Connectomics

Connectomics is the production and study of connectomes: comprehensive maps of connections within an organism's nervous system. More generally, it can be thought of as the study of neuronal wiring diagrams with a focus on how structural connectivity, individual synapses, cellular morphology, and cellular ultrastructure contribute to the make up of a network. The nervous system is a network made of billions of connections and these connections are responsible for our thoughts, emotions, actions, memories, function and dysfunction. Therefore, the study of connectomics aims to advance our understanding of mental health and cognition by understanding how cells in the nervous system are connected and communicate. Because these structures are extremely complex, methods within this field use a high-throughput application of functional and structural neural imaging, most commonly magnetic resonance imaging (MRI), electron microscopy, and histological techniques in order to increase the speed, efficiency, and resolution of these nervous system maps. To date, tens of large scale datasets have been collected spanning the nervous system including the various areas of cortex, cerebellum,[1][2] the retina,[3] the peripheral nervous system[4] and neuromuscular junctions.[5]

Generally speaking, there are two types of connectomes; macroscale and microscale. Macroscale connectomics refers to using functional and structural MRI data to map out large fiber tracts and functional gray matter areas within the brain in terms of blood flow (functional) and water diffusivity (structural). Microscale connectomics is the mapping of small organisms' complete connectome using microscopy and histology. That is, all connections that exist in their central nervous system.

  1. ^ Quartarone A, Cacciola A, Milardi D, Ghilardi MF, Calamuneri A, Chillemi G, et al. (February 2020). "New insights into cortico-basal-cerebellar connectome: clinical and physiological considerations". Brain. 143 (2): 396–406. doi:10.1093/brain/awz310. PMID 31628799.
  2. ^ Nguyen TM, Thomas LA, Rhoades JL, Ricchi I, Yuan XC, Sheridan A, et al. (2023-01-19). "Structured cerebellar connectivity supports resilient pattern separation". Nature. 613 (7944): 543–549. bioRxiv 10.1101/2021.11.29.470455. doi:10.1038/s41586-022-05471-w. ISSN 0028-0836. PMC 10324966. PMID 36418404.
  3. ^ Helmstaedter M, Briggman KL, Turaga SC, Jain V, Seung HS, Denk W (August 2013). "Connectomic reconstruction of the inner plexiform layer in the mouse retina". Nature. 500 (7461): 168–174. Bibcode:2013Natur.500..168H. doi:10.1038/nature12346. PMID 23925239. S2CID 3119909.
  4. ^ Phelps JS, Hildebrand DG, Graham BJ, Kuan AT, Thomas LA, Nguyen TM, et al. (February 2021). "Reconstruction of motor control circuits in adult Drosophila using automated transmission electron microscopy". Cell. 184 (3): 759–774.e18. doi:10.1016/j.cell.2020.12.013. PMC 8312698. PMID 33400916.
  5. ^ Boonstra TW, Danna-Dos-Santos A, Xie HB, Roerdink M, Stins JF, Breakspear M (December 2015). "Muscle networks: Connectivity analysis of EMG activity during postural control". Scientific Reports. 5: 17830. Bibcode:2015NatSR...517830B. doi:10.1038/srep17830. PMC 4669476. PMID 26634293.

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