Slipping into Sleep: neurodynamics of alertness transitions in humans and fruit flies

The ability to react to events in the external world determines the fate of every living organism, this general state of readiness is called as ’alertness’. What happens to neurodynamics in the brain when alertness fades away as we fall asleep? How is behaviour affected? These questions will help us understand the organizing principles in the brain and functions of sleep itself. Here I use two distant animal models, the richness in behaviour and complexity of the human brain to understand how alertness transitions affects attention; and the experimental flexibility of the fruit fly, to understand its effect over longer time intervals. I first develop an objective method to track alertness using Electroencephalography (EEG). Then, I investigate the behavioural dynamics using an auditory spatial attention task while participants fall asleep. By using multilevel modelling and psychophysics, I show that participants systematically misclassify tones from the left side when drowsy, and further with a hierarchical drift diffusion model (HDDM) show how drift-rate (evidence accumulation) explains errors. Then, I show convergent evidence in the neural dynamics using multivariate pattern analysis (MVPA). Next, I probe the effect of handedness on the same task. Handedness affects behaviour only under drowsy condition and I show how neural dynamics are affected by a combination of handedness and alertness. To approach alertness transitions in a system with reduced neural complexity, I explore those dynamics in the fruit fly (Drosophila melanogaster), using both single and multichannel local field potential (LFP) data to show how alertness transitions and sleep modulate different regions of the fly brain. Further, I validate the results by converging evidence from causal manipulations. Finally, I discuss how the mapping of alertness transitions -under natural conditions- can help us understand fundamental questions in neuroscience such as the functions of sleep or the mechanisms of general anaesthesia.Gates Cambridg

Novel mutations of the carbohydrate sulfotransferase-6 (CHST6) gene causing macular corneal dystrophy in India

Purpose: Macular corneal dystrophy (MCD) is an autosomal recessive disorder characterized by progressive central haze, confluent punctate opacities and abnormal deposits in the cornea. It is caused by mutations in the carbohydrate sulfotransferase-6 (CHST6) gene, encoding corneal N-acetyl glucosamine-6-O-sulfotransferase (C-GlcNAc-6-ST). We screened the CHST6 gene for mutations in Indian families with MCD, in order to determine the range of pathogenic mutations. Methods: Genomic DNA was isolated from peripheral blood leukocytes of patients with MCD and normal controls. The coding regions of the CHST6 gene were amplified using three pairs of primers and amplified products were directly sequenced. Results: We identified 22 (5 nonsense, 5 frameshift, 2 insertion, and 10 missense) mutations in 36 patients from 31 families with MCD, supporting the conclusion that loss of function of this gene is responsible for this corneal disease. Seventeen of these mutations are novel. Conclusions: These data highlight the allelic heterogeneity of macular corneal dystrophy in Indian patients

The natverse, a versatile toolbox for combining and analysing neuroanatomical data.

To analyse neuron data at scale, neuroscientists expend substantial effort reading documentation, installing dependencies and moving between analysis and visualisation environments. To facilitate this, we have developed a suite of interoperable open-source R packages called the natverse. The natverse allows users to read local and remote data, perform popular analyses including visualisation and clustering and graph-theoretic analysis of neuronal branching. Unlike most tools, the natverse enables comparison across many neurons of morphology and connectivity after imaging or co-registration within a common template space. The natverse also enables transformations between different template spaces and imaging modalities. We demonstrate tools that integrate the vast majority of Drosophila neuroanatomical light microscopy and electron microscopy connectomic datasets. The natverse is an easy-to-use environment for neuroscientists to solve complex, large-scale analysis challenges as well as an open platform to create new code and packages to share with the community

The natverse, a versatile toolbox for combining and analysing neuroanatomical data.

To analyse neuron data at scale, neuroscientists expend substantial effort reading documentation, installing dependencies and moving between analysis and visualisation environments. To facilitate this, we have developed a suite of interoperable open-source R packages called the natverse. The natverse allows users to read local and remote data, perform popular analyses including visualisation and clustering and graph-theoretic analysis of neuronal branching. Unlike most tools, the natverse enables comparison across many neurons of morphology and connectivity after imaging or co-registration within a common template space. The natverse also enables transformations between different template spaces and imaging modalities. We demonstrate tools that integrate the vast majority of Drosophila neuroanatomical light microscopy and electron microscopy connectomic datasets. The natverse is an easy-to-use environment for neuroscientists to solve complex, large-scale analysis challenges as well as an open platform to create new code and packages to share with the community

Information flow, cell types and stereotypy in a full olfactory connectome

Funder: Howard Hughes Medical Institute; FundRef: http://dx.doi.org/10.13039/100000011The hemibrain connectome provides large-scale connectivity and morphology information for the majority of the central brain of Drosophila melanogaster. Using this data set, we provide a complete description of the Drosophila olfactory system, covering all first, second and lateral horn-associated third-order neurons. We develop a generally applicable strategy to extract information flow and layered organisation from connectome graphs, mapping olfactory input to descending interneurons. This identifies a range of motifs including highly lateralised circuits in the antennal lobe and patterns of convergence downstream of the mushroom body and lateral horn. Leveraging a second data set we provide a first quantitative assessment of inter- versus intra-individual stereotypy. Comparing neurons across two brains (three hemispheres) reveals striking similarity in neuronal morphology across brains. Connectivity correlates with morphology and neurons of the same morphological type show similar connection variability within the same brain as across two brains

natverse/natmanager: cran version 0.5.0

switch to pak as default installer (should be faster and simpler) dev: simpler/faster v2 r-lib/actions by @jefferis in https://github.com/natverse/natmanager/pull/20 dev: set up weekly natverse build by @jefferis in https://github.com/natverse/natmanager/pull/21 Switch to Greg as maintainer Full Changelog: https://github.com/natverse/natmanager/compare/v0.4.9...v0.5.

On the q-analogues of the Zassenhaus formula for disentangling exponential operators

To our dear friend Srinivasa Rao with admiration, affection, and best wishes on his sixtieth birthday Katriel, Rasetti and Solomon introduced a q-analogue of the Zassenhaus · · ·, where A and B are two formula written as e (A+B) q = eA q eBq ec2 q ec3 q ec4 q ec5 q generally noncommuting operators and ez q is the Jackson q-exponential, and derived the expressions for c2, c3 and c4. It is shown that one can also write e (A+B) q = eA q eBq eC