Semi-supervised learning of hierarchical latent trait models for data visualisation

An interactive hierarchical Generative Topographic Mapping (HGTM) ¸iteH_GTM has been developed to visualise complex data sets. In this paper, we build a more general visualisation system by extending the HGTM visualisation system in 3 directions: bf (1) We generalize HGTM to noise models from the exponential family of distributions. The basic building block is the Latent Trait Model (LTM) developed in ¸iteKaban_pami. bf (2) We give the user a choice of initializing the child plots of the current plot in either em interactive, or em automatic mode. In the interactive mode the user interactively selects ``regions of interest'' as in ¸iteH_GTM, whereas in the automatic mode an unsupervised minimum message length (MML)-driven construction of a mixture of LTMs is employed. bf (3) We derive general formulas for magnification factors in latent trait models. Magnification factors are a useful tool to improve our understanding of the visualisation plots, since they can highlight the boundaries between data clusters. The unsupervised construction is particularly useful when high-level plots are covered with dense clusters of highly overlapping data projections, making it difficult to use the interactive mode. Such a situation often arises when visualizing large data sets. We illustrate our approach on a toy example and apply our system to three more complex real data sets.

Progressive supranuclear palsy (PSP):A quantitative study of the pathological changes in cortical and subcortical regions of eight cases

In eight cases of progressive supranuclear palsy (PSP), neurofibrillary tangles (NFT) were numerous in the substantia nigra (SN), red nucleus (RN), locus caeruleus (LC), pontine nuclei (PN), and inferior olivary nucleus (ION) and abnormally enlarged neurons (EN) in the ION, LC and PN. Loss of Purkinje cells was evident in the cerebellum. Tufted astrocytes (TA) were abundant in the striatum, SN and RN and glial inclusions ('coiled bodies') (GI) in the midbrain (SN, RN) and pons (LC). Neuritic plaques were frequent in one case. NFT, GI, and TA densities were uncorrelated in most areas. NFT and EN densities were positively correlated in the midbrain and surviving neurons and disease duration in several areas. These results suggest: 1) predominantly subcortical pathology in PSP with widespread NFT while TA and GI have a more localized distribution, 2) little correlation between neuronal and glial pathologies, and 3) shorter duration cases may be more likely to develop cortical pathology. © 2007 Springer-Verlag.

Common variants in left/right asymmetry genes and pathways are associated with relative hand skill

Humans display structural and functional asymmetries in brain organization, strikingly with respect to language and handedness. The molecular basis of these asymmetries is unknown. We report a genome-wide association study meta-analysis for a quantitative measure of relative hand skill in individuals with dyslexia [reading disability (RD)] (n = 728). The most strongly associated variant, rs7182874 (P = 8.68×10-9), is located in PCSK6, further supporting an association we previously reported. We also confirmed the specificity of this association in individuals with RD; the same locus was not associated with relative hand skill in a general population cohort (n = 2,666). As PCSK6 is known to regulate NODAL in the development of left/right (LR) asymmetry in mice, we developed a novel approach to GWAS pathway analysis, using gene-set enrichment to test for an over-representation of highly associated variants within the orthologs of genes whose disruption in mice yields LR asymmetry phenotypes. Four out of 15 LR asymmetry phenotypes showed an over-representation (FDR≤5%). We replicated three of these phenotypes; situs inversus, heterotaxia, and double outlet right ventricle, in the general population cohort (FDR≤5%). Our findings lead us to propose that handedness is a polygenic trait controlled in part by the molecular mechanisms that establish LR body asymmetry early in development. © 2013 Brandler et al.

Quantitative analysis of multi-spectral fundus images

We have developed a new technique for extracting histological parameters from multi-spectral images of the ocular fundus. The new method uses a Monte Carlo simulation of the reflectance of the fundus to model how the spectral reflectance of the tissue varies with differing tissue histology. The model is parameterised by the concentrations of the five main absorbers found in the fundus: retinal haemoglobins, choroidal haemoglobins, choroidal melanin, RPE melanin and macular pigment. These parameters are shown to give rise to distinct variations in the tissue colouration. We use the results of the Monte Carlo simulations to construct an inverse model which maps tissue colouration onto the model parameters. This allows the concentration and distribution of the five main absorbers to be determined from suitable multi-spectral images. We propose the use of "image quotients" to allow this information to be extracted from uncalibrated image data. The filters used to acquire the images are selected to ensure a one-to-one mapping between model parameters and image quotients. To recover five model parameters uniquely, images must be acquired in six distinct spectral bands. Theoretical investigations suggest that retinal haemoglobins and macular pigment can be recovered with RMS errors of less than 10%. We present parametric maps showing the variation of these parameters across the posterior pole of the fundus. The results are in agreement with known tissue histology for normal healthy subjects. We also present an early result which suggests that, with further development, the technique could be used to successfully detect retinal haemorrhages.

Semisupervised learning of hierarchical latent trait models for data visualization

Recently, we have developed the hierarchical Generative Topographic Mapping (HGTM), an interactive method for visualization of large high-dimensional real-valued data sets. In this paper, we propose a more general visualization system by extending HGTM in three ways, which allows the user to visualize a wider range of data sets and better support the model development process. 1) We integrate HGTM with noise models from the exponential family of distributions. The basic building block is the Latent Trait Model (LTM). This enables us to visualize data of inherently discrete nature, e.g., collections of documents, in a hierarchical manner. 2) We give the user a choice of initializing the child plots of the current plot in either interactive, or automatic mode. In the interactive mode, the user selects "regions of interest," whereas in the automatic mode, an unsupervised minimum message length (MML)-inspired construction of a mixture of LTMs is employed. The unsupervised construction is particularly useful when high-level plots are covered with dense clusters of highly overlapping data projections, making it difficult to use the interactive mode. Such a situation often arises when visualizing large data sets. 3) We derive general formulas for magnification factors in latent trait models. Magnification factors are a useful tool to improve our understanding of the visualization plots, since they can highlight the boundaries between data clusters. We illustrate our approach on a toy example and evaluate it on three more complex real data sets. © 2005 IEEE.

The handedness-associated PCSK6 locus spans an intronic promoter regulating novel transcripts

We recently reported the association of the PCSK6 gene with handedness through a quantitative genome-wide association study (GWAS; P < 0.5 × 10(-8)) for a relative hand skill measure in individuals with dyslexia. PCSK6 activates Nodal, a morphogen involved in regulating left-right body axis determination. Therefore, the GWAS data suggest that the biology underlying the patterning of structural asymmetries may also contribute to behavioural laterality, e.g. handedness. The association is further supported by an independent study reporting a variable number tandem repeat (VNTR) within the same PCSK6 locus to be associated with degree of handedness in a general population cohort. Here, we have conducted a functional analysis of the PCSK6 locus combining further genetic analysis, in silico predictions and molecular assays. We have shown that the previous GWAS signal was not tagging a VNTR effect, suggesting that the two markers have independent effects. We demonstrated experimentally that one of the top GWAS-associated markers, rs11855145, directly alters the binding site for a nuclear factor. Furthermore, we have shown that the predicted regulatory region adjacent to rs11855415 acts as a bidirectional promoter controlling the expression of novel RNA transcripts. These include both an antisense long non-coding RNA (lncRNA) and a short PCSK6 isoform predicted to be coding. This is the first molecular characterization of a handedness-associated locus that supports the role of common variants in non-coding sequences in influencing complex phenotypes through gene expression regulation.