{"@context":"https://schema.org","@type":"ScholarlyArticle","identifier":"https://research.mahastrategies.com/papers/readout_plasticity_paper","name":"Evolving Local Synaptic Plasticity Rules to Track Representational Drift","version":"1.0.0","dateModified":"2026-06-07","creativeWorkStatus":"Working paper","reviewStatus":"Not peer reviewed","url":"https://research.mahastrategies.com/papers/readout_plasticity_paper","encoding":[{"@type":"MediaObject","encodingFormat":"application/pdf","contentUrl":"https://research.mahastrategies.com/papers/readout_plasticity_paper.pdf"},{"@type":"MediaObject","encodingFormat":"application/x-bibtex","contentUrl":"https://research.mahastrategies.com/papers/readout_plasticity_paper/citation.bib"},{"@type":"MediaObject","encodingFormat":"text/yaml","contentUrl":"https://research.mahastrategies.com/papers/readout_plasticity_paper/citation.cff"}],"citation":[{"id":"readout_plasticity_paper-ref-1","text":"**Driscoll, L. N., Pettit, N. L., Minderer, M., Chettih, S. N., & Harvey, C. D. (2017).** *Dynamic reorganization of neuronal activity patterns in parietal cortex.* Cell, 170(5), 986-999.","verification":"unclassified"},{"id":"readout_plasticity_paper-ref-2","text":"**Rule, M. E., & O'Leary, T. (2022).** *Self-healing codes: How stable neural populations can track continually reconfiguring neural representations.* PNAS, 119(7), e2106692119.","verification":"unclassified"},{"id":"readout_plasticity_paper-ref-3","text":"**Oja, E. (1982).** *Simplified neuron model as a principal component analyzer.* Journal of Mathematical Biology, 15(3), 267-273.","verification":"unclassified"}],"bibtex":"@article{rajan2026readoutplasticitypaper,\n  author = {Rajan, Mayone Maha},\n  title = {Evolving Local Synaptic Plasticity Rules to Track Representational Drift},\n  journal = {Maha Strategies Research},\n  year = {2026},\n  version = {1.0.0},\n  url = {https://research.mahastrategies.com/papers/readout_plasticity_paper},\n  note = {Working paper; not peer reviewed}\n}"}