1,720,961 research outputs found
Visual short-term memory binding and attentional processes during object-scene integration are preserved in mild cognitive impairment
No full textBinding, a critical cognitive process likely mediated by attention, is essential for creating coherent object representations within a scene. This process is vulnerable in individuals with dementia, who exhibit deficits in visual working memory (VWM) binding, primarily tested using abstract arrays of standalone objects. To explore how binding operates in more realistic settings across the lifespan, we examined the impact of object saliency and semantic consistency on VWM binding and the role of overt attention. Using an eye-tracking change detection task, we compared younger adults, healthy older adults, and individuals with Mild Cognitive Impairment (MCI). Participants were presented with naturalistic scenes and asked to detect changes in the identity and/or location of objects that were either semantically consistent or inconsistent with their scene context. Across all age groups, semantically inconsistent objects were prioritised during encoding, leading to better change detection than consistent objects. Highly salient objects decreased the inconsistency advantage while being detrimental to detection accuracy when inspected at longer latencies to the first fixation. Longer fixation durations on the critical object were beneficial for recognition. In contrast, delayed initial inspection or frequent subsequent fixations on other objects were detrimental to detection, regardless of age or cognitive impairment. These findings challenge the notion of generalised semantic memory impairment in the prodromal stages of dementia and highlight the importance of efficient attentional control in supporting VWM binding, even in the face of cognitive decline. Overall, preserved low-level and high-level mechanisms of object-scene integration can compensate for age-related cognitive decline, enabling successful binding in naturalistic contexts
The Visual Integration of Semantic and Spatial Information of Objects in Naturalistic Scenes (VISIONS) database: attentional, conceptual, and perceptual norms
No full textThe complex interplay between low- and high-level mechanisms governing our visual system can only be fully understood within ecologically valid naturalistic contexts. For this reason, in recent years, substantial efforts have been devoted to equipping the scientific community with datasets of realistic images normed on semantic or spatial features. Here, we introduce VISIONS, an extensive database of 1136 naturalistic scenes normed on a wide range of perceptual and conceptual norms by 185 English speakers across three levels of granularity: isolated object, whole scene, and object-in-scene. Each naturalistic scene contains a critical object systematically manipulated and normed regarding its semantic consistency (e.g., a toothbrush vs. a flashlight in a bathroom) and spatial position (i.e., left, right). Normative data are also available for low- (i.e., clarity, visual complexity) and high-level (i.e., name agreement, confidence, familiarity, prototypicality, manipulability) features of the critical object and its embedding scene context. Eye-tracking data during a free-viewing task further confirms the experimental validity of our manipulations while theoretically demonstrating that object semantics is acquired in extra-foveal vision and used to guide early overt attention. To our knowledge, VISIONS is the first database exhaustively covering norms about integrating objects in scenes and providing several perceptual and conceptual norms of the two as independently taken. We expect VISIONS to become an invaluable image dataset to examine and answer timely questions above and beyond vision science, where a diversity of perceptual, attentive, mnemonic, or linguistic processes could be explored as they develop, age, or become neuropathological
Semantic interference mechanisms on long-term visual memory and their eye-movement signatures in mild cognitive impairment
No full textOBJECTIVE: Long-term visual memory representations, measured by recognition performance, degrade as a function of semantic interference, and their strength is related to eye-movement responses. Even though clinical research has examined interference mechanisms in pathological cognitive aging and explored the diagnostic potential of eye-movements in this context, little is known about their interaction in long-term visual memory. METHOD: An eye-tracking study compared a Mild Cognitive Impaired group with healthy adults. Participants watched a stream of 129 naturalistic images from different semantic categories, presented at different frequencies (1, 6, 12, 24) to induce semantic interference (SI), then asked in a 2-Alternative Forced Choice paradigm to verbally recognize the scene they remembered (old/novel). RESULTS: Recognition accuracy of both groups was negatively impacted by SI, especially in healthy adults. A wider distribution of overt attention across the scene predicted better recognition, especially by the Mild Cognitive Impaired (MCI) participants, although these fixation patterns were influenced by SI. MCI compensated the detrimental effect of SI by focusing overt attention during encoding and so accruing distinctive details of the scene. During recognition, MCI participants widened overt attention to boost retrieval. Independently of the group: (a) the re-instatement of fixations indicated a more successful recall and increased as a function of SI; and (b) attending visually salient regions negatively impacted on recognition accuracy, although the reliance on such regions grew as SI increased. CONCLUSIONS: Effects of SI on long-term memory were reduced in MCI participants. They used different oculomotor strategies compared to healthy adults to compensate for its detrimental effects. (PsycInfo Database Record (c) 2021 APA, all rights reserved)
Eye-movements reveal semantic interference effects during the encoding of naturalistic scenes in long-term memory
No full textSimilarity-based semantic interference (SI) hinders memory recognition. Within long-term visual memory paradigms, the more scenes (or objects) from the same semantic category are viewed, the harder it is to recognize each individual instance. A growing body of evidence shows that overt attention is intimately linked to memory. However, it is yet to be understood whether SI mediates overt attention during scene encoding, and so explain its detrimental impact on recognition memory. In the current experiment, participants watched 372 photographs belonging to different semantic categories (e.g., a kitchen) with different frequency (4, 20, 40 or 60 images), while being eye-tracked. After 10 minutes, they were presented with the same 372 photographs plus 372 new photographs and asked whether they recognized (or not) each photo (i.e., old/new paradigm). We found that the more the SI, the poorer the recognition performance, especially for old scenes of which memory representations existed. Scenes more widely explored were better recognized, but for increasing SI, participants focused on more local regions of the scene in search for its potentially distinctive details. Attending to the centre of the display, or to scene regions rich in low-level saliency was detrimental to recognition accuracy, and as SI increased participants were more likely to rely on visual saliency. The complexity of maintaining faithful memory representations for increasing SI also manifested in longer fixation durations; in fact, a more successful encoding was also associated with shorter fixations. Our study highlights the interdependence between attention and memory during high-level processing of semantic information
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Moving to continuous classifications of bilingualism through machine learning trained on language production
Full text linkRecent conceptualisations of bilingualism are moving away from strict categorisations, towards continuous approaches. This study supports this trend by combining empirical psycholinguistics data with machine learning classification modelling. Support vector classifiers were trained on two datasets of coded productions by Italian speakers to predict the class they belonged to (“monolingual”, “attriters” and “heritage”). All classes can be predicted above chance (>33%), even if the classifier's performance substantially varies, with monolinguals identified much better (f-score >70%) than attriters (f-score <50%), which are instead the most confusable class. Further analyses of the classification errors expressed in the confusion matrices qualify that attriters are identified as heritage speakers nearly as often as they are correctly classified. Cluster clitics are the most identifying features for the classification performance. Overall, this study supports a conceptualisation of bilingualism as a continuum of linguistic behaviours rather than sets of a priori established classes
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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