Gendered citation practices in the field of communication

Wang, X.; Dworkin, Jordan D.; Zhou, Dale; Stiso, Jennifer; Falk, Emily B.; Bassett, Dani S.; Zurn, Perry; Lydon‐Staley, David M.

doi:10.1080/23808985.2021.1960180

Cited by 79 publications

(63 citation statements)

References 66 publications

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“…References. Recent work in several fields of science has identified a bias in citation practices such that papers from women and other minority scholars are undercited relative to the number of such papers in the field [61][62][63][64][65][66][67][68][69] . Here we sought to proactively consider choosing references that reflect the diversity of the field in thought, form of contribution, gender, race, ethnicity, and other factors.…”

Section: Methodsmentioning

confidence: 99%

Neuronal activity in sensory cortex predicts the specificity of learning in mice

et al. 2022

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Learning to avoid dangerous signals while preserving normal responses to safe stimuli is essential for everyday behavior and survival. Following identical experiences, subjects exhibit fear specificity ranging from high (specializing fear to only the dangerous stimulus) to low (generalizing fear to safe stimuli), yet the neuronal basis of fear specificity remains unknown. Here, we identified the neuronal code that underlies inter-subject variability in fear specificity using longitudinal imaging of neuronal activity before and after differential fear conditioning in the auditory cortex of mice. Neuronal activity prior to, but not after learning predicted the level of specificity following fear conditioning across subjects. Stimulus representation in auditory cortex was reorganized following conditioning. However, the reorganized neuronal activity did not relate to the specificity of learning. These results present a novel neuronal code that determines individual patterns in learning.

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Section: Methodsmentioning

confidence: 99%

Neuronal activity in sensory cortex predicts the specificity of learning in mice

et al. 2022

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“…Recent work in several fields of science has identified a bias in citation practices such that papers from women and other minority scholars are undercited relative to the number of such papers in the field ( Maliniak et al, 2013 ; Mitchell et al, 2013 ; Caplar et al, 2017 ; Dion et al, 2018 ; Bertolero et al, 2020 ; Dworkin et al, 2020 ; Chatterjee and Werner, 2021 ; Fulvio et al, 2021 ; Wang et al, 2021 ). Here, we sought to proactively consider choosing references that reflect the diversity of the field in thought, form of contribution, gender, race, ethnicity, and other factors.…”

Section: Methodsmentioning

confidence: 99%

Neurophysiological Evidence for Cognitive Map Formation during Sequence Learning

Stiso

Lynn

Kahn

et al. 2022

eNeuro

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Humans deftly parse statistics from sequences. Some theories posit that humans learn these statistics by forming cognitive maps, or underlying representations of the latent space which links items in the sequence. Here, an item in the sequence is a node, and the probability of transitioning between two items is an edge. Sequences can then be generated from walks through the latent space, with different spaces giving rise to different sequence statistics. Individual or group differences in sequence learning can be modeled by changing the time scale over which estimates of transition probabilities are built, or in other words, by changing the amount of temporal discounting. Latent space models with temporal discounting bear a resemblance to models of navigation through Euclidean spaces. However, few explicit links have been made between predictions from Euclidean spatial navigation and neural activity during human sequence learning. Here, we use a combination of behavioral modeling and intracranial encephalography (iEEG) recordings to investigate how neural activity might support the formation of space-like cognitive maps through temporal discounting during sequence learning. Specifically, we acquire human reaction times from a sequential reaction time task, to which we fit a model that formulates the amount of temporal discounting as a single free parameter. From the parameter, we calculate each individual’s estimate of the latent space. We find that neural activity reflects these estimates mostly in the temporal lobe, including areas involved in spatial navigation. Similar to spatial navigation, we find that low-dimensional representations of neural activity allow for easy separation of important features, such as modules, in the latent space. Lastly, we take advantage of the high temporal resolution of iEEG data to determine the time scale on which latent spaces are learned. We find that learning typically happens within the first 500 trials, and is modulated by the underlying latent space and the amount of temporal discounting characteristic of each participant. Ultimately, this work provides important links between behavioral models of sequence learning and neural activity during the same behavior, and contextualizes these results within a broader framework of domain general cognitive maps.

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“…Recent work in several fields of science-including physics and biology, where our work here is situated [42][43][44][45][46]-has identified a bias in citation practices such that papers from women and other minority scholars are under-cited relative to the number of such papers in the field [47][48][49][50][51]. Here we sought to proactively consider choosing references that reflect the diversity of the field in thought, form of contribution, gender, race, ethnicity, and other factors.…”

Section: Citation Diversity Statementmentioning

confidence: 99%

Excitation and inhibition imbalance affects dynamical complexity through symmetries

Ouellet¹,

Kim²,

Guillaume³

et al. 2022

Preprint

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Gendered citation practices in the field of communication

Cited by 79 publications

References 66 publications

Neuronal activity in sensory cortex predicts the specificity of learning in mice

Neuronal activity in sensory cortex predicts the specificity of learning in mice

Neurophysiological Evidence for Cognitive Map Formation during Sequence Learning

Excitation and inhibition imbalance affects dynamical complexity through symmetries

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