High feature overlap and incidental encoding drive rapid semantic integration in the fast mapping paradigm.

Author(s):  
Ann-Kathrin Zaiser ◽  
Patric Meyer ◽  
Regine Bader
2020 ◽  
Author(s):  
Ann-Kathrin Zaiser ◽  
Regine Bader ◽  
Patric Meyer

AbstractContrary to traditional theories of declarative memory, it has recently been shown that novel, arbitrary associations can be rapidly and directly integrated into cortical memory networks by means of a learning procedure called fast mapping (FM), possibly bypassing time-consuming hippocampal-neocortical consolidation processes. In the typical FM paradigm, a picture of a previously unknown item is presented next to a picture of a previously known item and participants answer a question referring to an unfamiliar label. It is assumed that they thereby incidentally create associations between the unknown item and the label. However, contradictory findings have been reported and factors moderating rapid cortical integration through FM yet need to be identified. In the context of previous behavioral results showing rapid semantic integration through FM especially if the unknown and the known item shared many features, we propose that due to its computational mechanisms during the processing of complex and particularly highly similar objects, the perirhinal cortex might be especially qualified to support the rapid incorporation of these associations into cortical memory networks within the FM paradigm. We therefore expected that a high degree of feature overlap between the unknown and the known item would trigger strong engagement of the perirhinal cortex at encoding, which in turn might enhance rapid cortical integration of the novel picture-label associations. Within an fMRI experiment, we observed stronger activation for subsequent hits than misses during encoding in the perirhinal cortex and an associated anterior temporal network if the items shared many features than if they shared few features, indicating that the perirhinal cortex indeed contributes to the acquisition of novel associations by means of FM if feature overlap is high.


2019 ◽  
Author(s):  
Ann-Kathrin Zaiser ◽  
Patric Meyer ◽  
Regine Bader

AbstractThere is evidence that rapid integration of novel associations into cortical networks is possible if associations are acquired through a learning procedure called fast mapping (FM). FM requires precise visual discrimination of sometimes highly similar pictures of a previously unknown and a known item, and linking an unfamiliar label to the unknown item. In order to shed light on the mechanisms underlying learning through FM, we manipulated feature overlap between the two items as potential modulating factor. In Experiment 1, we found that labels of the unknown items generally evoked instantaneous lexical competition when encoded through FM, indicating rapid integration into lexical networks. In Experiment 2, we observed semantic priming immediately after FM encoding but only if the items shared many features. This indicates that whereas feature overlap leaves item-level lexical integration unaffected, it might mediate semantic integration of arbitrary picture-label associations, which could explain contradictory findings in the literature.HighlightsWe examined cortical integration of associations using implicit memory measures.Fast mapping enables immediate integration of associations into cortical networks.Semantic integration requires the discrimination between items sharing many features.Item-level lexical integration is unaffected by feature overlap.


2019 ◽  
Author(s):  
Markus J. Hofmann ◽  
Mareike Kleemann ◽  
Andre Roelke ◽  
Christian Vorstius ◽  
Ralph Radach

The present study uses a computational approach to examine the role of semantic constraints in normal reading. This methodology avoids confounds inherent in conventional measures of predictability, allowing for theoretically deeper accounts of semantic processing. We start from a definition of associations between words based on the significant log likelihood that two words co-occur frequently together in the sentences of a large text corpus. Direct associations between stimulus words were controlled, and semantic feature overlap between prime and target words was manipulated by their common associates. The stimuli consisted of sentences of the form pronoun, verb, article, adjective and noun, followed by a series of closed class words, e. g. "She rides the grey elephant on one of her many exploratory voyages". The results showed that verb- noun overlap reduces single and first fixation durations of the target noun and adjective-noun overlap reduces go-past durations. A dynamic spreading of activation account suggests that associates of the prime words take some time to become activated: The verb can act on the target noun's early eye-movement measures presented three words later, while the adjective is presented immediately prior to the target, which induces sentence re-examination after a difficult adjective- noun semantic integration.


2014 ◽  
Author(s):  
Marc N. Coutanche ◽  
Sharon L. Thompson-Schill
Keyword(s):  

2019 ◽  
Author(s):  
Danielle M. Douglas ◽  
Louisa Lok Yee Man ◽  
Rachel N. Newsome ◽  
Haley Park ◽  
Hira M. Aslam ◽  
...  

Semantic features, such as prototypical visual form or function, are often shared across multiple object concepts. How, then, are we able to resolve interference between object concepts that look alike but perform different functions (e.g., hairdryer and gun) or that do similar things but look rather dissimilar (e.g., hairdryer and comb)? We examined this issue in the current neuropsychological single-case study by asking whether perirhinal cortex (PRC) critically enables resolution of interference among object concepts at the level of their conceptually- and visually-based semantic features. We tested three patients with differing lesion profiles using a novel discrimination task involving stimuli for which visual and conceptual similarity were not linked across object concepts. We found that D.A., an individual with a brain lesion that includes PRC, was impaired at discriminating among object concepts when there was a high degree conceptual and visual semantic feature overlap among choices. We replicated this result in a second testing session. Conversely, patients with selective hippocampal or ventromedial prefrontal cortical lesions were unimpaired on this task. Importantly, D.A.’s performance was intact when (i) conceptual and visual interference among object concepts was minimized, and (ii) when the discriminations involved simple stimuli that did not require assessment of multiple stimulus dimensions. These results reveal a novel semantic deficit in a patient with PRC damage, suggesting that this structure represents object concepts in a manner that can be flexibly reshaped to emphasize task relevant semantic features.


2020 ◽  
Vol 15 ◽  
Author(s):  
Omer Irshad ◽  
Muhammad Usman Ghani Khan

Aim: To facilitate researchers and practitioners for unveiling the mysterious functional aspects of human cellular system through performing exploratory searching on semantically integrated heterogeneous and geographically dispersed omics annotations. Background: Improving health standards of life is one of the motives which continuously instigates researchers and practitioners to strive for uncovering the mysterious aspects of human cellular system. Inferring new knowledge from known facts always requires reasonably large amount of data in well-structured, integrated and unified form. Due to the advent of especially high throughput and sensor technologies, biological data is growing heterogeneously and geographically at astronomical rate. Several data integration systems have been deployed to cope with the issues of data heterogeneity and global dispersion. Systems based on semantic data integration models are more flexible and expandable than syntax-based ones but still lack aspect-based data integration, persistence and querying. Furthermore, these systems do not fully support to warehouse biological entities in the form of semantic associations as naturally possessed by the human cell. Objective: To develop aspect-oriented formal data integration model for semantically integrating heterogeneous and geographically dispersed omics annotations for providing exploratory querying on integrated data. Method: We propose an aspect-oriented formal data integration model which uses web semantics standards to formally specify its each construct. Proposed model supports aspect-oriented representation of biological entities while addressing the issues of data heterogeneity and global dispersion. It associates and warehouses biological entities in the way they relate with Result: To show the significance of proposed model, we developed a data warehouse and information retrieval system based on proposed model compliant multi-layered and multi-modular software architecture. Results show that our model supports well for gathering, associating, integrating, persisting and querying each entity with respect to its all possible aspects within or across the various associated omics layers. Conclusion: Formal specifications better facilitate for addressing data integration issues by providing formal means for understanding omics data based on meaning instead of syntax


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