Locating what comes to mind in empirically derived representational spaces

Mills, Tracey; Phillips, Jonathan

doi:10.1016/j.cognition.2023.105549

Cited by 3 publications

(3 citation statements)

References 22 publications

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“…Recent research using process-tracing techniques suggests that how samples come to mind and what the task at hand is are largely independent. For example, Mills and Phillips [ 46 ] ask their participants to generate a list of animals as they come to mind, and find that doing so with no other purpose, or in order to answer a specific question, does not change the types of items participants produce. Similarly, Hardisty, Johnson and Weber [ 47 ] find that reporting ideas that come to mind while making a decision makes no qualitative difference on the resulting choice, compared to a condition without thought listing.…”

Section: Discussionmentioning

confidence: 99%

Explaining the flaws in human random generation as local sampling with momentum

Castillo,

León-Villagrá,

Chater

et al. 2024

PLoS Comput Biol

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In many tasks, human behavior is far noisier than is optimal. Yet when asked to behave randomly, people are typically too predictable. We argue that these apparently contrasting observations have the same origin: the operation of a general-purpose local sampling algorithm for probabilistic inference. This account makes distinctive predictions regarding random sequence generation, not predicted by previous accounts—which suggests that randomness is produced by inhibition of habitual behavior, striving for unpredictability. We verify these predictions in two experiments: people show the same deviations from randomness when randomly generating from non-uniform or recently-learned distributions. In addition, our data show a novel signature behavior, that people’s sequences have too few changes of trajectory, which argues against the specific local sampling algorithms that have been proposed in past work with other tasks. Using computational modeling, we show that local sampling where direction is maintained across trials best explains our data, which suggests it may be used in other tasks too. While local sampling has previously explained why people are unpredictable in standard cognitive tasks, here it also explains why human random sequences are not unpredictable enough.

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Section: Discussionmentioning

confidence: 99%

Explaining the flaws in human random generation as local sampling with momentum

Castillo,

León-Villagrá,

Chater

et al. 2024

PLoS Comput Biol

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“…Beyond examining emotion fluency variables themselves, here we borrowed from the cognitive literature (Sauzéon et al, 2004;Zemla & Austerweil;Mills & Phillips 2023) and tested whether analyzing the order in which participants thought of emotion words could reveal the dimensions underlying emotion word representation. We hypothesized that dimensions of the circumplex model would structure word order (e.g., people would move along the dimensions of valence, arousal, and dominance as they search semantic space for emotion words; Russell & Mehrabian;1977;Russell et al, 1980;Posner et al, 2005).…”

Section: Discussionmentioning

confidence: 99%

“…Beyond these questions regarding the development of emotion fluency and valence bias, emotion fluency tasks offer an opportunity to identify what dimensions structure the order in which emotion words spontaneously come to mind. Studies in cognitive psychology have shown that people produce words in fluency tasks by moving through semantic networks (Mills & Phillips, 2023;Sauzéon et al, 2004). Participant responses on memory retrieval and verbal fluency tasks often "cluster" around semantically related words.…”

Section: Introductionmentioning

confidence: 99%

Emotion word production tasks grant insight into the development of emotion word organization and accessibility

Valdivia-Moreno,

Sasse,

Lambert

et al. 2023

Preprint

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Children are often instructed to “use their words” to communicate their emotions, which requires them to quickly access words that best describe their feelings. Adults vary in their ability to bring both non-emotion and emotion words to mind (two capacities called verbal fluency and emotion fluency). However, no studies have examined how emotion fluency emerges across development, despite the fact that mastering emotion language is an important developmental task. A cross-sectional sample of participants aged 4-25 years (N = 194) generated as many fruit words as possible in 60 seconds (to measure verbal fluency) and as many emotion words as possible in 60 seconds (to measure emotion fluency). Emotion fluency was highly correlated with verbal fluency and both showed similar increases across age, plateauing in late adolescence. Participants produced more negative emotion words than positive or neutral words, and these proportions were invariant across age. Finally, age of acquisition, valence, dominance, concreteness, and word length were significantly associated with the order in which emotion words came to participants’ minds, suggesting that these dimensions structure the accessibility of emotion concepts. Interestingly, the influence of these dimensions on the order of emotion word production was invariant across age. Results from this study illustrate the developmental emergence of an important, yet understudied, affective skill and provide new insight into the key features that structure which emotion words rapidly come to mind.

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Navigating choices: a framework of consumer search

Moore,

Hastie

2024

Mark Lett

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Locating what comes to mind in empirically derived representational spaces

Cited by 3 publications

References 22 publications

Explaining the flaws in human random generation as local sampling with momentum

Explaining the flaws in human random generation as local sampling with momentum

Emotion word production tasks grant insight into the development of emotion word organization and accessibility

Navigating choices: a framework of consumer search

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