{"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/stick-spike-time-interval-computational","title":"STICK: Spike Time Interval Computational Kernel, A Framework for General Purpose Computation using Neurons, Precise Timing, Delays, and Synchrony","arxiv_id":"1507.06222","date":"2015-07-22","proceeding":null,"authors":["Xavier Lagorce","Ryad Benosman"],"abstract":"There has been significant research over the past two decades in developing\nnew platforms for spiking neural computation. Current neural computers are\nprimarily developed to mimick biology. They use neural networks which can be\ntrained to perform specific tasks to mainly solve pattern recognition problems.\nThese machines can do more than simulate biology, they allow us to re-think our\ncurrent paradigm of computation. The ultimate goal is to develop brain inspired\ngeneral purpose computation architectures that can breach the current\nbottleneck introduced by the Von Neumann architecture. This work proposes a new\nframework for such a machine. We show that the use of neuron like units with\nprecise timing representation, synaptic diversity, and temporal delays allows\nus to set a complete, scalable compact computation framework. The presented\nframework provides both linear and non linear operations, allowing us to\nrepresent and solve any function. We show usability in solving real use cases\nfrom simple differential equations to sets of non-linear differential equations\nleading to chaotic attractors.","url_abs":"http://arxiv.org/abs/1507.06222v1","url_pdf":"http://arxiv.org/pdf/1507.06222v1.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":"stick-spike-time-interval-computational","repo_url":"https://github.com/MarionTormento/GML_STICK","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"diversity","task_name":"Diversity"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}