46 research outputs found
Single-cell analysis of long non-coding RNAs in the developing human neocortex
Single cell transcriptomics of lncRNA expression in K562 cell cultures. A Distributions of median lncRNA expression to median mRNA expression ratios (lncRNA:mRNA) in populations, in silico merged single cells, and single cells from K562 cultures. B Proportion of K562 cells that expressed each lncRNA (blue) and mRNA (red), separated by maximum expression in single cells. C Same as in (B) but grouped by maximum expression quantile. D Distributions of non-zero lncRNA (blue) and mRNA (red) expression in 46 single K562 cells. Green squares, housekeeping genes; black triangles, ERCC Spike-In Controls. (PDF 454 kb
Prevention of Alzheimer's disease in high risk groups: statin therapy in subjects with PSEN1 mutations or heterozygosity for apolipoprotein E epsilon 4
Because cerebrospinal fluid (CSF) abnormalities in presymptomatic subjects with PSEN1 (presenilin 1) mutations may be observed 4 to 12 years prior to the estimated age at onset, it is possible to test putative therapies on the CSF analytes that correlate with neurodegeneration during this presymptomatic window of clinical opportunity. It is also possible to test the same therapy on a comparison group with increased risk status conferred by both hyperlipidemia and heterozygosity for apolipoprotein Eε4. To our knowledge, the only putative therapy thus far tested in such a common design has been statin therapy. The results of these tests show increases in soluble amyloid precursor protein (sAPP)α correlating with statin-induced decreases in serum cholesterol levels in the non-PSEN1 subjects. This result could be one functional correlate for part of the substantial risk reduction for late onset Alzheimer\u27s disease recently reported in the Rotterdam study, a large, long-term prospective statin trial. Statin therapy significantly decreased both sAPPα and sAPPβ in presymptomatic PSEN1 subjects. Initially, elevated phospho-tau levels in PSEN1 subjects did not further increase during the 2 to 3 years of statin therapy, possibly indicative of a prophylactic effect. These results suggest that large and longer term trials of statin therapy correlating changes in CSF biomarker levels with clinical course may be warranted in both presymptomatic PSEN1 and non-PSEN1 subjects
Explicit neural representations, recursive neural networks and conscious visual perception
The fundamental question as to whether the neural correlates of any given conscious visual experience are expressed locally within a given cortical area or more globally within some widely distributed network remains unresolved. We inquire as to whether recursive processing-by which we mean the combined flow and integrated outcome of afferent and recurrent activity across a series of cortical areas-is essential for the emergence of conscious visual experience. If so, we further inquire as to whether such recursive processing is essential only for loops between extrastriate cortical areas explicitly representing experiences such as color or motion back to V1 or whether it is processing between still higher levels and the areas computing such explicit representations that is exclusively or additionally essential for visual experience. If recursive processing is not essential for the emergence of conscious visual experience, then it should also be possible to determine whether it is only the intracortical sensory processing within areas computing explicit sensory representations that is required for perceptual experience or whether it is the subsequent processing of the output of such areas within more anterior cortical regions that engenders perception. The present analysis suggests that the questions posed here may ultimately become experimentally resolvable. Whatever the outcome, the results will likely open new approaches to identify the neural correlates of conscious visual perception
On the neural correlates of visual perception
Neurological findings suggest that the human striate cortex (V1) is an indispensable component of a neural substratum subserving static achromatic form perception in its own right and not simply as a central distributor of retinally derived information to extrastriate visual areas. This view is further supported by physiological evidence in primates that the finest-grained conjoined representation of spatial detail and retinotopic localization that underlies phenomenal visual experience for local brightness discriminations is selectively represented at cortical levels by the activity of certain neurons in V1. However, at first glance, support for these ideas would appear to be undermined by incontrovertible neurological evidence (visual hemineglect and the simultanagnosias) and recent psychophysical results on \u27crowding\u27 that confirm that activation of neurons in V1 may, at times, be insufficient to generate a percept. Moreover, a recent proposal suggests that neural correlates of visual awareness must project directly to those in executive space, thus automatically excluding V1 from a related perceptual space because V1 lacks such direct projections. Both sets of concerns are, however, resolved within the context of adaptive resonance theories. Recursive loops, linking the dorsal lateral geniculate nucleus (LGN) through successive cortical visual areas to the temporal lobe by means of a series of ascending and descending pathways, provide a neuronal substratum at each level within a modular framework for mutually consistent descriptions of sensory data. At steady state, such networks obviate the necessity that neural correlates of visual experience project directly to those in executive space because a neural phenomenal perceptual space subserving form vision is continuously updated by information from an object recognition space equivalent to that destined to reach executive space. Within this framework, activity in V1 may engender percepts that accompany figure-ground segregations only when dynamic incongruities are resolved both within and between ascending and descending streams. Synchronous neuronal activity on a short timescale within and across cortical areas, proposed and sometimes observed as perceptual correlates, may also serve as a marker that a steady state has been achieved, which, in turn, may be a requirement for the longer time constants that accompany the emergence and stability of perceptual states compared to the faster dynamics of adapting networks and the still faster dynamics of individual action potentials. Finally, the same consensus of neuronal activity across ascending and descending pathways linking multiple cortical areas that in anatomic sequence subserve phenomenal visual experiences and object recognition may underlie the normal unity of conscious experience
Visual cortical neurons as localized spatial frequency filters
This paper relates to the receptive field properties of neurons in the primary visual cortex, i.e. the striate cortex, to current issues in spatial visual information processing. Particular attention is given to the fact that receptive field profiles of simple cells in the visual cortex often resemble even-symmetric or odd-symmetric Gabor filters; i.e. their receptive field profiles can be described by the product of a Gaussian and either a cosine or sine function. Their spatial frequency tuning is of medium bandwidth (~one octave) which is narrow enough for a cell to distinguish the third harmonic from the fundamental frequency for square-wave gratings of low spatial frequency. The responses of adjacent simple cells, tuned to the same spatial frequency, orientation, and direction, differ in their phase response to drifting sine-wave gratings by approximately either 90° or 180°. This latter result makes it possible to consider two adjacent simple cell pairs as operating like paired Gaussian-attenuated sine and cosine filters of Gabor filters for restricted regions of visual space. The entire set of simple cells provides a complete representation of the visual scene, yet each simple cell is unique in its response properties. At the complex cell stage, the cell\u27s mean firing rate appears to represent the amplitude of a local Fourier coefficient, but phase information is seldom conveyed with much precision in the action potential code
Spatial receptive field organization of macaque V4 neurons
Subfield analysis of the receptive fields (RFs) of parafoveal V4 complex cells demonstrates directly that most RFs are tiled by overlapping second-order excitatory inputs that for any given V4 cell are predominantly selective to the same preferred values of spatial frequency and orientation. These results extend hierarchical principles of RF organization in the spatial, orientation and spatial frequency domains, first recognized in V1, to an intermediate extrastriate cortex. Spatial interaction studies across subfields demonstrate that the responses of V4 neurons to paired stimuli may either decrease or increase as a function of inter-stimulus distance across the width axis. These intra-RF suppressions and facilitations vary independently in magnitude and spatial extent from cell to cell. These results taken together with the relatively large RF sizes of V4 neurons - as compared with RF sizes of their afferent inputs - lead us to hypothesize a novel property, namely that classes of stimulus configurations that enhance areal summation while reducing suppressive interactions between excitatory inputs will evoke especially robust responses. We tested, and found support for, this hypothesis by presenting stimuli consisting of optimally tuned sine-wave gratings visible only within an annular region and found that such stimuli vigorously activate V4 neurons at firing rates far higher than those evoked by comparable stimuli to either the full-field or central core. On the basis of these results we propose a framework for a new class of neural network models for the spatial RF organizations of prototypic V4 neurons
SCell: integrated analysis of single-cell RNA-seq data
Summary: Analysis of the composition of heterogeneous tissue has been greatly enabled by recent developments in single-cell transcriptomics. We present SCell, an integrated software tool for quality filtering, normalization, feature selection, iterative dimensionality reduction, clustering and the estimation of gene-expression gradients from large ensembles of single-cell RNA-seq datasets. SCell is open source, and implemented with an intuitive graphical interface. Scripts and protocols for the high-throughput pre-processing of large ensembles of single-cell, RNA-seq datasets are provided as an additional resource. Availability and Implementation: Binary executables for Windows, MacOS and Linux are available at http://sourceforge.net/projects/scell, source code and pre-processing scripts are available from https://github.com/diazlab/SCell. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: [email protected]
SCell: integrated analysis of single-cell RNA-seq data.
UnlabelledAnalysis of the composition of heterogeneous tissue has been greatly enabled by recent developments in single-cell transcriptomics. We present SCell, an integrated software tool for quality filtering, normalization, feature selection, iterative dimensionality reduction, clustering and the estimation of gene-expression gradients from large ensembles of single-cell RNA-seq datasets. SCell is open source, and implemented with an intuitive graphical interface. Scripts and protocols for the high-throughput pre-processing of large ensembles of single-cell, RNA-seq datasets are provided as an additional resource.Availability and implementationBinary executables for Windows, MacOS and Linux are available at http://sourceforge.net/projects/scell, source code and pre-processing scripts are available from https://github.com/diazlab/SCellSupplementary information: Supplementary data are available at Bioinformatics [email protected]