Bobby Kasthuri - Academia.edu (original) (raw)

Papers by Bobby Kasthuri

Nature Communications, Dec 3, 2023

The neotenous, or delayed, development of primate neurons, particularly human ones, is thought to... more The neotenous, or delayed, development of primate neurons, particularly human ones, is thought to underlie primate-specific abilities like cognition. We tested whether synaptic development follows suit-would synapses, in absolute time, develop slower in longer-lived, highly cognitive species like nonhuman primates than in shorter-lived species with less human-like cognitive abilities, e.g., the mouse? Instead, we find that excitatory and inhibitory synapses in the male Mus musculus (mouse) and Rhesus macaque (primate) cortex form at similar rates, at similar times after birth. Primate excitatory and inhibitory synapses and mouse excitatory synapses also prune in such an isochronic fashion. Mouse inhibitory synapses are the lone exception, which are not pruned and instead continuously added throughout life. The monotony of synaptic development clocks across species with disparate lifespans, experiences, and cognitive abilities argues that such programs are likely orchestrated by genetic events rather than experience.

arXiv (Cornell University), Apr 12, 2016

Imaging methods used in modern neuroscience experiments are quickly producing large amounts of da... more Imaging methods used in modern neuroscience experiments are quickly producing large amounts of data capable of providing increasing amounts of knowledge about neuroanatomy and function. A great deal of information in these datasets is relatively unexplored and untapped. One of the bottlenecks in knowledge extraction is that often there is no feedback loop between the knowledge produced (e.g., graph, density estimate, or other statistic) and the earlier stages of the pipeline (e.g., acquisition). We thus advocate for the development of sample-to-knowledge discovery pipelines that one can use to optimize acquisition and processing steps with a particular end goal (i.e., piece of knowledge) in mind. We therefore propose that optimization takes place not just within each processing stage but also between adjacent (and non-adjacent) steps of the pipeline. Furthermore, we explore the existing categories of knowledge representation and models to motivate the types of experiments and analysis needed to achieve the ultimate goal. To illustrate this approach, we provide an experimental paradigm to answer questions about large-scale synaptic distributions through a multimodal approach combining X-ray microtomography and electron microscopy.

arXiv (Cornell University), Oct 11, 2021

Feedback is ubiquitous in both biological and engineered control systems. In biology, in addition... more Feedback is ubiquitous in both biological and engineered control systems. In biology, in addition to typical feedback between plant and controller, we observe feedback pathways within control systems, which we call internal feedback pathways (IFPs), that are often very complex. IFPs are most familiar in neural systems, our primary motivation, but they appear everywhere from bacterial signal transduction to the human immune system. In this paper, we describe these very different motivating examples and introduce the concepts necessary to explain their complex IFPs, particularly the severe speed-accuracy tradeoffs that constrain the hardware in biology. We also sketch some minimal theory for extremely simplified toy models that nevertheless highlight the importance of diversity-enabled sweet spots (DESS) in mitigating the impact of hardware tradeoffs. For more realistic models, standard modern and robust control theory can give some insights into previously cryptic IFPs, and the new System Level Synthesis theory expands this substantially. These additional theories explaining IFPs will be explored in more detail in several companion papers.

Bulletin of the American Physical Society, Jun 15, 2011

Bioengineering

The COVID-19 pandemic has brought attention to the need for developing effective respiratory supp... more The COVID-19 pandemic has brought attention to the need for developing effective respiratory support that can be rapidly implemented during critical surge capacity scenarios in healthcare settings. Lung support with bubble continuous positive airway pressure (B-CPAP) is a well-established therapeutic approach for supporting neonatal patients. However, the effectiveness of B-CPAP in larger pediatric and adult patients has not been addressed. Using similar principles of B-CPAP pressure generation, application of intermittent positive pressure inflations above CPAP could support gas exchange and high work of breathing levels in larger patients experiencing more severe forms of respiratory failure. This report describes the design and performance characteristics of the BubbleVent, a novel 3D-printed valve system that combined with commonly found tubes, hoses, and connectors can provide intermittent mandatory ventilation (IMV) suitable for adult mechanical ventilation without direct elec...

arXiv (Cornell University), Aug 6, 2012

Correlative light and electron microscopy promises to combine molecular specificity with nanoscal... more Correlative light and electron microscopy promises to combine molecular specificity with nanoscale imaging resolution. However, there are substantial technical challenges including reliable co-registration of optical and electron images, and rapid optical signal degradation under electron beam irradiation. Here, we introduce a new approach to solve these problems: multi-color imaging of stable optical cathodoluminescence emitted in a scanning electron microscope by nanoparticles with controllable surface chemistry. We demonstrate well-correlated cathodoluminescence and secondary electron images using three species of semiconductor nanoparticles that contain defects providing stable, spectrally-distinguishable cathodoluminescence. We also demonstrate reliable surface functionalization of the particles. The results pave the way for the use of such nanoparticles for targeted labeling of surfaces to provide nanoscale mapping of molecular composition, indicated by cathodoluminescence color, simultaneously acquired with structural electron images in a single instrument.

2019 IEEE/ACM Third Workshop on Deep Learning on Supercomputers (DLS), 2019

Mapping all the neurons in the brain requires automatic reconstruction of entire cells from volum... more Mapping all the neurons in the brain requires automatic reconstruction of entire cells from volume electron microscopy data. The flood-filling network (FFN) architecture has demonstrated leading performance for segmenting structures from this data. However, the training of the network is computationally expensive. In order to reduce the training time, we implemented synchronous and data-parallel distributed training using the Horovod library, which is different from the asynchronous training scheme used in the published FFN code. We demonstrated that our distributed training scaled well up to 2048 Intel Knights Landing (KNL) nodes on the Theta supercomputer. Our trained models achieved similar level of inference performance, but took less training time compared to previous methods. Our study on the effects of different batch sizes on FFN training suggests ways to further improve training efficiency. Our findings on optimal learning rate and batch sizes agree with previous works.

2020 IEEE/ACM 2nd Annual Workshop on Extreme-scale Experiment-in-the-Loop Computing (XLOOP), 2020

We present a fully modular and scalable software pipeline for processing electron microscope (EM)... more We present a fully modular and scalable software pipeline for processing electron microscope (EM) images of brain slices into 3D visualization of individual neurons and demonstrate an end-to-end segmentation of a large EM volume using a supercomputer. Our pipeline scales multiple packages used by the EM community with minimal changes to the original source codes. We tested each step of the pipeline individually, on a workstation, a cluster, and a supercomputer. Furthermore, we can compose workflows from these operations using a Balsam database that can be triggered during the data acquisition or with the use of different front ends and control the granularity of the pipeline execution. We describe the implementation of our pipeline and modifications required to integrate and scale up existing codes. The modular nature of our environment enables diverse research groups to contribute to the pipeline without disrupting the workflow, i.e. new individual codes can be easily integrated for each step on the pipeline.

IEEE Transactions on Computational Imaging, 2021

Resolution level and reconstruction quality in nano-computed tomography (nano-CT) are in part lim... more Resolution level and reconstruction quality in nano-computed tomography (nano-CT) are in part limited by the stability of microscopes, because the magnitude of mechanical vibrations during scanning becomes comparable to the imaging resolution, and the ability of the samples to resist beam damage during data acquisition. In such cases, there is no incentive in recovering the sample state at different time steps like in time-resolved reconstruction methods, but instead the goal is to retrieve a single reconstruction at the highest possible spatial resolution and without any imaging artifacts. Here we propose a joint solver for imaging samples at the nanoscale with projection alignment, unwarping and regularization. Projection data consistency is regulated by dense optical flow estimated by Farneback's algorithm, leading to sharp sample reconstructions with less artifacts. Synthetic data tests show robustness of the method to Poisson and low-frequency background noise. Applicability of the method is demonstrated on two large-scale nano-imaging experimental data sets.

Neural cytoarchitecture is heterogeneous, varying both across and within brain regions. The consi... more Neural cytoarchitecture is heterogeneous, varying both across and within brain regions. The consistent identification of regions of interest is one of the most critical aspects in examining neurocircuitry, as these structures serve as the vital landmarks with which to map brain pathways. Access to continuous, three-dimensional volumes that span multiple brain areas not only provides richer context for identifying such landmarks, but also enables a deeper probing of the microstructures within. Here, we describe a three-dimensional X-ray microtomography imaging dataset of a well-known and validated thalamocortical sample, encompassing a range of cortical and subcortical structures. In doing so, we provide the field with access to a micron-scale anatomical imaging dataset ideal for studying heterogeneity of neural structure.

Scientific reports, Jan 7, 2018

Synchrotron-based X-ray tomography offers the potential for rapid large-scale reconstructions of ... more Synchrotron-based X-ray tomography offers the potential for rapid large-scale reconstructions of the interiors of materials and biological tissue at fine resolution. However, for radiation sensitive samples, there remain fundamental trade-offs between damaging samples during longer acquisition times and reducing signals with shorter acquisition times. We present a deep convolutional neural network (CNN) method that increases the acquired X-ray tomographic signal by at least a factor of 10 during low-dose fast acquisition by improving the quality of recorded projections. Short-exposure-time projections enhanced with CNNs show signal-to-noise ratios similar to long-exposure-time projections. They also show lower noise and more structural information than low-dose short-exposure acquisitions post-processed by other techniques. We evaluated this approach using simulated samples and further validated it with experimental data from radiation sensitive mouse brains acquired in a tomographi...

Microscopy and Microanalysis, 2016

The rodent brain is organized with length scales spanning centimeters to nanometers-6 orders of m... more The rodent brain is organized with length scales spanning centimeters to nanometers-6 orders of magnitude [1]. At the centimeter scale, the brain consist of lobes of cortex, the cerebellum, the brainstem and the spinal cord. The millimeter scale have neurons arranged in columns, layers, or otherwise clustered. Recent technological imaging advances allow the generation of neuronal datasets spanning the spatial range from nanometers to 100s of microns [2,3]. Collecting a 1 mm 3 volume dataset of brain tissue at 4 nm x-y resolution using the fastest signal-beam SEM would require ~6 years. To move to the next length and volume scale of neuronal circuits requires several technological advances. The multibeam scanning electron microscope (mSEM) represents a transformative imaging technology that enables neuroscientists to tackle millimeter scale cortical circuit problems. In this work we describe a workflow from tissue harvest to imaging that will generate a 2 petabyte dataset (> 300,000,000 images) of rat visual cortex imaged at a 4nm x 4nm x-y (Nyquist sampling of membranes) and 30nm section thickness in less than 6 months.

We propose a new gradient-domain technique for processing registered EM image stacks to remove th... more We propose a new gradient-domain technique for processing registered EM image stacks to remove the inter-image discontinuities while preserving intra-image detail. To this end, we process the image stack by first performing anisotropic diffusion to smooth the data along the slice axis and then solving a screened-Poisson equation within each slice to reintroduce the detail. The final image stack is both continuous across the slice axis (facilitating the tracking of information between slices) and maintains sharp details within each slice (supporting automatic feature detection). To support this editing, we describe the implementation of the first multigrid solver designed for efficient gradient domain processing of large, out-of-core, voxel grids.

IEEE Transactions on Visualization and Computer Graphics, 2014

Fig. 1: Proofreading with Dojo. We present a web-based application for interactive proofreading o... more Fig. 1: Proofreading with Dojo. We present a web-based application for interactive proofreading of automatic segmentations of connectome data acquired via electron microscopy. Split, merge and adjust functionality enables multiple users to correct the labeling of neurons in a collaborative fashion. Color-coded structures can be explored in 2D and 3D.

The Journal of Physiology, 2000

This has led to the suggestion that these oscillations play a role in these behaviours. However, ... more This has led to the suggestion that these oscillations play a role in these behaviours. However, the function of this oscillatory activity in terms of neuronal signal processing remains unknown.

Nature Protocols, 2012

Conventional heavy metal post staining methods on thin sections lend contrast but often cause con... more Conventional heavy metal post staining methods on thin sections lend contrast but often cause contamination. To avoid this problem, we tested several en bloc staining techniques to contrast tissue in serial sections mounted on solid substrates for examination by Field Emission Scanning Electron Microscope (FESEM). Because FESEM section imaging requires that specimens have higher contrast and greater electrical conductivity than transmission electron microscope (TEM) samples, our technique utilizes osmium impregnation (OTO) to make the samples conductive while heavily staining membranes for segmentation studies. Combining this step with other classic heavy metal en bloc stains including uranyl acetate, lead aspartate, copper sulfate and lead citrate produced clean, highly contrasted TEM and SEM samples of insect, fish, and mammalian nervous system. This protocol takes 7-15 days to prepare resin embedded tissue, cut sections and produce serial section images. The authors of this manuscript declare that they have no competing financial interests. Author contributions JB developed the staining concept, prepared the fish and Drosophila samples and prepared the manuscript. JCT, NK, and RS imaged the Drosophila sections. RS assisted with the sectioning, imaging and overall block quality assessment. KH, RS, JCT and NK improved ultra thin sectioning and collection. KH developed the method of collecting ultrathin sections on tape and built the ATUM devices used. JWL helped motivate the effort to find better en bloc staining protocols, oversaw all the imaging experiments that were carried out in his laboratory and helped interpret the image data. SJS helped motivate the effort to improve en bloc staining, and oversaw and assisted with imaging experiments carried out at Stanford.

Microscopy and Microanalysis, 2006

Extended abstract of a paper presented at Microscopy and Microanalysis 2006 in Chicago, Illinois,... more Extended abstract of a paper presented at Microscopy and Microanalysis 2006 in Chicago, Illinois, USA, July 30 – August 3, 2005

Cell, 2013

The endoplasmic reticulum (ER) often forms stacked membrane sheets, an arrangement that is likely... more The endoplasmic reticulum (ER) often forms stacked membrane sheets, an arrangement that is likely required to accommodate a maximum of membrane-bound polysomes for secretory protein synthesis. How sheets are stacked is unknown. Here, we used improved staining and automated ultrathin sectioning electron microscopy methods to analyze stacked ER sheets in neuronal cells and secretory salivary gland cells of mice. Our results show that stacked ER sheets form a continuous membrane system in which the sheets are connected by twisted membrane surfaces with helical edges of left-or right-handedness. The three-dimensional structure of tightly stacked ER sheets resembles a parking garage, in which the different levels are connected by helicoidal ramps. A theoretical model explains the experimental observations and indicates that the structure corresponds to a minimum of elastic energy of sheet edges and surfaces. The structure allows the dense packing of ER sheets in the restricted space of a cell.