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Feature-based attention: behavioral tasks and effects of attention on accuracy and certainty.
No full text<p><b>A</b>, Timing of events for an example feature-based attention trial. The test stimulus consisted of two interlacing RDKs differing in color and was presented randomly left or right of the fixation point (1–1.5 s), modulation of the independent RDKs otherwise matched the spatial attention tasks. Color changes of the fixation point to red or green before (0.5–1 s) and after the presentation (1.5–2 s) of this test stimulus instructed subjects which dot elements to direct attention to and which to actually indicate the direction of global motion for. The other cueing and response modalities were identical to the spatial attention tasks. <b>B–I</b>, Percentage of correct responses or certainty index, respectively, vs. motion coherence for all subjects. Conventions are identical to the spatial attention tasks in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041136#pone-0041136-g001" target="_blank">Fig. 1</a>. <i>*</i> tags p<0.05; <i>***</i> p<0.001 derived from model comparison statistics using Monte-Carlo simulations of the two respective fits, missing asterisk in I: no significant difference between fits. Feature-based attention with numerical certainty ratings (FN): B–E, feature-based attention with certainty wager (FW): F–I. B, F compare accuracy for valid and invalid cues. C, G compare certainty for valid and invalid cues. D, H compare accuracy and certainty for valid trials. E, I compare accuracy and certainty for invalid trials.</p
Observers use high and low certainty ratings uniformly.
No full text<p>Frequencies of respective certainty ratings for a ±10% range of coherence levels around the inflection point of the individual logistic fits: <b>A</b>, valid trials in the spatial attention task with numerical certainty. <b>B</b>, invalid trials in the spatial attention task with numerical certainty. <b>C</b>, valid trials in the feature-based attention task with numerical certainty. Right: Certainty index as function of motion coherence, group data (part of Fig. 1C/2C). Left: Means and S.E.M.s of the frequencies of the four different certainty ratings for all subjects. Grey labels: P-values, statistical significance of paired <i>t</i>-tests comparing the frequency of certainty ratings on a group level. Numerical certainty ratings in the left and right panel: <i>0</i> corresponds to 0.25, <i>1</i> to 0.5, <i>2</i> to 0.75, <i>3</i> to 1.</p
Attention-related change in z-standardized accuracy and certainty.
No full text<p>Differences of mean performance values across subjects observed for the valid condition minus those observed for the invalid condition plotted as Δ z-value (means ± standard errors of the mean). Positive <i>Δ</i>s reflect increases with attention. Both z-transformed accuracy and certainty increase significantly with attention for all four experiments. Certainty increases with valid cueing when correct and incorrect trials are analyzed separately. Increases of certainty are significantly larger than increases of accuracy (grey labels) for SN, SW and FN and tend to be in FW. Detailed p-values see main text. <i>(*)</i> tags p<0.1; <i>**</i> p<0.01; <i>***</i> p<0.001 derived from paired <i>t</i>-tests.</p
Spatial attention: behavioral tasks and effects of attention on accuracy and certainty.
No full text<p><b>A</b>, Timing of events for an example spatial attention trial. The test stimulus consisted of two RDKs presented simultaneously left and right of the fixation point (1.5 – 2s), level of motion coherence and direction of global motion (four alternatives) were modulated on a trial-by-trial basis. An arrow before stimulus presentation (0.5 – 1s) indicated which RDK covertly shift attention to, a second arrow after the stimulus (2.5 – 3s) instructed subjects which RDK they actually had to indicate the direction of coherent motion for. Valid cueing - as defined by congruent orientation of the attentional and the instructional cue - was applied in 80% of trials, see dark blue option. Invalid cueing (incongruent arrows, light blue option) was applied in the remaining 20% of trials. Subjects reported perceived motion direction with a first button press and decision certainty with either a second press of the same buttons using four predefined numerical ratings (SN) or of two of the buttons corresponding to a high (10) or low (1) wager (SW). For the separate wagering variation, wager feedback was given via a continuously updated point score adding or subtracting the chosen virtual bet. <b>B–I</b>, Percentage of correct responses or certainty index, respectively, vs. motion coherence for all subjects. Data points show the proportion of correct choices or the certainty index, respectively. Size of the points is scaled pursuant to the number of corresponding trials. Solid curves are logistic fits to the data using a Maximum Likelihood criterion. <i>**</i> tags p<0.01; <i>***</i> p<0.001 derived from model comparison statistics using Monte-Carlo simulations of the two respective fits, missing asterisk in h: no significant difference between fits. Spatial attention with numerical certainty ratings: B–E; spatial attention with certainty wager: F–I. B,F compare accuracy for valid and invalid cues. C,G compare certainty for valid and invalid cues. D,H compare accuracy and certainty for valid trials. E,I compare accuracy and certainty for invalid trials.</p
Z-standardized certainty increases significantly more with attention than z-standardized accuracy if controlled for the overall success rate.
No full text<p><b>A</b>, Mean accuracy for the group of valid cue trials next to the mean accuracy for invalid cues, all subjects. B, Δ z-values for accuracy and certainty for overlapping coherences of the attended and the unattended condition when overall perceptual success rate is the same for the two cueing conditions. A, <b>B</b>, means ± standard errors of the mean.</p
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
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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