used for direct courtship. These results suggest that although mice have a much more limited ability of song modification, they could still be used as animal models for understanding some vocal communication features that songbirds are used for.