Stimulus–response learning and expected reward value enhance stimulus cognitive processing: An ERP study

2021 ◽  
Author(s):  
Sara Molinero ◽  
Tamara Giménez‐Fernández ◽  
Francisco J. López ◽  
Luis Carretié ◽  
David Luque
Keyword(s):  
Cognitive Processing ◽  
Response Learning ◽  
Stimulus Response ◽  
Reward Value

scholarly journals EXPRESS: When Symmetric and Curved Visual Contour Meet Intentional Instructions: Hedonic Value and Preference

2021 ◽  
pp. 174702182110215
Author(s):  
Erick G. Chuquichambi Apaza ◽  
Guido B. Corradi ◽  
Enric Munar ◽  
Jaume Rosselló-Mir
Keyword(s):  
Cognitive Processing ◽  
Experimental Session ◽  
Hedonic Tone ◽  
Stimulus Response ◽  
Negative Valence ◽  
Visual Contour ◽  
Positive Valence ◽  
Positive And Negative Valence ◽  
Implicit And Explicit ◽  
Explicit Measures

Symmetry and contour take part in shaping visual preference. However, less is known about their combined contribution to preference. We examined the hedonic tone and preference triggered by the interaction of symmetry and contour. Symmetric/curved, symmetric/sharp-angled, asymmetric/curved, and asymmetric/sharp-angled stimuli were presented in an implicit and explicit task. The implicit task consisted of an affective stimulus-response compatibility task where participants matched the stimuli with positive and negative valence response cues. The explicit task recorded liking ratings from the same stimuli. We used instructed mindset to induce participants to focus on symmetry or contour in different parts of the experimental session. We found an implicit compatibility of symmetry and curvature with positive hedonic tone. Explicit results showed preference for symmetry and curvature. In both tasks, symmetry and curvature showed a cumulative interaction, with a larger contribution of symmetry to the overall effect. While symmetric and asymmetric stimuli contributed to the implicit positive valence of symmetry, the effect of curvature was mainly caused by inclination toward curved contours rather than rejection of sharp-angled contours. We did not find any correlation between implicit and explicit measures, suggesting that they may involve different cognitive processing.

scholarly journals When Symmetric and Curved Visual Contour Meet Intentional Instructions: Hedonic Value and Preference

2021 ◽  
Author(s):  
Erick Gustavo Chuquichambi ◽  
Guido Corradi ◽  
Jaume Rossello ◽  
Enric Munar
Keyword(s):  
Cognitive Processing ◽  
Experimental Session ◽  
Hedonic Tone ◽  
Stimulus Response ◽  
Negative Valence ◽  
Visual Contour ◽  
Positive Valence ◽  
Positive And Negative Valence ◽  
Implicit And Explicit ◽  
Explicit Measures

Symmetry and contour take part in shaping visual preference. However, less is known about their combined contribution to preference. We examined the hedonic tone and preference triggered by the interaction of symmetry and contour. Symmetric/curved, symmetric/sharp-angled, asymmetric/curved, and asymmetric/sharp-angled stimuli were presented in an implicit and explicit task. The implicit task consisted of an affective stimulus-response compatibility task where participants matched the stimuli with positive and negative valence response cues. The explicit task recorded liking ratings from the same stimuli. We used instructed mindset to induce participants to focus on symmetry or contour in different parts of the experimental session. We found an implicit compatibility of symmetry and curvature with positive hedonic tone. Explicit results showed preference for symmetry and curvature. In both tasks, symmetry and curvature showed a cumulative interaction, with a larger contribution of symmetry to the overall effect. While symmetric and asymmetric stimuli contributed to the implicit positive valence of symmetry, the effect of curvature was mainly caused by inclination toward curved contours rather than rejection of sharp-angled contours. We did not find any correlation between implicit and explicit measures, suggesting that they may involve different cognitive processing.

scholarly journals Striatum-Mediated Deficits in Stimulus-Response Learning and Decision-Making in OCD

2020 ◽  
Vol 11 ◽  
Author(s):  
Nole M. Hiebert ◽  
Marc R. Lawrence ◽  
Hooman Ganjavi ◽  
Mark Watling ◽  
Adrian M. Owen ◽  
...  
Keyword(s):  
Decision Making ◽  
Response Learning ◽  
Stimulus Response

scholarly journals A general model of hippocampal and dorsal striatal learning and decision making

2020 ◽  
Vol 117 (49) ◽  
pp. 31427-31437
Author(s):  
Jesse P. Geerts ◽  
Fabian Chersi ◽  
Kimberly L. Stachenfeld ◽  
Neil Burgess
Keyword(s):  
Decision Making ◽  
Reference Frame ◽  
Place Cells ◽  
Cognitive Map ◽  
Relational Structure ◽  
Place Learning ◽  
Response Learning ◽  
Adaptive Combination ◽  
Stimulus Response ◽  
Model Free

Humans and other animals use multiple strategies for making decisions. Reinforcement-learning theory distinguishes between stimulus–response (model-free; MF) learning and deliberative (model-based; MB) planning. The spatial-navigation literature presents a parallel dichotomy between navigation strategies. In “response learning,” associated with the dorsolateral striatum (DLS), decisions are anchored to an egocentric reference frame. In “place learning,” associated with the hippocampus, decisions are anchored to an allocentric reference frame. Emerging evidence suggests that the contribution of hippocampus to place learning may also underlie its contribution to MB learning by representing relational structure in a cognitive map. Here, we introduce a computational model in which hippocampus subserves place and MB learning by learning a “successor representation” of relational structure between states; DLS implements model-free response learning by learning associations between actions and egocentric representations of landmarks; and action values from either system are weighted by the reliability of its predictions. We show that this model reproduces a range of seemingly disparate behavioral findings in spatial and nonspatial decision tasks and explains the effects of lesions to DLS and hippocampus on these tasks. Furthermore, modeling place cells as driven by boundaries explains the observation that, unlike navigation guided by landmarks, navigation guided by boundaries is robust to “blocking” by prior state–reward associations due to learned associations between place cells. Our model, originally shaped by detailed constraints in the spatial literature, successfully characterizes the hippocampal–striatal system as a general system for decision making via adaptive combination of stimulus–response learning and the use of a cognitive map.

scholarly journals Stress modulates the use of spatial versus stimulus-response learning strategies in humans

2007 ◽  
Vol 14 (1-2) ◽  
pp. 109-116 ◽  
Author(s):  
L. Schwabe ◽  
M. S. Oitzl ◽  
C. Philippsen ◽  
S. Richter ◽  
A. Bohringer ◽  
...  
Keyword(s):  
Learning Strategies ◽  
Response Learning ◽  
Stimulus Response ◽  
Versus Stimulus
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