{"id":1899,"date":"2019-05-29T22:10:59","date_gmt":"2019-05-29T12:10:59","guid":{"rendered":"https:\/\/www.cognav.net\/?p=1899"},"modified":"2019-05-29T22:10:59","modified_gmt":"2019-05-29T12:10:59","slug":"planning-at-decision-time-and-in-the-background-during-spatial-navigation","status":"publish","type":"post","link":"https:\/\/braininspirednavigation.com\/?p=1899","title":{"rendered":"Planning at decision time and in the background during spatial navigation"},"content":{"rendered":"<p>Pezzulo, Giovanni, Francesco Donnarumma, Domenico Maisto, and Ivilin Stoianov. &#8220;<a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S2352154618301682\"><strong>Planning at decision time and in the background during spatial navigation<\/strong><\/a>.&#8221;\u00a0<i>Current Opinion in Behavioral Sciences<\/i>\u00a029 (2019): 69-76.<\/p>\n<p>Highlights<br \/>\n\u2022 Planning is the model-based approach to solving control problems.<\/p>\n<p>\u2022 We review recent studies of planning during spatial navigation in rodents and humans.<\/p>\n<p>\u2022 We distinguish two complementary planning modes: \u2018at decision time\u2019 and \u2018in the background\u2019.<\/p>\n<p>\u2022 We discuss the putative neuronal signatures of the two planning modes in the rodent brain.<\/p>\n<p>\u2022 We make parallels between empirical evidence and planning models in artificial intelligence.<\/p>\n<p style=\"text-align: justify;\">Planning is the model-based approach to solving control problems. <strong><span style=\"color: #ff0000;\">The hallmark of planning is the endogenous generation of dynamical representations of future states, like goal locations, or state sequences, like trajectories to the goal location, using an internal model of the task.<\/span><\/strong> We <strong><span style=\"color: #ff0000;\">review recent evidence of model-based planning processes and the representation of future goal states in the brain of rodents and humans engaged in spatial navigation tasks.<\/span><\/strong> We highlight two distinct but complementary usages of planning as identified in artificial intelligence:<strong><span style=\"color: #ff0000;\"> \u2018at decision time\u2019<\/span><\/strong>, to support goal-directed choices and sequential\u00a0<a title=\"Learn more about Memory from ScienceDirect's AI-generated Topic Pages\" href=\"https:\/\/www.sciencedirect.com\/topics\/neuroscience\/memory\">memory<\/a>\u00a0encoding, and <span style=\"color: #ff0000;\"><strong>\u2018in the background\u2019,<\/strong> <\/span>to learn behavioral policies and to optimize internal models. We discuss how two kinds of internally generated sequences in the\u00a0<a title=\"Learn more about Hippocampus from ScienceDirect's AI-generated Topic Pages\" href=\"https:\/\/www.sciencedirect.com\/topics\/neuroscience\/hippocampus\">hippocampus<\/a>\u2013 theta and SWR sequences \u2013 might participate in the neuronal implementation of these two planning modes, thus supporting a flexible model-based system for adaptive cognition and action.<\/p>\n<p>For further info, please read the paper\u00a0Pezzulo et al. 2019<\/p>\n<p>Pezzulo, Giovanni, Francesco Donnarumma, Domenico Maisto, and Ivilin Stoianov. &#8220;<a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S2352154618301682\"><strong>Planning at decision time and in the background during spatial navigation<\/strong><\/a>.&#8221;\u00a0<i>Current Opinion in Behavioral Sciences<\/i>\u00a029 (2019): 69-76.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Pezzulo, Giovanni, Francesco Donnarumma, Domenico Maisto, and Ivilin Stoianov. &#8220;Planning at decision time and in the background during spatial navigation.&#8221;\u00a0Current Opinion in Behavioral Sciences\u00a029 (2019): 69-76. Highlights \u2022 Planning is the model-based approach to solving control problems. \u2022 We review recent studies of planning during spatial navigation in rodents and humans. \u2022 We distinguish two [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[346],"tags":[149,211],"_links":{"self":[{"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=\/wp\/v2\/posts\/1899"}],"collection":[{"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1899"}],"version-history":[{"count":1,"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=\/wp\/v2\/posts\/1899\/revisions"}],"predecessor-version":[{"id":1900,"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=\/wp\/v2\/posts\/1899\/revisions\/1900"}],"wp:attachment":[{"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1899"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1899"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/braininspirednavigation.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1899"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}