A5003215697- Neural dynamics and brain function
- Neurobiology and Insect Physiology Research
- Cell Image Analysis Techniques
- Advanced Memory and Neural Computing
- Advanced Fluorescence Microscopy Techniques
- Plant and animal studies
- Machine Learning in Materials Science
- Insect Pheromone Research and Control
- Advanced Electron Microscopy Techniques and Applications
- Insect and Arachnid Ecology and Behavior
- EEG and Brain-Computer Interfaces
- Insect Utilization and Effects
- Photoreceptor and optogenetics research
- Neuroinflammation and Neurodegeneration Mechanisms
- Muscle activation and electromyography studies
- Neuroscience and Neural Engineering
Johns Hopkins University Applied Physics Laboratory
2020-2024
Howard Hughes Medical Institute
2024
Janelia Research Campus
2024
Johns Hopkins University
2020-2022
Earth Resources Technology (United States)
2020
Abstract To understand the brain we must relate neurons’ functional responses to circuit architecture that shapes them. Here, present a large connectomics dataset with dense calcium imaging of millimeter scale volume. We recorded activity from approximately 75,000 neurons in primary visual cortex (VISp) and three higher areas (VISrl, VISal VISlm) an awake mouse viewing natural movies synthetic stimuli. The data were co-registered volumetric electron microscopy (EM) reconstruction containing...
1. Abstract NeuVue is a software platform created for large-scale proofreading of machine segmentation and neural circuit reconstruction in high-resolution electron microscopy connectomics datasets. The provides robust web-based interface proofreaders to collaboratively view, annotate, edit connectivity data. A backend queuing service organizes proofreader tasks into purpose-driven task types increases throughput by limiting actions simple, atomic operations. collection analytical...
Insect neural systems are a promising source of inspiration for new navigation algorithms, especially on low size, weight, and power platforms. There have been unprecedented recent neuroscience breakthroughs with Drosophila in behavioral imaging experiments as well the mapping detailed connectivity structures. General mechanisms learning orientation central complex (CX) investigated previously; however, it is unclear how these underlying extend to cases where there translation through an...
The immense scale and complexity of neuronal electron microscopy (EM) datasets pose significant challenges in data processing, validation, interpretation, necessitating the development efficient, automated, scalable error-detection methodologies. This paper proposes a novel approach that employs mesh processing techniques to identify potential error locations near tips. Error detection at tips is particularly important challenge since these errors usually indicate many synapses are falsely...
Abstract Continual learning without catastrophic forgetting is a challenge for artificial systems but it done naturally across range of biological systems, including in insects. A recurrent circuit has been identified the fruit fly mushroom body to consolidate long term memories (LTM), there not currently an algorithmic understanding this LTM formation. We hypothesize that generative replay occurring circuit, and find anatomical evidence synapse-level connectivity supports hypothesis. Next,...
The learning center in the insect, mushroom body (MB) with its predominant population of Kenyon Cells (KCs), is a widely studied model system to investigate neural processing principles, both experimentally and theoretically. While many computational models MB have been studied, role recurrent connectivity between KCs remains inadequately understood. Dynamical point attractors are candidate theoretical framework where connections network can enable discrete set stable activation patterns....
Continuous state estimation is a fundamental problem addressed by neural systems which underlies complex capabilities such as navigation. While studies in heading direction of the fruit fly D. melanogaster have uncovered how this computation can be performed ring attractor architecture, it unclear additional synapse-level architectural details contribute to functional performance estimation. In work, we find consistent, repeated, motif connectivity data captures distributions connections...
Abstract Insect neural systems are a promising source of inspiration for new algorithms navigation, especially on low size, weight, and power platforms. There have been unprecedented recent neuroscience breakthroughs with Drosophila in behavioral imaging experiments as well the mapping detailed connectivity structures. General mechanisms learning orientation central complex (CX) investigated previously; however, it is unclear how these underlying extend to cases where there translation...
Despite the progress in deep learning networks, efficient at edge (enabling adaptable, low-complexity machine solutions) remains a critical need for defense and commercial applications. We envision pipeline to utilize large neuroimaging datasets, including maps of brain which capture neuron synapse connectivity, improve approaches. have pursued different approaches within this structure. First, as demonstration data-driven discovery, team has developed technique discovery repeated...
Abstract As biological imaging datasets continue to grow in size, extracting information from large image volumes presents a computationally intensive challenge. State-of-the-art algorithms are almost entirely dominated by the use of convolutional neural network approaches that may be diffcult run at scale given schedule, cost, and resource limitations. We demonstrate novel solution for high-resolution electron microscopy brain permits identification individual neurons synapses. Instead...
The sense of touch provides an intimate connection to our surroundings and is a critical component for navigating the environment manipulating objects. To better capture convey information prosthetic arm users or autonomous robots, it useful leverage biological representations tactile signals rapid efficient processing. We developed software pipeline that simulates analyzes biomimetic developing techniques approaches robotic systems rely on touch. Touch sensor were simulated with virtual...