Alexander B. Kunin
A5008932301- Neurobiology and Insect Physiology Research
- Insect and Arachnid Ecology and Behavior
- Memory and Neural Mechanisms
- Neural dynamics and brain function
- Alzheimer's disease research and treatments
- Plant and animal studies
- Neuroscience and Neuropharmacology Research
- Topological and Geometric Data Analysis
- Advanced Fluorescence Microscopy Techniques
- Modular Robots and Swarm Intelligence
- Neuroinflammation and Neurodegeneration Mechanisms
- Animal Behavior and Reproduction
- Visual perception and processing mechanisms
- Advanced Software Engineering Methodologies
- Embedded Systems Design Techniques
- Neural Networks and Applications
- Cell Image Analysis Techniques
Baylor College of Medicine
2020-2025
Creighton University
2023-2025
Abstract Understanding the relationship between circuit connectivity and function is crucial for uncovering how brain computes. In mouse primary visual cortex, excitatory neurons with similar response properties are more likely to be synaptically connected 1–8 ; however, broader rules remain unknown. Here we leverage millimetre-scale MICrONS dataset analyse synaptic functional of across cortical layers areas. Our results reveal that preferentially within areas—including feedback...
We are in the era of millimetre-scale electron microscopy volumes collected at nanometre resolution1,2. Dense reconstruction cellular compartments these has been enabled by recent advances machine learning3-6. Automated segmentation methods produce exceptionally accurate reconstructions cells, but post hoc proofreading is still required to generate large connectomes that free merge and split errors. The elaborate 3D meshes neurons contain detailed morphological information multiple scales,...
Understanding the relationship between circuit connectivity and function is crucial for uncovering how brain implements computation. In mouse primary visual cortex (V1), excitatory neurons with similar response properties are more likely to be synaptically connected, but previous studies have been limited within V1, leaving much unknown about broader rules. this study, we leverage millimeter-scale MICrONS dataset analyze synaptic functional of individual across cortical layers areas. Our...
We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution (Shapson-Coe et al., 2021; Consortium 2021). Dense reconstruction cellular compartments these EM has been enabled by recent advances Machine Learning (ML) (Lee 2017; Wu Lu Macrina Automated segmentation methods produce exceptionally accurate reconstructions cells, but post-hoc proofreading is still required to generate large connectomes free merge and split errors. The elaborate 3-D...
A combinatorial neural code \({\mathscr C}\subseteq 2^{[n]}\) is called convex if it arises as the intersection pattern of open subsets \(\mathbb{R}^d\). We relate emerging theory codes to established oriented matroids, both with respect geometry and computational complexity categorically. For complexity, we show that a has realization polytopes only lies below representable matroid in partial order introduced by Jeffs. previously published examples non-convex do not lie any construct lying...
The structure of neural circuitry plays a crucial role in brain function. Previous studies organization generally had to trade off between coarse descriptions at large scale and fine on small scale. Researchers have now reconstructed tens hundreds thousands neurons synaptic resolution, enabling investigations into the interplay global, modular organization, cell type-specific wiring. Analyzing data this scale, however, presents unique challenges. To address problem, we applied novel...
A combinatorial neural code $\mathscr C\subseteq 2^{[n]}$ is convex if it arises as the intersection pattern of open subsets $\mathbb R^d$. We relate emerging theory codes to established oriented matroids, both categorically and with respect geometry computational complexity. On categorical side, we show that map taking an acyclic matroid positive parts its topes a faithful functor. adapt ideal introduced by Novik, Postnikov, Sturmfels into functor from category matroids rings; then,...
Abstract Understanding how neural circuits integrate sensory and state information to support context-dependent behavior is a central issue in neuroscience. In Drosophila, oviposition complex process which the fly integrates context choose an optimal location lay her eggs. The circuit that controls sequence known, but multiple modalities internal states not. We investigated circuitry underlying high-level processing related using Hemibrain connectome. identified Oviposition Inhibitory Neuron...
ABSTRACT The structure of neural circuitry plays a crucial role in brain function. Previous studies organization generally had to trade off between coarse descriptions at large scale and fine on small scale. Researchers have now reconstructed tens hundreds thousands neurons synaptic resolution, enabling investigations into the interplay global, modular organization, cell type-specific wiring. Analyzing data this scale, however, presents unique challenges. To address problem we applied novel...