scholarly journals Positive and negative polarity contrast sensitivity measuring app

2016 ◽  
Vol 2016 (16) ◽  
pp. 1-6 ◽  
Author(s):  
Alex D Hwang ◽  
Eli Peli
2002 ◽  
Vol 16 (2) ◽  
pp. 114-118 ◽  
Author(s):  
Timo Ruusuvirta ◽  
Heikki Hämäläinen

Abstract Human event-related potentials (ERPs) to a tone continuously alternating between its two spatial loci of origin (middle-standards, left-standards), to repetitions of left-standards (oddball-deviants), and to the tones originally representing these repetitions presented alone (alone-deviants) were recorded in free-field conditions. During the recordings (Fz, Cz, Pz, M1, and M2 referenced to nose), the subjects watched a silent movie. Oddball-deviants elicited a spatially diffuse two-peaked deflection of positive polarity. It differed from a deflection elicited by left-standards and commenced earlier than a prominent deflection of negative polarity (N1) elicited by alone-deviants. The results are discussed in the context of the mismatch negativity (MMN) and previous findings of dissociation between spatial and non-spatial information in auditory working memory.


1973 ◽  
Author(s):  
Randolph Blake ◽  
Steven Cool
Keyword(s):  

2018 ◽  
Vol 3 (3) ◽  
pp. 193-199
Author(s):  
L. Kharchenko ◽  
◽  
I. Kadoshnikova ◽  
O. Plyska ◽  
I. Shkrobanets ◽  
...  

2019 ◽  
Vol 43 (1) ◽  
pp. 50
Author(s):  
Aquirina Caesari Putri ◽  
Rozalina Loebis

Background: Pediatric cataracts are major causes of children’s blindness. Surgery has proven to be beneficial in terms of visual function prognosis. Contrast sensitivity evaluation after surgery is as important as visual acuity considering that natural world consists of various objects in low-to-medium contrasts. The purpose of this study is to analyze the difference of contrast sensitivity outcomes based on ages at surgery. Method: Retrospective data of children with pediatric developmental cataract from July 2013 to November 2015 were collected. All children who underwent cataract surgery at 60-months-old or less were randomized into two groups, ≤24 months and >24-to-60 months. Contrast sensitivity was then examined with preferential-looking method using Hiding Heidi low-contrast test face chart. The main outcome measures were contrast sensitivity of both groups. Age-at-evaluation, cataract onset, duration of follow-up, duration of deprivation and visual acuity were also noted. Result: Of 14 children (23 eyes), 11 eyes (47,8%) were in ≤24 months group, 12eyes (52,2%) were in >24-to-60 months group. All eyes underwent cataract extraction and similar type of intraocular lens implantation. Mean age-at-surgery was 28,2 months±16,8 (SD). Mean contrast sensitivity for each group was 47,50 %±42,29 and 18,33%±27,38, respectively, with p-value 0,031. Further analysis of Spearman’s correlation test demonstrated significant negative correlation (rs = -0,559; p = 0,006) between the two groups. Conclusion: There was statistically significant difference in contrast sensitivity between those who underwent surgery at ≤24 months and >24-to-60 months. Children who underwent surgery at older ages tend to have better contrast sensitivity afterwards.


2020 ◽  
Author(s):  
Sarah Delanys ◽  
Farah Benamara ◽  
Véronique Moriceau ◽  
François Olivier ◽  
Josiane Mothe

BACKGROUND With the advent of digital technology and specifically user generated contents in social media, new ways emerged for studying possible stigma of people in relation with mental health. Several pieces of work studied the discourse conveyed about psychiatric pathologies on Twitter considering mostly tweets in English and a limited number of psychiatric disorders terms. This paper proposes the first study to analyze the use of a wide range of psychiatric terms in tweets in French. OBJECTIVE Our aim is to study how generic, nosographic and therapeutic psychiatric terms are used on Twitter in French. More specifically, our study has three complementary goals: (1) to analyze the types of psychiatric word use namely medical, misuse, irrelevant, (2) to analyze the polarity conveyed in the tweets that use these terms (positive/negative/neural), and (3) to compare the frequency of these terms to those observed in related work (mainly in English ). METHODS Our study has been conducted on a corpus of tweets in French posted between 01/01/2016 to 12/31/2018 and collected using dedicated keywords. The corpus has been manually annotated by clinical psychiatrists following a multilayer annotation scheme that includes the type of word use and the opinion orientation of the tweet. Two analysis have been performed. First a qualitative analysis to measure the reliability of the produced manual annotation, then a quantitative analysis considering mainly term frequency in each layer and exploring the interactions between them. RESULTS One of the first result is a resource as an annotated dataset . The initial dataset is composed of 22,579 tweets in French containing at least one of the selected psychiatric terms. From this set, experts in psychiatry randomly annotated 3,040 tweets that corresponds to the resource resulting from our work. The second result is the analysis of the annotations; it shows that terms are misused in 45.3% of the tweets and that their associated polarity is negative in 86.2% of the cases. When considering the three types of term use, 59.5% of the tweets are associated to a negative polarity. Misused terms related to psychotic disorders (55.5%) are more frequent to those related to mood disorders (26.5%). CONCLUSIONS Some psychiatric terms are misused in the corpora we studied; which is consistent with the results reported in related work in other languages. Thanks to the great diversity of studied terms, this work highlighted a disparity in the representations and ways of using psychiatric terms. Moreover, our study is important to help psychiatrists to be aware of the term use in new communication media such as social networks which are widely used. This study has the huge advantage to be reproducible thanks to the framework and guidelines we produced; so that the study could be renewed in order to analyze the evolution of term usage. While the newly build dataset is a valuable resource for other analytical studies, it could also serve to train machine learning algorithms to automatically identify stigma in social media.


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