{"pk":5346,"title":"Misbehavior in a Neural Network Model","subtitle":null,"abstract":"This paper describes a neural network account of misbehavior with an extant neural network model of conditioning.  The model makes no distinction between learning (weight-change mechanisms) in operant and Pavlovian conditioning, but preserves the standard behavioral distinctions between types of stimuli, responses, and contingencies, with connectionist interpretations of some possible neuroanatomical substrates.  Misbehavior has been traditionally conceived as a species-specific response \nR*\n that is unnecessary for a biologically significant reward \nS*\n but interferes with another response \nR \nthat is necessary for \nS*\n.  Misbehavior thus conceived has been explained as interfering Pavlovian conditioned responding.  Three four-layer feedforward neural networks were designed to differ only in their output layers, as a connectionist interpretation of three hypothetical operant-Pavlovian relations in misbehavior, namely, interference (Pavlovian output to operant output lateral inhibitory connection), compatibility (Pavlovian output to operant output lateral excitatory connection), and independence (no lateral connection in the output layer).  These relations are proposed as neural-network interpretations of neuroanatomical substrates of conditioning with three biologically significant stimuli, namely, food, water, and sexual mate, respectively.  Each network first received pairings of contextual cues with its respective \nS*\n, to simulate pretraining with such stimuli.  Then, networks received operant contingencies where \nS* \nwas paired with the same contextual cues, as well as cues from a token dependently on \nR\n responding, defined as a minimal \nR \nactivation of 0.5.  Networks showed substantial misbehavior (qua conditioned \nR*\n responding) that interfered with \nR\n to different extents, food causing the most, sexual mate the least interference.  Limitations, future directions, and implications for biological constraints and the generality of learning are discussed.","language":"en","license":{"name":"Creative Commons Attribution 4.0","short_name":"CC BY 4.0","text":"Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.\r\n\r\nNo additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.","url":"https://creativecommons.org/licenses/by/4.0"},"keywords":[{"word":"misbehavior"},{"word":"artificial neural networks"},{"word":"Pavlovian Conditioning"},{"word":"inhibition"},{"word":"biological constraints on learning"},{"word":"general learning processes"}],"section":"Special Issue on Biological Constraints on Learning","is_remote":true,"remote_url":"https://escholarship.org/uc/item/3vb500tv","frozenauthors":[{"first_name":"José","middle_name":"E","last_name":"Burgos","name_suffix":"","institution":"University of Guadalajara","department":"None"}],"date_submitted":"2015-02-09T20:40:26Z","date_accepted":"2015-02-09T20:40:26Z","date_published":"2015-07-29T03:47:47Z","render_galley":null,"galleys":[{"label":"","type":"","path":"https://journalpub.escholarship.org/uclapsych_ijcp/article/5346/galley/3204/download/"}]}