scholarly journals Prior Verbal Description of Novel Stimuli Improves the Learning of Information Integration Categories but not Rule-Described Categories

2018 ◽  
Author(s):  
John Paul Minda ◽  
Bailey Brashears ◽  
Joshua John Hatherley

A prominent theory of category learning assumes that people rely on two parallel and competing systems that make use of either the abstraction of verbal rules (explicit system) or the gradual association of the category exemplars with the appropriate response (implicit system). Because the explicit system relies on verbal processing, we hypothesized that priming the verbal system by asking participants to provide a verbal description of some of the stimuli prior to classification would enhance the learning of rule-described categories but would have no effect on the learning of information integration categories. Our results failed to confirm the hypothesis, and we observed the opposite pattern: prior verbal description enhanced learning of the information integration categories but not the rule-described categories. Our data and subsequent modelling suggest that participants in both categories tended to rely on a rule-based strategy, but participants were quicker to abandon that strategy when they had prior exposure to the stimuli.

2010 ◽  
Vol 48 (10) ◽  
pp. 2998-3008 ◽  
Author(s):  
W. Todd Maddox ◽  
Jennifer Pacheco ◽  
Maia Reeves ◽  
Bo Zhu ◽  
David M. Schnyer

2020 ◽  
Vol 30 (8) ◽  
pp. 4563-4580 ◽  
Author(s):  
Andrés Canales-Johnson ◽  
Alexander J Billig ◽  
Francisco Olivares ◽  
Andrés Gonzalez ◽  
María del Carmen Garcia ◽  
...  

Abstract At any given moment, we experience a perceptual scene as a single whole and yet we may distinguish a variety of objects within it. This phenomenon instantiates two properties of conscious perception: integration and differentiation. Integration is the property of experiencing a collection of objects as a unitary percept and differentiation is the property of experiencing these objects as distinct from each other. Here, we evaluated the neural information dynamics underlying integration and differentiation of perceptual contents during bistable perception. Participants listened to a sequence of tones (auditory bistable stimuli) experienced either as a single stream (perceptual integration) or as two parallel streams (perceptual differentiation) of sounds. We computed neurophysiological indices of information integration and information differentiation with electroencephalographic and intracranial recordings. When perceptual alternations were endogenously driven, the integrated percept was associated with an increase in neural information integration and a decrease in neural differentiation across frontoparietal regions, whereas the opposite pattern was observed for the differentiated percept. However, when perception was exogenously driven by a change in the sound stream (no bistability), neural oscillatory power distinguished between percepts but information measures did not. We demonstrate that perceptual integration and differentiation can be mapped to theoretically motivated neural information signatures, suggesting a direct relationship between phenomenology and neurophysiology.


Author(s):  
W. Todd Maddox ◽  
J. Vincent Filoteo ◽  
J. Scott Lauritzen ◽  
Emily Connally ◽  
Kelli D. Hejl

2006 ◽  
Vol 17 (1) ◽  
pp. 37-43 ◽  
Author(s):  
E. Nomura ◽  
W. Maddox ◽  
J. Filoteo ◽  
A. Ing ◽  
D. Gitelman ◽  
...  

2016 ◽  
Author(s):  
D. Botskaris ◽  
B. Kriengwatana ◽  
C. ten Cate

AbstractThe survival of organisms depends highly on their ability to adjust their behavior according to proper categorizations of various events. More than one strategy can be used in categorization. One is the Rule-Based (RB) strategy and the other is Information-Integration (II) strategy. In this research we analyzed the differences between avian and human cognition. Twelve Greek listeners and four Zebra finches were tested in speech category learning tasks. In particular, both humans and Zebra finches had to categorize between Dutch vowels that differ on duration, frequency or both depending on the condition. Feedback was given for correct and incorrect responses. The results showed that humans and Zebra finches are probably using the same methods of learning depending on the categorization tasks that they are exposed to. If Zebra Finches are actually able to acquire (RB) and (II) category structures using the same strategies as humans, the utility of multiple systems of categorization might not be restricted to primates as current literature suggest.


2020 ◽  
Author(s):  
Casey L Roark ◽  
Kirsten Smayda ◽  
Bharath Chandrasekaran

We compare the ability of amateur musicians and non-musicians in learning artificial auditory and visual categories that can be described as either rule-based (RB) or information-integration (II) category structures. RB categories are optimally learned using a reflective reasoning process, whereas II categories are optimally learned by integrating information from two stimulus dimensions at a reflexive, pre-decisional processing stage. Across two experiments, we found that music experience was beneficial to learning auditory categories. In Experiment 1, musicians enrolled in a music college demonstrated advantages over non-musicians in learning RB auditory categories defined on pitch frequency and duration dimensions but did not demonstrate differences in learning II auditory categories or either RB or II visual categories. In Experiment 2, a broader online sample of musicians demonstrated advantages over non-musicians in learning both RB and II auditory categories defined on spectral and temporal modulation dimensions. Musicians’ category learning advantage is limited to their modality of expertise and is category-specific in a way that depends on the dimensions used to define the categories.


2010 ◽  
Vol 72 (4) ◽  
pp. 1013-1031 ◽  
Author(s):  
Sébastien Hélie ◽  
Jennifer G. Waldschmidt ◽  
F. Gregory Ashby

2013 ◽  
Vol 20 (6) ◽  
pp. 1343-1349 ◽  
Author(s):  
Helen Tam ◽  
W. Todd Maddox ◽  
Cynthia L. Huang-Pollock

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