scholarly journals The unequal variance signal-detection model of recognition memory: Investigating the encoding variability hypothesis

2020 ◽  
Vol 73 (8) ◽  
pp. 1242-1260
Author(s):  
Rory W Spanton ◽  
Christopher J Berry
Keyword(s):  
Recognition Memory ◽  
Signal Detection ◽  
Psychological Explanation ◽  
Memory Strength ◽  
Unequal Variance ◽  
Detection Model ◽  
The Mean ◽  
Encoding Variability ◽  
Strength Variance ◽  
Back Task

Despite the unequal variance signal-detection (UVSD) model’s prominence as a model of recognition memory, a psychological explanation for the unequal variance assumption has yet to be verified. According to the encoding variability hypothesis, old item memory strength variance (σo) is greater than that of new items because items are incremented by variable, rather than fixed, amounts of strength at encoding. Conditions that increase encoding variability should therefore result in greater estimates of σo. We conducted three experiments to test this prediction. In Experiment 1, encoding variability was manipulated by presenting items for a fixed or variable (normally distributed) duration at study. In Experiment 2, we used an attentional manipulation whereby participants studied items while performing an auditory one-back task in which distractors were presented at fixed or variable intervals. In Experiment 3, participants studied stimuli with either high or low variance in word frequency. Across experiments, estimates of σo were unaffected by our attempts to manipulate encoding variability, even though the manipulations weakly affected subsequent recognition. Instead, estimates of σo tended to be positively correlated with estimates of the mean difference in strength between new and studied items ( d), as might be expected if σo generally scales with d. Our results show that it is surprisingly hard to successfully manipulate encoding variability, and they provide a signpost for others seeking to test the encoding variability hypothesis.

scholarly journals A direct test of the unequal-variance signal detection model of recognition memory

2007 ◽  
Vol 14 (5) ◽  
pp. 858-865 ◽  
Author(s):  
Laura Mickes ◽  
John T. Wixted ◽  
Peter E. Wais
Keyword(s):  
Recognition Memory ◽  
Signal Detection ◽  
Direct Test ◽  
Unequal Variance ◽  
Detection Model

scholarly journals Pre-experimental Familiarization Increases Hippocampal Activity for Both Targets and Lures in Recognition Memory: An fMRI Study

2011 ◽  
Vol 23 (12) ◽  
pp. 4164-4173 ◽  
Author(s):  
Greig I. de Zubicaray ◽  
Katie L. McMahon ◽  
Lydia Hayward ◽  
John C. Dunn
Keyword(s):  
Signal Detection ◽  
Dual Process ◽  
Memory Strength ◽  
High Confidence ◽  
Unequal Variance ◽  
Detection Model ◽  
Parahippocampal Cortex ◽  
Hippocampal Activity ◽  
Model Account ◽  
List Discrimination

In the present study, items pre-exposed in a familiarization series were included in a list discrimination task to manipulate memory strength. At test, participants were required to discriminate strong targets and strong lures from weak targets and new lures. This resulted in a concordant pattern of increased “old” responses to strong targets and lures. Model estimates attributed this pattern to either equivalent increases in memory strength across the two types of items (unequal variance signal detection model) or equivalent increases in both familiarity and recollection (dual process signal detection [DPSD] model). Hippocampal activity associated with strong targets and lures showed equivalent increases compared with missed items. This remained the case when analyses were restricted to high-confidence responses considered by the DPSD model to reflect predominantly recollection. A similar pattern of activity was observed in parahippocampal cortex for high-confidence responses. The present results are incompatible with “noncriterial” or “false” recollection being reflected solely in inflated DPSD familiarity estimates and support a positive correlation between hippocampal activity and memory strength irrespective of the accuracy of list discrimination, consistent with the unequal variance signal detection model account.

scholarly journals Evidence for the Contribution of A Threshold Retrieval Process to Semantic Memory

2017 ◽  
Vol 70 (10) ◽  
pp. 2026-2047 ◽  
Author(s):  
Maria Kempnich ◽  
Josephine A. Urquhart ◽  
Akira R. O'Connor ◽  
Chris J.A. Moulin
Keyword(s):  
Signal Detection ◽  
Semantic Memory ◽  
Target Identification ◽  
Dual Process ◽  
Semantic Retrieval ◽  
Retrieval Process ◽  
Operating Characteristics ◽  
Semantic Task ◽  
Unequal Variance ◽  
Detection Model

It is widely held that episodic retrieval can recruit two processes: a threshold context retrieval process (recollection) and a continuous signal strength process (familiarity). Conversely the processes recruited during semantic retrieval are less well specified. We developed a semantic task analogous to single-item episodic recognition to interrogate semantic recognition receiver-operating characteristics (ROCs) for a marker of a threshold retrieval process. We fitted observed ROC points to three signal detection models: two models typically used in episodic recognition (unequal variance and dual-process signal detection models) and a novel dual-process recollect-to-reject (DP-RR) signal detection model that allows a threshold recollection process to aid both target identification and lure rejection. Given the nature of most semantic questions, we anticipated the DP-RR model would best fit the semantic task data. Experiment 1 (506 participants) provided evidence for a threshold retrieval process in semantic memory, with overall best fits to the DP-RR model. Experiment 2 (316 participants) found within-subjects estimates of episodic and semantic threshold retrieval to be uncorrelated. Our findings add weight to the proposal that semantic and episodic memory are served by similar dual-process retrieval systems, though the relationship between the two threshold processes needs to be more fully elucidated.

scholarly journals A Hierarchical Unequal-Variance Signal Detection Model for Binary Data

2021 ◽  
Author(s):  
Martin Lages
Keyword(s):  
Signal Detection ◽  
Binary Data ◽  
Population Level ◽  
Unequal Variance ◽  
Binary Responses ◽  
Detection Model ◽  
Sampling Distributions ◽  
Equal Variance ◽  
Gaussian Signal ◽  
Multiple Conditions

Gaussian signal detection models with equal variance are typically used for detection and discrimination data whereas models with unequal variance rely on data with multiple response categories or multiple conditions. Here a hier- archical signal detection model with unequal variance is suggested that requires only binary responses from a sample of participants. Introducing plausible constraints on the sampling distributions for sensitivity and response criterion makes it possible to estimate signal variance at the population level. This model was applied to existing data from memory and reasoning tasks and the results suggest that parameters can be reliably estimated, allowing a direct comparison of signal detection models with equal- and unequal-variance.

Recognition Memory for Self-Relevant Personality-Trait Words

2009 ◽  
Vol 68 (3) ◽  
pp. 133-142 ◽  
Author(s):  
Marek Nieznański
Keyword(s):  
Recognition Memory ◽  
Signal Detection ◽  
Response Bias ◽  
Personality Trait ◽  
Recognition Task ◽  
The Self ◽  
Rating Task ◽  
Detection Model ◽  
Self Study ◽  
Trait Words

Two studies based on a signal detection model of recognition memory are presented. Both studies investigated detection and response bias in the recognition of personality-trait words with respect to their relation to the self. Study 1 employed a yes-no task in which participants were to recognize trait adjectives. Study 2 employed a rating task in which participants declared their confidence with respect to whether a noun or an adjective had been presented. After the recognition task, participants selected personality-trait words that described them and ones that described other people. The results indicated a stronger tendency to say “old” for self-descriptive than for non-self-descriptive adjectives and nouns. Study 2 suggested that self-descriptive nouns are better detected than non-self-descriptive nouns.

Word-Imagery Effects on Recollection and Familiarity in Recognition Memory

2005 ◽  
Vol 100 (3) ◽  
pp. 716-722 ◽  
Author(s):  
Ward O'Neill
Keyword(s):  
Recognition Memory ◽  
Signal Detection ◽  
Undergraduate Students ◽  
Contextual Information ◽  
Dual Process ◽  
Significant Enhancement ◽  
Detection Model ◽  
Familiarity In Recognition Memory ◽  
Independent Analysis ◽  
French Speaking

The Remember/Know procedure was used to investigate the effects of word imageability on recognition memory. An experiment, using French-speaking undergraduate students (17 women and 3 men), replicated Dewhurst and Conway's 1994 finding that rated imageability significantly increased accurate Remember responses but not Know responses when analyzed in the traditional way, assuming that the response types are mutually exclusive. Data were also analyzed using the Yonelinas, et al. 1998 dual-process signal-detection model, for estimating recollection and familiarity while assuming that Remember and Know responses are independent. Analysis indicated significant enhancement of imageability for estimates of both recollection and familiarity. This was interpreted as meaning that imageability enhanced both item-specific and contextual information associated with studied words.

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