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  1. Article ; Online: Sadness facilitates "deeper" reading comprehension: a behavioural and eye tracking study.

    Mills, Caitlin / Southwell, Rosy / D'Mello, Sidney K

    Cognition & emotion

    2024  Volume 38, Issue 1, Page(s) 171–179

    Abstract: Reading is one of the most common everyday activities, yet research elucidating how affective influence reading processes and outcomes is sparse with inconsistent results. To investigate this question, we randomly assigned participants ( ...

    Abstract Reading is one of the most common everyday activities, yet research elucidating how affective influence reading processes and outcomes is sparse with inconsistent results. To investigate this question, we randomly assigned participants (
    MeSH term(s) Humans ; Comprehension/physiology ; Eye-Tracking Technology ; Reading ; Sadness ; Cognition
    Language English
    Publishing date 2024-01-05
    Publishing country England
    Document type Journal Article
    ZDB-ID 639123-0
    ISSN 1464-0600 ; 0269-9931
    ISSN (online) 1464-0600
    ISSN 0269-9931
    DOI 10.1080/02699931.2023.2258589
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.B 3087: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

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  2. Article ; Online: A possible shared underlying mechanism among involuntary autobiographical memory and déjà vu.

    Cleary, Anne M / Poulos, Cati / Mills, Caitlin

    The Behavioral and brain sciences

    2023  Volume 46, Page(s) e361

    Abstract: We propose that IAM and déjà vu may not share a placement on the same gradient, per se, but the mechanism ... ...

    Abstract We propose that IAM and déjà vu may not share a placement on the same gradient, per se, but the mechanism of
    MeSH term(s) Humans ; Memory, Episodic ; Recognition, Psychology ; Metacognition
    Language English
    Publishing date 2023-11-14
    Publishing country England
    Document type Journal Article ; Comment
    ZDB-ID 423721-3
    ISSN 1469-1825 ; 0140-525X
    ISSN (online) 1469-1825
    ISSN 0140-525X
    DOI 10.1017/S0140525X23000079
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1470: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  3. Article ; Online: What Flips Attention?

    Cleary, Anne M / Irving, Zachary C / Mills, Caitlin

    Cognitive science

    2023  Volume 47, Issue 4, Page(s) e13274

    Abstract: A central feature of our waking mental experience is that our attention naturally toggles back and forth between "external" and "internal" stimuli. In the midst of an externally demanding task, attention can involuntarily shift internally with no clear ... ...

    Abstract A central feature of our waking mental experience is that our attention naturally toggles back and forth between "external" and "internal" stimuli. In the midst of an externally demanding task, attention can involuntarily shift internally with no clear reason how or why thoughts momentarily shifted inward. In the case of external attention, we are typically exploring and encoding aspects of our external world, whereas internal attention often involves searching for and retrieving potentially relevant information from our memory networks. Cognitive science has traditionally focused on understanding forms of internal and external attention separately, leaving a mystery about what sparks the seemingly automatic shifts between the two. Specifically, what shifts attentional focus from being outward-directed to being inward-directed? We present a candidate mechanism: Familiarity-detection.
    MeSH term(s) Humans ; Attention ; Recognition, Psychology
    Language English
    Publishing date 2023-04-07
    Publishing country United States
    Document type Letter
    ZDB-ID 2002940-8
    ISSN 1551-6709 ; 0364-0213
    ISSN (online) 1551-6709
    ISSN 0364-0213
    DOI 10.1111/cogs.13274
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Paired evaluation of machine-learning models characterizes effects of confounders and outliers.

    Nariya, Maulik K / Mills, Caitlin E / Sorger, Peter K / Sokolov, Artem

    Patterns (New York, N.Y.)

    2023  Volume 4, Issue 8, Page(s) 100791

    Abstract: The true accuracy of a machine-learning model is a population-level statistic that cannot be observed directly. In practice, predictor performance is estimated against one or more test datasets, and the accuracy of this estimate strongly depends on how ... ...

    Abstract The true accuracy of a machine-learning model is a population-level statistic that cannot be observed directly. In practice, predictor performance is estimated against one or more test datasets, and the accuracy of this estimate strongly depends on how well the test sets represent all possible unseen datasets. Here we describe paired evaluation as a simple, robust approach for evaluating performance of machine-learning models in small-sample biological and clinical studies. We use the method to evaluate predictors of drug response in breast cancer cell lines and of disease severity in patients with Alzheimer's disease, demonstrating that the choice of test data can cause estimates of performance to vary by as much as 20%. We show that paired evaluation makes it possible to identify outliers, improve the accuracy of performance estimates in the presence of known confounders, and assign statistical significance when comparing machine-learning models.
    Language English
    Publishing date 2023-07-07
    Publishing country United States
    Document type Journal Article
    ISSN 2666-3899
    ISSN (online) 2666-3899
    DOI 10.1016/j.patter.2023.100791
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Erratum: Paired evaluation of machine-learning models characterizes effects of confounders and outliers.

    Nariya, Maulik K / Mills, Caitlin E / Sorger, Peter K / Sokolov, Artem

    Patterns (New York, N.Y.)

    2023  Volume 4, Issue 8, Page(s) 100824

    Abstract: This corrects the article DOI: 10.1016/j.patter.2023.100791.]. ...

    Abstract [This corrects the article DOI: 10.1016/j.patter.2023.100791.].
    Language English
    Publishing date 2023-08-11
    Publishing country United States
    Document type Published Erratum
    ISSN 2666-3899
    ISSN (online) 2666-3899
    DOI 10.1016/j.patter.2023.100824
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: PEACOCK: a machine learning approach to assess the validity of cell type-specific enhancer-gene regulatory relationships.

    Mills, Caitlin / Marconett, Crystal N / Lewinger, Juan Pablo / Mi, Huaiyu

    NPJ systems biology and applications

    2023  Volume 9, Issue 1, Page(s) 9

    Abstract: The vast majority of disease-associated variants identified in genome-wide association studies map to enhancers, powerful regulatory elements which orchestrate the recruitment of transcriptional complexes to their target genes' promoters to upregulate ... ...

    Abstract The vast majority of disease-associated variants identified in genome-wide association studies map to enhancers, powerful regulatory elements which orchestrate the recruitment of transcriptional complexes to their target genes' promoters to upregulate transcription in a cell type- and timing-dependent manner. These variants have implicated thousands of enhancers in many common genetic diseases, including nearly all cancers. However, the etiology of most of these diseases remains unknown because the regulatory target genes of the vast majority of enhancers are unknown. Thus, identifying the target genes of as many enhancers as possible is crucial for learning how enhancer regulatory activities function and contribute to disease. Based on experimental results curated from scientific publications coupled with machine learning methods, we developed a cell type-specific score predictive of an enhancer targeting a gene. We computed the score genome-wide for every possible cis enhancer-gene pair and validated its predictive ability in four widely used cell lines. Using a pooled final model trained across multiple cell types, all possible gene-enhancer regulatory links in cis (~17 M) were scored and added to the publicly available PEREGRINE database ( www.peregrineproj.org ). These scores provide a quantitative framework for the enhancer-gene regulatory prediction that can be incorporated into downstream statistical analyses.
    MeSH term(s) Enhancer Elements, Genetic/genetics ; Genome-Wide Association Study ; Gene Expression Regulation/genetics ; Machine Learning
    Language English
    Publishing date 2023-04-03
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ISSN 2056-7189
    ISSN (online) 2056-7189
    DOI 10.1038/s41540-023-00270-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Perceived Group Identity Alters Task-Unrelated Thought and Attentional Divergence During Conversations.

    Colby, Alexander / Wong, Aaron / Allen, Laura / Kun, Andrew / Mills, Caitlin

    Cognitive science

    2023  Volume 47, Issue 1, Page(s) e13236

    Abstract: Task-unrelated thought (TUT) occurs frequently in our daily lives and across a range of tasks, but we know little about how this phenomenon arises during and influences the way we communicate. Conversations also provide a novel opportunity to assess the ... ...

    Abstract Task-unrelated thought (TUT) occurs frequently in our daily lives and across a range of tasks, but we know little about how this phenomenon arises during and influences the way we communicate. Conversations also provide a novel opportunity to assess the alignment (or divergence) in TUT during dyadic interactions. We conducted a study to determine: (a) the frequency of TUT during conversation as well as how partners align/diverge in their rates of TUT, (b) the subjective and behavioral correlates of TUT and TUT divergence during conversation, and (c) if perceived social group identity impacts TUT and TUT divergence during conversation. We used a minimal groups induction procedure to assign participants (N = 126) to either an ingroup, outgroup, or control condition. We then asked them to converse with one another via a computer-mediated text chat application for 10 min while self-reporting TUTs. On average, participants reported TUT about once every 2 min; however, this rate was lower for participants in the ingroup condition, compared to the control condition. Conversational pairs in the ingroup condition were also aligned more in their rates of TUT compared to the outgroup condition. Finally, we discuss subjective and behavioral correlates of TUT and TUT divergence in conversations, such as valence, turn-taking ratios, and topic shifts.
    MeSH term(s) Humans ; Thinking ; Attention ; Communication
    Language English
    Publishing date 2023-01-23
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2002940-8
    ISSN 1551-6709 ; 0364-0213
    ISSN (online) 1551-6709
    ISSN 0364-0213
    DOI 10.1111/cogs.13236
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article: Automatically detecting task-unrelated thoughts during conversations using keystroke analysis.

    Kuvar, Vishal / Blanchard, Nathaniel / Colby, Alexander / Allen, Laura / Mills, Caitlin

    User modeling and user-adapted interaction

    2022  Volume 33, Issue 3, Page(s) 617–641

    Abstract: Task-unrelated thought (TUT), commonly referred to as mind wandering, is a mental state where a person's attention moves away from the task-at-hand. This state is extremely common, yet not much is known about how to measure it, especially during dyadic ... ...

    Abstract Task-unrelated thought (TUT), commonly referred to as mind wandering, is a mental state where a person's attention moves away from the task-at-hand. This state is extremely common, yet not much is known about how to measure it, especially during dyadic interactions. We thus built a model to detect when a person experiences TUTs while talking to another person through a computer-mediated conversation, using their keystroke patterns. The best model was able to differentiate between task-unrelated thoughts and task-related thoughts with a kappa of 0.363, using features extracted from a 15 second window. We also present a feature analysis to provide additional insights into how various typing behaviors can be linked to our ongoing mental states.
    Language English
    Publishing date 2022-08-19
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 1475734-5
    ISSN 1573-1391 ; 0924-1868
    ISSN (online) 1573-1391
    ISSN 0924-1868
    DOI 10.1007/s11257-022-09340-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Enhanced capacity to switch but not to maintain: The basis of attentional bias to high calorie foods in restrained eaters.

    Dondzilo, Laura / Mills, Caitlin / Pollitt, Shannon / MacLeod, Colin

    Appetite

    2022  Volume 172, Page(s) 105969

    Abstract: It has been argued that high restrained eaters (i.e., people who fluctuate between restrictive food intake and overeating) are characterised by a heightened attentional bias to high calorie foods. However, the validity of this hypothesis has not yet been ...

    Abstract It has been argued that high restrained eaters (i.e., people who fluctuate between restrictive food intake and overeating) are characterised by a heightened attentional bias to high calorie foods. However, the validity of this hypothesis has not yet been convincingly established. The current study sought to empirically evaluate this hypothesis using two directional measures of attentional bias: the well-established dot probe bias assessment task and the more novel Chase the Food bias assessment task. The latter attentional assessment approach has the capacity to differentiate between attentional switching and attentional maintenance within a complex and dynamic food environment. Participants (61 high restrained eaters and 38 low restrained eaters) completed the dot probe task and the Chase the Food task. Findings obtained on the dot probe task did not reveal a group difference in terms of biased attentional responding towards high calorie vs. low calorie food. Conversely, the two groups were found to differ on one of the measures obtained on the Chase the Food task. Specifically, high restrained eaters, as compared to low restrained eaters, demonstrated speeded attentional switching to high calorie foods, rather than a greater ability to maintain attention on high calorie foods when required to do so. These novel findings imply that high restrained eaters are potentially characterised by facilitated attentional switching towards high calorie foods. Implications are discussed including the possibility of targeting biased attentional switching using training variants of the Chase the Food task in interventions designed to reduce maladaptive eating behaviours.
    MeSH term(s) Attention ; Attentional Bias ; Cues ; Energy Intake ; Feeding Behavior ; Humans
    Language English
    Publishing date 2022-02-09
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1461347-5
    ISSN 1095-8304 ; 0195-6663
    ISSN (online) 1095-8304
    ISSN 0195-6663
    DOI 10.1016/j.appet.2022.105969
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Better than DFA? A Bayesian Method for Estimating the Hurst Exponent in Behavioral Sciences.

    Likens, Aaron D / Mangalam, Madhur / Wong, Aaron Y / Charles, Anaelle C / Mills, Caitlin

    ArXiv

    2023  

    Abstract: Detrended Fluctuation Analysis (DFA) is the most popular fractal analytical technique used to evaluate the strength of long-range correlations in empirical time series in terms of the Hurst exponent, ...

    Abstract Detrended Fluctuation Analysis (DFA) is the most popular fractal analytical technique used to evaluate the strength of long-range correlations in empirical time series in terms of the Hurst exponent,
    Language English
    Publishing date 2023-01-26
    Publishing country United States
    Document type Preprint
    ISSN 2331-8422
    ISSN (online) 2331-8422
    Database MEDical Literature Analysis and Retrieval System OnLINE

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