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Connectomics is a high-throughput application of neural imaging and histological techniques in order to increase the speed, efficiency, and resolution of maps of the multitude of neural connections in a nervous system. The principal focus of such a project is the brain, although any neural connections could theoretically be mapped by connectomics, including, for example, neuromuscular junctions. The map produced by such a project is called a connectome.
One of the main tools used for connectomics research at the macroscale level is diffusion MRI. The main tool for connectomics research at the microscale level is 3D electron microscopy. To see one of the first micro-connectomes at full-resolution, visit the Open Connectome Project, which is hosting several connectome datasets, including the 12TB dataset from Bock et al. (2011).
By comparing diseased connectome and healthy connectomes, we should gain insight into certain psychopathologies, such as neuropathic pain, and potential therapies for them. Generally, the field of neuroscience would benefit from standardization and raw data. For example, connectome maps can be used to inform computational models of whole-brain dynamics. Current neural networks mostly rely on probabilistic representations of connectivity patterns.
Local measures of difference between populations of those graph have been also introduced (e.g. to compare case versus control groups). Those can be found by using either an adjusted t-test or a sparsity model, with the aim of finding statistically significant connections which are different among those groups.
Template:Criticism section The use of the word -omics to describe this system has been criticized. The coinage of the word is seen in two sources, in an article by Olaf Sporns and a PhD thesis by Patric Hagmann.
Others have criticized attempts towards a microscale connectome, arguing that we don't have enough knowledge about where to look for insights, or that it cannot be completed within a realistic time frame.
Comparison to genomics
The human genome project initially faced many of the above criticisms, but was nevertheless completed ahead of schedule and has led to many advances in genetics. Some have argued that analogies can be made between genomics and connectomics, and therefore we should be at least slightly more optimistic about the prospects in connectomics.
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- http://www.scholarpedia.org/article/ConnectomeTemplate:Unreliable medical sourceTemplate:Self-published inline
- (2009). Towards Reproducible Descriptions of Neuronal Network Models. PLoS Computational Biology 5 (8): e1000456.
- (2019). MultiLink analysis: brain network comparison via sparse connectivity analysis. Nature Scientific reports 9 (1): 1–13.
- (2010). Network-based statistic: identifying differences in brain networks.. Neuroimage 53 (4): 1197-1207.
- "Bad omics word of the day: connectome" Kaboodle.nescent.org. January 31, 2010 Template:Self-published inline
- Talk:Connectome. Scholarpedia.org.Template:Unreliable medical sourceTemplate:Self-published inline
- (2005). The Human Connectome: A Structural Description of the Human Brain. PLoS Computational Biology 1 (4): e42.
- Hagmann, Patric (April 21, 2005). "From Diffusion MRI to Brain Connectomics" (PDF). Ecole Polytechnique Federale de Lausanne. Ph.D. Thesis. pp. 1, 107.
- includeonly>Vance, Ashlee. "Seeking the Connectome, a Mental Map, Slice by Slice", The New York Times, 27 December 2010.
- (2008). Ome sweet ome: what can the genome tell us about the connectome?. Current Opinion in Neurobiology 18 (3): 346–53.
- (2008). Mapping the Structural Core of Human Cerebral Cortex. PLoS Biology 6 (7): e159.
- Open Connectome Project
- The Connectome Project at Harvard
- Connectome Research by EPFL/CHUV, Lausanne, Switzerland
- The NIH Blueprint for Neuroscience Research
- TED talk by Sebastian Seung: "I am my connectome".
- TEDx talk by Alessandro Crimi: "Networks, From the Brain to the Internet and Back".
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