A collection of 4 brain maps. Each brain map is a 3D array of values representing properties of the brain at different locations.

Collection description

Comparison of RNFLT results to the Spectralis normative Database.

Purpose: The aim of this study is to present the largest normative database using multifocal electroretinography (mfERG) in the context of a multicenter clinical trial. Methods: This investigational study included 156 eyes from 78 Caucasian subjects aged 45-70 years without known ophthalmic disease or diabetes mellitus; the subjects were recruited from 11 clinical sites in the setting of the EUROCONDOR project. Standardized mfERG acquisition (103 hexagons per eye) was established based on the International Society of Clinical Electrophysiology in Vision. At least one technician per site received both specialized training and certification. The main variables that could have influenced the results were considered in the analyses. Results: The normative database was based on 111 eyes. The overall mean P1-implicit time (IT) was 33.94 ± 1.70 ms, and the mean P1 amplitude was 30.58 ± 5.20 nV/deg2. Age and gender were independently related to predictors of P1-IT but not of P1 amplitude. The responses that were averaged for the 6 rings showed a longer P1-IT time in the fovea, decreasing progressively to the parafovea and perifovea. By contrast, P1 amplitude values sharply decreased with retinal eccentricity. Conclusions: This normative database can be used as a comparative index of expected normal values in the clinical setting and for examining the effect of studies testing neuroprotective agents.

In pediatric patients with respiratory abnormalities, it is important to understand the alterations in regional dynamics of the lungs and other thoracoabdominal components, which in turn requires a quantitative understanding of what is considered as normal in healthy children. Currently, such a normative database of regional respiratory structure and function in healthy children does not exist. The shared open-source normative database is from our ongoing virtual growing child (VGC) project, which includes 4D dynamic magnetic resonance imaging (dMRI) images during one breathing cycle for each normal child and also 10 object segmentations at end expiration (EE) and end inspiration (EI) phases of the respiratory cycle in the 4D image. The lung volumes at EE and EI as well as the excursion volumes of chest wall and diaphragm from EE to EI, left and right separately, are also reported. The database has 2,820 3D segmentations from 141 healthy children, which to our knowledge is the largest d..., The normative database is from our ongoing NIH funded virtual growing child (VGC) project. All dMRI scans are acquired from healthy children during free-breathing. The dMRI protocol was as follows: 3T MRI scanner (Verio, Siemens, Erlangen, Germany), true-FISP bright-blood sequence, TR=3.82 ms, TE=1.91 ms, voxel size ~1×1×6 mm3, 320×320 matrix, bandwidth 258 Hz, and flip angle 76o. With recent advances, for each sagittal location across the thorax and abdomen, we acquire 40 2D slices over several tidal breathing cycles at ~480 ms/slice. On average, 35 sagittal locations are imaged, yielding a total of ~1400 2D MRI slices, with a resulting total scan time of 11-13 minutes for any particular subject. The collected dMRI goes through the procedure of 4D image construction, image processing, object segmentation, and then volumetric measurements from segmentations. (1) 4D image construction: For the acquired dMRI scans, we utilized an automated 4D image construction approach [1] to form one 4D..., , # A normative database of free-breathing pediatric thoracic 4D dynamic MRI images

https://doi.org/10.5061/dryad.vmcvdnczf

Description of the data and file structure

In total, dynamic MRI (dMRI) images from 141 healthy children were acquired and then constructed with a 4D image per subject, and 3D volumes at end expiration (EE) and end inspiration (EI) time points were segmented with each having 10 object segmentation, leading to a total of 2,820 (141×2×10) 3D segmented object samples. Each object sample has a 3D segmentation mask covering an average of 25 slices, for a total of 70,500 2D slices with object segmentation in the database.

Besides the dMRI and 3D segmentation masks, we also provide the volumetric measurements for the lung (left, right, separately) volumes at EE and EI, and also the chest wall and diaphragm (left, right, separately) tidal volumes in one Excel ("Dryad_dMRI_volumetric.xlsx").

All the images and segmentation m...

The full text of this article can be freely accessed on the publisher's website.

Neurodegenerative and neuroinflammatory diseases regularly cause optic nerve and retinal damage. Evaluating retinal changes using optical coherence tomography (OCT) in diseases like multiple sclerosis has thus become increasingly relevant. However, intraretinal segmentation, a necessary step for interpreting retinal changes in the context of these diseases, is not standardized and often requires manual correction. Here we present a semi-automatic intraretinal layer segmentation pipeline and establish normative values for retinal layer thicknesses at the macula, including dependencies on age, sex, and refractive error. Spectral domain OCT macular 3D volume scans were obtained from healthy participants using a Heidelberg Engineering Spectralis OCT. A semi-automated segmentation tool (SAMIRIX) based on an interchangeable third-party segmentation algorithm was developed and employed for segmentation, correction, and thickness computation of intraretinal layers. Normative data is reported from a 6 mm Early Treatment Diabetic Retinopathy Study (ETDRS) circle around the fovea. An interactive toolbox for the normative database allows surveying for additional normative data. We cross-sectionally evaluated data from 218 healthy volunteers (144 females/74 males, age 36.5 ± 12.3 years, range 18–69 years). Average macular thickness (MT) was 313.70 ± 12.02 μm, macular retinal nerve fiber layer thickness (mRNFL) 39.53 ± 3.57 μm, ganglion cell and inner plexiform layer thickness (GCIPL) 70.81 ± 4.87 μm, and inner nuclear layer thickness (INL) 35.93 ± 2.34 μm. All retinal layer thicknesses decreased with age. MT and GCIPL were associated with sex, with males showing higher thicknesses. Layer thicknesses were also positively associated with each other. Repeated-measurement reliability for the manual correction of automatic intraretinal segmentation results was excellent, with an intra-class correlation coefficient >0.99 for all layers. The SAMIRIX toolbox can simplify intraretinal segmentation in research applications, and the normative data application may serve as an expandable reference for studies, in which normative data cannot be otherwise obtained.

Normative data for VO2 max of men.

Trials data for normative subjects.

This dataset is a collaborative work for the subject "Neuropsychology of Language" taught at the Universidad Autónoma de Madrid, Spain (2023/2024 academic year). The aim is to determine the influence of age, years of education, and gender on four classic language assessment tasks: verbal repetition (subtest from the Test Barcelona Revisado; TBR), comprehension (subtest from the TBR), verbal fluency (COWAT and Isaacs Set-Test) and Boston Naming Test. Also, from the sample data, normative data in young and middle-aged adults can be obtained. For the application of the tests, the conventional instructions were followed, which can be consulted, for example, in Strauss et al. (2006). In addition to the sociodemographic variables above-mentioned, the following cognitive parameters are also included in the dataset: -Score for each item from the verbal repetition task -Total score for the verbal repetition task (range 0-60; a higher score means better performance) -Score for each item from the comprehension task -Total score for the comprehension task (range 0-16; a higher score means better performance) -Number of items correctly evoked in period 1-15" for each phonetic and semantic category -Number of items correctly evoked in the period 16-30" for each phonetic and semantic category -Number of items correctly evoked in the period 31-45" for each phonetic and semantic category -Number of items correctly evoked in the period 45-60" for each phonetic and semantic category -Number of items correctly evoked in the period 45-60" for each phonetic and semantic category -Total number of items correctly evoked 1-60" (sum of the above) for each phonetic and semantic category. -Total number of errors for each phonetic and semantic category -Total number of perseverations for each phonetic and semantic category -Total number of spontaneous hits in the BNT -Total number of hits after semantic clue in the BNT -Total number of hits after phonological clue in the BNT -Total number of hits after semantic clue in the BNT (sum of spontaneous hits + hits after semantic clue)

*All authors contributed equally in this work

Normative data from the general population for the RS-11.

This dataset was used to acquire normative data for a Flemish version of the Buschke selective reminding test (SRT). Data was obtained in 3257 neurologically healthy adults (age range: 18-94 years old). The influences of age, sex and educational level on SRT performance were analysed using robust regression. This study gained ethical approval from the Social and Societal Ethics Committee of the KU Leuven (reference number: G-2018 11 1388).

These data and plot files include movement, force and kinetic data aquired from 100 healthy participants during walking and allow researchers and clinicans to use them as comparators for clinical and research analyses. A detailed description can be found in the readme file.

Yearly citation counts for the publication titled "Normative data for a solution-based taste test".

Normative data for reaction time tests.

The primary purpose of this study is to obtain ABR recordings, create normative ABR values for infants seen at SPMC, and compare the values to published data.

A collection of 3 brain maps. Each brain map is a 3D array of values representing properties of the brain at different locations.

Collection description

Scaling maps at 20mm fwhm smoothing for the NIH, PNC, and HCP cohorts.

This record contains the analysis and underlying data presented in the manuscript Pfau et al. 'Multicenter normative data for mesopic microperimetry'.

Contents: 2024-08-30_Multicenter-Normal-Data.csv: Newly published normal data for mesopic microperimetry 2024-08-30_Analysis.R: Analysis script 2024-08-30_Vignette-to-create-normal-data.R: Software example to create normative maps

The subfolders Figures and Tables show the analysis results. The folder Intermediary_Results contains the results of the cross-validation folds to assess model performance.

To run the analysis code in 2024-08-30_Analysis.R, the following data is needed in addition: Astle et al. Data Brief. 2016 Aug 4;9:673-675. doi: 10.1016/j.dib.2016.07.061

The 2024-08-30_Multicenter-Normal-Data.csv file with the data contains the following columns: source: Describes the clinical site MachineID: ID of the MAIA device used for data collection ParticipantID: ID of the participant EID: ID of the eye eye: Laterality (either Right or Left) sex: Sex (f for female, m for male) age: Age in years ExamID: ID of the exam ExamBaselineID: ID of the corresponding baseline exam (-1 indicates that the exam itself is the baseline exam) GridUsed: Name of the grid falsepos: Rate of false positive responses to Heijl-Krakau stimulus presentations to the optic nerve head (blind spot) bcea63_area_deg2: Fixation stability in terms of the bivariate contour ellipse area covering 63% of the fixation points (in square degree) bcea95_area_deg2: Fixation stability in terms of the bivariate contour ellipse area covering 95% of the fixation points (in square degree) pointID: ID of the test point eccentricity: Eccentricity of the test point (in degree) x_coord: X-coordinate of the test point (in degree), negative values are temporal to the fovea and positive values are nasal to the fovea (in retinal space) y_coord: Y-coordinate of the test point (in degree), negative values are inferior to the fovea and positive values are superior to the fovea (in retinal space) sensitivity: Sensitivity at the test point (in dB)

Database of high-quality craniofacial anthropometric normative data for the research and clinical community based on digital stereophotogrammetry. Unlike traditional craniofacial normative datasets that are limited to measures obtained with handheld calipers and tape measurers, the anthropometric data provided here are based on digital stereophotogrammetry, a method of 3D surface imaging ideally suited for capturing human facial surface morphology. Also unlike more traditional normative craniofacial resources, the 3D Facial Norms Database allows users to interact with data via an intuitive graphical interface and - given proper credentials - gain access to individual-level data, allowing users to perform their own analyses.

Yearly citation counts for the publication titled "Some Normative Data for the Spiral Aftereffect".

Dataset for journal article:A Normative Database of A-Scan Data Using the Heidelberg Spectralis Spectral Domain Optical Coherence Tomography Machine