Longitudinal Scalar-on-Function Regression with Application to Tractography Data

We propose a class of estimation techniques for scalar-on-function regression in longitudinal studies where both outcomes, such as test results on motor functions, and functional predictors, such as brain images, may be observed at multiple visits. Our methods are motivated by a longitudinal brain diffusion tensor imaging (DTI) tractography study. One of the primary goals of the study is to evaluate the contemporaneous association between human function and brain imaging over time. The complexity of the study requires development of methods that can simultaneously incorporate: (1) multiple functional (and scalar) regressors; (2) longitudinal outcome and functional predictors measurements per patient; (3) Gaussian or non-Gaussian outcomes; and, (4) missing values within functional predictors. We review existing approaches designed to handle such types of data and discuss their limitations. We propose two versions of a new method, longitudinal functional principal components regression. These methods extend the well-known functional principal component regression and allow for different effects of subject-specific trends in curves and of visit-specific deviations from that trend. The different methods are compared in simulation studies, and the most promising approaches are used for analyzing the tractography data

Methods matter: A primer on permanent and reversible interference techniques in animals for investigators of human neuropsychology.

The study of patients with brain lesions has contributed greatly to our understanding of the biological bases of human cognition, but this approach also has several unavoidable limitations. Research that uses animal models complements and extends human neuropsychology by addressing many of these limitations. In this review, we provide an overview of permanent and reversible animal lesion techniques for researchers of human neuropsychology, with the aim of highlighting how these methods provide a valuable adjunct to behavioural, neuroimaging, physiological, and clinical investigations in humans. Research in animals has provided important lessons about how the limitations of one or more techniques, or differences in their mechanism of action, has impacted upon the understanding of brain organisation and function. These cautionary tales highlight the importance of striving for a thorough understanding of how any intereference technique works (whether in animal or human), and for how to best use animal research to clarify the precise mechanisms underlying temporary lesion methods in humans

Probabilistic Fluorescence-Based Synapse Detection

Brain function results from communication between neurons connected by complex synaptic networks. Synapses are themselves highly complex and diverse signaling machines, containing protein products of hundreds of different genes, some in hundreds of copies, arranged in precise lattice at each individual synapse. Synapses are fundamental not only to synaptic network function but also to network development, adaptation, and memory. In addition, abnormalities of synapse numbers or molecular components are implicated in most mental and neurological disorders. Despite their obvious importance, mammalian synapse populations have so far resisted detailed quantitative study. In human brains and most animal nervous systems, synapses are very small and very densely packed: there are approximately 1 billion synapses per cubic millimeter of human cortex. This volumetric density poses very substantial challenges to proteometric analysis at the critical level of the individual synapse. The present work describes new probabilistic image analysis methods for single-synapse analysis of synapse populations in both animal and human brains.Comment: Current awaiting peer revie

fMRI activation detection with EEG priors

The purpose of brain mapping techniques is to advance the understanding of the relationship between structure and function in the human brain in so-called activation studies. In this work, an advanced statistical model for combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) recordings is developed to fuse complementary information about the location of neuronal activity. More precisely, a new Bayesian method is proposed for enhancing fMRI activation detection by the use of EEG-based spatial prior information in stimulus based experimental paradigms. I.e., we model and analyse stimulus influence by a spatial Bayesian variable selection scheme, and extend existing high-dimensional regression methods by incorporating prior information on binary selection indicators via a latent probit regression with either a spatially-varying or constant EEG effect. Spatially-varying effects are regularized by intrinsic Markov random field priors. Inference is based on a full Bayesian Markov Chain Monte Carlo (MCMC) approach. Whether the proposed algorithm is able to increase the sensitivity of mere fMRI models is examined in both a real-world application and a simulation study. We observed, that carefully selected EEG--prior information additionally increases sensitivity in activation regions that have been distorted by a low signal-to-noise ratio

A zinc transporter gene required for development of the nervous system.

The essentiality of zinc for normal brain development is well established. It has been suggested that primary and secondary zinc deficiencies can contribute to the occurrence of numerous human birth defects, including many involving the central nervous system. In a recent study, we searched for zinc transporter genes that were critical for neurodevelopment. We confirmed that ZIP12 is a zinc transporter encoded by the gene slc39a12 that is highly expressed in the central nervous systems of human, mouse, and frog (Xenopus tropicalis).Using loss-of-function methods, we determined that ZIP12 is required for neuronal differentiation and neurite outgrowth and necessary for neurulation and embryonic viability. These results highlight an essential need for zinc regulation during embryogenesis and nervous system development. We suggest that slc39a12 is a candidate gene for inherited neurodevelopmental defects in humans

FGF2 is expressed in human and murine embryonic choroid plexus and affects choroid plexus cell behaviour

<p>Abstract</p> <p>Background</p> <p>Although fibroblast growth factor (Fgf) signalling plays crucial roles in several developing and mature tissues, little information is currently available on expression of Fgf2 during early choroid plexus development and whether Fgf2 directly affects the behaviour of the choroid plexus epithelium (CPe). The purpose of this study was to investigate expression of Fgf2 in rodent and human developing CPe and possible function of Fgf2, using <it>in vitro </it>models. The application of Fgf2 to brain <it>in vivo </it>can affect the whole tissue, making it difficult to assess specific responses of the CPe.</p> <p>Methods</p> <p>Expression of Fgf2 was studied by immunohistochemistry in rodent and human embryonic choroid plexus. Effects of Fgf2 on growth, secretion, aggregation and gene expression was investigated using rodent CPe vesicles, a three-dimensional polarized culture model that closely mimics CPe properties <it>in vivo</it>, and rodent CPe monolayer cultures.</p> <p>Results</p> <p>Fgf2 was present early in development of the choroid plexus both in mouse and human, suggesting the importance of this ligand in Fgf signalling in the developing choroid plexus. Parallel analysis of Fgf2 expression and cell proliferation during CP development suggests that Fgf2 is not involved in CPe proliferation <it>in vivo</it>. Consistent with this observation is the failure of Fgf2 to increase proliferation in the tri-dimensional vesicle culture model. The CPe however, can respond to Fgf2 treatment, as the diameter of CPe vesicles is significantly increased by treatment with this growth factor. We show that this is due to an increase in cell aggregation during vesicle formation rather than increased secretion into the vesicle lumen. Finally, Fgf2 regulates expression of the CPe-associated transcription factors, <it>Foxj1 </it>and <it>E2f5</it>, whereas transthyretin, a marker of secretory activity, is not affected by Fgf2 treatment.</p> <p>Conclusion</p> <p>Fgf2 expression early in the development of both human and rodent choroid plexus, and its ability to modulate behaviour and gene expression in CPe, supports the view that Fgf signalling plays a role in the maintenance of integrity and function of this specialized epithelium, and that this role is conserved between rodents and humans.</p

Newborns discriminate novel from harmonic sounds: a study using magnetoencephalography

Objective: We investigated whether newborns respond differently to novel and deviant sounds during quiet sleep. Methods: Twelve healthy neonates were presented with a three-stimulus oddball paradigm, consisting of frequent standard (76%), infrequent deviant (12%), and infrequent novel stimuli (12%). The standards and deviants were counterbalanced between the newborns and consisted of 500 and 750 Hz tones with two upper harmonics. The novel stimuli contained animal, human, and mechanical sounds. All stimuli had a duration of 300 ms and the stimulus onset asynchrony was 1 s. Evoked magnetic responses during quiet sleep were recorded and averaged offline. Results: Two deflections peaking at 345 and 615 ms after stimulus onset were observed in the evoked responses of most of the newborns. The first deflection was larger to novel and deviant stimuli than to the standard and, furthermore, larger to novel than to deviant stimuli. The second deflection was larger to novel and deviant stimuli than to standards, but did not differ between the novels and deviants. Conclusions: The two deflections found in the present study reflect different mechanisms of auditory change detection and discriminative processes. Significance: The early brain indicators of novelty detection may be crucial in assessing the normal and abnormal cortical function in newborns. Further, studying evoked magnetic fields to complex auditory stimulation in healthy newborns is needed for studying the newborns at-risk for cognitive or language problems

Neuronal Correlation Parameter in the Idea of Thermodynamic Entropy of an N-Body Gravitationally Bounded System

Understanding how the brain encodes information and performs computation requires statistical and functional analysis. Given the complexity of the human brain, simple methods that facilitate the interpretation of statistical correlations among different brain regions can be very useful. In this report we introduce a numerical correlation measure that may serve the interpretation of correlational neuronal data, and may assist in the evaluation of different brain states. The description of the dynamical brain system, through a global numerical measure may indicate the presence of an action principle which may facilitate a application of physics principles in the study of the human brain and cognition