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Functional neuroimaging studies have lead to understanding the brain as a collection of spatially segregated functional networks. It is thought that each of these networks is in turn composed of a set of distinct sub-regions that together…

Much of the human cortex seems to be organized into topographic cortical maps. Yet few quantitative methods exist for characterizing these maps. To address this issue we developed a modeling framework that can reveal group-level cortical…

Quantitative Methods · Quantitative Biology 2015-04-15 Alexander G. Huth , Thomas L. Griffiths , Frederic E. Theunissen , Jack L. Gallant

An open question in deep clustering is how to understand what in the image is creating the cluster assignments. This visual understanding is essential to be able to trust the results of an inherently complex algorithm like deep learning,…

Computer Vision and Pattern Recognition · Computer Science 2020-10-13 Sarah Ryan , Nichole Carlson , Harris Butler , Tasha Fingerlin , Lisa Maier , Fuyong Xing

A standard approach in functional neuroimaging explores how a particular cognitive task activates a set of brain regions (one task-to-many regions mapping). Importantly though, the same neural system can be activated by inherently different…

Neurons and Cognition · Quantitative Biology 2016-03-23 Romy Lorenz , Ricardo Pio Monti , Ines R. Violante , Christoforos Anagnostopoulos , Aldo A. Faisal , Giovanni Montana , Robert Leech

Cytoarchitectonic parcellations of the human brain serve as anatomical references in multimodal atlas frameworks. They are based on analysis of cell-body stained histological sections and the identification of borders between brain areas.…

Computer Vision and Pattern Recognition · Computer Science 2023-06-06 Hannah Spitzer , Kai Kiwitz , Katrin Amunts , Stefan Harmeling , Timo Dickscheid

Cytoarchitectonic mapping provides anatomically grounded parcellations of brain structure and forms a foundation for integrative, multi-modal neuroscience analyses. These parcellations are defined based on the shape, density, and spatial…

Image and Video Processing · Electrical Eng. & Systems 2026-01-16 Shiqi Zhang , Fang Xu , Pengcheng Zhou

Data-driven brain parcellations aim to provide a more accurate representation of an individual's functional connectivity, since they are able to capture individual variability that arises due to development or disease. This renders…

Neurons and Cognition · Quantitative Biology 2017-03-30 Sofia Ira Ktena , Salim Arslan , Sarah Parisot , Daniel Rueckert

Current theories hold that brain function is highly related to long-range physical connections through axonal bundles, namely extrinsic connectiv-ity. However, obtaining a groupwise cortical parcellation based on extrinsic connectivity…

Applications · Statistics 2017-01-06 Guillermo Gallardo , William Wells , Rachid Deriche , Demian Wassermann

Parcellation of human cerebellar pathways is essential for advancing our understanding of the human brain. Existing diffusion MRI tractography parcellation methods have been successful in defining major cerebellar fibre tracts, while…

Standard neuroimaging techniques provide non-invasive access not only to human brain anatomy but also to its physiology. The activity recorded with these techniques is generally called functional imaging, but what is observed per se is an…

Neurons and Cognition · Quantitative Biology 2019-02-25 David Papo

Recent deep learning approaches have shown promise in learning such individual brain parcellations from functional magnetic resonance imaging (fMRI). However, most existing methods assume consistent data distributions across domains and…

Artificial Intelligence · Computer Science 2025-07-30 Jianfei Zhu , Haiqi Zhu , Shaohui Liu , Feng Jiang , Baichun Wei , Chunzhi Yi

Segmentation of brain magnetic resonance images (MRI) into anatomical regions is a useful task in neuroimaging. Manual annotation is time consuming and expensive, so having a fully automated and general purpose brain segmentation algorithm…

Computer Vision and Pattern Recognition · Computer Science 2021-12-10 Yu Yan , Yael Balbastre , Mikael Brudfors , John Ashburner

We introduce a method that takes advantage of high-quality pretrained multimodal representations to explore fine-grained semantic networks in the human brain. Previous studies have documented evidence of functional localization in the…

Artificial Intelligence · Computer Science 2023-06-07 Cory Efird , Alex Murphy , Joel Zylberberg , Alona Fyshe

Understanding how the brain represents visual information is a fundamental challenge in neuroscience and artificial intelligence. While AI-driven decoding of neural data has provided insights into the human visual system, integrating…

Neural and Evolutionary Computing · Computer Science 2025-10-07 Dongyang Li , Haoyang Qin , Mingyang Wu , Chen Wei , Quanying Liu

The use of brain images as markers for diseases or behavioral differences is challenged by the small effects size and the ensuing lack of power, an issue that has incited researchers to rely more systematically on large cohorts. Coupled…

Machine Learning · Statistics 2015-11-17 Bertrand Thirion , Andrés Hoyos-Idrobo , Jonas Kahn , Gael Varoquaux

We consider the problem of explaining the decisions of deep neural networks for image recognition in terms of human-recognizable visual concepts. In particular, given a test set of images, we aim to explain each classification in terms of a…

Machine Learning · Computer Science 2018-12-21 Mandana Hamidi-Haines , Zhongang Qi , Alan Fern , Fuxin Li , Prasad Tadepalli

Background: Data driven stratification of patients into biologically informed subtypes holds promise for precision neuropsychiatry, yet neuroimaging-based clustering methods often fail to generalize across cohorts. While algorithmic…

Machine Learning · Computer Science 2025-06-12 Yuetong Yu , Ruiyang Ge , Ilker Hacihaliloglu , Alexander Rauscher , Roger Tam , Sophia Frangou

Structural and functional neuroimaging modalities provide complementary windows into brain organization: structural imaging characterizes neural tissue anatomy and microstructure, while functional imaging captures dynamic patterns of neural…

Methodology · Statistics 2026-03-24 Sakul Mahat , Sharmistha Guha , Jessica Bernard

The assessment of brain fingerprints has emerged in the recent years as an important tool to study individual differences and to infer quality of neuroimaging datasets. Studies so far have mainly focused on connectivity fingerprints between…

Neurons and Cognition · Quantitative Biology 2021-01-13 Uttara Tipnis , Kausar Abbas , Elizabeth Tran , Enrico Amico , Li Shen , Alan D. Kaplan , Joaquín Goñi

Microscopic analysis of histological sections is considered the "gold standard" to verify structural parcellations in the human brain. Its high resolution allows the study of laminar and columnar patterns of cell distributions, which build…

Computer Vision and Pattern Recognition · Computer Science 2017-08-01 Hannah Spitzer , Katrin Amunts , Stefan Harmeling , Timo Dickscheid