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Connectomics is an emerging field in neuroscience that aims to reconstruct the 3-dimensional morphology of neurons from electron microscopy (EM) images. Recent studies have successfully demonstrated the use of convolutional neural networks…

计算机视觉与模式识别 · 计算机科学 2017-02-27 Shibani Santurkar , David Budden , Alexander Matveev , Heather Berlin , Hayk Saribekyan , Yaron Meirovitch , Nir Shavit

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…

Extracting a connectome from an electron microscopy (EM) data set requires identification of neurons and determination of synapses between neurons. As manual extraction of this information is very time-consuming, there has been extensive…

计算机视觉与模式识别 · 计算机科学 2016-04-12 Gary B. Huang , Louis K. Scheffer , Stephen M. Plaza

Optical imaging of the brain has expanded dramatically in the past two decades. New optics, indicators, and experimental paradigms are now enabling in-vivo imaging from the synaptic to the cortex-wide scales. To match the resulting flood of…

图像与视频处理 · 电气工程与系统科学 2024-02-15 Gal Mishne , Adam Charles

Brain networks characterize complex connectivities among brain regions as graph structures, which provide a powerful means to study brain connectomes. In recent years, graph neural networks have emerged as a prevalent paradigm of learning…

机器学习 · 计算机科学 2022-06-10 Yi Yang , Yanqiao Zhu , Hejie Cui , Xuan Kan , Lifang He , Ying Guo , Carl Yang

Graphs are quickly emerging as a leading abstraction for the representation of data. One important application domain originates from an emerging discipline called "connectomics". Connectomics studies the brain as a graph; vertices…

Reconstructing neuronal circuits at the level of synapses is a central problem in neuroscience and becoming a focus of the emerging field of connectomics. To date, electron microscopy (EM) is the most proven technique for identifying and…

High-throughput methods for yielding the set of connections in a neural system, the connectome, are now being developed. This tutorial describes ways to analyze the topological and spatial organization of the connectome at the macroscopic…

神经元与认知 · 定量生物学 2011-12-23 Marcus Kaiser

How does the size of a neural circuit influence its learning performance? Intuitively, we expect the learning capacity of a neural circuit to grow with the number of neurons and synapses. Larger brains tend to be found in species with…

神经元与认知 · 定量生物学 2019-05-09 Dhruva V Raman , Timothy O'Leary

The emerging field of connectomics aims to unlock the mysteries of the brain by understanding the connectivity between neurons. To map this connectivity, we acquire thousands of electron microscopy (EM) images with nanometer-scale…

定量方法 · 定量生物学 2016-04-04 Stephen M. Plaza , Stuart E. Berg

Convolutional neural networks (CNNs) tend to become a standard approach to solve a wide array of computer vision problems. Besides important theoretical and practical advances in their design, their success is built on the existence of…

计算机视觉与模式识别 · 计算机科学 2015-12-08 Adrian Popescu , Etienne Gadeski , Hervé Le Borgne

Behavioural differences across organisms, whether healthy or pathological, are closely tied to the structure of their neural circuits. Yet, the fine-scale synaptic changes that give rise to these variations remain poorly understood, in part…

计算机视觉与模式识别 · 计算机科学 2025-09-23 Samia Mohinta , Daniel Franco-Barranco , Shi Yan Lee , Albert Cardona

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…

神经元与认知 · 定量生物学 2024-05-13 Anastasiya Salova , István A. Kovács

Evidence of critical dynamics has been recently found in both experiments and models of large scale brain dynamics. The understanding of the nature and features of such critical regime is hampered by the relatively small size of the…

无序系统与神经网络 · 物理学 2019-12-04 Mahdi Zarepour , Juan I. Perotti , Orlando V. Billoni , Dante R. Chialvo , Sergio A. Cannas

An open challenge problem at the forefront of modern neuroscience is to obtain a comprehensive mapping of the neural pathways that underlie human brain function; an enhanced understanding of the wiring diagram of the brain promises to lead…

Training segmentation models from scratch has been the standard approach for new electron microscopy connectomics datasets. However, leveraging pretrained models from existing datasets could improve efficiency and performance in constrained…

计算机视觉与模式识别 · 计算机科学 2025-03-11 Shashata Sawmya , Thomas L. Athey , Gwyneth Liu , Nir Shavit

Brain function results from communication between neurons connected by complex synaptic networks. Synapses are themselves highly complex and diverse signaling machines, containing protein products of hundreds of different genes, some in…

The structural human connectome (i.e.\ the network of fiber connections in the brain) can be analyzed at ever finer spatial resolution thanks to advances in neuroimaging. Here we analyze several large data sets for the human brain network…

神经元与认知 · 定量生物学 2016-06-08 Michael T. Gastner , Géza Ódor

The detailed functioning of the human brain is still poorly understood. Brain simulations are a well-established way to complement experimental research, but must contend with the computational demands of the approximately $10^{11}$ neurons…

分布式、并行与集群计算 · 计算机科学 2025-10-01 Fabian Czappa , Marvin Kaster , Felix Wolf

Human brain connectome studies aim at extracting and analyzing relevant features associated to pathologies of interest. Usually this consists in modeling the brain connectome as a graph and in using graph metrics as features. A fine brain…

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