A large network of interconnected neurons serves as the basis of brain function and of behavior. Methodological advances have enabled the reconstruction of large-scale and even whole-brain connectomes of various organisms.

Our ability to think, dream, plan and do critically depends on our brain and its billions of neurons and their trillions of connections. To gain a deeper understanding of the brain, a complete wiring diagram would be desirable, yet given the enormous size of the human brain and the comparatively tiny scale of neurons and synapses, this feat remains elusive. However, impressive strides have been made for smaller brains.

Almost forty years ago, heroic efforts by Sydney Brenner and colleagues led to the publication of the first wiring diagram of a model organism1. Ever since, the Caenorhabditis elegans connectome has served as a blueprint for researchers studying the behavior of these worms, as well as an inspiration for neuroscientists working with larger model organisms.

In the past year, two additional landmark connectomes have been published. The FlyWire consortium reported the full connectome of an adult Drosophila brain, and the MICrONS (Machine Intelligence from Cortical Networks) Project functionally characterized and fully reconstructed a cubic millimeter of mouse cortex. To celebrate these achievements and the long history of methodological developments that enabled them, we have chosen electron microscopy (EM)-based connectomics as the Method of the Year 2025.

To reconstruct a large tissue section or a whole brain, experimental and computational approaches go hand in hand. The tissue needs to be fixed, stained and embedded without artifacts or deterioration before imaging in thousands of sections or on the block face can be done. This imaging process takes months even when done in a parallelized fashion. Once the data are generated, neurons are traced for reconstruction. This can either be done manually or with the help of artificial intelligence. However, automated computational tools are not perfect, and proofreading of the generated reconstructions remains necessary. For now, this is the most time-consuming part of a connectomics project.

Our special issue highlights the challenges and promises of connectomics with a set of opinion and news pieces, as well as related primary research papers.

In their Comment, Albert Lin and Mala Murthy discuss how a complete connectome can lead to hypotheses about circuit function and generate predictions that can then be tested with genetic tools. Using the Drosophila connectome as an example, they illustrate how the FlyWire connectome helped to elucidate auditory circuits in the central brain, circuits for navigation in the central complex and visual circuits in the optic lobe that respond to looming stimuli. Further, they explain how the structural maps provided by connectomes can help with functional inferences.

In a related Comment, Clay Reid discusses functional connectomics, which links structure and function by combining electron microscopic reconstruction of brain tissue with calcium imaging of neuronal activity, as exemplified in the MICrONS study. Such studies can lead to mechanistic insights into emergent functional properties of neurons and their synaptic inputs or can provide correlations between structural and functional features of circuits.

In her Comment, Marta Costa highlights the challenges and prospects of comparative connectomics. Connectomes can not only help to infer circuit function but also provide insights into variability between individuals, changes during development, differences between sexes and evolutionary changes between species. Such studies require the availability of multiple connectomes for a single species or for closely related species. For smaller species such as nematodes and Drosophila, several connectomes at various stages of proofreading are available or on the horizon.

In a Comment that focuses on technical aspects, Jan Funke considers the current challenges in connectomics. Specifically, he looks into the proofreading process, which involves manual correction of errors in automatically generated reconstructions. This labor-intensive and time-consuming process can take years to obtain a high-quality reconstruction. Going forward, the field will have to grapple with trade-offs between effort and accuracy. Funke proposes that the field develops automated models that quantify the uncertainty in reconstructions and that researchers embrace this uncertainty.

In their Comment, Ramin Khajeh and Wei-Chung Allen Lee describe the imaging approaches that are currently used in connectomics before discussing alternatives to EM, such as various tomographic methods, which can be particularly attractive for large samples. However, higher throughput may come at the cost of lower resolution. Furthermore, light-microscopy-based approaches involving sample expansion are exciting developments that provide molecular in addition to structural information.

In his Comment, Moritz Helmstaedter looks into the future of connectomics and considers the matter of scale. He discusses the feasibility of generating a connectome of the whole mouse or even human brain. Furthermore, he introduces the idea of connectomic screening, in which connectomes of many smaller tissue samples could provide mechanistic insights into brain health, development or disease. Coincidentally, Helmstaedter has also written a Review on connectomics in large brains and connectomics screening for Nature Reviews Neuroscience2.

And in this month’s Technology Feature, Vivien Marx reports on how scientists strategize about scaling up connectomics projects to larger brains.

Our special issue also features four research articles related to EM-based connectomics. Meirovitch et al. present SmartEM, which increases speed of electron microscopy-based approaches via data-aware imaging. Bosch et al. demonstrate the use of X-ray tomography for ultrastructural imaging of brain tissue. Xiong et al. reconstruct light-microscopy-based connectomes from morphometric datasets. And Zhang et al. developed an approach for fiber tract mapping in macaque and human brains.

Finally, in addition to celebrating EM-based connectomics as our Method of the Year 2025, we also present eight Methods to Watch, which highlight technologies and research areas that we are especially excited to see develop.

We hope you enjoy this special issue!