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Optics and the Brain, BRAIN 2021 - Part of Biophotonics Congress: Optics in the Life sciences 2021

作者： Wu, Jimin Yan, Dong Boominathan, Vivek Adams, Jesse K. Veeraraghavan, Ashok Robinson, Jacob T. Department of Bioengineering Rice University 6100 Main Street HoustonTX77005 United States Applied Physics Program Rice University 6100 Main Street HoustonTX77005 United States Department of Electrical and Computer Engineering Rice University 6100 Main Street HoustonTX77005 United States Department of Neuroscience Baylor College of Medicine One Baylor Plaza HoustonTX77030 United States Department of Computer Science Rice University 6100 Main Street HoustonTX77005 United States

We developed a lensless microscope with small, inexpensive form factor, large field-of-view (FOV) and cellular resolution for fluorescence imaging. Proof-of-principle measurements with "Bio-FlatScope" are pr... 详细信息

ISBN: (纸本)9781557528209

关键词： Fluorescence imaging

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Advanced Methods for Connectome-Based Predictive Modeling of Human Intelligence: A Novel Approach Based on Individual Differences in Cortical Topography

arXiv

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arXiv 2022年

作者： Anderson, Evan D. Wilcox, Ramsey Nayak, Anuj Zwilling, Christopher Robles-Granda, Pablo Kim, Been Varshney, Lav R. Barbey, Aron K. Neuroscience Program University of Illinois UrbanaIL United States Department of Psychology University of Illinois UrbanaIL United States Department of Electrical & Computer Engineering University of Illinois UrbanaIL United States Beckman Institute University of Illinois UrbanaIL United States Department of Computer Science University of Illinois UrbanaIL United States Google Brain Mountan View CA United States

Individual differences in human intelligence can be modeled and predicted from in vivo neurobiological connectivity. Many established modeling frameworks for predicting intelligence, however, discard higher-order information about individual differences in brain network topology, and show only moderate performance when generalized to make predictions in out-of-sample subjects. In this paper, we propose that connectome-based predictive modeling, a common predictive modeling framework for neuroscience data, can be productively modified to incorporate information about brain network topology and individual differences via the incorporation of bagged decision trees and the network based statistic. These modifications produce a novel predictive modeling framework that leverages individual differences in cortical tractography to generate accurate regression predictions of intelligence scores. Network topology-based feature selection provides for natively interpretable networks as input features, increasing the model's explainability. Investigating the proposed modeling framework's efficacy, we find that advanced connectome-based predictive modeling generates neuroscience predictions that account for a significantly greater proportion of variance in general intelligence scores than previously established methods, advancing our scientific understanding of the network architecture that underlies human intelligence. © 2022, CC BY-SA.

关键词： Forecasting

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Implantable Biosensor for Continuous Serotonin Detection in Freely Moving Crayfish

Implantable Biosensor for Continuous Serotonin Detection in ...

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International Conference on Solid State Sensors and Actuators (TRANSDUCERS)

作者： Jinjing Han Tawen Ho Justin M. Stine Michael A. Straker Jens Herberholz Reza Ghodssi Department of Electrical and Computer Engineering University of Maryland College Park MD USA Institute for System Research University of Maryland College Park MD USA Robert E. Fischell Institute for Biomedical Devices University of Maryland College Park MD USA Department of Psychology University of Maryland College Park MD USA Program in Neuroscience and Cognitive Science University of Maryland College Park MD USA Fischell Department of Bioengineering University of Maryland College Park MD USA

This work presents, for the first time, an implantable biosensor for continuous in vivo serotonin (5-HT) monitoring in freely moving crayfish. 5-HT is an important neurotransmitter that regulates animal behaviors. Conventional methods for detecting 5-HT do not provide real-time information. Our approach facilitates continuous electrochemical monitoring of 5-HT levels without impeding animal natural behavior. The sensing system shows a linear range of 0.4 - 1.2 μΜ with a sensitivity of 0.07 μΑ/μΜ for 5-HT detection. With a 3D-printed package, the sensor can be easily attached to crayfish dorsal carapace allowing electrodes implantation into crayfish heart to monitor neurohormonal dynamics of 5-HT. The implantable biosensor system displayed a significant increase in oxidation currents after 5-HT injections. The device successfully demonstrates the application for in vivo detection of 5-HT in the hemolymph (i.e., blood) of freely behaving crayfish underwater.

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Including Facial Expressions in Contextual Embeddings for Sign Language Generation

arXiv

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arXiv 2022年

作者： Viegas, Carla Inan, Mert Quandt, Lorna Alikhani, Malihe Stella AI Pittsburgh United States Language Technologies Institute Carnegie Mellon University Pittsburgh United States Computer Science Department School of Computing and Information University of Pittsburgh Pittsburgh United States Educational Neuroscience Program Gallaudet University D.C Washington United States

State-of-the-art sign language generation frameworks lack expressivity and naturalness which is the result of only focusing manual signs, neglecting the affective, grammatical and semantic functions of facial expressions. The purpose of this work is to augment semantic representation of sign language through grounding facial expressions. We study the effect of modeling the relationship between text, gloss, and facial expressions on the performance of the sign generation systems. In particular, we propose a Dual Encoder Transformer able to generate manual signs as well as facial expressions by capturing the similarities and differences found in text and sign gloss annotation. We take into consideration the role of facial muscle activity to express intensities of manual signs by being the first to employ facial action units in sign language generation. We perform a series of experiments showing that our proposed model improves the quality of automatically generated sign language. © 2022, CC BY.

关键词： Semantics

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How to Stay Curious while avoiding Noisy TVs using Aleatoric Uncertainty Estimation

arXiv

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arXiv 2021年

作者： Mavor-Parker, Augustine N. Young, Kimberly A. Barry, Caswell Griffin, Lewis D. Centre for Artificial Intelligence University College London United Kingdom Department of Cell and Developmental Biology University College London United Kingdom Boston University Center for Systems Neuroscience Graduate Program for Neuroscience United States Department of Computer Science University College London United Kingdom

When extrinsic rewards are sparse, artificial agents struggle to explore an environment. Curiosity, implemented as an intrinsic reward for prediction errors, can improve exploration but it is known to fail when faced with action-dependent noise sources ('noisy TVs'). In an attempt to make exploring agents robust to noisy TVs, we present a simple solution: aleatoric mapping agents (AMAs). AMAs are a novel form of curiosity that explicitly ascertain which state transitions of the environment are unpredictable, even if those dynamics are induced by the actions of the agent. This is achieved by generating separate forward predictions for the mean and aleatoric uncertainty of future states, with the aim of reducing intrinsic rewards for those transitions that are unpredictable. We demonstrate that in a range of environments AMAs are able to circumvent action-dependent stochastic traps that immobilise conventional curiosity driven agents. Furthermore, we demonstrate empirically that other common exploration approaches-previously thought to be immune to agent-induced randomness-can be trapped by stochastic dynamics. Code to reproduce our experiments is provided. © 2021, CC BY.

关键词： Stochastic systems

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Electrochemical measurement of serotonin by Au-CNT electrodes fabricated on microporous cell culture membranes

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Microsystems & Nanoengineering 2020年第1期6卷 494-506页

作者： Ashley A.Chapin Pradeep R.Rajasekaran David N.Quan Liangbing Hu Jens Herberholz William E.Bentley Reza Ghodssi Fischell Department of Bioengineering College ParkMD 20742USA Institute for Systems Research College ParkMD 20740USA Department of Materials Science and Engineering College ParkMD 20740USA Department of Psychology and Neuroscience and Cognitive Science Program College ParkMD 20740USA Institute for Bioscience and Biotechnology Research RockvilleMD 20850USA Robert E.Fischell Institute for Biomedical Devices RockvilleMD 20850USA Department of Electrical and Computer Engineering College ParkMD 20742USA

Gut–brain axis(GBA)communication relies on serotonin(5-HT)signaling between the gut epithelium and the peripheral nervous system,where 5-HT release patterns from the basolateral(i.e.,bottom)side of the epithelium activate nerve *** have been few quantitative studies of this gut-neuron signaling due to a lack of real-time measurement tools that can access the basolateral gut *** vitro platforms allow quantitative studies of cultured gut tissue,but they mainly employ offline and endpoint assays that cannot resolve dynamic molecular-release ***,we present the modification of a microporous cell culture membrane with carbon nanotube-coated gold(Au-CNT)electrodes capable of continuous,label-free,and direct detection of 5-HT at physiological *** characterization of single-walled carbon nanotube(SWCNT)-coated Au electrodes shows increased electroactive surface area,5-HT specificity,sensitivity,and saturation time,which are correlated with the CNT film drop-cast *** microliters of CNT films,with a 10-min saturation time,0.6μA/μM 5-HT sensitivity,and reliable detection within a linear range of 500 nM–10μM 5-HT,can be targeted for high-concentration,high-time-resolution 5-HT *** films(12.5μL)with a 2-h saturation time,4.5μA/μM 5-HT sensitivity,and quantitative detection in the linear range of 100 nM–1μM can target low concentrations with low time *** electrodes achieved continuous detection of dynamic diffusion across the porous membrane,mimicking basolateral 5-HT release from cells,and detection of cell-released 5-HT from separately cultured RIN14B cell ***-integrated cell culture systems such as this can improve in vitro molecular detection mechanisms and aid in quantitative GBA signaling studies.

关键词： release saturation dynamic

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Optogenetic Neural Probes: Fiberless, High-Density, Artifact-Free Neuromodulation : (Invited)

Optogenetic Neural Probes: Fiberless, High-Density, Artifact...

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International Electron Devices Meeting (IEDM)

作者： Eunah Ko Kanghwan Kim Mihály Vöröslakos Sungjin Oh György Buzsáki Kensall D. Wise Euisk Yoon Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA Center for BioMicrosystems Brain Science Institute Korea Institute of Science and Technology Seoul Korea Neuroscience Institute Langone Medical Center New York University New York NY USA Department of Biomedical Engineering University of Michigan Ann Arbor MI USA Center for Nanomedicine Institute for Basic Science (IBS) and Graduate Program of Nano Biomedical Engineering (Nano BME) Advanced Science Institute Yonsei University Seoul Korea

ISBN: (纸本)9781665489607

Evolution of “Michigan Probes” has enabled unraveling the connectivity of neurons at cellular resolution and their dynamic interaction within and across brain areas that underlie behavioral and cognitive functions. Recently, micro-LEDs were monolithically integrated for optogenetic neuromodulation at scale without requiring external optical fiber connection. The ‘hectoSTAR’ micro-LED optoelectrode features 256 recording electrodes and 128 stimulation micro-LEDs in four silicon micro-needle shanks, covering a large volume with 1.3-mm × 0.9-mm cross-sectional area located as deep as 6 mm inside the brain. Technical challenges to overcome in scaling of optogenetic probes will be discussed, followed by future direction.

关键词： Optical fibers Electrodes Brain Optogenetics Silicon Recording Optical fiber devices

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Learning Vector Quantized Shape Code for Amodal Blastomere Instance Segmentation

Learning Vector Quantized Shape Code for Amodal Blastomere I...

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IEEE International Symposium on Biomedical Imaging

作者： Won-Dong Jang Donglai Wei Xingxuan Zhang Brian Leahy Helen Yang James Tompkin Dalit Ben-Yosef Daniel Needleman Hanspeter Pfister School of Engineering and Applied Sciences Harvard University MA USA Boston College MA USA Department of Molecular and Cellular Biology Harvard University MA USA Harvard Graduate Program in Biophysics Harvard University MA USA Department of Computer Science Brown University RI USA Tel Aviv Sourasky Medical Center Fertility & IVF Institute Israel Dept. of Cell and Developmental Biology Sagol School of Neuroscience Tel Aviv University Israel

Blastomere instance segmentation is important for analyzing embryos’ abnormality. To measure the accurate shapes and sizes of blastomeres, their amodal segmentation is necessary. Amodal instance segmentation aims to recover an object’s complete silhouette even when the object is not fully visible. For each detected object, previous methods directly regress the target mask from input features. However, images of an object under different amounts of occlusion should have the same amodal mask output, making it harder to train the regression model. To alleviate the problem, we propose to classify input features into intermediate shape codes and recover complete object shapes. First, we pre-train the Vector Quantized Variational Autoencoder (VQ-VAE) model to learn these discrete shape codes from ground truth amodal masks. Then, we incorporate the VQ-VAE model into the amodal instance segmentation pipeline with an additional refinement module. We also detect an occlusion map to integrate occlusion information with a backbone feature. As such, our network faithfully detects bounding boxes of amodal objects. On an internal embryo cell image benchmark, the proposed method outperforms previous state-of-the-art methods. To show generalizability, we show segmentation results on the public KINS natural image benchmark. Our method would enable accurate measurement of blastomeres in In Vitro Fertilization (IVF) clinics, potentially increasing the IVF success rate.

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Beyond predictive R 2 : Quantile regression and non-equivalence tests reveal complex relationships of traits and polygenic scores

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The American Journal of Human Genetics 2025年第6期112卷 1363-1375页

作者： Joel Mefford Molly Smullen Felix Zhang Michal Sadowski Richard Border Andy Dahl Jonathan Flint Noah Zaitlen Semel Institute for Neuroscience and Human Behavior University of California Los Angeles Los Angeles CA USA Chan Medical School University of Massachusetts Worcester MA USA Department of Computer Science University of California Los Angeles Los Angeles CA USA Bioinformatics Interdepartmental Program University of California Los Angeles Los Angeles CA USA Department of Neurology University of California Los Angeles Los Angeles CA USA Department of Computational Medicine David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA Section of Genetic Medicine Department of Medicine University of Chicago Chicago IL USA Department of Psychiatry and Biobehavioral Sciences David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA

Polygenic scores (PGSs) are genetic predictions of trait values or disease risk that are increasingly finding applications in clinical predictive models and basic genetics research. However, the predictive value of a PGS can vary within similar population groups, depending on characteristics such as the environmental exposures, sex, age, or socioeconomic status of the individuals. To maximize the value of a PGS, approaches to screen trait-PGS pairs for evidence of such heterogeneity without having to specify the relevant exposure or individual characteristics would be useful. Here, in analyses from the UK Biobank, we show that a PGS’s predictive accuracy depends on the quantile of the phenotypic distribution to which the PGS is being applied. We quantify differences in predictive value across the phenotypic range using quantile regression linear models to estimate quantile-specific effect sizes for linear models of phenotype values as a function of PGS. Of 25 continuous traits, only three have no quantile-specific effect sizes that varied by at least 1.2-fold from the ordinary least squares estimate. Through simulation, we demonstrate that this heterogeneity of PGS predictive value can arise from gene-by-environment interactions. Our approach can be used to flag traits where the use of PGSs warrants extra caution, and perhaps stratification variables should be sought and used because PGSs perform substantially differently in portions of the sampled population than expected from quoted predictive R 2 or incremental R 2 values that represent average performance across a dataset.

关键词： polygenic score polygenic risk score PRS PGS quantile regression non-equivalence test equivalence test trend test gene-by-environment interaction heterogeneity

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Novel diamond shuttle to deliver flexible neural probe with reduced tissue compression

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Microsystems & Nanoengineering 2020年第1期6卷 903-915页

作者： Kyounghwan Na Zachariah J.Sperry Jiaao Lu Mihaly Voroslakos Saman S.Parizi Tim M.Bruns Euisik Yoon John P.Seymour Electrical Engineering&Computer Science Department University of MichiganAnn ArborMI 48105USA Biomedical Engineering Department University of MichiganAnn ArborMI 48105USA Biointerfaces Institute University of MichiganAnn ArborMI 48105USA The Neuroscience Institute New York UniversityNew YorkNY 10016USA Center for Nanomedicine Institute for Basic Science(IBS)Seoul 03722Korea Graduate Program of Nano Biomedical Engineering(Nano BME) Yonsei-IBS InstituteYonsei UniversitySeoul 03722Korea Vivian L Smith Department of Neurosurgery University of Texas Health Science CenterHoustonTX 77030USA Department of Electrical and Computer Engineering Rice UniversityHoustonTX 77005USA

The ability to deliver flexible biosensors through the toughest membranes of the central and peripheral nervous system is an important challenge in neuroscience and neural *** devices implanted through dura mater and thick epineurium would ideally create minimal compression and acute damage as they reach the neurons of *** demonstrate that a three-dimensional diamond shuttle can be easily made with a vertical support to deliver ultra-compliant polymer microelectrodes(4.5-µm thick)through dura mater and thick *** diamond shuttle has 54%less cross-sectional area than an equivalently stiff silicon shuttle,which we simulated will result in a 37%reduction in blood vessel *** also discovered that higher frequency oscillation of the shuttle(200Hz)significantly reduced tissue compression regardless of the insertion speed,while slow speeds also independently reduced tissue *** and recording performance are demonstrated in rat and feline models,but the large design space of these tools are suitable for research in a variety of animal models and nervous system targets.

关键词： sectional neural thick

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