{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/inferring-network-connectivity-from-event","title":"Inferring network connectivity from event timing patterns","arxiv_id":"1803.09974","date":"2018-03-27","proceeding":null,"authors":["Jose Casadiego","Dimitra Maoutsa","Marc Timme"],"abstract":"Reconstructing network connectivity from the collective dynamics of a system\ntypically requires access to its complete continuous-time evolution although\nthese are often experimentally inaccessible. Here we propose a theory for\nrevealing physical connectivity of networked systems only from the event time\nseries their intrinsic collective dynamics generate. Representing the patterns\nof event timings in an event space spanned by inter-event and cross-event\nintervals, we reveal which other units directly influence the inter-event times\nof any given unit. For illustration, we linearize an event space mapping\nconstructed from the spiking patterns in model neural circuits to reveal the\npresence or absence of synapses between any pair of neurons as well as whether\nthe coupling acts in an inhibiting or activating (excitatory) manner. The\nproposed model-independent reconstruction theory is scalable to larger networks\nand may thus play an important role in the reconstruction of networks from\nbiology to social science and engineering.","url_abs":"http://arxiv.org/abs/1803.09974v2","url_pdf":"http://arxiv.org/pdf/1803.09974v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"inferring-network-connectivity-from-event","repo_url":"https://gitlab.com/di.ma/Connectivity_from_event_timing_patterns","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"inferring-network-connectivity-from-event","repo_url":"https://github.com/networkinference/ESL","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"inferring-network-connectivity-from-event","repo_url":"https://github.com/dimitra-maoutsa/Connectivity_from_event_timing_patterns","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"time-series-1","task_name":"Time Series"},{"task_slug":"time-series","task_name":"Time Series Analysis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1803.09974","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1803.09974"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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