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Related papers: VESICLE: Volumetric Evaluation of Synaptic Interfa…

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Mammalian whole-brain connectomes are a foundational ingredient for holistic understanding of brains. Indeed, imaging connectomes at sufficient resolution to densely reconstruct cellular morphology and synapses represents a longstanding…

Neurons and Cognition · Quantitative Biology 2025-02-03 Logan Thrasher Collins , Todd Huffman , Randal Koene

The functions of different regions of the human brain are closely linked to their distinct cytoarchitecture, which is defined by the spatial arrangement and morphology of the cells. Identifying brain regions by their cytoarchitecture…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Pralaypati Ta , Sriram Venkatesaperumal , Keerthi Ram , Mohanasankar Sivaprakasam

This paper presents an annotated dataset of brain MRI images designed to advance the field of brain symmetry study. Magnetic resonance imaging (MRI) has gained interest in analyzing brain symmetry in neonatal infants, and challenges remain…

Computer Vision and Pattern Recognition · Computer Science 2024-01-23 Arnaud Gucciardi , Safouane El Ghazouali , Francesca Venturini , Vida Groznik , Umberto Michelucci

Introduction: Technical burdens and time-intensive review processes limit the practical utility of video capsule endoscopy (VCE). Artificial intelligence (AI) is poised to address these limitations, but the intersection of AI and VCE…

Robotic and animal mapping systems share many of the same objectives and challenges, but differ in one key aspect: where much of the research in robotic mapping has focused on solving the data association problem, the grid cell neurons…

Computer Vision and Pattern Recognition · Computer Science 2018-10-24 Huu Le , Michael Milford

Synaptic connectivity detection is a critical task for neural reconstruction from Electron Microscopy (EM) data. Most of the existing algorithms for synapse detection do not identify the cleft location and direction of connectivity…

Computer Vision and Pattern Recognition · Computer Science 2018-10-26 Toufiq Parag , Daniel Berger , Lee Kamentsky , Benedikt Staffler , Donglai Wei , Moritz Helmstaedter , Jeff W. Lichtman , Hanspeter Pfister

The analysis of complex networks has revealed patterns of organization in a variety of natural and artificial systems, including neuronal networks of the brain at multiple scales. In this paper, we describe a novel analysis of the…

Neurons and Cognition · Quantitative Biology 2015-06-26 Luciano da F. Costa , Olaf Sporns

Retrospective analysis of brain MRI scans acquired in the clinic has the potential to enable neuroimaging studies with sample sizes much larger than those found in research datasets. However, analysing such clinical images "in the wild" is…

Image and Video Processing · Electrical Eng. & Systems 2023-01-06 Benjamin Billot , Magdamo Colin , Sean E. Arnold , Sudeshna Das , Juan. E. Iglesias

Despite the progress in deep learning networks, efficient learning at the edge (enabling adaptable, low-complexity machine learning solutions) remains a critical need for defense and commercial applications. We envision a pipeline to…

Volumetric brain reconstructions provide an unprecedented opportunity to gain insights into the complex connectivity patterns of neurons in an increasing number of organisms. Here, we model and quantify the complexity of the resulting…

Neurons and Cognition · Quantitative Biology 2024-05-13 Anastasiya Salova , István A. Kovács

Biological synapses effortlessly balance memory retention and flexibility, yet artificial neural networks still struggle with the extremes of catastrophic forgetting and catastrophic remembering. Here, we introduce Metaplasticity from…

Machine Learning · Computer Science 2025-04-21 Djohan Bonnet , Kellian Cottart , Tifenn Hirtzlin , Tarcisius Januel , Thomas Dalgaty , Elisa Vianello , Damien Querlioz

Dendritic spines are key structural components of excitatory synapses in the brain. Given the size of dendritic spines provides a proxy for synaptic efficacy, their detection and tracking across time is important for studies of the neural…

Computer Vision and Pattern Recognition · Computer Science 2025-09-24 Pamela Osuna-Vargas , Altug Kamacioglu , Dominik F. Aschauer , Petros E. Vlachos , Sercan Alipek , Jochen Triesch , Simon Rumpel , Matthias Kaschube

We introduce BrainSAIL, a method for linking neural selectivity with spatially distributed semantic visual concepts in natural scenes. BrainSAIL leverages recent advances in large-scale artificial neural networks, using them to provide…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Andrew F. Luo , Jacob Yeung , Rushikesh Zawar , Shaurya Dewan , Margaret M. Henderson , Leila Wehbe , Michael J. Tarr

Blood vessel networks in the brain play a crucial role in stroke research, where understanding their topology is essential for analyzing blood flow dynamics. However, extracting detailed topological vessel network information from…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Joël Mathys , Andreas Plesner , Jorel Elmiger , Roger Wattenhofer

Whole-brain neural connectivity data are now available from viral tracing experiments, which reveal the connections between a source injection site and elsewhere in the brain. These hold the promise of revealing spatial patterns of…

Neurons and Cognition · Quantitative Biology 2016-10-27 Kameron Decker Harris , Stefan Mihalas , Eric Shea-Brown

Reconstructing the intricate local morphology of neurons and their long-range projecting axons can address many connectivity related questions in neuroscience. The main bottleneck in connectomics pipelines is correcting topological errors,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Anna Grim , Jayaram Chandrashekar , Uygar Sumbul

If we are ever to unravel the mysteries of brain function at its most fundamental level, we will need a precise understanding of how its component neurons connect to each other. Electron Microscopes (EM) can now provide the nanometer…

Computer Vision and Pattern Recognition · Computer Science 2016-09-28 Pascal Fua , Graham Knott

Neural networks are widely adopted to solve complex and challenging tasks. Especially in high-stakes decision-making, understanding their reasoning process is crucial, yet proves challenging for modern deep networks. Feature visualization…

Computer Vision and Pattern Recognition · Computer Science 2026-02-18 Ada Gorgun , Bernt Schiele , Jonas Fischer

The connectome, a map of the structural and/or functional connections in the brain, provides a complex representation of the neurobiological phenotypes on which it supervenes. This information-rich data modality has the potential to…

We present a novel method for quantifying the microscopic structure of brain tissue. It is based on the automated recognition of interpretable features obtained by analyzing the shapes of cells. This contrasts with prevailing methods of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Kui Qian , Litao Qiao , Beth Friedman , Edward O'Donnell , David Kleinfeld , Yoav Freund