Quantitative Biology > Neurons and Cognition
[Submitted on 17 May 2024 (v1), last revised 23 Nov 2024 (this version, v3)]
Title:Comparative prospects of imaging methods for whole-brain mammalian connectomics
View PDFAbstract:Mammalian whole-brain connectomes at nanoscale synaptic resolution are a crucial ingredient for holistic understanding of brain function. Imaging these connectomes at sufficient resolution to densely reconstruct cellular morphology and synapses represents a longstanding goal in neuroscience. Although the technologies needed to reconstruct whole-brain connectomes have not yet reached full maturity, they are advancing rapidly enough that the mouse brain might be within reach in the near future. Detailed exploration of these technologies is warranted to help plan projects with varying goals and requirements. Whole-brain human connectomes remain a more distant goal yet are worthy of consideration to orient large-scale neuroscience program plans. Here, we quantitatively compare existing and emerging imaging technologies that have potential to enable whole-brain mammalian connectomics. We perform calculations on electron microscopy (EM) techniques and expansion microscopy coupled with light-sheet fluorescence microscopy (ExLSFM) methods. We consider techniques from the literature that have sufficiently high resolution to identify all synapses and sufficiently high speed to be relevant for whole mammalian brains. Each imaging modality comes with benefits and drawbacks, so we suggest that attacking the problem through multiple approaches could yield the best outcomes. We offer this analysis as a resource for those considering how to organize efforts towards imaging whole-brain mammalian connectomes.
Submission history
From: Logan Thrasher Collins [view email][v1] Fri, 17 May 2024 01:26:22 UTC (438 KB)
[v2] Fri, 23 Aug 2024 04:16:54 UTC (450 KB)
[v3] Sat, 23 Nov 2024 21:31:54 UTC (1,081 KB)
Current browse context:
q-bio.NC
References & Citations
Bibliographic and Citation Tools
Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)
Code, Data and Media Associated with this Article
alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)
Demos
Recommenders and Search Tools
Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.