How eye movements improve vision and action – comment on Vickers

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Emotionen und Kontrollüberzeugungen beim komplexen Problemlösen : eine experimentelle Untersuchung anhand des computersimulierten Problemlöseszenarios FSYS 2.0

Diese Studie untersucht den Einfluss positiver und negativer Emotionen auf komplexes Problemlösen unter Berücksichtigung der Kompetenz- und Kontrollüberzeugungen als Traits. 74 studentische männliche und weibliche Probanden bearbeiteten das computersimulierte Szenario FSYS 2.0 (Wagener & Conrad, 1997), anhand dessen sich Aussagen sowohl über die Problemlösegüte als auch das Problemlöseverhalten (z.B. Informationsmanagement) treffen lassen. Emotionen wurden vor Beginn des Szenarios und nach der Hälfte der Bearbeitung experimentell durch Leistungsfeedback induziert und begleitend durch Fragebögen erhoben. Kompetenz- und Kontrollüberzeugungen wurden mittels einer für den Kontext des Problemlösens modifizierten Version des Fragebogens zu Kompetenz- und Kontrollüberzeugungen (FKK; Krampen, 1991) erfasst. Die Ergebnisse zeigen, dass Emotionen keinen Effekt auf die Problemlösegüte hatten. Auf der Ebene des Problemlöseverhaltens führten negative Emotionen jedoch zu einer stärker informationsgeleiteten Vorgehensweise. Internal kontrollüberzeugte Probanden wiesen ein besseres Informationsmanagement sowie eine höhere Problemlösegüte auf als external Kontrollüberzeugte, wobei Kontrollüberzeugungen in Bezug auf die Problemlösegüte die Rolle einer Moderatorvariable einnehmen. Als wesentliche Prädiktoren des Problemlöseerfolgs wurden jedoch Intelligenz und Geschlecht der Probanden identifiziert

Is Acceleration Used for Ocular Pursuit and Spatial Estimation during Prediction Motion?

Here we examined ocular pursuit and spatial estimation in a linear prediction motion task that emphasized extrapolation of occluded accelerative object motion. Results from the ocular response up to occlusion showed that there was evidence in the eye position, velocity and acceleration data that participants were attempting to pursue the moving object in accord with the veridical motion properties. They then attempted to maintain ocular pursuit of the randomly-ordered accelerative object motion during occlusion but this was not ideal, and resulted in undershoot of eye position and velocity at the moment of object reappearance. In spatial estimation there was a general bias, with participants less likely to report object reappearance being behind than ahead of the expected position. In addition, participants’ spatial estimation did not take into account the effects of object acceleration. Logistic regression indicated that spatial estimation was best predicted for the majority of participants by the difference between actual object reappearance position and an extrapolation based on pre-occlusion velocity. In combination, and in light of previous work, we interpret these findings as showing that eye movements are scaled in accord with the effects of object acceleration but do not directly specify information for accurate spatial estimation in prediction motion

Look where you go: characterizing eye movements toward optic flow: [Preprint]

When we move through our environment, objects in the visual scene create optic flow patterns on the retina. Even though optic flow is ubiquitous in everyday life, it is not well understood how our eyes naturally respond to it. In small groups of human and non-human primates, optic flow triggers intuitive, uninstructed eye movements to the focus of expansion of the pattern (Knöll, Pillow & Huk, 2018). Here we investigate whether such intuitive oculomotor responses to optic flow are generalizable to a larger group of human observers, and how eye movements are affected by motion signal strength and task instructions. Observers (n = 43) viewed expanding or contracting optic flow constructed by a cloud of moving dots radiating from or converging toward a focus of expansion that could randomly shift. Results show that 84% of observers tracked the focus of expansion with their eyes without being explicitly instructed to track. Intuitive tracking was tuned to motion signal strength: saccades landed closer to the focus of expansion and smooth tracking was more accurate when dot contrast, motion coherence, and translational speed were high. Under explicit tracking instruction, the eyes aligned with the focus of expansion more closely than without instruction. Our results highlight the sensitivity of intuitive eye movements as indicators of visual motion processing in dynamic contexts

Look where you go: Characterizing eye movements toward optic flow

When we move through our environment, objects in the visual scene create optic flow patterns on the retina. Even though optic flow is ubiquitous in everyday life, it is not well understood how our eyes naturally respond to it. In small groups of human and non-human primates, optic flow triggers intuitive, uninstructed eye movements to the focus of expansion of the pattern (Knöll, Pillow, & Huk, 2018). Here, we investigate whether such intuitive oculomotor responses to optic flow are generalizable to a larger group of human observers and how eye movements are affected by motion signal strength and task instructions. Observers (N = 43) viewed expanding or contracting optic flow constructed by a cloud of moving dots radiating from or converging toward a focus of expansion that could randomly shift. Results show that 84% of observers tracked the focus of expansion with their eyes without being explicitly instructed to track. Intuitive tracking was tuned to motion signal strength: Saccades landed closer to the focus of expansion, and smooth tracking was more accurate when dot contrast, motion coherence, and translational speed were high. Under explicit tracking instruction, the eyes aligned with the focus of expansion more closely than without instruction. Our results highlight the sensitivity of intuitive eye movements as indicators of visual motion processing in dynamic contexts

TaqMan probe array for quantitative detection of DNA targets

To date real-time quantitative PCR and gene expression microarrays are the methods of choice for quantification of nucleic acids. Herein, we described a unique fluorescence resonance energy transfer-based microarray platform for real-time quantification of nucleic acid targets that combines advantages of both and reduces their limitations. A set of 3′ amino-modified TaqMan probes were designed and immobilized on a glass slide composing a regular microarray pattern, and used as probes in the consecutive PCR carried out on the surface. During the extension step of the PCR, 5′ nuclease activity of DNA polymerase will cleave quencher dyes of the immobilized probe in the presence of nucleic acids targets. The increase of fluorescence intensities generated by the change in physical distance between reporter fluorophore and quencher moiety of the probes were collected by a confocal scanner. Using this new approach we successfully monitored five different pathogenic genomic DNAs and analyzed the dynamic characteristics of fluorescence intensity changes on the TaqMan probe array. The results indicate that the TaqMan probe array on a planar glass slide monitors DNA targets with excellent specificity as well as high sensitivity. This set-up offers the great advantage of real-time quantitative detection of DNA targets in a parallel array format

Mini-Mental State Examination (MMSE) for the detection of dementia in clinically unevaluated people aged 65 and over in community and primary care populations

BACKGROUND: The Mini Mental State Examination (MMSE) is a cognitive test that is commonly used as part of the evaluation for possible dementia. OBJECTIVES: To determine the diagnostic accuracy of the Mini‐Mental State Examination (MMSE) at various cut points for dementia in people aged 65 years and over in community and primary care settings who had not undergone prior testing for dementia. SEARCH METHODS: We searched the specialised register of the Cochrane Dementia and Cognitive Improvement Group, MEDLINE (OvidSP), EMBASE (OvidSP), PsycINFO (OvidSP), LILACS (BIREME), ALOIS, BIOSIS previews (Thomson Reuters Web of Science), and Web of Science Core Collection, including the Science Citation Index and the Conference Proceedings Citation Index (Thomson Reuters Web of Science). We also searched specialised sources of diagnostic test accuracy studies and reviews: MEDION (Universities of Maastricht and Leuven, www.mediondatabase.nl), DARE (Database of Abstracts of Reviews of Effects, via the Cochrane Library), HTA Database (Health Technology Assessment Database, via the Cochrane Library), and ARIF (University of Birmingham, UK, www.arif.bham.ac.uk). We attempted to locate possibly relevant but unpublished data by contacting researchers in this field. We first performed the searches in November 2012 and then fully updated them in May 2014. We did not apply any language or date restrictions to the electronic searches, and we did not use any methodological filters as a method to restrict the search overall. SELECTION CRITERIA: We included studies that compared the 11‐item (maximum score 30) MMSE test (at any cut point) in people who had not undergone prior testing versus a commonly accepted clinical reference standard for all‐cause dementia and subtypes (Alzheimer disease dementia, Lewy body dementia, vascular dementia, frontotemporal dementia). Clinical diagnosis included all‐cause (unspecified) dementia, as defined by any version of the Diagnostic and Statistical Manual of Mental Disorders (DSM); International Classification of Diseases (ICD) and the Clinical Dementia Rating. DATA COLLECTION AND ANALYSIS: At least three authors screened all citations.Two authors handled data extraction and quality assessment. We performed meta‐analysis using the hierarchical summary receiver‐operator curves (HSROC) method and the bivariate method. MAIN RESULTS: We retrieved 24,310 citations after removal of duplicates. We reviewed the full text of 317 full‐text articles and finally included 70 records, referring to 48 studies, in our synthesis. We were able to perform meta‐analysis on 28 studies in the community setting (44 articles) and on 6 studies in primary care (8 articles), but we could not extract usable 2 x 2 data for the remaining 14 community studies, which we did not include in the meta‐analysis. All of the studies in the community were in asymptomatic people, whereas two of the six studies in primary care were conducted in people who had symptoms of possible dementia. We judged two studies to be at high risk of bias in the patient selection domain, three studies to be at high risk of bias in the index test domain and nine studies to be at high risk of bias regarding flow and timing. We assessed most studies as being applicable to the review question though we had concerns about selection of participants in six studies and target condition in one study. The accuracy of the MMSE for diagnosing dementia was reported at 18 cut points in the community (MMSE score 10, 14‐30 inclusive) and 10 cut points in primary care (MMSE score 17‐26 inclusive). The total number of participants in studies included in the meta‐analyses ranged from 37 to 2727, median 314 (interquartile range (IQR) 160 to 647). In the community, the pooled accuracy at a cut point of 24 (15 studies) was sensitivity 0.85 (95% confidence interval (CI) 0.74 to 0.92), specificity 0.90 (95% CI 0.82 to 0.95); at a cut point of 25 (10 studies), sensitivity 0.87 (95% CI 0.78 to 0.93), specificity 0.82 (95% CI 0.65 to 0.92); and in seven studies that adjusted accuracy estimates for level of education, sensitivity 0.97 (95% CI 0.83 to 1.00), specificity 0.70 (95% CI 0.50 to 0.85). There was insufficient data to evaluate the accuracy of the MMSE for diagnosing dementia subtypes.We could not estimate summary diagnostic accuracy in primary care due to insufficient data. AUTHORS' CONCLUSIONS: The MMSE contributes to a diagnosis of dementia in low prevalence settings, but should not be used in isolation to confirm or exclude disease. We recommend that future work evaluates the diagnostic accuracy of tests in the context of the diagnostic pathway experienced by the patient and that investigators report how undergoing the MMSE changes patient‐relevant outcomes