[HTML][HTML] An embedded computational framework of memory: Accounting for the influence of semantic information in verbal short-term memory
Abstract We introduce the Embedded Computational Framework of Memory (eCFM), a
model that integrates structured semantic word representations with an instance-based …
model that integrates structured semantic word representations with an instance-based …
[HTML][HTML] Modelling orthographic similarity effects in recognition memory reveals support for open bigram representations of letter coding
A variety of letter string representations has been proposed in the reading literature to
account for empirically established orthographic similarity effects from masked priming …
account for empirically established orthographic similarity effects from masked priming …
A computational account of item-based directed forgetting for nonwords: Incorporating orthographic representations in MINERVA 2
Recent research on item-method directed forgetting demonstrates that forget instructions not
only decrease recognition for targets, but also decrease false recognition for foils from the …
only decrease recognition for targets, but also decrease false recognition for foils from the …
Working memory limitations constrain visual episodic long-term memory at both specific and gist levels of representation
Limitations in one's capacity to encode information in working memory (WM) constrain later
access to that information in long-term memory (LTM). The present study examined whether …
access to that information in long-term memory (LTM). The present study examined whether …
Mnemonic vs. Executive Contributions to the N400: A Connectionist Approach to False Memories
L Sokolovič, MJ Hofmann - Computational Brain & Behavior, 2024 - Springer
The associative-read-out model (AROM) is an interactive activation model (IAM) of semantic
and episodic memory, which has already predicted behavioral and neural data during …
and episodic memory, which has already predicted behavioral and neural data during …
[PDF][PDF] From Cosine Similarity to Likelihood Ratio: Coupling Representations From Machine Learning (and Other Sources) With Cognitive Models
GE Cox - 2024 - files.osf.io
Modern machine learning models yield vector representations that capture similarity
relations between complex items like text and images. These representations can help …
relations between complex items like text and images. These representations can help …
How to say 'no'to a false memory: Leaky and noisy evidence accumulation during associative read-out
L Sokolovič, MJ Hofmann - 2024 - researchsquare.com
The associative-read-out model (AROM) is an interactive activation model (IAM) of semantic
and episodic memory, which has already predicted behavioral and neural data during …
and episodic memory, which has already predicted behavioral and neural data during …
[PDF][PDF] A global matching model of choice and response times in the Deese-Roediger-McDermott semantic and perceptual false recognition paradigms
What is arguably the most common method of eliciting false memories in the laboratory is
the Deese-Roediger-McDermott paradigm (Deese, 1959; Roediger & McDermott, 1995) …
the Deese-Roediger-McDermott paradigm (Deese, 1959; Roediger & McDermott, 1995) …