{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,30]],"date-time":"2025-04-30T17:10:07Z","timestamp":1746033007157,"version":"3.40.4"},"reference-count":41,"publisher":"MIT Press","issue":"4","content-domain":{"domain":["direct.mit.edu"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2014,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Neuroanatomical tracer studies in the nonhuman primate macaque monkey are a valuable resource for cognitive neuroscience research. These data ground theories of cognitive function in anatomy, and with the emergence of graph theoretical analyses in neuroscience, there is high demand for these data to be consolidated into large-scale connection matrices (\u201cmacroconnectomes\u201d). Because manual review of the anatomical literature is time consuming and error prone, computational solutions are needed to accomplish this task. Here we describe the \u201cCoCoTools\u201d open-source Python library, which automates collection and integration of macaque connectivity data for visualization and graph theory analysis. CoCoTools both interfaces with the CoCoMac database, which houses a vast amount of annotated tracer results from 100 years (1905\u20132005) of neuroanatomical research, and implements coordinate-free registration algorithms, which allow studies that use different parcellations of the brain to be translated into a single graph. We show that using CoCoTools to translate all of the data stored in CoCoMac produces graphs with properties consistent with what is known about global brain organization. Moreover, in addition to describing CoCoTools' processing pipeline, we provide worked examples, tutorials, links to on-line documentation, and detailed appendices to aid scientists interested in using CoCoTools to gather and analyze CoCoMac data.<\/jats:p>","DOI":"10.1162\/jocn_a_00498","type":"journal-article","created":{"date-parts":[[2013,10,11]],"date-time":"2013-10-11T19:49:06Z","timestamp":1381520946000},"page":"722-745","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":8,"title":["CoCoTools: Open-source Software for Building Connectomes Using the CoCoMac Anatomical Database"],"prefix":"10.1162","volume":"26","author":[{"given":"Robert S.","family":"Blumenfeld","sequence":"first","affiliation":[]},{"given":"Daniel P.","family":"Bliss","sequence":"additional","affiliation":[]},{"given":"Fernando","family":"Perez","sequence":"additional","affiliation":[]},{"given":"Mark","family":"D'Esposito","sequence":"additional","affiliation":[]}],"member":"281","published-online":{"date-parts":[[2014,4,1]]},"reference":[{"key":"2021073000371227200_R1","doi-asserted-by":"crossref","DOI":"10.3389\/fninf.2012.00030","article-title":"CoCoMac 2.0 and the future of tract-tracing databases.","volume":"6","author":"Bakker","year":"2012","journal-title":"Frontiers in Neuroinformatics"},{"key":"2021073000371227200_R2","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1177\/1073858406293182","article-title":"Small-world brain networks.","volume":"12","author":"Bassett","year":"2006","journal-title":"The Neuroscientist: A Review Journal Bringing Neurobiology, Neurology and Psychiatry"},{"key":"2021073000371227200_R3","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/s12021-008-9039-5","article-title":"Matching spatial with ontological brain regions using Java tools for visualization, database access, and integrated data analysis.","volume":"7","author":"Bezgin","year":"2009","journal-title":"Neuroinformatics"},{"key":"2021073000371227200_R4","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.neuroimage.2012.04.013","article-title":"Hundreds of brain maps in one atlas: Registering coordinate-independent primate neuro-anatomical data to a standard brain.","volume":"62","author":"Bezgin","year":"2012","journal-title":"Neuroimage"},{"key":"2021073000371227200_R5","doi-asserted-by":"crossref","first-page":"1132","DOI":"10.1016\/j.neunet.2008.05.010","article-title":"Deducing logical relationships between spatially registered cortical parcellations under conditions of uncertainty.","volume":"21","author":"Bezgin","year":"2008","journal-title":"Neural Networks: The Official Journal of the International Neural Network Society"},{"key":"2021073000371227200_R6","first-page":"177","article-title":"Beitraege zur histologischen Lokalisation der Grosshirnrinde. 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