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Reinforcement learning in neural networks requires a mechanism for exploring new network states in response to a single, nonspecific reward signal. ... We suggest that stimulus sampling and reward attenuation are two key components of a framework by which any single-cell supervised learning rule can be converted into a reinforcement learning rule for ... Fusi for fruitful discussions and his contribution in starting this project. We thank Dr. W. ...doi:10.1007/s00422-009-0305-x pmid:19360435 fatcat:lmg7yuxtnrgvrladqbor4kh5qi
Reinforcement learning in neural networks requires a mechanism for exploring new network states in response to a single, nonspecific reward signal. ... We suggest that stimulus sampling and reward attenuation are two key components of a framework by which any single-cell supervised learning rule can be converted into a reinforcement learning rule for ... Fusi for fruitful discussions and his contribution in starting this project. We thank Dr. W. ...doi:10.7892/boris.31393 fatcat:wadtq7g4o5atzm2n6gxd7kyj5q
Please cite this article as: Guillette, L.M., Baron, D.M., Sturdy, C.B., Spetch, M.L., Fastand slow-exploring pigeons differ in how they use previously learned rules.Behavioural Processes http://dx. ... Exploration may influence learning because less exploratory animals are less likely to come in contact with to-be-learned stimuli. ... We predict that fast-explorers will learn more about the absolute features of a stimulus, as proposed by Guillette et al., (2015) , and thus will respond less to novel modified stimuli resulting in steep ...doi:10.1016/j.beproc.2016.07.006 pmid:27567525 fatcat:zctqbg5zlvcrdcifc6vyplrbza
It is concluded that stimulus en- hancement followed by operant conditioning were the mechanisms in- volved, which may have accounted for the fast spread of the stem-chewing tradition between family members ... After exposure to an imprinting stimulus for 30 min on day | after hatching, preferences were tested and then the chicks were exposed to the same stimulus for either 90 min, 3 hrs or 4 hrs on the next ...
As such it is opposed to incremental, slower reinforcement or procedural learning requiring repetitive training. ... In the search for the engrams of fast learning, a growing body of evidence highlights long-term changes in gene expression, structural, intrinsic, and synaptic plasticities. ... ACKNOWLEDGMENTS We thank Gaëtan Vignoud and Nicolas Gervasi for helpful suggestions and critical comments. ...doi:10.3389/fncel.2020.575915 pmid:33250712 pmcid:PMC7676431 fatcat:mt6pm6cdpjdphppcaufotj5g2e
inhibitory control mechanisms. 49 participants performed a reinforcement-learning task and a stop-signal task while fMRI was recorded. ... A reinforcement-learning model was used to quantify learning strategies. ... Acknowledgments This work was supported with an ABC grant from the university of Amsterdam and National Science Foundation grant #1460604 to MJF. ...doi:10.1101/199299 fatcat:berevforhrbwnjpqprpg2ddrbm
incorporating associative reinforcement learning rules for conditioning and fixation of circuitry into hardwire to form innate responses such that contextual feel of sensation is evolved as an emergent ... property known as emotional feel. ... Based on this framework, we will explore the neural mechanisms for establishing this contextual sensation for an autonomous system. ...doi:10.2174/1874110x00701010028 fatcat:3ffgaztizbdmrbyyhg6qsipxya
errors, as well as (iii) selective suppression of non-chosen features values, and (iv) meta-learning based adjustment of exploration rates given a memory trace of recent errors. ... How the fast and slow strategies work together in scenarios with real-world stimulus complexity is not well known. ... Empirically, such an attentional mechanism accounts for learning values of objects and features within complex multidimensional stimulus spaces (Wilson and Niv, 2011; Niv et al., 2015; Hassani et al., ...doi:10.1101/2020.09.27.315432 fatcat:cigb5t42kzandkjxefnqlykesq
Quantitative modeling of the data revealed that adding a mechanism for error discounting significantly improved the fits of an exemplar-based and a rule-based associative learning model, as well as of ... We conclude that error discounting is an important component of probabilistic learning. ... The GCM was used to explore an alternative explanation for error discounting based on sample size. ...doi:10.1037/a0022473 pmid:21355666 pmcid:PMC3102123 fatcat:tiyqtidmorfj3ep3c7xockwtyu
Nonetheless, these results provide the first demonstration of an impairment that implicates Ser 831 phosphorylation of the AMPA-GluR1 receptor as a critical mechanism for a form of incentive learning in ... Our findings provide novel evidence for a molecular mechanism in a form of appetitive incentive learning critical in regulating normal motivated behavior, as well as maladaptive forms such as addiction ...doi:10.1016/j.bbr.2008.03.026 pmid:18455244 pmcid:PMC2478746 fatcat:2ymq7bcaifgorh3fhasbhshrmu
Results are consistent with models of associative learning that assume that learning depends on the temporal overlap of a CS with a fast excitatory and a slow inhibitory one both evoked by a reinforcer ... Nine pigeons were trained in a choice matching-to-duration task in which the samples were 2 and 8 sec in duration for Exp 1, and | and 30 sec in duration for Exp 2. ...
Quantitative model fits reveal that genetic factors modulate independent parameters of a reinforcement learning system. ... We show that two genes controlling striatal dopamine function, DARPP-32 (also called PPP1R1B) and DRD2, are associated with exploitative learning to adjust response times incrementally as a function of ... Uncertainty-based exploration The above model provides an account of incremental RT changes as a function of reward prediction error, and it provides evidence for the mechanisms posited to mediate these ...doi:10.1038/nn.2342 pmid:19620978 pmcid:PMC3062477 fatcat:jlyx4f3iqvezlhyyubbdrndqoy
Transfer tests to new stimulus values revealed that the birds processed the stimuli in an absolute, rather than a relational fashion. ... The psychophysics and short-term retention of pigeons' responses to rate of stimulus change were assessed in two experiments, using a symbolic delayed matching-to-sample procedure. ... Figure 6 shows the retention data separately for slow (3 Hz) and fast (9 Hz) samples. As in Experiment 1, there was an asymmetry in forgetting. ...doi:10.3758/bf03199773 fatcat:uq3jxodnkzdlzfls2jzmtqdb4q
In this paper, we first present a comprehensive review on the psychological study of curiosity and summarize a unified framework for quantifying curiosity as well as its arousal mechanism. ... Psychological curiosity plays a significant role in human intelligence to enhance learning through exploration and information acquisition. ... well as computational models in reinforcement learning. ...arXiv:2201.08300v1 fatcat:ume57gb4lzfxle6yuruum4onqq
For example, the zebrafish may have utility in the analysis of the biological mechanisms of learning and memory. ... For example, we found experimental zebrafish that experienced an open left tunnel or an open right tunnel of a maze during the unrewarded exploration phase of the test to show the appropriate side bias ... We would like to thank Ryan Hoffman for conducting pilot studies and constructing the maze. ...doi:10.1016/j.bbr.2009.12.031 pmid:20043955 pmcid:PMC2831165 fatcat:i2re3osr65akvmpwyqg7tvoy3m
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