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Predictability, surprise, attention, and conditioning

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TLDR
The role of attention in Pavlovian conditioning, and use of auditory and visual stimuli to condition rats is discussed in this article, where the authors discuss the use of both visual and auditory stimuli.
Abstract
Role of attention in Pavlovian conditioning, and use of auditory and visual stimuli to condition rats

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Book ChapterDOI

Hybrid Theory of Classical Conditioning

TL;DR: The substance of a reductive theory of behavior incorporating both S-S ( Stimulus–stimulus) and S-R (stimulus–respone) conceptualizations along with related notions developed by a variety of theorists is presented.
Journal ArticleDOI

Enclosure shape influences cue competition effects and goal location learning.

TL;DR: In virtual-environment spatial-learning procedures, investigating blocking of learning about distal landmarks beyond the walls of an enclosure following preliminary training to find a goal using local landmarks within the enclosure blocked spatial learning based on a circular enclosure divided into four differently coloured sections.
Journal ArticleDOI

Are Distal and Proximal Visual Cues Equally Important during Spatial Learning in Mice? A Pilot Study of Overshadowing in the Spatial Domain.

TL;DR: The results of the present study offer a first insight about the occurrence of associative mechanisms during spatial learning in mice, and may open the way to promising new investigations in this area of research.
Journal ArticleDOI

Infant Cognitive Training Preshapes Learning-Relevant Prefrontal Circuits for Adult Learning: Learning-Induced Tagging of Dendritic Spines

TL;DR: Using a two-way active avoidance (TWA) paradigm, it is found that avoidance training during infancy, even though the infant rats were not capable to learn a successful avoidance strategy, improves avoidance learning in adulthood.
Journal ArticleDOI

The geometry of learning

TL;DR: A correspondence between Pavlovian conditioning processes and fractals is established and the association strength at a training trial corresponds to a point in a disconnected set at a given iteration level, which can represent a training process as a hopping on a fractal set, instead of the traditional learning curve as a function of the trial.