The boundaries of self face perception: Response time distributions, perceptual categories, and decision weighting

People show systematic biases in perception, memory, and attention to favor information related to themselves over information related to other people. Researchers have examined these biases in order to throw light on the nature of the self. We review this evidence in memory, face recognition, and simple perceptual matching tasks through objective measures of self-biases. We argue that the self serves as a stable anchor across different forms of judgment and that referring a stimulus to ourselves enhances the binding of stimulus features at different stages of processing (e.g., in perception and in memory) and also the binding between processing stages. There is neural evidence that self-biases reflect an underlying neural network that interacts with but is independent of attentional control networks in the brain, and that damage to the self-related network disrupts the bias effects. We discuss the implications for understanding the nature of the self.

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“…(C) Stability within different decision contexts for self‐related stimuli compared with other‐related stimuli (from Ref. ).…”

Section: Properties Of Self‐reference Effectsmentioning

confidence: 99%

“…This within‐subject stability is also apparent across different types of decision. Sui and Humphreys had participants make varying judgments to stimuli associated to the self or other people. The participants saw images of their own face, their friend's face, or the face of a stranger.…”

Section: Properties Of Self‐reference Effectsmentioning

confidence: 99%

The ubiquitous self: what the properties of self‐bias tell us about the self

Sui

Humphreys

2016

Annals of the New York Academy of Sciences

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100

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“…This approach allowed us to reveal the possible accounts of the three distributional parameters-shift, shape, and scale-by associating them with the nondecision time, drift rate, and boundary separation estimated from the diffusion model. Our study goes farther than most previous ones (Balota & Yap, 2011;Heathcote et al, 1991;Sui & Humphreys, 2013;Tse & Altarriba, 2012) that have applied distributional analyses to RT data. We used conventional distributional analyses to examine empirical RT distributions, and the associated parameters were complemented with Bayesian-based hierarchical modeling to optimize the estimates.…”

Section: Discussionmentioning

confidence: 79%

“…Additionally, because the density curve for the mean RTs is usually constructed by means of a biased central-location parameter (with respect to a skewed RT distribution), the nature of the RT distribution (e.g., if there are a majority of quick responses and a minority of slow responses) is hidden by an unrepresentative central-location parameter. A solution has been proposed recently of using some variants of distributional analyses (Balota & Yap, 2011;Bricolo et al, 2002;Heathcote et al, 1991), and these have been applied to various cognitive tasks (Palmer et al, 2011;Sui & Humphreys, 2013;Tse & Altarriba, 2012;Wolfe et al, 2010). Essentially, the distributional approach constructs an empirical distribution by using the trial RTs from each individual in a condition and uses a plausible distributional function (such as Weibull or ex-Gaussian) to extract distributional parameters, with the parameters being averaged across participants and then compared across the different conditions.…”

Section: Methodological Issuesmentioning

confidence: 99%

“…Distributional analyses are becoming an increasingly popular method of analyzing performance in cognitive tasks (e.g., Balota & Yap, 2011;Heathcote, Popiel, & Mewhort, 1991;Hockley & Corballis, 1982;Ratcliff & Murdock, 1976;Sui & Humphreys, 2013;Tse & Altarriba, 2012). When compared with analyses based on mean performance, distributional analyses potentially allow a more detailed assessment of the underlying processes that lead to a final decision.…”

Section: Abstract Bayesian Modeling Visual Search Response Time Mmentioning

confidence: 99%

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Modeling visual search using three-parameter probability functions in a hierarchical Bayesian framework

Lin

Heinke

Humphreys

2015

Atten Percept Psychophys

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In this study, we applied Bayesian-based distributional analyses to examine the shapes of response time (RT) distributions in three visual search paradigms, which varied in task difficulty. In further analyses we investigated two common observations in visual search-the effects of display size and of variations in search efficiency across different task conditions-following a design that had been used in previous studies (Palmer, Horowitz, Torralba, & Wolfe, Journal of Experimental Psychology: Human Perception and Performance, 37, 58-71, 2011; Wolfe, Palmer, & Horowitz, Vision Research, 50, 1304-1311 in which parameters of the response distributions were measured. Our study showed that the distributional parameters in an experimental condition can be reliably estimated by moderate sample sizes when Monte Carlo simulation techniques are applied. More importantly, by analyzing trial RTs, we were able to extract paradigm-dependent shape changes in the RT distributions that could be accounted for by using the EZ2 diffusion model. The study showed that Bayesian-based RT distribution analyses can provide an important means to investigate the underlying cognitive processes in search, including stimulus grouping and the bottom-up guidance of attention.

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The ownership memory self-reference effect shifts recognition criterion but not recognition sensitivity

Sparks,

Kritikos

2024

Psychological Research

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Information referenced to the self is retrieved more accurately than information referenced to others, known as the memory self-reference effect. It is unclear, however, whether social context (identity of the other) or task factors alter decision-making processes. In a virtual object allocation task, female participants sorted objects into their own or another’s (stranger or mother) basket based on a colour cue. Subsequently, they performed a recognition memory task in which they first indicated whether each object was old or new, and then whether it had been allocated to themselves or to the other. We obtained owner-specific hit rates and false-alarm rates and applied signal detection theory to derive separate recognition sensitivity (d’) and recognition criterion parameters (c) for self- and other-owned objects. While there was no clear evidence of a recognition self-reference effect, or a change in sensitivity, participants adopted a more conservative recognition criterion for self- compared with other-owned objects, and particularly when the other-referent was the participant’s mother compared with the stranger. Moreover, when discriminating whether the originally presented objects were self- or other-owned, participants were biased toward ascribing ownership to the ‘other’. We speculate that these findings reflect ownership-based changes in decisional processing during the recognition memory self-reference paradigm.

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The boundaries of self face perception: Response time distributions, perceptual categories, and decision weighting

Cited by 31 publications

References 58 publications

The ubiquitous self: what the properties of self‐bias tell us about the self

The ubiquitous self: what the properties of self‐bias tell us about the self

Modeling visual search using three-parameter probability functions in a hierarchical Bayesian framework

The ownership memory self-reference effect shifts recognition criterion but not recognition sensitivity

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