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DOE OSTI2023

A Conceptual Architecture for a Quantum-HPC Middleware

Abstract-Quantum computing promises potential for science and industry by solving certain computationally complex problems faster than classical computers. Quantum computing systems evolved from coupled to classical computing nodes (HPC). With the increasing monolithic systems towards modular architectures comprising multiple quantum processing units (QPUs) scale, middleware systems that facilitate the efficient coupling of quantum-classical computing are becoming critical. Through an in-depth analysis of quantum applications, integration patterns and systems, we identified a gap in understanding Quantum HPC middleware systems. We present a conceptual middleware to facilitate reasoning about quantum-classical integration and serve as the basis for a future middleware system. An essential contribution of this paper lies in leveraging well-established high performance computing abstractions for managing workloads, tasks, and resources to integrate quantum computing into HPC systems seamlessly

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Status of the Full Circumference Examination of the Inner Container Closure Weld Region for Selected 3013 DE Container

One of the main focus areas of the 3013 Surveillance Program is a thorough evaluation of the inner container closure weld region (ICCWR) opened for destructive examination (DE). As part of the protocol to investigate the corrosion in the ICCWR a laser confocal microscope (LCM) is used to perform close visual examination of the surface and measurements of corrosion features on the surface. In FY17, DE containers from FY13 through FY16 were evaluated to select candidates for a full circumference analysis of the ICCWR. In FY18, the selected DE containers for full circumference evaluation (FCE) were processed according to the ICCWR protocol. However, due to the time intensive task for collecting high magnification images for a full circumference, only FY15 DE07 was selected for completion of LCM data collection in FY18 with the remaining DE containers scheduled to be completed in FY19.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

A unified large language model–based framework for heterogeneous PV image diagnosis

With advances in imaging technologies, modern photovoltaic (PV) systems generate large volumes of heterogeneous image data, including visible, electroluminescence (EL), and infrared (IR) images. Existing PV image analysis models, particularly deep learning approaches, are typically task-specific and lack cross-modality generalization. To address this limitation, this paper proposes an open-source large language model (LLM)–based unified framework for heterogeneous PV image diagnostics. Through task-aware diagnostic prompting, the framework enables analysis of visible, EL, and IR images within a single pipeline, supporting both zero-shot and few-shot inference and binary and multiclass classification. It is compatible with state-of-the-art multimodal LLMs, including ChatGPT, Gemini, Claude, Qwen, and CLIP. The framework is evaluated on PV module condition classification (clean, soiling, snow, hail, and bird droppings) using visible images, cell crack detection using EL images, and hotspot detection using IR images. GPT-5.1 in few-shot mode achieves the best performance, with classification accuracy exceeding 97.3%. Open-source models such as Qwen and CLIP also deliver competitive results on visible images (around 90% accuracy), though their performance is more limited on EL and IR modalities. On the full ELPV dataset, the framework achieves 83.5% zero-shot accuracy, within 2.8% of the supervised CNN baseline, confirming scalability to larger benchmarks. Practical aspects such as reproducibility, response latency, and confidence estimation are systematically analyzed. The framework operates across PV image modalities without modality- or task-specific training, making it well suited as a rapid pre-screening tool to support downstream detailed diagnostics. A benchmark dataset of diverse labeled PV images is also released.

Li, Baojie↗

DOE OSTI2022

CLARIFYING THE NEXUS BETWEEN LIFE CYCLE ASSESSMENT AND CIRCULARITY INDICATORS: A SETAC/ACLCA INTEREST GROUP

Purpose Improving the circularity of resources is important to the sustainability of consumer goods. Current research has indicated that circularity practices and circular economy (CE) methods do not always reduce environmental impacts. The aim of this research is to investigate the adoption of the life cycle assessment (LCA) methodology to improve the environmental impacts of circularity practices. Methods As part of the Society for Environmental Toxicology And Chemistry (SETAC) forum, an interest group (IG) on Circularity and LCA was formed in partnership with the American Center for Life Cycle Assessment (ACLCA) to tackle methodological and technical issues related to circularity in LCA. The IG’s research approach is summarized in four key steps: defining goals and objectives, literature review and gap analysis, ideation, and experimentation. The twelve active persons within this IG meet monthly and have been divided into four sub-working groups (sub-WGs) so that complementary tasks can be completed concurrently in an effective manner. Each sub-WG meets monthly and reports back to the main group for collaboration and brainstorming to meet the research objectives. Results and discussion First, the sub-WG #1, focusing on the “pool of circularity and LCA-based indicators”, analyzed the complementarity between two of the most used circularity indicators and LCA. Second, the sub-WG #2, working on the “evaluation of CE loops performance through LCA”, built a mind map of pain points that reflect the challenges that the LCA practitioners face when combining LCA with CE approaches. Third, the sub-WG #3, dealing with the “trade-offs between circularity and sustainability”, highlighted key alignments and/or conflicts between circularity and sustainability performance depending on the scope, product, industry, or system of analysis. Fourth, the sub-WG #4, focusing on “business and industrial cases”, plans to leverage the knowledge base developed within this IG to develop use cases documenting the benefits and challenges associated with CE-related loops modeling in LCA. Conclusions The first findings of this SETAC/ACLCA IG provide a state-of-the-art overview of the synergists of LCA methodology and the CE measurement frameworks reported in the literature. To move forward and capitalize on the first findings, one valuable point will be to discuss and provide concrete solutions to the pain points that emerged when considering circularity in LCA. Eventually, the knowledge base and resources created within this IG ultimately aim to support the proper application of LCA for practitioners in CE contexts, and could provide relevant inputs for the ISO Technical Committee ISO/TC 323 working on the upcoming standard for the measurement of CE performance.

Life cycle assessment, circular economy, circulari↗

DOE OSTI2014

Structure Slicing: Extending Logical Regions with Fields, In: SC '14: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis

Applications on modern supercomputers are increasingly limited by the cost of data movement, but mainstream programming systems have few abstractions for describing the structure of a program's data. Consequently, the burden of managing data movement, placement, and layout currently falls primarily upon the programmer. To address this problem we previously proposed a data model based on logical regions and described Legion, a programming system incorporating logical regions. In this paper, we present structure slicing, which incorporates fields into the logical region data model. We show that structure slicing enables Legion to automatically infer task parallelism from field non-interference, decouple the specification of data usage from layout, and reduce the overall amount of data moved. We demonstrate that structure slicing enables both strong and weak scaling of three Legion applications including S3D, a production combustion simulation that uses logical regions with thousands of fields, with speedups of up to 3.68X over a vectorized CPU-only Fortran implementation and 1.88X over an independently hand-tuned OpenACC code.

Computer Science↗

DOE OSTI2025

Covariance-Free Bifidelity Control Variates Importance Sampling for Rare Event Reliability Analysis

Multifidelity modeling has been steadily gaining attention as a tool to address the problem of exorbitant model evaluation costs that makes the estimation of failure probabilities a significant computational challenge for complex real-world problems, particularly when failure is a rare event. To implement multifidelity modeling, estimators that efficiently combine information from multiple models/sources are necessary. In past works, the variance reduction techniques of control variates (CV) and importance sampling (IS) have been leveraged for this task. In this paper, we present the CVIS framework—a creative take on a coupled CV and IS estimator for bifidelity reliability analysis. The framework addresses some of the practical challenges of the CV method by using an estimator for the control variate mean and sidestepping the need to estimate the covariance between the original estimator and the control variate through a clever choice for the tuning constant. Furthermore, the task of selecting an efficient IS distribution is also considered, with a view towards maximally leveraging the bifidelity structure and maintaining expressivity. Additionally, a diagnostic is provided that indicates both the efficiency of the algorithm as well as the relative predictive quality of the models utilized. Finally, the behavior and performance of the framework is explored through analytical and numerical examples.

Markov chain Monte Carlo↗

DOE OSTI2017

Maintaining Continuity of Knowledge over Spent Fuel Pools- IR Imaging

This report covers the experiments performed by Pacific Northwest National Laboratory and Oregon State University at their Testing, Research, Isotope, and General Atomic (TRIGA) test reactor. These experiments fall under a larger goal to maintain Continuity of Knowledge (CoK) over a spent fuel pool in the absence of light. During FY 17, PNNL was tasked with investigating the ex-pool solutions to this investigation. Preliminary analysis done in FY 16 resulted in the identification of IR and UV cameras as a viable option. One experiment conducted that year yield results showing that a pure IR camera would not function to image thermal objects through water due to the large absorption cross section of IR light within water. This experiment lead PNNL to investigate cameras that ranged from UV to IR in the hopes that the cameras would be able to image the objects more efficiently with cameras that ranged across these spectra. This constraint lead us to being conversations with Phoenix Engineering based out of Georgia as they have cameras that sample UV-IR and Vis – IR light spectra. The two cameras identified and eventually used for this experiment were the HAWK-216 and OWL 640 cameras. The specific QE curves of these cameras can be found in subsequent sections. The results discussed in this report pertain to the images captured at the OSU TRIGA reactor under varying power levels to see what thresholds and minimum detectable thermal output could be detected by these cameras.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2018

Quantifying Analysis of Uncertainty in Medical Reporting: Creation of User and Context-Specific Uncertainty Profiles

While uncertainty is ubiquitous in medical practice, minimal work to date has been performed to analyze the cause and effect relationship between uncertainty and patient outcomes. In medical imaging practice, uncertainty in the radiology report has been well documented to be a source of clinician dissatisfaction. Before one can effectively create intervention strategies aimed at reducing uncertainty, it must first be better understood through context- and user-specific analysis. One strategy for accomplishing this task is to characterize the source of uncertainty and create user-specific uncertainty profiles which take into account a number of provider-specific variables which may contribute to report uncertainty. The resulting data can in turn be used to create real-time report uncertainty metrics aimed at providing uncertainty analytics at the point of care, for the combined purposes of decision support, improved communication, and enhanced clinical/economic outcomes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2024

Advancing Building Energy Modeling with Large Language Models: Exploration and Case Studies

The rapid progression in artificial intelligence has facilitated the emergence of large language models like ChatGPT, offering potential applications extending into specialized engineering modeling, especially physics-based building energy modeling. This paper investigates the innovative integration of large language models with building energy modeling software, focusing specifically on the fusion of ChatGPT with EnergyPlus. A literature review is first conducted to reveal a growing trend of incorporating large language models in engineering modeling, albeit limited research on their application in building energy modeling. We underscore the potential of large language models in addressing building energy modeling challenges and outline potential applications including simulation input generation, simulation output analysis and visualization, conducting error analysis, co-simulation, simulation knowledge extraction and training, and simulation optimization. Three case studies reveal the transformative potential of large language models in automating and optimizing building energy modeling tasks, underscoring the pivotal role of artificial intelligence in advancing sustainable building practices and energy efficiency. The case studies demonstrate that selecting the right large language model techniques is essential to enhance performance and reduce engineering efforts. The findings advocate a multidisciplinary approach in future artificial intelligence research, with implications extending beyond building energy modeling to other specialized engineering modeling.

building energy modeling↗

DOE OSTI2014

Process-based quality management for clinical implementation of adaptive radiotherapy

Purpose: Intensity-modulated adaptive radiotherapy (ART) has been the focus of considerable research and developmental work due to its potential therapeutic benefits. However, in light of its unique quality assurance (QA) challenges, no one has described a robust framework for its clinical implementation. In fact, recent position papers by ASTRO and AAPM have firmly endorsed pretreatment patient-specific IMRT QA, which limits the feasibility of online ART. The authors aim to address these obstacles by applying failure mode and effects analysis (FMEA) to identify high-priority errors and appropriate risk-mitigation strategies for clinical implementation of intensity-modulated ART. Methods: An experienced team of two clinical medical physicists, one clinical engineer, and one radiation oncologist was assembled to perform a standard FMEA for intensity-modulated ART. A set of 216 potential radiotherapy failures composed by the forthcoming AAPM task group 100 (TG-100) was used as the basis. Of the 216 failures, 127 were identified as most relevant to an ART scheme. Using the associated TG-100 FMEA values as a baseline, the team considered how the likeliness of occurrence (O), outcome severity (S), and likeliness of failure being undetected (D) would change for ART. New risk priority numbers (RPN) were calculated. Failures characterized by RPN ≥ 200 were identified as potentially critical. Results: FMEA revealed that ART RPN increased for 38% (n = 48/127) of potential failures, with 75% (n = 36/48) attributed to failures in the segmentation and treatment planning processes. Forty-three of 127 failures were identified as potentially critical. Risk-mitigation strategies include implementing a suite of quality control and decision support software, specialty QA software/hardware tools, and an increase in specially trained personnel. Conclusions: Results of the FMEA-based risk assessment demonstrate that intensity-modulated ART introduces different (but not necessarily more) risks than standard IMRT and may be safely implemented with the proper mitigations.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Battery Second Use Analysis and Demonstration: Cooperative Research and Development Final Report, CRADA Number CRD-13 -537

The goal of this project is to test the performance of used automotive batteries providing stationary energy storage services to the grid, identifying barriers and opportunities for widespread battery second use strategies. These goals will be achieved by the installation and testing of an energy storage system comprised of used EV batteries and supporting data provided by BMW. The National Renewable Energy Laboratory (NREL) will complete test planning, modeling, and analysis tasks in support of this effort. Once complete, results will be applied to make recommendations on use strategies for used EV batteries, and to identify areas requiring further research.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

NRC Multiphysics Analysis Capability Deployment FY2020 - Part 4

This report details progress and activities of Idaho National Laboratory (INL) on the Nuclear Regulatory Commission (NRC) project “Development and Modeling Sup- port for Advanced Non-Light Water Reactors.” The tasks completed for this report are: • Task 3a: This task demonstrates the effectiveness of Griffin’s methods for interpolating cross sections and SPH correction factors as a function of control drum rotation. The Monte Carlo code Serpent is used to generate reference results. The accuracy of Griffin-calculated eigenvalues and reaction rates are studied as a function of control drum rotation for cross section and SPH factor libraries of varying fidelity. Higher-fidelity libraries require less interpolation and are therefore inherently more accurate; however, they require more computational resources to create. Overall, Griffin is able to accurately model eigenvalue and reaction rates over the full range of drum rotation using a library generated from three to five discrete drum rotations for a particular microreactor design. • Task 3c: This preliminary task successfully demonstrates the performance of a coupled neutron-photon transport calculation with Griffin using the spherical harmonics approximation. The Griffin solutions are compared to reference solutions from the continuous energy Monte Carlo codes MCNP and Serpent. Furthermore, this work also demonstrates how to prepare the neutron and photon libraries using NJOY, MCNP, and Serpent with the latest ENDF/B-VIII data for 235 U and graphite. The Griffin total energy deposition in the active core region is calculated within 0.3% of the reference, but it degrades in the reflector regions with a maximum difference of -1.5%. Overall, the results look promising and future analysis should use an improved data stream and focus on determining the potential cancellation of error within each energy group.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

High Temperature Anode Recycle Blower for Solid Oxide Fuel Cell, Phase II (Final Report)

Broad commercialization of solid oxide fuel cells (SOFCs) requires anode offgas recycle blowers (ARCB) that are specifically designed for handling the challenging operating conditions presented by the SOFC process gases. Otherwise, they can be susceptible to frequent maintenance, low reliability, and short life. This report presents details of a DOE-funded Phase II effort conducted by Mohawk Innovative Technology, Inc. (MiTi®) for the development and testing of an oil-free, low cost, high-temperature centrifugal ARCB based on compliant foil bearing (CFB) technology for support of a 100 kW solid oxide fuel cell power plant. This Phase II builds on the results of a successful Phase I development project that resulted in the demonstration of a low TRL-6 prototype, shown in Figure 1. This Phase II final report presents design improvements over the Phase I prototype, presents the assembled test ARCBs, and discusses the advantages of this novel technology, particularly its long life and maintenance-free operation, which are derived from the use of CFBs. Also included are preliminary techno-economic analysis considerations for cost-effective deployment of the technology. The specific objectives of this project, as stated in the statement of program objectives (SOPO) were 1) to follow the methodology of design for manufacturing (or manufacturability) and assembly for implementing improvements identified as part of the Phase I effort with the purpose of reducing cost, enabling mass production, and facilitating the commercialization of a revised ARCB design, and 2) to fabricate four complete ARCB units based on the revised design and demonstrating their performance in both a laboratory setting and in an actual SOFC power plant. Execution of this SOPO would be supported by a number of technical tasks resulting in the fabrication and testing of the prototypes. To this end, MiTi continued the teaming relationship started during Phase I of the program with subcontracting partner FuelCell Energy, Inc. (FCE), which integrated (under a parallel effort funded by DOE Award DE-FE0026199) a modular 200 kWe SOFC power plant. MiTi and FCE coordinated to ultimately incorporate one of MiTi’s ARCB prototypes into one of the 100 kWe SOFC Modular Power Blocks (MPB) that constitute the core of FCE’s SOFC power plant for in-situ long-duration testing. Additionally, MiTi would explore the scalability and extendibility of the technology to other applications, as well as conduct a basic techno-economic analysis.

03 NATURAL GAS↗

DOE OSTI2018

Aluminum Clad Spent Nuclear Fuel Task 4: Performance of Aluminum SNF in Dry Storage Experiment Test Plan

This document presents the activities to be performed in support of understanding the performance of aluminum spent nuclear fuel (ASNF) in dry storage. These activities will visually examine and acquire baseline samples of as-irradiated ATR fuel assembly components to determine fuel condition and the morphology of the aluminum oxyhydroxides present on the fuel external surfaces. Because the boehmite phase of oxyhydroxide is projected to be a significant contributor to radiolytic hydrogen production and general corrosion, being able to quantify its presence is of major importance to long term storage of aluminum spent nuclear fuel. Baseline samples will be taken from irradiated end adapters, removed from ATR SNF elements, stored in the ATR Canal. These will be transferred to Idaho National Laboratory (INL) Materials and Fuels Complex (MFC) to perform non-destructive and destructive testing to determine the degree of hydration of the wet-stored aluminum components prior to drying and air storage. Examination of the dry stored SNF at Idaho Nuclear Technology and Engineering Center (INTEC) in CPP-603 Irradiated Fuel Storage Facility (IFSF) will allow the opportunity to identify gross degradation and as conditions permit, sample the surface oxide on fueled and un-fueled portions of the stored assemblies. The information resulting from analysis of the ATR Canal samples will be used to support validation of surrogate samples prepared under Task 6, sample surrogate preparation, and used in Task 1, oxyhydroxide layer behavior and chemistry, Task 2, oxide layer radiolytic gas generation, and Task 5, oxide layer response to drying. Surface oxide samples collected from SNF in IFSF dry storage will SNF dry storage prediction modeling from Task 3, sealed and vented system episodic breathing and gas generation prediction.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2018

Decontamination and Decommissioning Activities of a Radiopharmaceuticals Production Facility - 18067

On May 2012, Best Medical Belgium S.A. (BMB), a manufacturer of pharmaceutical products located on the nuclear site of Fleurus, was declared bankrupt. According to the Belgian law, ONDRAF/NIRAS (Belgian Radioactive Waste Management Agency) was entrusted with the clean-up and decommissioning operations of the former BMB facilities, nowadays known as 'ONDRAF Site Fleurus' (ONSF). In June 2015, ONSF launched a Decontamination and Decommissioning (D and D) program, for which Tractebel: - Supports the definition of the clean-up and decommissioning strategies; - Drafts the Final Decommissioning Plan (FDP) and Safety Analysis Report (SAR) that will be submitted to FANC/AFCN (Belgian Federal Agency for Nuclear Control) in order to get the License for decommissioning; - Drafts the technical specifications of the public tendering process related to the D and D program; - Ensures the day to-day follow-up of the D and D activities on site. Four nuclear buildings are part of the D and D activities. One of them, building 14 (B14), represents the most challenging and extensive task with the clean-up of highly contaminated areas and its further decommissioning up to the final state. This building features two cyclotrons (CGR and IBA cyclotrons) successively used to produce radioisotopes, as well as hot cells and glove boxes used for their purification and the conditioning of the final pharmaceutical product. The present paper aims at presenting the most recent development steps of the clean-up phase regarding the adaptations of existing facilities and the upcoming activities in preparation of the decommissioning activities. To allow the sorting and the treatment of the radioactive material identified in the physical and radiological inventory, several workshops have been implemented within the B14 building in order to deal with radioactive materials arising from the clean-up and D and D activities. Following the conceptual design phase, Tractebel has actively monitored the on-site activities for the construction of those workshops such as: - The modification of the civil works; - The revamping of the ventilation system; - The installation of dedicated lifting equipment and workstations equipped with cutting devices; - The assembly of a docking station for filling the radioactive packages. The removal of the activated concrete surrounding the IBA cyclotron requires the erection of a containment structure and an extension structure. The containment structure, composed of light metallic beams, is located above the cyclotron and its irradiation zones. For operational security reasons and working efficiency, the cutting process of the concrete ceilings and walls will be performed from the top inside the containment structure by means of an eight tons overhead bridge crane. Concrete blocks resulting from the cutting process will then be lifted, without any loss of containment, towards the extension zone of the nuclear zone of the IBA cyclotron for further resizing, sorting and evacuation towards the identified waste routes. To prepare this task which will be performed during the decommissioning phase, Tractebel sets up the necessary technical specifications. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Detecting new physics as novelty — Complementarity matters

Novelty detection is a task of machine learning that aims at detecting novel events without a prior knowledge. In particular, its techniques can be applied to detect unexpected signals from new phenomena at colliders. In this paper, we develop an analysis scheme that exploits the complementarity, originally studied in ref. [1], between isolation-based and clustering-based novelty evaluators. This approach can significantly improve the performance and overall applicability of novelty detection at colliders, which we demonstrate using a variety of two dimensional Gaussian samples mimicking collider events. As a further proof of principle, we subsequently apply this scheme to the detection of two significantly different signals at the LHC featuring a $t\bar{t}γγ$ final state: $t\bar{t}h$, giving a narrow resonance in the diphoton mass spectrum, and gravity-mediated supersymmetry, resulting in broad distributions at high transverse momentum. Compared to existing dedicated searches at the LHC, the sensitivities for detecting both signals are found to be encouraging.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Improved Accuracy for Trotter Simulations Using Chebyshev Interpolation

Quantum metrology allows for measuring properties of a quantum system at the optimal Heisenberg limit. However, when the relevant quantum states are prepared using digital Hamiltonian simulation, the accrued algorithmic errors will cause deviations from this fundamental limit. In this work, we show how algorithmic errors due to Trotterized time evolution can be mitigated through the use of standard polynomial interpolation techniques. Our approach is to extrapolate to zero Trotter step size, akin to zero-noise extrapolation techniques for mitigating hardware errors. We perform a rigorous error analysis of the interpolation approach for estimating eigenvalues and time-evolved expectation values, and show that the Heisenberg limit is achieved up to polylogarithmic factors in the error. Our work suggests that accuracies approaching those of state-of-the-art simulation algorithms may be achieved using Trotter and classical resources alone for a number of relevant algorithmic tasks.

Rendon, Gumaro↗

DOE OSTI2022

Transience of the Retinal Output Is Determined by a Great Variety of Circuit Elements

Retinal ganglion cells (RGCs) encrypt stimulus features of the visual scene in action potentials and convey them toward higher visual centers in the brain. Although there are many visual features to encode, our recent understanding is that the ~46 different functional subtypes of RGCs in the retina share this task. In this scheme, each RGC subtype establishes a separate, parallel signaling route for a specific visual feature (e.g., contrast, the direction of motion, luminosity), through which information is conveyed. The efficiency of encoding depends on several factors, including signal strength, adaptational levels, and the actual efficacy of the underlying retinal microcircuits. Upon collecting inputs across their respective receptive field, RGCs perform further analysis (e.g., summation, subtraction, weighting) before they generate the final output spike train, which itself is characterized by multiple different features, such as the number of spikes, the inter-spike intervals, response delay, and the rundown time (transience) of the response. These specific kinetic features are essential for target postsynaptic neurons in the brain in order to effectively decode and interpret signals, thereby forming visual perception. We review recent knowledge regarding circuit elements of the mammalian retina that participate in shaping RGC response transience for optimal visual signaling.

59 BASIC BIOLOGICAL SCIENCES↗