scholarly journals Behavioral clusters revealed by end-to-end decoding from microendoscopic imaging

2021 ◽  
Author(s):  
Chia-Jung Chang ◽  
Wei Guo ◽  
Jie Zhang ◽  
Jon Newman ◽  
Shao-Hua Sun ◽  
...  
Keyword(s):  
Parameter Tuning ◽  
Relevant Information ◽  
User Input ◽  
Functional Clustering ◽  
Saliency Maps ◽  
Behavioral Variables ◽  
Roi Extraction ◽  
Freely Behaving ◽  
End To End

AbstractIn vivo calcium imaging using head-mounted miniature microscopes enables tracking activity from neural populations over weeks in freely behaving animals. Previous studies focus on inferring behavior from a population of neurons, yet it is challenging to extract neuronal signals given out-of-focus fluorescence in endoscopic data. Existing analysis pipelines include regions of interest (ROIs) identification, which might lose relevant information from false negatives or introduce unintended bias from false positives. Moreover, these methods often require prior knowledge for parameter tuning and are time-consuming for implementation. Here, we develop an end-to-end decoder to predict the behavioral variables directly from the raw microendoscopic images. Our framework requires little user input and outperforms existing decoders that need ROI extraction. We show that neuropil/background residuals carry additional behaviorally relevant information. Video analysis further reveals an optimal decoding window and dynamics between residuals and cells. Critically, saliency maps reveal the emergence of video-decomposition across our decoder, and identify distinct clusters representing different behavioral aspects. Together, we present a framework that is efficient for decoding behavior from microendoscopic imaging, and may help discover functional clustering for a variety of imaging studies.

Photocontrolling Microtubule Dynamics with Photoswitchable Chemical Reagents

2021 ◽  
Author(s):  
Oliver Thorn-Seshold ◽  
Joyce Meiring
Keyword(s):  
3D Culture ◽  
3D Cell Culture ◽  
Relevant Information ◽  
Microtubule Dynamics ◽  
Model Organisms ◽  
Chemical Reagents ◽  
Cellular Assays ◽  
General Protein ◽  
Spatial Specificity

Microtubule dynamics can be inhibited with sub-second temporal resolution and cellular-scale spatial resolution, by using precise illuminations to optically pattern where and when photoswitchable microtubule-inhibiting chemical reagents exert their latent bioactivity. The recently-available reagents (SBTub, PST, STEpo, AzTax, PHTub) now enable researchers to use light to reversibly modulate microtubule-dependent processes in eukaryotes, in 2D and 3D cell culture as well as in vivo, across a variety of model organisms: with applications in fields from cargo transport to cell migration, cell division, and embryonic development.<br><br>However, a wide knowledge gap has remained in the literature, which has blocked further translation of these and many other classes of photopharmaceuticals. No generally-applicable procedures or workflows to establish biological assays using photopharmaceuticals have been published. Accordingly, the rate of adoption of photopharmaceutical tools in the broader chemical biology community (beyond the original chemical developers of the tools) has remained very low. Vital information about assay benchmarking for photoconversion, testing for isomer solubility, proving the retention of mechanism of action, estimating the limits of phototoxicity etc has either simply not been formalised in the literature, or has remained buried in diverse reports without being unified and codified for an audience beyond that of synthetic organic chemists.<br><br>Here we have developed a robust four-step assay establishment procedure to optimise assay parameters for achieving reliable photocontrol over microtubule dynamics, that is applicable to diverse families of photoswitchable inhibitors. This procedure also controls for these common sources of irreproducibility and includes numerous troubleshooting steps. We also collect together the relevant information for non-chemist "users" such as microscopists and biologists, to introduce the theory of small molecule photoswitching; the unique features, usage requirements, and limitations that photoswitchable chemical reagents have; and the specific performance features of the major classes of photoswitchable microtubule inhibitors that are currently available; to highlight their properties that suit them to different applications. The generally-applicable workflows that we present allow establishing cellular assays optically controlling microtubule dynamics in a temporally reversible fashion with spatial specificity down to a single selected cell within a field of view. These workflows and methods also equip the reader to tackle advanced uses of photoswitchable chemical reagents for general protein targets, in 3D culture and in vivo, and can represent an important bridge to reach the high-value biological applications that photopharmacology can promise.<br>

scholarly journals End-to-end automated cache-timing attack driven by Machine Learning

10.29007/nwj8 ◽  
2019 ◽  
Author(s):  
Sebastien Carré ◽  
Victor Dyseryn ◽  
Adrien Facon ◽  
Sylvain Guilley ◽  
Thomas Perianin
Keyword(s):  
Neural Network ◽  
Language Processing ◽  
Relevant Information ◽  
Security Threats ◽  
Cache Memories ◽  
Function Calls ◽  
Timing Data ◽  
Timing Attack ◽  
End To End ◽  
Timing Attacks

Cache timing attacks are serious security threats that exploit cache memories to steal secret information.We believe that the identification of a sequence of operations from a set of cache-timing data measurements is not a trivial step when building an attack. We present a recurrent neural network model able to automatically retrieve a sequence of function calls from cache-timings. Inspired from natural language processing, our model is able to learn on partially labelled data. We use the model to unfold an end-to-end automated attack on OpenSSL ECDSA on the secp256k1 curve. Contrary to most research, we did not need human processing of the traces to retrieve relevant information.

scholarly journals A Compact Head-Mounted Endoscope for In Vivo Calcium Imaging in Freely Behaving Mice

2018 ◽  
Vol 84 (1) ◽  
pp. e51 ◽  
Author(s):  
Alexander D. Jacob ◽  
Adam I. Ramsaran ◽  
Andrew J. Mocle ◽  
Lina M. Tran ◽  
Chen Yan ◽  
...  
Keyword(s):  
Calcium Imaging ◽  
Freely Behaving ◽  
In Vivo Calcium Imaging

scholarly journals EHSOD: CAM-Guided End-to-End Hybrid-Supervised Object Detection with Cascade Refinement

2020 ◽  
Vol 34 (07) ◽  
pp. 10778-10785
Author(s):  
Linpu Fang ◽  
Hang Xu ◽  
Zhili Liu ◽  
Sarah Parisot ◽  
Zhenguo Li
Keyword(s):  
Object Detection ◽  
State Of The Art ◽  
Detection System ◽  
Parameter Tuning ◽  
Heat Map ◽  
Level Data ◽  
End To End ◽  
Weakly Supervised ◽  
Yield State ◽  
Activation Heat

Object detectors trained on fully-annotated data currently yield state of the art performance but require expensive manual annotations. On the other hand, weakly-supervised detectors have much lower performance and cannot be used reliably in a realistic setting. In this paper, we study the hybrid-supervised object detection problem, aiming to train a high quality detector with only a limited amount of fully-annotated data and fully exploiting cheap data with image-level labels. State of the art methods typically propose an iterative approach, alternating between generating pseudo-labels and updating a detector. This paradigm requires careful manual hyper-parameter tuning for mining good pseudo labels at each round and is quite time-consuming. To address these issues, we present EHSOD, an end-to-end hybrid-supervised object detection system which can be trained in one shot on both fully and weakly-annotated data. Specifically, based on a two-stage detector, we proposed two modules to fully utilize the information from both kinds of labels: 1) CAM-RPN module aims at finding foreground proposals guided by a class activation heat-map; 2) hybrid-supervised cascade module further refines the bounding-box position and classification with the help of an auxiliary head compatible with image-level data. Extensive experiments demonstrate the effectiveness of the proposed method and it achieves comparable results on multiple object detection benchmarks with only 30% fully-annotated data, e.g. 37.5% mAP on COCO. We will release the code and the trained models.

scholarly journals GPCR-Based Dopamine Sensors—A Detailed Guide to Inform Sensor Choice for In Vivo Imaging

2020 ◽  
Vol 21 (21) ◽  
pp. 8048
Author(s):  
Marie A. Labouesse ◽  
Reto B. Cola ◽  
Tommaso Patriarchi
Keyword(s):  
In Vivo Imaging ◽  
Dynamic Range ◽  
New Techniques ◽  
Experimental Parameters ◽  
Sensor Properties ◽  
Molecular Specificity ◽  
Freely Behaving ◽  
The Brain ◽  
Da Release

Understanding how dopamine (DA) encodes behavior depends on technologies that can reliably monitor DA release in freely-behaving animals. Recently, red and green genetically encoded sensors for DA (dLight, GRAB-DA) were developed and now provide the ability to track release dynamics at a subsecond resolution, with submicromolar affinity and high molecular specificity. Combined with rapid developments in in vivo imaging, these sensors have the potential to transform the field of DA sensing and DA-based drug discovery. When implementing these tools in the laboratory, it is important to consider there is not a ‘one-size-fits-all’ sensor. Sensor properties, most importantly their affinity and dynamic range, must be carefully chosen to match local DA levels. Molecular specificity, sensor kinetics, spectral properties, brightness, sensor scaffold and pharmacology can further influence sensor choice depending on the experimental question. In this review, we use DA as an example; we briefly summarize old and new techniques to monitor DA release, including DA biosensors. We then outline a map of DA heterogeneity across the brain and provide a guide for optimal sensor choice and implementation based on local DA levels and other experimental parameters. Altogether this review should act as a tool to guide DA sensor choice for end-users.

GROUP EXPOSURE IN VIVO FOR AGORAPHOBICS (1974): A MULTIFACETED PILOT STUDY AND ITS IMPACT ON SUBSEQUENT AGORAPHOBIA RESEARCH

2000 ◽  
Vol 28 (4) ◽  
pp. 335-351 ◽  
Author(s):  
Iver Hand
Keyword(s):  
Data Quality ◽  
Information Quality ◽  
Relevant Information ◽  
Scientific Paper ◽  
Future Research ◽  
Behavioural Intervention ◽  
Behaviour Therapy ◽  
High Data ◽  
Cognitive Behavioural

This paper reviews the research in agoraphobia in four areas: (i) Is the group application of exposure in vivo really the most effective treatment for agoraphobia? (ii) Does high group cohesion really increase the power of group exposure? (iii) Was the exposure mode applied in this study actually the first cognitive-behavioural intervention in behaviour therapy of anxiety disorders? (iv) How often do agoraphobics really suffer from marital discord, and how does this affect the outcome of short-term, massed exposure-treatment? It describes the development of concepts and the evolution of knowledge, but it also points out the redundancies, misunderstandings and pitfalls in research that have hindered progress. This paper does not deal with the data quality of the studies reviewed; sometimes high data quality does not result in high information quality, and vice versa. This is therefore not a scientific paper but a non-comprehensive journey through the recent history of research in behaviour therapy for agoraphobia. It is hoped to give practice-relevant information for clinicians and some new ideas for future research.

scholarly journals In Vivo Analysis of Dynamic Tensile Stresses at Arterial End-to-end Anastomoses. Influence of Suture-line and Graft on Anastomotic Biomechanics

1999 ◽  
Vol 18 (6) ◽  
pp. 515-522 ◽  
Author(s):  
M Ulrich ◽  
N.-H Staalsen ◽  
C.B Djurhuus ◽  
T.D Christensen ◽  
H Nygaard ◽  
...  
Keyword(s):  
Suture Line ◽  
Tensile Stresses ◽  
In Vivo Analysis ◽  
End To End

Multispecialty Microsurgical Course Utilizing the Blue-Blood Chicken Thigh Model Significantly Improves Resident Comfort, Confidence, and Attitudes in Multiple Domains

2019 ◽  
Vol 36 (02) ◽  
pp. 142-150 ◽  
Author(s):  
Nikita O. Shulzhenko ◽  
Weifeng Zeng ◽  
Nicholas J. Albano ◽  
Sarah M. Lyon ◽  
Aaron M. Wieland ◽  
...  
Keyword(s):  
Technical Skill ◽  
Educational Models ◽  
Training Course ◽  
Ethical Implications ◽  
End To End ◽  
Case Presentations ◽  
High Level ◽  
Multiple Domains

Abstract Background The high level of technical skill required by microsurgical procedures has prompted the development of in vitro educational models. Current models are cost-ineffective, unrealistic, or carry ethical implications and are utilized as isolated experiences within single surgical specialties. The purpose of this study was to assess the educational and interprofessional effect of a microsurgical training course utilizing the nonliving “Blue-Blood” chicken thigh model (BBCTM) in a multidisciplinary environment. Methods A 10-hour course was developed integrating didactic lectures, case presentations, and one-on-one practical sessions utilizing hydrogel microvessels and the BBCTM. Pre- and postcourse surveys were administered assessing participants' self-reported comfort and confidence within fundamental microsurgical domains, assessments of the models utilized, and the effects of a multidisciplinary environment on the experience. Results A total of 19 residents attended the course on two separate occasions (n = 10 and n = 9, respectively). Respondents varied from postgraduate year-2 (PGY-2) to PGY-6+ and represented plastic and reconstructive surgery (n = 10), urology (n = 6), and otolaryngology (n = 3). On average, each participant performed 4.3 end-to-end, 1.3 end-to-side, and 0.4 coupler-assisted anastomoses. Following the course, participants felt significantly more comfortable operating a microscope and handling microsurgical instruments. They felt significantly more confident handling tissues, manipulating needles, microdissecting, performing end-to-end anastomoses, performing end-to-side anastomoses, using an anastomotic coupler, and declaring anastomoses suitable (all p < 0.05). The majority of participants believed that the use of live animals in the course would have minimally improved their learning. All but two respondents believed the course improved their awareness of the value of microsurgery in other specialties “very much” or “incredibly.” Conclusion A microsurgical training course utilizing nonliving models such as the “BBCTM significantly improves resident comfort and confidence in core operative domains and offers an in vivo experience without the use of live animals. Multispecialty training experiences in microsurgery are beneficial, desired, and likely underutilized.

scholarly journals Most Relevant Spectral Bands Identification for Brain Cancer Detection Using Hyperspectral Imaging

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5481 ◽  
Author(s):  
Beatriz Martinez ◽  
Raquel Leon ◽  
Himar Fabelo ◽  
Samuel Ortega ◽  
Juan F. Piñeiro ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Brain Cancer ◽  
Near Infrared ◽  
Relevant Information ◽  
Support Vector ◽  
Algorithm Optimization ◽  
Spectral Bands ◽  
Tumor Identification ◽  
Spectral Ranges

Hyperspectral imaging (HSI) is a non-ionizing and non-contact imaging technique capable of obtaining more information than conventional RGB (red green blue) imaging. In the medical field, HSI has commonly been investigated due to its great potential for diagnostic and surgical guidance purposes. However, the large amount of information provided by HSI normally contains redundant or non-relevant information, and it is extremely important to identify the most relevant wavelengths for a certain application in order to improve the accuracy of the predictions and reduce the execution time of the classification algorithm. Additionally, some wavelengths can contain noise and removing such bands can improve the classification stage. The work presented in this paper aims to identify such relevant spectral ranges in the visual-and-near-infrared (VNIR) region for an accurate detection of brain cancer using in vivo hyperspectral images. A methodology based on optimization algorithms has been proposed for this task, identifying the relevant wavelengths to achieve the best accuracy in the classification results obtained by a supervised classifier (support vector machines), and employing the lowest possible number of spectral bands. The results demonstrate that the proposed methodology based on the genetic algorithm optimization slightly improves the accuracy of the tumor identification in ~5%, using only 48 bands, with respect to the reference results obtained with 128 bands, offering the possibility of developing customized acquisition sensors that could provide real-time HS imaging. The most relevant spectral ranges found comprise between 440.5–465.96 nm, 498.71–509.62 nm, 556.91–575.1 nm, 593.29–615.12 nm, 636.94–666.05 nm, 698.79–731.53 nm and 884.32–902.51 nm.

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