# Connectomics & Brain Mapping Domain: Neuroscience & Brain-Computer Interfaces · 338 papers indexed · newest 2026-10-27 Whole-brain connectomes, cubic-millimeter cortical reconstructions, expansion microscopy and brain-wide cell atlases. Key concepts: connectome, connectomics, electron microscopy reconstruction, brain atlas ## Most influential - **[An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging](https://space-kitty.com/papers/doi:10.1016/j.neuroimage.2015.10.019)**. Andersson JLR, Sotiropoulos SN · 2016 · NeuroImage (doi:10.1016/j.neuroimage.2015.10.019 · 3,382 citations). Source: > In this paper we describe a method for retrospective estimation and correction of eddy current (EC)-induced distortions and subject movement in diffusion imaging. In addition a susceptibility-induced field can be supplied and will be incorporated into the calculations in a way that accurately reflects that the two fields (susceptibility- and EC-induced) behave differently in the presence of subject movement. The method is based on registering the individual volumes to a model free prediction of what each volume should look like, thereby enabling its use on high b-value data where the contrast … > _Abstract excerpt by Andersson JLR et al., CC-BY, https://doi.org/10.1016/j.neuroimage.2015.10.019; truncated._ - **[BrainNet Viewer: a network visualization tool for human brain connectomics](https://space-kitty.com/papers/doi:10.1371/journal.pone.0068910)**. Xia M, Wang J, He Y · 2013 · PloS one (doi:10.1371/journal.pone.0068910 · 3,349 citations). Source: > The human brain is a complex system whose topological organization can be represented using connectomics. Recent studies have shown that human connectomes can be constructed using various neuroimaging technologies and further characterized using sophisticated analytic strategies, such as graph theory. These methods reveal the intriguing topological architectures of human brain networks in healthy populations and explore the changes throughout normal development and aging and under various pathological conditions. However, given the huge complexity of this methodology, toolboxes for graph-based… > _Abstract excerpt by Xia M et al., CC-BY, https://doi.org/10.1371/journal.pone.0068910; truncated._ - **[A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain](https://space-kitty.com/papers/doi:10.1038/s41586-023-06812-z)**. Zizhen Yao, Cindy T. J. van Velthoven, Michael Kunst et al. · 2023 · Nature (doi:10.1038/s41586-023-06812-z · 1,325 citations). Source: > . Here we report a comprehensive and high-resolution transcriptomic and spatial cell-type atlas for the whole adult mouse brain. The cell-type atlas was created by combining a single-cell RNA-sequencing (scRNA-seq) dataset of around 7 million cells profiled (approximately 4.0 million cells passing quality control), and a spatial transcriptomic dataset of approximately 4.3 million cells using multiplexed error-robust fluorescence in situ hybridization (MERFISH). The atlas is hierarchically organized into 4 nested levels of classification: 34 classes, 338 subclasses, 1,201 supertypes and 5,322 c… > _Abstract excerpt by Zizhen Yao et al., CC-BY, https://doi.org/10.1038/s41586-023-06812-z; truncated._ - **[Neuronal wiring diagram of an adult brain](https://space-kitty.com/papers/doi:10.1038/s41586-024-07558-y)**. Sven Dorkenwald, Arie Matsliah, Amy Robinson Sterling et al. · 2024 · Nature (doi:10.1038/s41586-024-07558-y · 574 citations). Source: > Abstract Connections between neurons can be mapped by acquiring and analysing electron microscopic brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative 1–6 , but nevertheless inadequate for understanding brain function more globally. Here we present a neuronal wiring diagram of a whole brain containing 5 × 10 7 chemical synapses 7 between 139,255 neurons reconstructed from an adult female Drosophila melanogaster 8,9 . The resource also incorporates annotations of cell classes and types, nerves, hemi… > _Abstract excerpt by Sven Dorkenwald et al., CC-BY, https://doi.org/10.1038/s41586-024-07558-y; truncated._ - **[Whole-brain annotation and multi-connectome cell typing of Drosophila](https://space-kitty.com/papers/doi:10.1038/s41586-024-07686-5)**. Philipp Schlegel, Yijie Yin, Alexander Shakeel Bates et al. · 2024 · Nature (doi:10.1038/s41586-024-07686-5 · 412 citations). Source: > Abstract The fruit fly Drosophila melanogaster has emerged as a key model organism in neuroscience, in large part due to the concentration of collaboratively generated molecular, genetic and digital resources available for it. Here we complement the approximately 140,000 neuron FlyWire whole-brain connectome 1 with a systematic and hierarchical annotation of neuronal classes, cell types and developmental units (hemilineages). Of 8,453 annotated cell types, 3,643 were previously proposed in the partial hemibrain connectome 2 , and 4,581 are new types, mostly from brain regions outside the hemib… > _Abstract excerpt by Philipp Schlegel et al., CC-BY, https://doi.org/10.1038/s41586-024-07686-5; truncated._ - **[The challenge of mapping the human connectome based on diffusion tractography](https://space-kitty.com/papers/doi:10.1038/s41467-017-01285-x)**. Maier-Hein KH, Neher PF, Houde JC et al. · 2017 · Nature communications (doi:10.1038/s41467-017-01285-x · 1,123 citations). Source: > Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more… > _Abstract excerpt by Maier-Hein KH et al., CC-BY, https://doi.org/10.1038/s41467-017-01285-x; truncated._ - **[A connectome and analysis of the adult \Drosophila\ central brain](https://space-kitty.com/papers/doi:10.7554/elife.57443)**. Scheffer LK, Xu CS, Januszewski M et al. · 2020 · eLife (doi:10.7554/elife.57443 · 968 citations). Source: > The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster . Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data publ… > _Abstract excerpt by Scheffer LK et al., CC-BY, https://doi.org/10.7554/elife.57443; truncated._ - **[Deterministic diffusion fiber tracking improved by quantitative anisotropy](https://space-kitty.com/papers/doi:10.1371/journal.pone.0080713)**. Yeh FC, Verstynen TD, Wang Y et al. · 2013 · PloS one (doi:10.1371/journal.pone.0080713 · 962 citations). Source: > Diffusion MRI tractography has emerged as a useful and popular tool for mapping connections between brain regions. In this study, we examined the performance of quantitative anisotropy (QA) in facilitating deterministic fiber tracking. Two phantom studies were conducted. The first phantom study examined the susceptibility of fractional anisotropy (FA), generalized factional anisotropy (GFA), and QA to various partial volume effects. The second phantom study examined the spatial resolution of the FA-aided, GFA-aided, and QA-aided tractographies. An in vivo study was conducted to track the arcua… > _Abstract excerpt by Yeh FC et al., CC-BY, https://doi.org/10.1371/journal.pone.0080713; truncated._ - **[The hubs of the human connectome are generally implicated in the anatomy of brain disorders](https://space-kitty.com/papers/doi:10.1093/brain/awu132)**. Crossley NA, Mechelli A, Scott J et al. · 2014 · Brain : a journal of neurology (doi:10.1093/brain/awu132 · 959 citations). Source: > Brain networks or 'connectomes' include a minority of highly connected hub nodes that are functionally valuable, because their topological centrality supports integrative processing and adaptive behaviours. Recent studies also suggest that hubs have higher metabolic demands and longer-distance connections than other brain regions, and therefore could be considered biologically costly. Assuming that hubs thus normally combine both high topological value and high biological cost, we predicted that pathological brain lesions would be concentrated in hub regions. To test this general hypothesis, w… > _Abstract excerpt by Crossley NA et al., CC-BY, https://doi.org/10.1093/brain/awu132; truncated._ - **[GRETNA: a graph theoretical network analysis toolbox for imaging connectomics](https://space-kitty.com/papers/doi:10.3389/fnhum.2015.00386)**. Wang J, Wang X, Xia M et al. · 2015 · Frontiers in human neuroscience (doi:10.3389/fnhum.2015.00386 · 958 citations). Source: > Recent studies have suggested that the brain's structural and functional networks (i.e., connectomics) can be constructed by various imaging technologies (e.g., EEG/MEG; structural, diffusion and functional MRI) and further characterized by graph theory. Given the huge complexity of network construction, analysis and statistics, toolboxes incorporating these functions are largely lacking. Here, we developed the GRaph thEoreTical Network Analysis (GRETNA) toolbox for imaging connectomics. The GRETNA contains several key features as follows: (i) an open-source, Matlab-based, cross-platform (Wind… > _Abstract excerpt by Wang J et al., CC-BY, https://doi.org/10.3389/fnhum.2015.00386; truncated._ - **[Neurotransmitter classification from electron microscopy images at synaptic sites in Drosophila melanogaster](https://space-kitty.com/papers/doi:10.1016/j.cell.2024.03.016)**. Nils Eckstein, Alexander Shakeel Bates, Andrew S Champion et al. · 2024 · Cell (doi:10.1016/j.cell.2024.03.016 · 214 citations). Source: > High-resolution electron microscopy of nervous systems has enabled the reconstruction of synaptic connectomes. However, we do not know the synaptic sign for each connection (i.e., whether a connection is excitatory or inhibitory), which is implied by the released transmitter. We demonstrate that artificial neural networks can predict transmitter types for presynapses from electron micrographs: a network trained to predict six transmitters (acetylcholine, glutamate, GABA, serotonin, dopamine, octopamine) achieves an accuracy of 87% for individual synapses, 94% for neurons, and 91% for known cel… > _Abstract excerpt by Nils Eckstein et al., CC-BY, https://doi.org/10.1016/j.cell.2024.03.016; truncated._ - **[Sex Differences in the Adult Human Brain: Evidence from 5216 UK Biobank Participants](https://space-kitty.com/papers/doi:10.1093/cercor/bhy109)**. Ritchie SJ, Cox SR, Shen X et al. · 2018 · Cerebral cortex (New York, N.Y. : 1991) (doi:10.1093/cercor/bhy109 · 649 citations). Source: > Sex differences in the human brain are of interest for many reasons: for example, there are sex differences in the observed prevalence of psychiatric disorders and in some psychological traits that brain differences might help to explain. We report the largest single-sample study of structural and functional sex differences in the human brain (2750 female, 2466 male participants; mean age 61.7 years, range 44-77 years). Males had higher raw volumes, raw surface areas, and white matter fractional anisotropy; females had higher raw cortical thickness and higher white matter tract complexity. The… > _Abstract excerpt by Ritchie SJ et al., CC-BY, https://doi.org/10.1093/cercor/bhy109; truncated._ - **[FlyWire: online community for whole-brain connectomics](https://space-kitty.com/papers/doi:10.1038/s41592-021-01330-0)**. Sven Dorkenwald, Claire E. McKellar, Thomas Macrina et al. · 2021 · Nature Methods (doi:10.1038/s41592-021-01330-0 · 289 citations). Source: - **[BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets](https://space-kitty.com/papers/doi:10.1038/s42003-020-0794-7)**. Vos de Wael R, Benkarim O, Paquola C et al. · 2020 · Communications biology (doi:10.1038/s42003-020-0794-7 · 580 citations). Source: > Understanding how cognitive functions emerge from brain structure depends on quantifying how discrete regions are integrated within the broader cortical landscape. Recent work established that macroscale brain organization and function can be described in a compact manner with multivariate machine learning approaches that identify manifolds often described as cortical gradients. By quantifying topographic principles of macroscale organization, cortical gradients lend an analytical framework to study structural and functional brain organization across species, throughout development and aging, … > _Abstract excerpt by Vos de Wael R et al., CC-BY, https://doi.org/10.1038/s42003-020-0794-7; truncated._ - **[TractSeg - Fast and accurate white matter tract segmentation](https://space-kitty.com/papers/doi:10.1016/j.neuroimage.2018.07.070)**. Wasserthal J, Neher P, Maier-Hein KH · 2018 · NeuroImage (doi:10.1016/j.neuroimage.2018.07.070 · 582 citations). Source: > The individual course of white matter fiber tracts is an important factor for analysis of white matter characteristics in healthy and diseased brains. Diffusion-weighted MRI tractography in combination with region-based or clustering-based selection of streamlines is a unique combination of tools which enables the in-vivo delineation and analysis of anatomically well-known tracts. This, however, currently requires complex, computationally intensive processing pipelines which take a lot of time to set up. TractSeg is a novel convolutional neural network-based approach that directly segments tra… > _Abstract excerpt by Wasserthal J et al., CC-BY, https://doi.org/10.1016/j.neuroimage.2018.07.070; truncated._ ## Newest - **[Every route counts, but some count more: a max-plus view of the C. elegans brain](https://space-kitty.com/papers/arxiv:2610.37587)**. Emma Reyner-Fuentes, Sebastian Rudolph, Carmen Peláez-Moreno et al. · 2026 (arXiv:2610.37587). Source: - **[Which build of the connectome a whole-brain fly model runs on changes what it can do](https://space-kitty.com/papers/doi:10.5281/zenodo.23678525)**. Brandon Cho · 2026 · Zenodo (CERN European Organization for Nuclear Research) (doi:10.5281/zenodo.23678525). Source: - **[Phase response approach to networked neural activity models with delays](https://space-kitty.com/papers/arxiv:2610.35638)**. Martin R Nelson, Jonathan J Crofts · 2026 (arXiv:2610.35638). Source: - **[Flybrain: an untrained, connectome-faithful simulation of the whole Drosophila brain and nerve cord, and what its memory system suggests for continual learning in AI](https://space-kitty.com/papers/doi:10.5281/zenodo.23648099)**. Miltiadis Argianis Karakitsos · 2026 · Zenodo (CERN European Organization for Nuclear Research) (doi:10.5281/zenodo.23648099). Source: - **[Sensorimotor behaviour from an untrained brain-and-nerve-cord connectome](https://space-kitty.com/papers/arxiv:2610.33881)**. John R. Minnick, Jesus Gonzalez-Ferrer, Jinghui Geng et al. · 2026 (arXiv:2610.33881). Source: - **[Cross-species molecular mapping of the photoreceptor sensory cilium and periciliary structures identifies conserved and species-specific architectural features](https://space-kitty.com/papers/doi:10.1242/jcs.265080)**. Takahashi K, Obayashi M, Sudharsan R et al. · 2026 · Journal of cell science (doi:10.1242/jcs.265080). Source: - **[Multivariate prediction of white matter BOLD activity and its relationship to marginal connectivity](https://space-kitty.com/papers/doi:10.1016/j.neuroimage.2026.122297)**. Li M, Ding Z, Gore JC · 2026 · NeuroImage (doi:10.1016/j.neuroimage.2026.122297). Source: - **[Longitudinal fMRI reveals multi-network reconfiguration and a recurrent frontoparietal shift across rest and task states during adult aging](https://space-kitty.com/papers/arxiv:2610.24433)**. Tingshan Liu, Wanxin Dong, Hairong Zheng et al. · 2026 (arXiv:2610.24433). Source: - **[Reciprocity coordinates a three-way trade-off in recurrent neural circuits](https://space-kitty.com/papers/arxiv:2610.19949)**. Xiaoyu Zhang, Mingyi Huang, Yixuan Cui et al. · 2026 (arXiv:2610.19949). Source: - **[Years-long stability of X10 expansion microscopy hydrogels](https://space-kitty.com/papers/doi:10.1186/s13036-026-00781-3)**. Abbas E, Shaib AH, Hassan MA et al. · 2026 · Journal of biological engineering (doi:10.1186/s13036-026-00781-3). Source: --- Space Kitty Archive · https://space-kitty.com · API: https://space-kitty.com/api/v1 · MCP: https://space-kitty.com/mcp · Premium: $0.20/request via x402 (Base Sepolia (testnet)). 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