arXiv subjects

Partha P. Mitra

Publications and source records attributed to Partha P. Mitra.

27 records · Page 2Linked to original sources

arXiv2011

Statistical analysis of co-expression properties of sets of genes in the mouse brain

We propose a quantitative method to estimate the statistical properties of sets of genes for which expression data are available and co-registered to a reference atlas of the brain. It is based on graph-theoretic properties of co-expression coefficients between pairs of genes. We apply this method to mouse genes from the Allen Gene Expression Atlas. Co-expression patterns of a list of several hundreds of genes related to addiction are analyzed, using ISH data produced for the mouse brain at the Allen Institute. It appears that large subsets of this set of genes are much more highly co-expressed than expected by chance.

q-bio.QM↗

arXiv2011

Marker Genes for Anatomical Regions in the Brain: Insights from the Allen Gene Expression Atlas

Quantitative criteria are proposed to identify genes (and sets of genes) whose expression marks a specific brain region (or a set of brain regions). Gene-expression energies, obtained for thousands of mouse genes by numerization of in-situ hybridization images in the Allen Gene Expression Atlas, are used to test these methods in the mouse brain. Individual genes are ranked using integrals of their expression energies across brain regions. The ranking is generalized to sets of genes and the problem of optimal markers of a classical region receives a linear-algebraic solution. Moreover, the goodness of the fitting of the expression profile of a gene to the profile of a brain region is closely related to the co-expression of genes. The geometric interpretation of this fact leads to a quantitative criterion to detect markers of pairs of brain regions. Local properties of the gene-expression profiles are also used to detect genes that separate a given grain region from its environment.

q-bio.QM↗

arXiv2011

Algorithmic choice of coordinates for injections into the brain: encoding a neuroanatomical atlas on a grid

Given an atlas of the brain and a number of injections to be performed in order to map out the connections between parts of the brain, we propose an algorithm to compute the coordinates of the injections. The algorithm is designed to sample the brain in the most homogeneous way compatible with the separation of brain regions. It can be applied to other species for which a neuroanatomical atlas is available. The computation is tested on the annotation at a resolution of 25 microns corresponding to the Allen Reference Atlas, which is hierarchical and consists of 209 regions. The resulting injection coordinates are being used for the injection protocol of the Mouse Brain Architecture project. Due to its large size and layered structure, the cerebral cortex is treated in a separate algorithm, which is more adapted to its geometry.

q-bio.QM↗

arXiv2009

Compressed Genotyping

Significant volumes of knowledge have been accumulated in recent years linking subtle genetic variations to a wide variety of medical disorders from Cystic Fibrosis to mental retardation. Nevertheless, there are still great challenges in applying this knowledge routinely in the clinic, largely due to the relatively tedious and expensive process of DNA sequencing. Since the genetic polymorphisms that underlie these disorders are relatively rare in the human population, the presence or absence of a disease-linked polymorphism can be thought of as a sparse signal. Using methods and ideas from compressed sensing and group testing, we have developed a cost-effective genotyping protocol. In particular, we have adapted our scheme to a recently developed class of high throughput DNA sequencing technologies, and assembled a mathematical framework that has some important distinctions from 'traditional' compressed sensing ideas in order to address different biological and technical constraints.

q-bio.GN↗

arXiv2009

A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale

In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly sparse. Such knowledge is however critical both for basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brain-wide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brain-wide coverage; validated and extensible experimental techniques suitable for standardization and automation; centralized, open access data repository; compatibility with existing resources, and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additional efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.

q-bio.NC↗

arXiv2006

Bending a slab of neural tissue

In comparative and developmental neuroanatomy one encounters questions regarding the deformation of neural tissue under stress. The motivation of this note is an observation (Barbas {\it et al}) that at cortical folds or gyri, the layers of neural tissue show relative thickening or thinning of upper or deep layers. In general, the material properties of a slab of neural tissue are not known, and even if known, would probably lead to a difficult problem in elasticity theory. Here a simple argument is presented to show that bending an elastic slab should produce a relative thickening of the layers on the inside of the bend. The argument is based on the incompressibility of the material and should therefore be fairly robust.

q-bio.TO↗

arXiv2005

A framework for detection and classification of events in neural activity

We present a method for the real time prediction of punctate events in neural activity, based on the time-frequency spectrum of the signal, applicable both to continuous processes like local field potentials (LFP) as well as to spike trains. We test it on recordings of LFP and spiking activity acquired previously from the lateral intraparietal area (LIP) of macaque monkeys performing a memory-saccade task. In contrast to earlier work, where trials with known start times were classified, our method detects and classifies trials directly from the data. It provides a means to quantitatively compare and contrast the content of LFP signals and spike trains: we find that the detector performance based on the LFP matches the performance based on spike rates. The method should find application in the development of neural prosthetics based on the LFP signal. Our approach uses a new feature vector, which we call the 2D cepstrum.

q-bio.NC↗

arXiv2000

Nonlinear limits to the information capacity of optical fiber communications

The exponential growth in the rate at which information can be communicated through an optical fiber is a key element in the so called information revolution. However, like all exponential growth laws, there are physical limits to be considered. The nonlinear nature of the propagation of light in optical fiber has made these limits difficult to elucidate. Here we obtain basic insights into the limits to the information capacity of an optical fiber arising from these nonlinearities. The key simplification lies in relating the nonlinear channel to a linear channel with multiplicative noise, for which we are able to obtain analytical results. In fundamental distinction to the linear additive noise case, the capacity does not grow indefinitely with increasing signal power, but has a maximal value. The ideas presented here have broader implications for other nonlinear information channels, such as those involved in sensory transduction in neurobiology. These have been often examined using additive noise linear channel models, and as we show here, nonlinearities can change the picture qualitatively.

physics.data-an↗

arXiv1993

Understanding Far-Infrared Absorption in the S=1 Antiferromagnetic Chain Compound NENP

Infrared transmission measurements on the $S=1$ antiferromagnetic chain compound NENP in applied magnetic fields show a sharp absorption line at the field-shifted Haldane gap. This violates a wave-vector selection rule of the Hamiltonian normally used for NENP, as the gap excitations occur at the Brillouin zone boundary. We argue that the crystal structure admits terms which can explain the absorption lines. In addition, in an applied field, staggered orientations of the g-tensors produce a staggered magnetic field. This can explain the observation of a finite gap at all applied fields.

cond-mat↗