Hierarchical and configural control in conditional discrimination learning [0.03%]
条件化辨别学习中的层次控制和构念控制
Ellen M O&#x;Donoghue,Leyre Castro,Edward A Wasserman
Ellen M O&#x;Donoghue
Considerable discussion has concerned the role of context in conditional discrimination learning. Some authors have proposed that contexts might operate hierarchically on CS-US associations, whereas others have proposed that the context plu...
Assessing complex odor discrimination in mice using a novel instrumental patterning task [0.03%]
利用新型仪器模式任务评估小鼠复杂的嗅觉辨别能力
Tanya A Gupta,Carter W Daniels,Jorge I Espinoza et al.
Tanya A Gupta et al.
Negative patterning tasks are a key tool to unveil the mechanisms by which stimulus representations are acquired-a central concern in Robert Rescorla's research. In these tasks, target stimuli are reinforced when presented individually (A+/...
Reinforcement rate and the balance between excitatory and inhibitory learning: Insights from deletion of the GluA1 AMPA receptor subunit [0.03%]
增强速率及兴奋性与抑制性学习间的平衡：来自GluA1型AMPA受体亚单位敲除的启示
Joseph M Austen,Rolf Sprengel,David J Sanderson
Joseph M Austen
Conditioned responding is sensitive to reinforcement rate. This rate-sensitivity is impaired in genetically modified mice that lack the GluA1 subunit of the AMPA receptor. A time-dependent application of the Rescorla-Wagner learning rule ca...
On the importance of feedback for categorization: Revisiting category learning experiments using an adaptive filter model [0.03%]
反馈对分类的重要性：使用自适应滤波模型重新审视类别学习实验
Nicolás Marchant,Sergio E Chaigneau
Nicolás Marchant
Associative accounts of category learning have been, for the most part, abandoned in favor of cognitive explanations (e.g., similarity, explicit rules). In the current work, we implement an Adaptive Linear Filter (ALF) closely related to th...
Developments in associative theory: A tribute to the contributions of Robert A. Rescorla [0.03%]
联想理论的发展：献给Robert A. Rescorla的贡献
Ruth M Colwill,Andrew R Delamater,K Matthew Lattal
Ruth M Colwill
The field of associative learning theory was forever changed by the contributions of Robert A. Rescorla. He created an organizational structure that gave us a framework for thinking about the key questions surrounding learning theory: what ...
There's something about a pattern: Choice between pattern and random sequences in implicit learning [0.03%]
模式的魅力：内隐学习中序列模式与随机序列的选择
Charles Locurto,James Donohue,Amy Hasenauer et al.
Charles Locurto et al.
Three experiments examined the preference for pattern versus random sequences. In all experiments the elements composing the sequences were visual images presented sequentially on a touchscreen. Reinforcement was randomly programmed on .16 ...
Behavioral studies of spinal conditioning: The spinal cord is smarter than you think it is [0.03%]
脊髓条件作用的行为学研究——脊髓比你想象的要聪明得多
James W Grau,Kelsey E Hudson,Megan M Tarbet et al.
James W Grau et al.
In 1988 Robert Rescorla published an article in the Annual Review of Neuroscience that addressed the circumstances under which learning occurs, some key methodological issues, and what constitutes an example of learning. The article has ins...
Carla J Eatherington,Mark Haselgrove
Carla J Eatherington
Learning permits even relatively uninteresting stimuli to capture attention if they are established as predictors of important outcomes. Associative theories explain this "learned predictiveness" effect by positing that attention is a funct...
Signal detection analysis of contingency assessment: Associative interference and nonreinforcement impact cue-outcome contingency sensitivity, whereas cue density affects bias [0.03%]
联结评估的信号检测分析：联结干扰和不予强化影响联结-结果敏感性，而线索密度影响偏差
Jérémie Jozefowiez,Gonzalo P Urcelay,Ralph R Miller
Jérémie Jozefowiez
In a signal detection theory approach to associative learning, the perceived (i.e., subjective) contingency between a cue and an outcome is a random variable drawn from a Gaussian distribution. At the end of the sequence, participants repor...
Generalization following symmetrical intradimensional discrimination training [0.03%]
对称性内在维度辨别训练后的泛化效应
David W Ng,Jessica C Lee,Brett K Hayes et al.
David W Ng et al.
A challenge for generalization models is to specify how excitation generated from a CS+ (i.e., positive evidence) should interact with inhibition from a CS- (i.e., negative evidence) to produce generalized responding. Empirically, many gene...