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Natl. Acad. Sci. U.S.A."],"published-print":{"date-parts":[[2018,10,30]]},"abstract":"<jats:title>Significance<\/jats:title>\n                  <jats:p>\n                    Artificial neural networks can suffer from catastrophic forgetting, in which learning a new task causes the network to forget how to perform previous tasks. While previous studies have proposed various methods that can alleviate forgetting over small numbers (\n                    <jats:inline-formula>\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" overflow=\"scroll\">\n                        <mml:mo>\u2a7d<\/mml:mo>\n                      <\/mml:math>\n                    <\/jats:inline-formula>\n                    10) of tasks, it is uncertain whether they can prevent forgetting across larger numbers of tasks. In this study, we propose a neuroscience-inspired scheme, called \u201ccontext-dependent gating,\u201d in which mostly nonoverlapping sets of units are active for any one task. Importantly, context-dependent gating has a straightforward implementation, requires little extra computational overhead, and when combined with previous methods to stabilize connection weights, can allow networks to maintain high performance across large numbers of sequentially presented tasks.\n                  <\/jats:p>","DOI":"10.1073\/pnas.1803839115","type":"journal-article","created":{"date-parts":[[2018,10,12]],"date-time":"2018-10-12T14:25:11Z","timestamp":1539354311000},"update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":215,"title":["Alleviating catastrophic forgetting using context-dependent gating and synaptic stabilization"],"prefix":"10.1073","volume":"115","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9094-1298","authenticated-orcid":false,"given":"Nicolas Y.","family":"Masse","sequence":"first","affiliation":[{"name":"Department of Neurobiology, The University of Chicago, Chicago, IL 60637;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gregory D.","family":"Grant","sequence":"additional","affiliation":[{"name":"Department of Neurobiology, The University of Chicago, Chicago, IL 60637;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David J.","family":"Freedman","sequence":"additional","affiliation":[{"name":"Department of Neurobiology, The University of Chicago, Chicago, IL 60637;"},{"name":"The Grossman Institute for Neuroscience, Quantitative Biology and Human Behavior, The University of Chicago, Chicago, IL 60637"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"341","published-online":{"date-parts":[[2018,10,12]]},"reference":[{"key":"e_1_3_4_1_2","volume-title":"The Fine Structure of the Nervous System: Neurons and Their Supporting Cells","author":"Peters A","year":"1991","unstructured":"A Peters The Fine Structure of the Nervous System: Neurons and Their Supporting Cells (Oxford Univ Press, Oxford, 1991)."},{"key":"e_1_3_4_2_2","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1016\/S0166-2236(03)00162-0","article-title":"Structure\u2013stability\u2013function relationships of dendritic spines","volume":"26","author":"Kasai H","year":"2003","unstructured":"H Kasai, M Matsuzaki, J Noguchi, N Yasumatsu, H Nakahara, Structure\u2013stability\u2013function relationships of dendritic spines. Trends Neurosci 26, 360\u2013368 (2003).","journal-title":"Trends Neurosci"},{"key":"e_1_3_4_3_2","doi-asserted-by":"crossref","first-page":"1071","DOI":"10.1146\/annurev.neuro.24.1.1071","article-title":"Morphological changes in dendritic spines associated with long-term synaptic plasticity","volume":"24","author":"Yuste R","year":"2001","unstructured":"R Yuste, T Bonhoeffer, Morphological changes in dendritic spines associated with long-term synaptic plasticity. Annu Rev Neurosci 24, 1071\u20131089 (2001).","journal-title":"Annu Rev Neurosci"},{"key":"e_1_3_4_4_2","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.conb.2009.05.013","article-title":"Dendritic spine formation and stabilization","volume":"19","author":"Yoshihara Y","year":"2009","unstructured":"Y Yoshihara, M De Roo, D Muller, Dendritic spine formation and stabilization. Curr Opin Neurobiol 19, 146\u2013153 (2009).","journal-title":"Curr Opin Neurobiol"},{"key":"e_1_3_4_5_2","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1016\/S0896-6273(00)80467-5","article-title":"Rapid actin-based plasticity in dendritic spines","volume":"20","author":"Fischer M","year":"1998","unstructured":"M Fischer, S Kaech, D Knutti, A Matus, Rapid actin-based plasticity in dendritic spines. Neuron 20, 847\u2013854 (1998).","journal-title":"Neuron"},{"key":"e_1_3_4_6_2","doi-asserted-by":"crossref","first-page":"920","DOI":"10.1038\/nature08577","article-title":"Stably maintained dendritic spines are associated with lifelong memories","volume":"462","author":"Yang G","year":"2009","unstructured":"G Yang, F Pan, W-B Gan, Stably maintained dendritic spines are associated with lifelong memories. Nature 462, 920\u2013924 (2009).","journal-title":"Nature"},{"key":"e_1_3_4_7_2","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1038\/nature08389","article-title":"Rapid formation and selective stabilization of synapses for enduring motor memories","volume":"462","author":"Xu T","year":"2009","unstructured":"T Xu, , Rapid formation and selective stabilization of synapses for enduring motor memories. Nature 462, 915\u2013919 (2009).","journal-title":"Nature"},{"key":"e_1_3_4_8_2","first-page":"3987","volume-title":"International Conference on Machine Learning","author":"Zenke F","year":"2017","unstructured":"F Zenke, B Poole, S Ganguli, Continual learning through synaptic intelligence. International Conference on Machine Learning (International Machine Learning Society, Princeton), pp. 3987\u20133995 (2017)."},{"key":"e_1_3_4_9_2","doi-asserted-by":"crossref","first-page":"3521","DOI":"10.1073\/pnas.1611835114","article-title":"Overcoming catastrophic forgetting in neural networks","volume":"114","author":"Kirkpatrick J","year":"2017","unstructured":"J Kirkpatrick, , Overcoming catastrophic forgetting in neural networks. Proc Natl Acad Sci USA 114, 3521\u20133526 (2017).","journal-title":"Proc Natl Acad Sci USA"},{"key":"e_1_3_4_10_2","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1038\/nature14251","article-title":"Branch-specific dendritic Ca2+ spikes cause persistent synaptic plasticity","volume":"520","author":"Cichon J","year":"2015","unstructured":"J Cichon, W-B Gan, Branch-specific dendritic Ca2+ spikes cause persistent synaptic plasticity. Nature 520, 180\u2013185 (2015).","journal-title":"Nature"},{"key":"e_1_3_4_11_2","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.neuron.2013.12.025","article-title":"Sleep and the price of plasticity: From synaptic and cellular homeostasis to memory consolidation and integration","volume":"81","author":"Tononi G","year":"2014","unstructured":"G Tononi, C Cirelli, Sleep and the price of plasticity: From synaptic and cellular homeostasis to memory consolidation and integration. Neuron 81, 12\u201334 (2014).","journal-title":"Neuron"},{"key":"e_1_3_4_12_2","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/j.neuron.2017.05.029","article-title":"Memory takes time","volume":"95","author":"Kukushkin NV","year":"2017","unstructured":"NV Kukushkin, TJ Carew, Memory takes time. Neuron 95, 259\u2013279 (2017).","journal-title":"Neuron"},{"key":"e_1_3_4_13_2","unstructured":"IJ Goodfellow M Mirza Da Xiao A Courville Y Bengio An empirical investigation of catastrophic forgetting in gradient-based neural networks. arXiv:1312.6211. (2013)."},{"key":"e_1_3_4_14_2","first-page":"248","article-title":"Imagenet: A large-scale hierarchical image database","author":"Deng J","year":"2009","unstructured":"J Deng, , Imagenet: A large-scale hierarchical image database. IEEE Conference on Computer Vision and Pattern Recognition, pp. 248\u2013255 (2009).","journal-title":"IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"e_1_3_4_15_2","doi-asserted-by":"crossref","unstructured":"G Robert Yang H Francis Song WT Newsome X-J Wang Clustering and compositionality of task representations in a neural network trained to perform many cognitive tasks bioRxiv:183632. 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Neuron 53, 453\u2013462 (2007).","journal-title":"Neuron"},{"key":"e_1_3_4_18_2","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1146\/annurev.neuro.24.1.167","article-title":"An integrative theory of prefrontal cortex function","volume":"24","author":"Miller EK","year":"2001","unstructured":"EK Miller, JD Cohen, An integrative theory of prefrontal cortex function. Annu Rev Neurosci 24, 167\u2013202 (2001).","journal-title":"Annu Rev Neurosci"},{"key":"e_1_3_4_19_2","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1038\/nn.4436","article-title":"Parallel processing by cortical inhibition enables context-dependent behavior","volume":"20","author":"Kuchibhotla KV","year":"2017","unstructured":"KV Kuchibhotla, , Parallel processing by cortical inhibition enables context-dependent behavior. 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Neural Comput 9, 1735\u20131780 (1997).","journal-title":"Neural Comput"},{"key":"e_1_3_4_22_2","unstructured":"A Santoro S Bartunov M Botvinick D Wierstra T Lillicrap One-shot learning with memory-augmented neural networks. arXiv:1605.06065. (2016)."},{"key":"e_1_3_4_23_2","first-page":"2526","volume-title":"Advances in Neural Information Processing Systems","author":"Lake BM","year":"2013","unstructured":"BM Lake, RR Salakhutdinov, J Tenenbaum, One-shot learning by inverting a compositional causal process. Advances in Neural Information Processing Systems, eds CJC Burges, L Bottou, M Welling, Z Ghahramani, KQ Weinberger (Curran Assoc, Red Hook, NY), pp. 2526\u20132534 (2013)."},{"key":"e_1_3_4_24_2","unstructured":"C Fernando PathNet: Evolution channels gradient descent in super neural networks. arXiv:1701.08734. (2017)."},{"key":"e_1_3_4_25_2","doi-asserted-by":"crossref","first-page":"7641","DOI":"10.1073\/pnas.1018985108","article-title":"Dynamic reconfiguration of human brain networks during learning","volume":"108","author":"Bassett DS","year":"2011","unstructured":"DS Bassett, , Dynamic reconfiguration of human brain networks during learning. Proc Natl Acad Sci USA 108, 7641\u20137646 (2011).","journal-title":"Proc Natl Acad Sci USA"},{"key":"e_1_3_4_26_2","doi-asserted-by":"crossref","unstructured":"R Velez J Clune Diffusion-based neuromodulation can eliminate catastrophic forgetting in simple neural networks. arXiv:1705.07241. (2017).","DOI":"10.1371\/journal.pone.0187736"},{"key":"e_1_3_4_27_2","unstructured":"AA Rusu Progressive neural networks. arXiv:1606.04671. (2016)."},{"key":"e_1_3_4_28_2","article-title":"Learning without forgetting","author":"Li Z","year":"2018","unstructured":"Z Li, D Hoiem, Learning without forgetting. IEEE Trans Pattern Anal Mach Intell, 2018).","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"e_1_3_4_29_2","doi-asserted-by":"crossref","unstructured":"R Aljundi F Babiloni M Elhoseiny M Rohrbach T Tuytelaars Memory aware synapses: Learning what (not) to forget. arXiv:1711.09601. (2017).","DOI":"10.1007\/978-3-030-01219-9_9"},{"key":"e_1_3_4_30_2","unstructured":"CV Nguyen Y Li TD Bui RE Turner Variational continual learning. arXiv:1710.10628. (2017)."},{"key":"e_1_3_4_31_2","unstructured":"X He H Jaeger Overcoming catastrophic interference by conceptors. arXiv:1707.04853. (2017)."},{"key":"e_1_3_4_32_2","doi-asserted-by":"crossref","unstructured":"A Mallya S Lazebnik Packnet: Adding multiple tasks to a single network by iterative pruning. arXiv:1711.05769. (2017).","DOI":"10.1109\/CVPR.2018.00810"},{"key":"e_1_3_4_33_2","unstructured":"J Serr\u00e0 D Sur\u00eds M Miron A Karatzoglou Overcoming catastrophic forgetting with hard attention to the task. arXiv:1801.01423. (2018)."},{"key":"e_1_3_4_34_2","unstructured":"M Abadi Tensorflow: Large-scale machine learning on heterogeneous distributed systems. arXiv:1603.04467. (2016)."},{"key":"e_1_3_4_35_2","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava N","year":"2014","unstructured":"N Srivastava, G Hinton, A Krizhevsky, I Sutskever, R Salakhutdinov, Dropout: A simple way to prevent neural networks from overfitting. J Machine Learn Res 15, 1929\u20131958 (2014).","journal-title":"J Machine Learn Res"},{"key":"e_1_3_4_36_2","unstructured":"D Kingma J Ba Adam: A method for stochastic optimization. arXiv:1412.6980. (2014)."},{"key":"e_1_3_4_37_2","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1109\/TSMC.1983.6313077","article-title":"Neuronlike adaptive elements that can solve difficult learning control problems","volume":"5","author":"Barto AG","year":"1983","unstructured":"AG Barto, RS Sutton, CW Anderson, Neuronlike adaptive elements that can solve difficult learning control problems. IEEE Trans Syst Man Cybernetics 5, 834\u2013846 (1983).","journal-title":"IEEE Trans Syst Man Cybernetics"},{"key":"e_1_3_4_38_2","unstructured":"J Schulman P Moritz S Levine M Jordan P Abbeel High-dimensional continuous control using generalized advantage estimation. arXiv:1506.02438. 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