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  • 1
    Online Resource
    Online Resource
    Suboptimal Engagement of High-Level Cortical Regions Predicts Random-Noise-Related Gains in Sustained Attention
    SAGE Publications ; 2019
    In:  Psychological Science Vol. 30, No. 9 ( 2019-09), p. 1318-1332
    Details
    In: Psychological Science, SAGE Publications, Vol. 30, No. 9 ( 2019-09), p. 1318-1332
    Abstract: Interindividual variability in outcomes across individuals poses great challenges for the application of noninvasive brain stimulation in psychological research. Here, we examined how the effects of high-frequency transcranial random-noise stimulation (tRNS) on sustained attention varied as a function of a well-studied electrocortical marker: spontaneous theta:beta ratio. Seventy-two participants received sham, 1-mA, and 2-mA tRNS in a double-blind, crossover manner while they performed a sustained-attention task. Receiving 1-mA tRNS was associated with improved sustained attention, whereas the effect of 2-mA tRNS was similar to the effect of sham tRNS. Furthermore, individuals’ baseline theta:beta ratio moderated the effects of 1-mA tRNS and provided explanatory power beyond baseline behavioral performance. The tRNS-related effects on sustained attention were also accompanied by reductions in theta:beta ratio. These findings impart novel insights into mechanisms underlying tRNS effects and emphasize how designing studies that link variability in cognitive outcomes to variability in neurophysiology can improve inferential power in neurocognitive research.
    Type of Medium: Online Resource
    ISSN: 0956-7976 , 1467-9280
    URL: Article
    DOI: 10.1177/0956797619856658
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2019
    detail.hit.zdb_id: 2022256-7
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  • 2
    Online Resource
    Online Resource
    Numerical representation: Abstract or nonabstract?
    SAGE Publications ; 2008
    In:  Quarterly Journal of Experimental Psychology Vol. 61, No. 8 ( 2008-08), p. 1160-1168
    Details
    In: Quarterly Journal of Experimental Psychology, SAGE Publications, Vol. 61, No. 8 ( 2008-08), p. 1160-1168
    Abstract: Until now it has been a commonly held view that numbers are represented abstractly in the human brain. However, a recent imaging study challenged the existence of an abstract representation at least of digits and number words, at the brain level, and argued that previous studies and paradigms were not sensitive enough to detect deviations from abstract representation at the behavioural level. The current study addressed this issue with an analysis of distance and sequential effects in magnitude classification. Previous studies that used this paradigm did not find deviation from abstract representation for digits and number words (e.g., Dehaene, 1996; Schwarz & Ischebeck, 2000). However, in the current study a short stimulus–response interval was used, which reduced subjective expectancy and increased automatic processing. The current results showed deviation from abstract representation in both reaction time and accuracy and therefore support the idea that nonabstract representations of numbers do exist.
    Type of Medium: Online Resource
    ISSN: 1747-0218 , 1747-0226
    URL: Article
    DOI: 10.1080/17470210801994989
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2008
    detail.hit.zdb_id: 2225936-3
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  • 3
    Online Resource
    Online Resource
    Exceptional Abilities in the Spatial Representation of Numbers and Time : Insights from Synesthesia
    SAGE Publications ; 2012
    In:  The Neuroscientist Vol. 18, No. 3 ( 2012-06), p. 208-215
    Details
    In: The Neuroscientist, SAGE Publications, Vol. 18, No. 3 ( 2012-06), p. 208-215
    Abstract: In the study of basic and high-level cognitive functions, neuroscientists, psychologists, and philosophers have tended to focus on normal psychological processes and on deficits in these processes, whereas the study of exceptional abilities has been largely neglected. Here the authors emphasize the value of researching exceptional abilities. They make the case that studies of exceptional representations, such as of time, number, and space in synesthesia, can provide us with insights regarding the nature of the neurocognitive mechanisms of these dimensions, as well as their developmental, evolutionary, and cultural origins.
    Type of Medium: Online Resource
    ISSN: 1073-8584 , 1089-4098
    URL: Article
    DOI: 10.1177/1073858411402835
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2012
    detail.hit.zdb_id: 2029471-2
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  • 4
    Online Resource
    Online Resource
    Induced Cross-Modal Synaesthetic Experience Without Abnormal Neuronal Connections
    SAGE Publications ; 2009
    In:  Psychological Science Vol. 20, No. 2 ( 2009-02), p. 258-265
    Details
    In: Psychological Science, SAGE Publications, Vol. 20, No. 2 ( 2009-02), p. 258-265
    Abstract: Are the kinds of abnormal cross-modal interactions seen in synaesthesia or following brain damage due to hyperconnectivity between or within brain areas, or are they a result of lack of inhibition? This question is highly contested. Here we show that posthypnotic suggestion induces abnormal cross-modal experience similar to that observed in congenital grapheme-color synaesthesia. Given the short time frame of the experiment, it is unlikely that new cortical connections were established, so we conclude that synaesthesia can result from disinhibition between brain areas.
    Type of Medium: Online Resource
    ISSN: 0956-7976 , 1467-9280
    URL: Article
    DOI: 10.1111/j.1467-9280.2009.02286.x
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2009
    detail.hit.zdb_id: 2022256-7
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  • 5
    Online Resource
    Online Resource
    Evaluation of a New Neural Network Classifier for Diabetic Retinopathy
    SAGE Publications ; 2022
    In:  Journal of Diabetes Science and Technology Vol. 16, No. 6 ( 2022-11), p. 1401-1409
    Details
    In: Journal of Diabetes Science and Technology, SAGE Publications, Vol. 16, No. 6 ( 2022-11), p. 1401-1409
    Abstract: Medical image segmentation is a well-studied subject within the field of image processing. The goal of this research is to create an AI retinal screening grading system that is both accurate and fast. We introduce a new segmentation network which achieves state-of-the-art results on semantic segmentation of color fundus photographs. By applying the net-work to identify anatomical markers of diabetic retinopathy (DR) and diabetic macular edema (DME), we collect sufficient information to classify patients by grades R0 and R1 or above, M0 and M1. Methods: The AI grading system was trained on screening data to evaluate the presence of DR and DME. The core algorithm of the system is a deep learning network that segments relevant anatomical features in a retinal image. Patients were graded according to the standard NHS Diabetic Eye Screening Program feature-based grading protocol. Results: The algorithm performance was evaluated with a series of 6,981 patient retinal images from routine diabetic eye screenings. It correctly predicted 98.9% of retinopathy events and 95.5% of maculopathy events. Non-disease events prediction rate was 68.6% for retinopathy and 81.2% for maculopathy. Conclusion: This novel deep learning model was trained and tested on patient data from annual diabetic retinopathy screenings can classify with high accuracy the DR and DME status of a person with diabetes. The system can be easily reconfigured according to any grading protocol, without running a long AI training procedure. The incorporation of the AI grading system can increase the graders’ productivity and improve the final outcome accuracy of the screening process.
    Type of Medium: Online Resource
    ISSN: 1932-2968 , 1932-2968
    URL: Article
    DOI: 10.1177/19322968211042665
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2022
    detail.hit.zdb_id: 2467312-2
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