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112 results for “Brain measures”
Correlations between a Shintergy synchronized brain and a laser eld; a possible fractal structure of Consciousness (Part I of 7 – Local measure in time and space).
<p>Data set from Correlations between a Shintergy synchronized brain and a laser eld; a possible fractal structure of Consciousness (Part I of 7 – Local measure in time and space), and figures.</p>
BRAIN Journal-Brain signal analysis using EEG and Entropy to study the effect of physical and mental tasks on cognitive performance-Figure 2. Energy-VAS subjective measures for the participants (n=12) under two conditions (control and exercise involved cognitive task).
<p>As shown in Figure 2, it was found that there was a statistically significant interaction in the<br> percentage of mental fatigue between the condition type and time-on-task factor times (F(6, 22) =<br> 492.19, p < 0.001) as well as there was a significant main effect of time-on-task (time5 to time30)<br> (F(5, 22) = 463.794, p < 0.001). In addition, there was also a significant main effect in the condition type (F (1, 22) = 713.133, p < 0.001) which represented a large effect size. For the physical fatigue<br> subjective measure, there was a significant difference between the two experimental conditions (p <<br> 0.001), and within the subject test times (p < 0.001). However, there was no significant difference<br> between the means of the concentration visual analogue scale for these two experimental conditions<br> (p = 0.057) despite a significant difference (p < 0.001) in the time-on-task repeated measures.</p>
Simultaneous dynamic glucose-enhanced (DGE) MRI and fiber photometry measurements of glucose in the healthy mouse brain
<p>This dataset was acquired for the DGE and fiber photometry study published in NeuroImage ( <a href="https://doi.org/10.1016/j.neuroimage.2022.119762">https://doi.org/10.1016/j.neuroimage.2022.119762</a>).<br> Comprises of three datasets: DGE MRI, fiber photometry and two-photon microscopy.</p>
Data from: Measuring instability in chronic human intracortical neural recordings towards stable, long-term brain-computer interfaces
Open the record for dataset details and reuse information.
Longitudinal stability of brain and spinal cord quantitative MRI measures
<p><strong>About: </strong>Tabular (CSV) files are generated by the Courtois Neuromod<a href="https://github.com/courtois-neuromod/anat-processing"> structural data processing workflow</a>. These files contain quantitative MRI metrics such as T1, MTsat, and MTR, in addition to fundamental diffusion tensor imaging indices like RD and FA derived from brain data. The results also encompass the same metrics for spinal cord imaging data, supplemented with additional metrics for spinal cord morphometry. For details regarding the raw data please visit <a href="https://www.cneuromod.ca">https://www.cneuromod.ca</a>. </p><p>Dataset provided for NeuroLibre preprint. Author repo: https://github.com/courtois-neuromod/anat-processing-paper NeuroLibre fork:https://github.com/roboneurolibre/anat-processing-paper</p><p>For details, please visit the corresponding <a href="https://github.com/neurolibre/neurolibre-reviews/issues/18">NeuroLibre technical screening.</a></p><p><a href="https://neurolibre.org"><strong>https://neurolibre.org</strong></a></p>
Derived brain morphology measures from CamCAN data
<p>Derived brain morphology measures from CamCAN data.</p>
Measuring Brain Amyloid Plaque Load in Older Adults Using BAY 94-9172
ClinicalTrials.gov study NCT01222351. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Measuring Brain Activity of School Age Children
ClinicalTrials.gov study NCT03407729. IPD Sharing: UNDECIDED. Countries: 1. Publications: 20.
Data from: Circulating cortisol and cognitive and structural brain measures in a middle-aged cohort: the Framingham Heart Study
Objective: To assess the association of early morning serum cortisol with cognitive performance and brain structural integrity in community-dwelling young and middle-aged adults without dementia. Methods: We evaluated dementia-free Framingham Study (Generation 3) participants (mean age 48.5 years; 46.8% men), who underwent cognitive testing for memory, abstract reasoning, visual perception, attention, and executive function (n= 2231), and brain MRI (n=2018) to assess total white matter, lobar gray matter, and white matter hyperintensity volumes and fractional anisotropy (FA) measures. We used linear and logistic regression to assess the relations of cortisol (categorized in tertiles, with the middle tertile as referent) to measures of cognition, MRI volumes, presence of covert brain infarcts (CBI) and cerebral microbleeds (CMB), and voxel-based microstructural white matter integrity and gray matter density, adjusting for age, sex, APOE and vascular risk factors. Results: Higher cortisol (highest tertile vs. middle tertile) was associated with worse memory and visual perception, as well as lower total cerebral brain, occipital and frontal lobar gray matter volumes. Higher cortisol was associated with multiple areas of microstructural changes (decreased regional FA), especially in the splenium of corpus callosum and the posterior corona radiata. The association of cortisol with total cerebral brain volume varied by sex (p interaction=0.048); higher cortisol was inversely associated with cerebral brain volume in women [p=0.001] but not in men [p=0.717]). There was no effect modification by the apoE4 genotype of the relations of cortisol and cognition or imaging traits. Conclusions: Higher serum cortisol was associated with lower brain volumes and impaired memory in asymptomatic younger to middle-aged adults, with the association being evident particularly in women.
Targeted micro-fiber arrays for measuring and manipulating localized multi-scale neural dynamics over large, deep brain volumes during behavior: resources and main figure data
<p><strong>Summary:</strong></p> <p>Neural population dynamics relevant for behavior vary over multiple spatial and temporal scales across 3-dimensional volumes. Current optical approaches lack the spatial coverage and resolution necessary to measure and manipulate naturally occurring patterns of large-scale, distributed dynamics within and across deep brain regions such as the striatum. We designed a new micro-fiber array approach capable of chronically measuring and optogenetically manipulating local dynamics across over 100 targeted locations simultaneously in head-fixed and freely moving mice. We developed a semi-automated micro-CT based strategy to precisely localize positions of each optical fiber. This highly-customizable approach enables investigation of multi-scale spatial and temporal patterns of cell-type and neurotransmitter specific signals over arbitrary 3-D volumes at a spatial resolution and coverage previously inaccessible. We applied this method to resolve rapid dopamine release dynamics across the striatum volume which revealed distinct, modality specific spatiotemporal patterns in response to salient sensory stimuli extending over millimeters of tissue. Targeted optogenetics through our fiber arrays enabled flexible control of neural signaling on multiple spatial scales, better matching endogenous signaling patterns, and spatial localization of behavioral function across large circuits. </p> <p><strong>Files included: </strong></p> <ul> <li>Vu, M-A. et al. (2023) - Key Resources Table.xlsx -- key resources used in this study</li> <li>README_figure_data_and_analysis.txt --a description of the organization of the files within this repository</li> <li>README_preprocessing_code.txt -- details about the preprocessing pipeline (including registration and localization pipelines) and annotation of the preprocessed data structure</li> <li>preprocessing_code.zip -- contains all the preprocessing code</li> <li>Fig01.zip -- preprocessed data and analysis code for main Figure 1</li> <li>Fig03.zip -- preprocessed data and analysis code for main Figure 3</li> <li>Fig04.zip -- preprocessed data and analysis code for main Figure 4</li> <li>Fig05.zip -- preprocessed data and analysis code for main Figure 5</li> <li>Fig06.zip -- preprocessed data and analysis code for main Figure 6</li> <li>Fig07.zip -- preprocessed data and analysis code for main Figure 7</li> <li>SuppFig01.zip -- preprocessed data and analysis code for supplemental Figure 1</li> <li>SuppFig02.zip -- preprocessed data and analysis code for supplemental Figure 2</li> <li>SuppFig03.zip -- preprocessed data and analysis code for supplemental Figure 3</li> <li>SuppFig04.zip -- preprocessed data and analysis code for supplemental Figure 4</li> <li>SuppFig05.zip -- preprocessed data and analysis code for supplemental Figure 5</li> <li>SuppFig06.zip -- preprocessed data and analysis code for supplemental Figure 6</li> <li>SuppFig07.zip -- preprocessed data and analysis code for supplemental Figure 7</li> </ul> <p>Each .zip file contains a folder corresponding to a figure. Within each figure folder will be a folder corresponding to the letter (e.g., A, B, C) of the panel within the figure. In addition to the panel folders, when applicable, there may also be a folder containing general-use functions or scripts, or interim results .mat files, that are called by the scripts within the subfolders. In each subfolder there will be 3 things:</p> <ol> <li>a folder of preprocessed data (see README_preprocessing_code.txt)</li> <li>a folder of the analysis scripts that analyzed the preprocessed data and generated the figure</li> <li>a README text file detailing the contents of both folders and the analysis workflow.</li> </ol> <p> </p>
Dataset from the study: "Brain Haemorrhage Detection using a SVM Classifier with Electrical Impedance Tomography Measurement Frames"
<p>This repository contains the scripts and other resources used in:</p> <p>“Brain Haemorrhage Detection using a SVM Classifier with Electrical Impedance Tomography Measurement Frames”, McDermott B et al. 10.1371/journal.pone.0200469</p> <p> </p> <p>>> THIS DATA IS FREE FOR USE IN ANY SCIENTIFIC RESEARCH WITH CITATION (PLEASE USE THE DOI FOR PRECISE CITATION): DOI 10.1371/journal.pone.0200469</p> <p> </p> <p>>> IF YOU USE THESE RESOURCES, CITE!!!</p> <p> </p> <p>The repository contains the code and resources to generate the EIT Measurement Frames used in Numerical Models (STL models, code to mesh, code to generate frames)</p> <p> </p> <p>Also included are the Measurement Frames generated from the Phantom Studies.</p> <p> </p> <p><strong>=> This is all the data (how to replicate it for numerical studies and the actual data for the phantom part) used in the study</strong></p> <p> </p> <p>Classifier generation, training, testing, cross validation etc uses standard MATLAB methods and resources: fitcsvm() etc.</p> <p> </p> <p>The subfolders are ordered numerically in the logical order of use</p> <p>The subfolders contain text files with more details and description relevant to the contents of the respective subfolder.</p> <p> </p> <p>Note:</p> <p> </p> <p>Software used in this study:</p> <p>At a minimum the first 2 will be needed to be installed on your computer</p> <p>(other methods etc needed are detailed within the folders)</p> <p> </p> <p><strong>MATLAB 2017B</strong> (<a href="https://uk.mathworks.com/products/matlab.html">https://uk.mathworks.com/products/matlab.html</a>):</p> <p>The primary software tool used throughout</p> <p> </p> <p><strong>EIDORS </strong>(<a href="http://eidors3d.sourceforge.net/index.shtml">http://eidors3d.sourceforge.net/index.shtml</a>)<strong>: </strong></p> <p>Open Source software package, compatible with MATLAB, with tools for use in Electrical Impedance Tomography studies.</p> <p> </p> <p><strong>Autodesk Fusion 360</strong> (<a href="https://www.autodesk.com/products/fusion-360/overview?mktvar002=685209&mkwid=sMHGuhLcc%7Cpcrid%7C209188650131%7Cpkw%7Cfusion%20360%7Cpmt%7Ce%7Cpdv%7Cc%7Cslid%7C%7Cpgrid%7C34851227038%7Cptaid%7Ckwd-11029869505%7C&intent=&utm_medium=cpc&utm_source=google&utm_campaign=GGL_Fusion+360_IE_BR_SEM&utm_term=fusion%20360&utm_content=sMHGuhLcc%7Cpcrid%7C209188650131%7Cpkw%7Cfusion%20360%7Cpmt%7Ce%7Cpdv%7Cc%7Cslid%7C%7Cpgrid%7C34851227038%7Cptaid%7Ckwd-11029869505%7C&gclid=Cj0KCQjw1NzZBRCoARIsAIaMwut5zqUE_d7oieOvw6H3SpU45Jw7vwL5KAKqyRYW20Be6QWE-V3HaB0aAnW0EALw_wcB">https://www.autodesk.com/products/fusion-360/overview?mktvar002=685209&mkwid=sMHGuhLcc|pcrid|209188650131|pkw|fusion%20360|pmt|e|pdv|c|slid||pgrid|34851227038|ptaid|kwd-11029869505|&intent=&utm_medium=cpc&utm_source=google&utm_campaign=GGL_Fusion+360_IE_BR_SEM&utm_term=fusion%20360&utm_content=sMHGuhLcc|pcrid|209188650131|pkw|fusion%20360|pmt|e|pdv|c|slid||pgrid|34851227038|ptaid|kwd-11029869505|&gclid=Cj0KCQjw1NzZBRCoARIsAIaMwut5zqUE_d7oieOvw6H3SpU45Jw7vwL5KAKqyRYW20Be6QWE-V3HaB0aAnW0EALw_wcB</a>):</p> <p>Used to generate the head, brain and lesion STL files. These final STL files are provided in this repository.</p>
Data from: Application of Spatial-ID to large field mouse brain hemisphere dataset measured by Stereo-seq
<p>The application of Spatial-ID on the large field mouse brain hemisphere dataset measured by Stereo-seq technology. Briefly, three adjacent coronal sections along the anterior-posterior axis were cut from the brain 5-week-old male mouse. It fully proves the innovation and applicability of Spatial-ID.</p>
Independent Use of Brain Measurement-Based Rehabilitation System by Stroke Survivors
ClinicalTrials.gov study NCT05016193. IPD Sharing: NO. Countries: 1. Publications: 1.
Brain Activity Changes Measured by EEG and fMRI on Healthy Volunteers After Complex Somatosensory Stimulation
ClinicalTrials.gov study NCT01079689. IPD Sharing: Not stated. Countries: 1. Publications: 1.
In Vivo Measurement of the Accuracy of the "Neurolocate" Module of the Neurosurgical Robot "Neuromate" in Its Application to Deep Brain Stimulation
ClinicalTrials.gov study NCT04712552. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Invasive Versus Non Invasive Measurement of Intracranial Pressure in Brain Injury Trial (IMPRESSIT)
ClinicalTrials.gov study NCT02322970. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Measuring and Mapping Cognitive Decline After Brain Radiosurgery
ClinicalTrials.gov study NCT06466720. IPD Sharing: NO. Countries: 1. Publications: 21.
Measuring Effects of Alcohol on Brain Chemistry
ClinicalTrials.gov study NCT01492933. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Effects of Nicotine on Brain Activity as Measured by fMRI
ClinicalTrials.gov study NCT01037153. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Functional Connectivity Measurement After Severe Traumatic Brain Injury
ClinicalTrials.gov study NCT02647996. IPD Sharing: Not stated. Countries: 1. Publications: 2.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.