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Robotic Brain Universe

Mapping the brain: the breakthroughs

From Golgi and Brodmann to whole-brain connectomes, cell atlases and AI foundation models: how the brain is mapped and where mapping is heading.

Introductory · about 9 min · updated 2026-10-02 · awaiting clinical review

See it in 3D:

Illustrative simulation excitatory inhibitory

Maps of cells, genes, cell types, connections, areas and growth; connectomes from the worm to the adult fly and cubic millimetres of mouse and human cortex; tissue clearing, expansion microscopy, Neuropixels, whole-brain imaging and optogenetics; AI that traces neurons and predicts their responses; limits of templates and fragments; the diffraction limit, wiring density and tracing error rates.

Contents
  1. From one worm to a map of every synapse
  2. What kinds of map exist
  3. Why we map
  4. How the maps are made
  5. When: the acceleration
  6. Limits and pitfalls
  7. The numbers behind the maps
  8. Technology and AI
  9. Milestones
  10. Frontiers
  11. Check yourself

From one worm to a map of every synapse

In 1986 a team traced every neuron of the roundworm Caenorhabditis elegans through serial electron micrographs: 302 neurons and about 5,000 chemical synapses. In 2024 a whole adult fruit fly brain was mapped, with 139,255 neurons and 50 million synapses, and a cubic millimetre of human cortex revealed about 150 million synapses.[1,2,3]

Brain mapping has moved from drawings of single cells to maps of genes, cell types, connections and activity, and artificial intelligence now does much of the tracing and is learning to predict how neurons respond.[4,5,6]

This final reading draws the threads of the others together: the main kinds of brain map, the technologies that made them, how AI is changing the field, the limits that remain, and where it is heading. The atlas you are using is itself one of these maps, built on a template brain.[7,8]

What kinds of map exist

Cells and architecture. Golgi and Ramón y Cajal shared the 1906 Nobel Prize for their work on the structure of the nervous system. Brodmann's 1909 maps divided the cortex by its cellular architecture, and BigBrain digitised a whole human brain from histological sections at nearly cellular resolution.[4,9,10]

Genes and cell types. Gene-expression atlases mapped about 20,000 genes across the adult mouse brain and the transcriptome of the adult human brain; a 2023 census of more than three million nuclei from across the human brain identified 461 clusters and 3,313 subclusters of cell types.[11,12,13]

Connections. Connectomes map synapses with electron microscopy, from the worm to the larval and adult fly and to cubic millimetres of mouse and human cortex; at the scale of the whole human brain, MRI tractography maps the major pathways, as in this atlas's tract layer.[1,2,3,8,14,15]

Areas and growth. A multimodal MRI parcellation divided each cortical hemisphere into 180 areas, and lifespan brain charts from more than 100,000 people describe how brain structure changes from before birth to old age.[16,17]

Key numbers

Neurons in the first complete connectome (C. elegans, 1986)
302[1]
Neurons and synapses in the larval fruit fly brain connectome
3,016 and 548,000[14]
Neurons and synapses in the adult fruit fly brain connectome
139,255 and 5 × 10⁷[2]
Data in one cubic millimetre of human cortex at nanoscale resolution
1.4 petabytes[3]
Genes mapped in the adult mouse brain atlas
about 20,000[11]

Why we map

Structure constrains function. The larval fly connectome revealed highly recurrent circuits, abundant feedback, and features such as multilayer shortcuts and nested recurrent loops that resemble state-of-the-art deep-learning architectures.[14]

Linking activity to wiring. In the MICrONS project, calcium imaging of about 75,000 neurons in the visual cortex of an awake mouse was co-registered with an electron-microscopy reconstruction of more than 200,000 cells and 0.5 billion synapses, bringing each neuron's responses together with its connections.[15]

Shared references. Maps in a common space let researchers compare findings and individuals; the brain charts, for example, provide normative trajectories against which any person's scan can be benchmarked.[16,17]

How the maps are made

Seeing through tissue. CLARITY turns intact brain tissue into a transparent, molecule-permeable hydrogel hybrid, so that long-range projections, local wiring and molecules can be imaged without cutting the brain into sections. Expansion microscopy physically swells a specimen within a polymer network so that ordinary microscopes resolve details closer together than the diffraction limit, about 70 nm laterally.[18,19]

Recording many neurons. Each Neuropixels probe has 384 recording channels addressing 960 sites along a 10 mm shank; two probes recorded more than 700 well-isolated neurons from five brain structures in an awake mouse. Light-sheet microscopy recorded calcium activity from more than 80% of all neurons in the larval zebrafish brain at single-cell resolution.[20,21]

Testing the map. Optogenetics uses a light-sensitive algal channel, channelrhodopsin-2, to control spiking in genetically chosen neurons with millisecond precision, so that the role of a mapped circuit can be tested by switching it on or off.[22]

From tissue to a connectome (simplified)Tissue samplefor example surgically removedhuman cortexSerial electron microscopythe tissue is imaged slice bysliceAligned image volumepetabytes per cubic millimetreAI segmentationneural networks trace eachneuronProofreadingpeople correct the remainingerrorsConnectomeneurons and synapses as a graph
From tissue to a connectome (simplified). The pipeline behind the electron-microscopy connectomes in this reading; each project differs in detail.[2,3,5]
Text version of the diagram
  1. Tissue sample: for example surgically removed human cortex. Leads to Serial electron microscopy.
  2. Serial electron microscopy: the tissue is imaged slice by slice. Leads to Aligned image volume.
  3. Aligned image volume: petabytes per cubic millimetre. Leads to AI segmentation.
  4. AI segmentation: neural networks trace each neuron. Leads to Proofreading.
  5. Proofreading: people correct the remaining errors. Leads to Connectome.
  6. Connectome: neurons and synapses as a graph.

When: the acceleration

Mapping a whole nervous system took from the worm's 302 neurons in 1986 to the larval fly's 3,016 in 2023 and the adult fly's 139,255 in 2024. Over the same period automated tracing improved: flood-filling networks reached a mean error-free neurite path length of 1.1 mm, an order of magnitude better than earlier methods on the same data.[1,2,5,14]

Human maps have grown in scale too: from one brain digitised from 7,404 histological sections in 2013 to transcriptomes of more than three million nuclei in 2023 and charts built from more than 100,000 MRI scans in 2022.[10,13,17]

Limits and pitfalls

Errors still need people. Even flood-filling networks needed far more computation than earlier methods, and automated tracing still has errors that must be proofread before a connectome is reliable.[5]

Small pieces of large brains. The human cortex reconstruction covers one cubic millimetre of temporal cortex, removed to reach an epileptic focus beneath it: a tiny sample of one person's brain.[3]

Templates are not individuals. Population atlases such as the ones in this viewer show where structures usually lie; brain charts and parcellations reveal how much individuals differ from them.[7,16,17]

The numbers behind the maps

Simple calculations show what limits optical maps and how wiring density grows across connectomes.[1,19,23]

Diffraction limit and expansion[19,23]
d≈λ2 NA,deff≈dEd \approx \frac{\lambda}{2\,\mathrm{NA}}, \qquad d_{\text{eff}} \approx \frac{d}{E}

Abbe's limit sets the smallest separation d a light microscope can resolve, a fraction of the wavelength of light. Expanding the specimen by a factor E shrinks the effective limit by the same factor, which is how expansion microscopy reached about 70 nm with a conventional confocal microscope.

Symbols in Diffraction limit and expansion
SymbolMeaningUnit
ddsmallest resolvable separationnm
λ\lambdawavelength of lightnm
NANAnumerical aperture of the objective—
EElinear expansion factor of the specimen—
Synapses per neuron[1,2,14]
sˉ=SN\bar{s} = \frac{S}{N}

The average number of synapses per neuron in a connectome: about 5,000 / 302 ≈ 17 in the worm, 548,000 / 3,016 ≈ 182 in the larval fly and 5 × 10⁷ / 139,255 ≈ 359 in the adult fly. In these three connectomes, the larger brains also have more synapses per neuron.

Symbols in Synapses per neuron
SymbolMeaningUnit
SSnumber of chemical synapses—
NNnumber of neurons—
Tracing error rate[5]
merge rate=mergerspath length=497 mm≈0.04 mm−1\text{merge rate} = \frac{\text{mergers}}{\text{path length}} = \frac{4}{97\ \mathrm{mm}} \approx 0.04\ \mathrm{mm^{-1}}

On a test set with 97 mm of neurite, flood-filling networks made only four merge errors, about one per 24 mm of traced path.

Symbols in Tracing error rate
SymbolMeaningUnit
mergersmergersnumber of times two neurons were wrongly joined—
pathlengthpath lengthtotal neurite length checkedmm

Technology and AI

AI that traces neurons. Flood-filling networks combine convolutional neural networks with a recurrent pathway that iteratively extends each neuronal process, and made automated reconstruction precise enough for large connectomes.[5]

AI that predicts neurons. A foundation model trained on large recordings from mouse visual cortex predicted responses to arbitrary natural videos, generalised to new mice with little training and to new kinds of stimulus, and even predicted cell types, dendritic features and connectivity in the MICrONS dataset.[6,15]

Video framesShared core networkPer-mouse readoutNeuron responses
A foundation model of visual cortex (schematic). A schematic of the idea: a large shared network learns from many mice, and a small readout adapts it to each new animal's neurons.[6]

From maps to medicine. Mapping speech-related activity in motor cortex underpins brain–computer interfaces that decode attempted speech; see Brain–computer interfaces.[24]

Connectomes compared[1,2,3,14,15]
BrainYearNeuronsSynapses
Roundworm (C. elegans)1986302about 5,000 chemical
Larval fruit fly20233,016548,000
Adult fruit fly2024139,2555 × 10⁷
Human cortex, 1 mm³2024about 57,000 cellsabout 150 million
Mouse visual cortex (MICrONS)2025more than 200,000 cells0.5 billion

Milestones

Two centuries of brain maps

  1. 1873Abbe's theory of the microscope sets the diffraction limit.[23]
  2. 1906Golgi and Ramón y Cajal share the Nobel Prize for the structure of the nervous system.[4]
  3. 1909Brodmann maps the cortex by its cellular architecture.[9]
  4. 1986The first complete connectome: C. elegans.[1]
  5. 2005Optogenetics controls neurons with light.[22]
  6. 2007A genome-wide atlas of gene expression in the mouse brain.[11]
  7. 2012An atlas of the adult human brain transcriptome.[12]
  8. 2013BigBrain, CLARITY and whole-brain imaging of the larval zebrafish.[10,18,21]
  9. 2015Expansion microscopy.[19]
  10. 2016180 areas per cortical hemisphere.[16]
  11. 2017Neuropixels probes record hundreds of neurons at once.[20]
  12. 2018Flood-filling networks automate neuron tracing.[5]
  13. 2023The larval fly connectome; a census of human brain cell types.[13,14]
  14. 2025Functional connectomics of mouse visual cortex and a foundation model of neural activity.[6,15]

Frontiers

Bigger connectomes. The adult fly connectome's authors present its technologies and open ecosystem as groundwork for large-scale connectome projects in other species.[2]

Foundation models of the brain. As neuroscience accumulates larger, multimodal datasets, foundation models may reveal statistical regularities and adapt rapidly to new questions.[6]

The human brain at nanoscale. The petavoxel human fragment found that glia outnumber neurons two to one and that rare, powerful connections of up to 50 synapses stand out among thousands of weak ones; its authors expect such resources to bring valuable insights.[3]

Check yourself

Check yourself

  1. Which animal had the first complete connectome, and how many neurons does it have?
    Show answer

    The roundworm C. elegans, with 302 neurons.

  2. How many neurons were mapped in the adult fruit fly brain?
    Show answer

    139,255, with about 50 million synapses.

  3. What does expansion microscopy do?
    Show answer

    It physically expands a specimen in a swellable polymer so ordinary microscopes resolve details below the diffraction limit.

  4. How many recording channels does a Neuropixels probe have?
    Show answer

    384, addressing 960 sites.

  5. What role does AI play in connectomics?
    Show answer

    Neural networks such as flood-filling networks trace neurons through electron-microscopy volumes.

  6. What did the 2025 foundation model of visual cortex predict?
    Show answer

    Responses to new videos and stimulus types, and even cell types and connectivity.

  7. Why does a connectome alone not explain behaviour?
    Show answer

    It shows connections, not activity; it must be combined with recordings and models.

  8. What does optogenetics allow?
    Show answer

    Millisecond control of genetically chosen neurons with light.

Glossary[1,5,6,9,11,18,19,20,22]

Connectome
A map of neurons and the synapses between them.
Electron microscopy
Imaging with electrons, fine enough to see synapses.
Transcriptome
The set of genes being expressed in a tissue or cell.
Cytoarchitecture
The arrangement of cells, used by Brodmann to map cortex.
Tissue clearing
Making tissue transparent for imaging, as in CLARITY.
Expansion microscopy
Physically enlarging a specimen to resolve finer detail.
Neuropixels
Dense silicon probes recording hundreds of neurons at once.
Optogenetics
Controlling genetically targeted neurons with light.
Segmentation
Tracing each neuron's outline through an image volume.
Foundation model
A large model trained on broad data that adapts to new tasks.

References

  1. White JG, Southgate E, Thomson JN, Brenner S. The structure of the nervous system of the nematode Caenorhabditis elegans. Philosophical Transactions of the Royal Society of London. B, Biological Sciences 1986;314(1165):1-340. doi:10.1098/rstb.1986.0056
  2. Dorkenwald S, Matsliah A, Sterling AR, Schlegel P, Yu SC, McKellar CE, et al.. Neuronal wiring diagram of an adult brain. Nature 2024;634(8032):124-138. doi:10.1038/s41586-024-07558-y
  3. Shapson-Coe A, Januszewski M, Berger DR, Pope A, Wu Y, Blakely T, et al.. A petavoxel fragment of human cerebral cortex reconstructed at nanoscale resolution. Science 2024;384(6696):eadk4858. doi:10.1126/science.adk4858
  4. Nobel Prize Outreach. The Nobel Prize in Physiology or Medicine 1906. NobelPrize.org 1906. https://www.nobelprize.org/prizes/medicine/1906/summary/
  5. Januszewski M, Kornfeld J, Li PH, Pope A, Blakely T, Lindsey L, et al.. High-precision automated reconstruction of neurons with flood-filling networks. Nature Methods 2018;15(8):605-610. doi:10.1038/s41592-018-0049-4
  6. Wang EY, Fahey PG, Ding Z, Papadopoulos S, Ponder K, Weis MA, et al.. Foundation model of neural activity predicts response to new stimulus types. Nature 2025;640(8058):470-477. doi:10.1038/s41586-025-08829-y
  7. Fischl B. FreeSurfer. NeuroImage 2012;62(2):774-781. doi:10.1016/j.neuroimage.2012.01.021
  8. Yeh F-C. Population-Probability Atlas and Tract-to-Region Connectome (HCP-1065), data release. brain.labsolver.org 2022. https://brain.labsolver.org/hcp_trk_atlas.html
  9. Brodmann K, Garey LJ (translator). Brodmann's Localisation in the Cerebral Cortex. Springer (English translation of the 1909 original) 2005. doi:10.1007/b138298
  10. Amunts K, Lepage C, Borgeat L, Mohlberg H, Dickscheid T, Rousseau MÉ, et al.. BigBrain: an ultrahigh-resolution 3D human brain model. Science 2013;340(6139):1472-1475. doi:10.1126/science.1235381
  11. Lein ES, Hawrylycz MJ, Ao N, Ayres M, Bensinger A, Bernard A, et al.. Genome-wide atlas of gene expression in the adult mouse brain. Nature 2007;445(7124):168-176. doi:10.1038/nature05453
  12. Hawrylycz MJ, Lein ES, Guillozet-Bongaarts AL, Shen EH, Ng L, Miller JA, et al.. An anatomically comprehensive atlas of the adult human brain transcriptome. Nature 2012;489(7416):391-399. doi:10.1038/nature11405
  13. Siletti K, Hodge R, Mossi Albiach A, Lee KW, Ding SL, Hu L, et al.. Transcriptomic diversity of cell types across the adult human brain. Science 2023;382(6667):eadd7046. doi:10.1126/science.add7046
  14. Winding M, Pedigo BD, Barnes CL, Patsolic HG, Park Y, Kazimiers T, et al.. The connectome of an insect brain. Science 2023;379(6636):eadd9330. doi:10.1126/science.add9330
  15. The MICrONS Consortium, Bae JA, Baptiste M, et al.. Functional connectomics spanning multiple areas of mouse visual cortex. Nature 2025;640(8058):435-447. doi:10.1038/s41586-025-08790-w
  16. Glasser MF, Coalson TS, Robinson EC, Hacker CD, Harwell J, Yacoub E, et al.. A multi-modal parcellation of human cerebral cortex. Nature 2016;536(7615):171-178. doi:10.1038/nature18933
  17. Bethlehem RAI, Seidlitz J, White SR, Vogel JW, Anderson KM, Adamson C, et al.. Brain charts for the human lifespan. Nature 2022;604(7906):525-533. doi:10.1038/s41586-022-04554-y
  18. Chung K, Wallace J, Kim SY, Kalyanasundaram S, Andalman AS, Davidson TJ, et al.. Structural and molecular interrogation of intact biological systems. Nature 2013;497(7449):332-337. doi:10.1038/nature12107
  19. Chen F, Tillberg PW, Boyden ES. Expansion microscopy. Science 2015;347(6221):543-548. doi:10.1126/science.1260088
  20. Jun JJ, Steinmetz NA, Siegle JH, Denman DJ, Bauza M, Barbarits B, et al.. Fully integrated silicon probes for high-density recording of neural activity. Nature 2017;551(7679):232-236. doi:10.1038/nature24636
  21. Ahrens MB, Orger MB, Robson DN, Li JM, Keller PJ. Whole-brain functional imaging at cellular resolution using light-sheet microscopy. Nature Methods 2013;10(5):413-420. doi:10.1038/nmeth.2434
  22. Boyden ES, Zhang F, Bamberg E, Nagel G, Deisseroth K. Millisecond-timescale, genetically targeted optical control of neural activity. Nature Neuroscience 2005;8(9):1263-1268. doi:10.1038/nn1525
  23. Abbe E. Beiträge zur Theorie des Mikroskops und der mikroskopischen Wahrnehmung. Archiv für Mikroskopische Anatomie 1873;9(1):413-468. doi:10.1007/BF02956173
  24. Willett FR, Kunz EM, Fan C, Avansino DT, Wilson GH, Choi EY, et al.. A high-performance speech neuroprosthesis. Nature 2023;620(7976):1031-1036. doi:10.1038/s41586-023-06377-x

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Template anatomy for education. Not patient-specific. Not for clinical decision-making.