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478 results for “Adult Brain”
Brain Correlates of Deductive Reasoning in Adults
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Brain Correlates of Math Processing in Adults
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Differences in Chemo-signaling Compound-Evoked Brain Activity in Male and Female Young Adults: A Pilot Study in the Role of Sexual Dimorphism in Olfactory Chemo-Signaling
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A deep learning-based dataset of WFA-positive perineuronal nets and parvalbumin neurons localizations in the adult mouse brain
<p><strong>Quality-controlled predictions of deep learning models for cell counting</strong></p> <p>This dataset contains high-resolution images for the visualization of perineuronal nets (PNNs) and parvalbumin-expressing (PV) cells analyzed in the paper:</p> <p><em>A Comprehensive Atlas of Perineuronal Net Distribution and Colocalization with Parvalbumin in the Adult Mouse Brain.</em></p> <p>The dataset integrates the raw data published on a <a href="https://zenodo.org/record/7419282">previous upload</a> on Zenodo.</p> <p>Cell locations were obtained using two deep-learning models for cell counting (publicly available on <a href="http://github.com/ciampluca/counting_perineuronal_nets">GitHub</a>, details in the paper by <a href="https://www.sciencedirect.com/science/article/pii/S1361841522001475">Ciampi et al., 2022</a>). The output of the deep-learning pipeline was filtered based on the <em>score</em> assigned to each cell prediction, by removing all the PNNs with a score lower than 0.4 and all the PV cells with a score lower than 0.55. Cases of artefactual cell detection were finally removed manually by visual inspection of the images. </p> <p><strong>Content</strong></p> <p>The dataset contains microscopy images of coronal brain slices from 7 adult mice. The objects highlighted in these images represent the final set of PNNs/PV cells that were used in all the analysis of the paper.</p> <p><strong>Folder Structure and file naming conventions</strong></p> <p>There are separate folders for each mouse. Each folder is named with the ID of that mouse. Within each folder, images are assigned a code specifying the channel (C1 for PNNs, C2 for PV cells).</p> <p> </p>
Serial Coronal Sections Of An Adult Mouse Brain - Sample Dataset
<p>Experimental data: 88 serial coronal sections of the full brain of an adult mouse.</p> <p>Preparation of the sample: details to come...</p> <p>Imaging of the sample: details to come...</p> <p>2 channels per section are present:</p> <ul> <li>DAPI</li> <li>autofluorescence</li> </ul> <p>This dataset is used in particular as a test dataset for the <a href="https://c4science.ch/w/bioimaging_and_optics_platform_biop/image-processing/image-to-atlas-registration/">Allen Brain Biop Aligner Fiji plugin</a>.</p> <p>Some sections are flipped (left / right), for workflow documentation purpose.</p> <p>Animal handling according to protocols approved by the Swiss animal license VD2808.1</p>
Restricted language access during childhood affects adult brain structure in selective language regions
<p>Anatomical measurements data and analysis codes in R used in manuscript 'Restricted language access during childhood affects adult brain structure in selective language regions'.</p>
A brain-wide, annotated dataset of WFA-positive perineuronal nets and parvalbumin neurons in the adult mouse brain
<p><strong>Microscopy dataset for perineuronal nets and parvalbumin-positive interneurons in the adult mouse brain</strong></p> <p>This dataset contains the data used in the paper titled:</p> <p><em>A Comprehensive Atlas of Perineuronal Net Distribution and Colocalization with Parvalbumin in the Adult Mouse Brain</em></p> <p><strong>Content</strong></p> <p>The dataset contains microscopy images of coronal brain slices of 7 adult mice and several kinds of biological annotations.</p> <p>For each mouse, the annotations contain information about:</p> <ul> <li>Several files related to the alignment of each brain slice to the Allen Brain Institute CCFv3 atlas (for a more detailed description see <a href="https://github.com/LeonardoLupori/brainAlignment">here</a>)</li> <li>Location of individual PNNs and PV cells in each slice</li> </ul> <p><strong>Folder Structure</strong></p> <p>There are separate folders for each mouse. Each folder is named with the ID of that mouse.</p> <p>Each mouse folder contains:</p> <ol> <li>a <em>MOUSEID-info.xml</em> file - Contains general information for the mouse and images</li> <li>a <em>MOUSEID-quicknii.xml</em> file - Contains information for the alignment to the Allen Brain Atlas CCFv3</li> <li>a <em>MOUSEID-visualign.json</em> file - Contains information for the alignment to the Allen Brain Atlas CCFv3</li> <li>a <em>counts </em>folder - Contains annotations for PNNs and PV cell locations for each slice</li> <li>a <em>dispField </em>folder - Contains displacement fields for non-rigid alignment to the Allen Brain Atlas CCFv3</li> <li>a <em>hiRes </em>folder - Contains original, full-resolution, experimental images</li> <li>a <em>masks </em>folder - Contains binary masks for restricting the analysis</li> <li>a <em>thumbnails </em>folder - Contains low-resolution</li> </ol> <p><strong>Files Description</strong></p> <ul> <li><em>MOUSEID-info.xml</em> <ul> <li>XML file containing information about this mouse and details on each image</li> </ul> </li> <li><em>MOUSEID-quicknii.xml</em> <ul> <li>XML file used for global alignment of all the images to the CCFv3 using the software <a href="https://www.nitrc.org/projects/quicknii">QuickNII</a></li> </ul> </li> <li><em>MOUSEID-visualign.json</em> <ul> <li>JSON file used for the interactive local non-rigid alignment of brain slices to the CCFv3 using the software <a href="https://www.nitrc.org/projects/visualign">VisuAlign</a></li> </ul> </li> <li><em>counts </em>folder <ul> <li>Folder containing two .csv files for each high-resolution image. Each .csv file contains the (x,y) location of all PNNs (channel 1) and PV cells (channel 2) detected in that image</li> </ul> </li> <li><em>dispField </em>folder <ul> <li>This folder contains displacement fields in the X and Y direction for each image. These files are meant to be loaded in MATLAB and fed to the function <a href="https://it.mathworks.com/help/images/ref/imwarp.html">imwarp</a>. This function can be used to apply a non-rigid transformation to the reference volume slices in order for it to closely match experimental images.</li> </ul> </li> <li><em>hiRes </em>folder <ul> <li>Folder containing high-resolution experimental images split by channels</li> </ul> </li> <li><em>masks </em>folder <ul> <li>Folder containing binary masks. These files are used to restrict the analysis to portions of the image containing biological tissue and to exclude areas where the tissue was damaged or presented artifacts</li> </ul> </li> <li><em>thumbnails </em>folder <ul> <li>Folder containing a low-resolution RGB version of the experimental images </li> </ul> </li> </ul> <p> </p>
Data from: Extensive, transient, and long-lasting gene regulation in a song-controlling brain area during testosterone-induced song development in adult female canaries
<p>Like other canary reproductive behaviors, song production occurs seasonally and can be triggered by gonadal hormones. Adult female canaries treated with testosterone sing first songs after four days and progressively develop towards typical canary song structure over several weeks, a behavior that females otherwise rarely or never show. We compared gene regulatory networks in the song-controlling brain area HVC after 1 hour (h), 3 h, 8 h, 3 days (d), 7d, and 14d testosterone treatment with placebo-treated control females, paralleling HVC and song development. Rapid onset (1 h or less) of extensive transcriptional changes (2,700 genes) preceded the onset of song production by four days. The highest level of differential gene expression occurred at 14 days when song structure was most elaborate, and song activity was highest. The transcriptomes changed massively several times during the two-week of song production. A total of 9,710 genes were differentially expressed, corresponding to about 60% of the known protein-coding genes of the canary genome. Most (99%) of the differentially expressed genes were regulated only at specific stages. The differentially expressed genes were associated with diverse biological functions, of which cellular level occurring early and nervous system level occurring primarily after prolonged testosterone treatment. Thus, the development of adult songs requires restructuring the entire HVC, including most HVC cell types, rather than altering only neuronal subpopulations or cellular components. Parallel regulation directly by androgen and estrogen receptors and by other hub genes such as the transcription factor SP8, which are under steroidogenic control, lead to massive transcriptomic and neural changes in the specific behavior-controlling brain areas and gradual seasonal occurrence of singing behavior.</p>
Extensive, transient, and long-lasting gene regulation in a song-controlling brain area during testosterone-induced song development in adult female canaries
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Whole-brain mapping in adult zebrafish and identification of the functional brain network underlying the novel tank test
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Mobile Brain-Body Imaging (MoBI) dual-tasking datasets (response inhibition while walking): Young adults
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Mobile Brain-Body Imaging (MoBI) dual-tasking datasets (response inhibition while walking): Older adults
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Supplemental data S1 to accompany Marin et al 2020 "Connectomics analysis reveals first, second, and third order thermosensory and hygrosensory neurons in the adult Drosophila brain"
<p>Neuronal skeletons and meshes. Related to STAR Methods. marin2020-skeletons contains files describing the morphology of each neuron in this study (in FAFB14 space, .swc format). glomeruli_meshes contains the glomerular meshes (in FAFB14 space, .stl format). neuropil_meshes contains the glomerular meshes (in FAFB14 space, .stl format).</p>
Data sets comparing Ca(2+) dynamics in whole-cell and β-escin-based perforated patch clamp recordings in adult mouse brain slices.
<p># Hess-et-al-beta-escin-2020<br> Data of the "Data in Brief" article concerning the added buffer approach with beta-escin perforated patch.</p> <p>A joint work by: Simon Hess (`simon.hess@uni-koeln.de`), Christophe Pouzat (`christophe.pouzat@math.unistra.fr`), and Peter Kloppenburg (`peter.kloppenburg@uni-koeln.de`).</p> <p>## Content</p> <p>This repository contains:</p> <p>- Directory `data_whole_cell` contains the experimental data in [HDF5](https://en.wikipedia.org/wiki/Hierarchical_Data_Format) format. The data contains recordings of _Substantia nigra_ dopaminergic neurons recorded in the whole-cell configuration.<br> - Directory `data_beta_escin` contains the experimental data in [HDF5](https://en.wikipedia.org/wiki/Hierarchical_Data_Format) format. The data contains recordings of _Substantia nigra_ dopaminergic neurons recorded in the β-escin perforated patch clamp configuration.</p>
Serial Coronal Sections Of An Adult Mouse Brain - Sample Dataset
<p>Experimental data: serial coronal sections of the brain of an adult mouse.</p> <p>20 um brain sections sampled every 80 um, imaged on an Olympus VS120 slide scanners with a 10x objective</p> <p>Contains label and overview images and 3 fluorescent channels:</p> <ul> <li>DAPI channel, cell nuclei</li> <li>FITC channel, autofluorescence</li> <li>Cy3 channel, fluorescent sparse mCherry labelled cells</li> </ul> <p>This dataset can be used as a test dataset for the <a href="https://biop.github.io/ijp-imagetoatlas/">Aligning Big Brain and Atlases</a> tool.</p> <p>Animal handling according to protocols approved by the Swiss animal license VD2808.2</p> <p>Two zipped QuPath project that are using the OMERO extension are also provided. One contains the full 97 section dataset, one contains a subset of 25 sections. These data are present in the German BioImaging public OMERO instance (<a href="https://omero-tim.gerbi-gmb.de">https://omero-tim.gerbi-gmb.de</a>).</p> <p> </p> <p> </p>
Impacts of development and adult sex on brain cell numbers in the Black Soldier Fly, Hermetia illucens L. (Diptera: Stratiomyidae)
<p>The Black Soldier Fly (<em>Hermetia illucens</em>, Diptera: Stratiomyidae) has been introduced across the globe, with numerous industry applications predicated on its tremendous growth during the larval stage. However, basic research on <em>H. illucens</em> biology (for example, studies of their central nervous system) are lacking. Despite their small brain volumes, insects are capable of complex behaviors; understanding how these behaviors are completed with such a small amount of neural tissue requires understanding processing power (e.g. number of cells) within the brain. Brain cell counts have been completed in only a few insect species (mostly Hymenoptera), and almost exclusively in adults. This limits the taxonomic breadth of comparative analyses, as well as any conclusions about how development and body size growth may impact brain cell populations. Here, we present the first images and cell counts of the <em>H. illucens</em> brain at four time points across development (early, mid, and late larval stages, and both male and female adults) using immunohistochemistry and isotropic fractionation. To assess sexual dimorphism in adults, we quantified the number of cells in the central brain vs. optic lobes of males and females separately. To assess if increases in body size during development might independently affect different regions of the CNS, we quantified the larval ventral nerve cord and central brain separately at all three stages. Together, these data provide the first description of the nervous system of a popular, farmed invertebrate and the first study of brain cell numbers using IF across developmental stages in any insect.</p>
REXCO Project :Physical exercise increases overall brain oscillatory activity but does not influence inhibitory control in young adults
<p><strong>Methods and design</strong></p> <p><em>Participants</em></p> <p>We recruited 20 young males (19-32 years old, average age 23.8 years old) from the University of Granada (Spain). All participants met the inclusion criteria of normal or corrected to normal vision, reported no neurological, cardiovascular or musculoskeletal disorders, were taking no medication and reporting less than 3 hours of moderate exercise per week. Participants were required to maintain regular sleep-wake cycle for at least one day before each experimental session and to abstain from stimulating beverages or any intense exercise 24 hours before each session. From the 20 participants, one was excluded from the analyses because he did not attend to the last experimental session and another one because of technical issues. Thus, only data from the remaining 18 participants are reported. All subjects gave written informed consent before the study and received 20 euros for their participation. The protocol was approved in accordance with both the ethical guidelines of the University of Granada and the Declaration of Helsinki of 1964.</p> <p><em>Apparatus and materials</em></p> <p>All participants were fitted with a Polar RS800 CX monitor (Polar Electro Öy, Kempele, Finland) to record their heart rate (HR) during the incremental exercise test. We used a ViaSprint 150 P cycle ergometer (Ergoline GmbH, Germany) to induce physical effort and to obtain power values, and a JAEGER Master Screen gas analyser (CareFusion GmbH, Germany) to provide a measure of gas exchange during the effort test. Flanker task stimuli were presented on a 21-inch BENQ screen maintaining a fixed distance of 50 cm between the head of participants and the center of the screen. E-Prime software (Psychology Software Tools, Pittsburgh, PA, USA) was used for stimulus presentation and behavioural data collection.</p> <p><em>Procedure</em></p> <p>Participants completed two counterbalanced experimental sessions of approximately 120 min each. Sessions were scheduled on different days allowing a time interval of 48–72 hours between them to avoid possible fatigue and/or training effects. On each experimental session (see Fig. 1), participants completed a 15’ resting state period sitting in a comfortable chair with closed eyes. Subsequently, they performed 10’ warm-up on a cycle-ergometer at a power load of 20% of their individual VO<sub>2</sub> VAT, following by 30’ exercise at 80% (moderate-intensity exercise session) or at 20% (light intensity exercise session) of their VO<sub>2</sub> VAT (see Table 1). Upon completion of the exercise, a 10’ cool down period at 20% VO<sub>2</sub> VAT of intensity followed. Each participant set his preferred cadence (between 60-90 rpm • min-1) before the warm-up and was asked to maintain this cadence throughout the session in order to match conditions in terms of dual-task demands. Later, participants waited sitting in a comfortable chair until their heart rate returned to within their 130% of heart rate at resting (average waiting time 5’ 44’’). The first flanker task was then performed for 6’, followed by a 15’ resting period with closed eyes. Finally, they again completed the 6’ flanker task.</p> <p><em>Flanker task</em></p> <p>We used a modified version of the Eriksen flanker task based on that reported in Eriksen and Eriksen (1974). The task consisted of a random presentation of a set arrows flanked by other arrows that faced the same or the opposite direction. In the congruent trials, the central arrow is flanked by arrows in the same direction (e.g., <<<<< or >>>>>), while in the incongruent trials, the central arrow is flanked by arrows in the opposite direction (e.g., <<><< or >><>>). Stimuli were displayed sequentially on the center of the screen on a black background. Each trial started with the presentation of a white fixation cross in a black background with random duration between 1000 and 1500 ms. Then, the stimulus was presented during 150 ms and a variable interstimulus interval (1000–1500 ms). Participants were instructed to respond by pressing the left tab button with their left index finger when the central arrow (regardless of condition) faced to the left and the right tab button with their right index finger when the central arrow faced to the right. Participants were encouraged to respond as quick as possible, being accurate. A total of 120 trials were randomly presented (60 congruent and 60 incongruent trials) in each task. Each task lasted for 6 minutes approximately without breaks.</p> <p><em>EEG recording and analysis</em></p> <p>EEG data were recorded at 1000 Hz using a 30-channel actiCHamp System (Brain Products GmbH, Munich, Germany) with active electrodes positioned according to the 10-20 EEG International System and referenced to the Cz electrode. The cap was adapted to individual head size, and each electrode was filled with Signa Electro-Gel (Parker Laboratories, Fairfield, NJ). Participants were instructed to avoid body movements as much as possible, and to keep their gaze on the center of the screen during the exercise. Electrode impedances were kept below 10 kΩ. EEG preprocessing was conducted using custom Matlab scripts and the EEGLAB (Delorme & Makeig, 2004) and Fieldtrip (Oostenveld et al., 2011) Matlab toolboxes. EEG data were resampled at 500 Hz, bandpass filtered offline from 1 and 40 Hz to remove signal drifts and line noise, and re-referenced to a common average reference. Horizontal electrooculograms (EOG) were recorded by bipolar external electrodes for the offline detection of ocular artifacts. The potential influence of electromyographic (EMG) activity in the EEG signal was minimized by using the available EEGLAB routines (Delorme & Makeig, 2004). Independent component analysis was used to detect and remove EEG components reflecting eye blinks (Hoffmann and Falkenstein, 2008). Abnormal spectra epochs which spectral power deviated from the mean by +/-50 dB in the 0-2 Hz frequency window (useful for catching eye movements) and by +25 or -100 dB in the 20-40 Hz frequency window (useful for detecting muscle activity) were rejected. On average, 5.1% of epochs per participant were rejected.</p> <p><em>Spectral power analysis</em>. Processed EEG data from each experimental period (Resting 1, Warm-up, Exercise, Cool Down, Flanker Task 1, Resting 2, Flanker Task 2) were subsequently segmented to 1-s epochs. The spectral decomposition of each epoch was computed using Fast Fourier Transformation (FFT) applying a symmetric Hamming window and the obtained power values were averaged across experimental periods.</p> <p><em>Event-Related Spectral Perturbation (ERSP) analysis.</em> Task-evoked spectral EEG activity was assessed by computing ERSP in epochs extending from –500 ms to 500 ms time-locked to stimulus onset for frequencies between 4 and 40 Hz. Spectral decomposition was performed using sinusoidal wavelets with 3 cycles at the lowest frequency and increasing by a factor of 0.8 with increasing frequency. Power values were normalized with respect to a −300 ms to 0 ms pre-stimulus baseline and transformed into the decibel scale.</p>
REXCO Project :Physical exercise increases overall brain oscillatory activity but does not influence inhibitory control in young adults
<p><strong>Methods and design</strong></p> <p><em>Participants</em></p> <p>We recruited 20 young males (19-32 years old, average age 23.8 years old) from the University of Granada (Spain). All participants met the inclusion criteria of normal or corrected to normal vision, reported no neurological, cardiovascular or musculoskeletal disorders, were taking no medication and reporting less than 3 hours of moderate exercise per week. Participants were required to maintain regular sleep-wake cycle for at least one day before each experimental session and to abstain from stimulating beverages or any intense exercise 24 hours before each session. From the 20 participants, one was excluded from the analyses because he did not attend to the last experimental session and another one because of technical issues. Thus, only data from the remaining 18 participants are reported. All subjects gave written informed consent before the study and received 20 euros for their participation. The protocol was approved in accordance with both the ethical guidelines of the University of Granada and the Declaration of Helsinki of 1964.</p> <p><em>Apparatus and materials</em></p> <p>All participants were fitted with a Polar RS800 CX monitor (Polar Electro Öy, Kempele, Finland) to record their heart rate (HR) during the incremental exercise test. We used a ViaSprint 150 P cycle ergometer (Ergoline GmbH, Germany) to induce physical effort and to obtain power values, and a JAEGER Master Screen gas analyser (CareFusion GmbH, Germany) to provide a measure of gas exchange during the effort test. Flanker task stimuli were presented on a 21-inch BENQ screen maintaining a fixed distance of 50 cm between the head of participants and the center of the screen. E-Prime software (Psychology Software Tools, Pittsburgh, PA, USA) was used for stimulus presentation and behavioural data collection.</p> <p><em>Procedure</em></p> <p>Participants completed two counterbalanced experimental sessions of approximately 120 min each. Sessions were scheduled on different days allowing a time interval of 48–72 hours between them to avoid possible fatigue and/or training effects. On each experimental session (see Fig. 1), participants completed a 15’ resting state period sitting in a comfortable chair with closed eyes. Subsequently, they performed 10’ warm-up on a cycle-ergometer at a power load of 20% of their individual VO<sub>2</sub> VAT, following by 30’ exercise at 80% (moderate-intensity exercise session) or at 20% (light intensity exercise session) of their VO<sub>2</sub> VAT (see Table 1). Upon completion of the exercise, a 10’ cool down period at 20% VO<sub>2</sub> VAT of intensity followed. Each participant set his preferred cadence (between 60-90 rpm • min-1) before the warm-up and was asked to maintain this cadence throughout the session in order to match conditions in terms of dual-task demands. Later, participants waited sitting in a comfortable chair until their heart rate returned to within their 130% of heart rate at resting (average waiting time 5’ 44’’). The first flanker task was then performed for 6’, followed by a 15’ resting period with closed eyes. Finally, they again completed the 6’ flanker task.</p> <p><em>Flanker task</em></p> <p>We used a modified version of the Eriksen flanker task based on that reported in Eriksen and Eriksen (1974). The task consisted of a random presentation of a set arrows flanked by other arrows that faced the same or the opposite direction. In the congruent trials, the central arrow is flanked by arrows in the same direction (e.g., <<<<< or >>>>>), while in the incongruent trials, the central arrow is flanked by arrows in the opposite direction (e.g., <<><< or >><>>). Stimuli were displayed sequentially on the center of the screen on a black background. Each trial started with the presentation of a white fixation cross in a black background with random duration between 1000 and 1500 ms. Then, the stimulus was presented during 150 ms and a variable interstimulus interval (1000–1500 ms). Participants were instructed to respond by pressing the left tab button with their left index finger when the central arrow (regardless of condition) faced to the left and the right tab button with their right index finger when the central arrow faced to the right. Participants were encouraged to respond as quick as possible, being accurate. A total of 120 trials were randomly presented (60 congruent and 60 incongruent trials) in each task. Each task lasted for 6 minutes approximately without breaks.</p> <p><em>EEG recording and analysis</em></p> <p>EEG data were recorded at 1000 Hz using a 30-channel actiCHamp System (Brain Products GmbH, Munich, Germany) with active electrodes positioned according to the 10-20 EEG International System and referenced to the Cz electrode. The cap was adapted to individual head size, and each electrode was filled with Signa Electro-Gel (Parker Laboratories, Fairfield, NJ). Participants were instructed to avoid body movements as much as possible, and to keep their gaze on the center of the screen during the exercise. Electrode impedances were kept below 10 kΩ. EEG preprocessing was conducted using custom Matlab scripts and the EEGLAB (Delorme & Makeig, 2004) and Fieldtrip (Oostenveld et al., 2011) Matlab toolboxes. EEG data were resampled at 500 Hz, bandpass filtered offline from 1 and 40 Hz to remove signal drifts and line noise, and re-referenced to a common average reference. Horizontal electrooculograms (EOG) were recorded by bipolar external electrodes for the offline detection of ocular artifacts. The potential influence of electromyographic (EMG) activity in the EEG signal was minimized by using the available EEGLAB routines (Delorme & Makeig, 2004). Independent component analysis was used to detect and remove EEG components reflecting eye blinks (Hoffmann and Falkenstein, 2008). Abnormal spectra epochs which spectral power deviated from the mean by +/-50 dB in the 0-2 Hz frequency window (useful for catching eye movements) and by +25 or -100 dB in the 20-40 Hz frequency window (useful for detecting muscle activity) were rejected. On average, 5.1% of epochs per participant were rejected.</p> <p><em>Spectral power analysis</em>. Processed EEG data from each experimental period (Resting 1, Warm-up, Exercise, Cool Down, Flanker Task 1, Resting 2, Flanker Task 2) were subsequently segmented to 1-s epochs. The spectral decomposition of each epoch was computed using Fast Fourier Transformation (FFT) applying a symmetric Hamming window and the obtained power values were averaged across experimental periods.</p> <p><em>Event-Related Spectral Perturbation (ERSP) analysis.</em> Task-evoked spectral EEG activity was assessed by computing ERSP in epochs extending from –500 ms to 500 ms time-locked to stimulus onset for frequencies between 4 and 40 Hz. Spectral decomposition was performed using sinusoidal wavelets with 3 cycles at the lowest frequency and increasing by a factor of 0.8 with increasing frequency. Power values were normalized with respect to a −300 ms to 0 ms pre-stimulus baseline and transformed into the decibel scale.</p>
A 3D Adult Zebrafish Brain Atlas (AZBA) for the Digital Age
<p>Zebrafish have made significant contributions to our understanding of the vertebrate brain and the neural basis of behavior, earning a place as one of the most widely used model organisms in neuroscience. Their appeal arises from the marriage of low cost, early life transparency, and ease of genetic manipulation with a behavioral repertoire that becomes more sophisticated as animals transition from larvae to adults. To further enhance the use of adult zebrafish, we created the first fully segmented three-dimensional digital <u>a</u>dult <u>z</u>ebrafish <u>b</u>rain <u>a</u>tlas (AZBA). AZBA was built by combining tissue clearing, light-sheet fluorescence microscopy, and three-dimensional image registration of nuclear and antibody stains. These images were used to guide segmentation of the atlas into over 200 neuroanatomical regions comprising the entirety of the adult zebrafish brain. As an open source, online (azba.wayne.edu), updatable digital resource, AZBA will significantly enhance the use of adult zebrafish in furthering our understanding of vertebrate brain function in both health and disease.</p>
Raw Data for the article: Brain magnetic resonance imaging radiomics features associated with hepatic encephalopathy in adult cirrhotic patients
<p><strong>Purpose: </strong>Hepatic encephalopathy (HE) is a potential complication of cirrhosis. Magnetic resonance imaging (MRI) may demonstrate hyperintense T1 signal in the globi pallidi. The purpose of this study was to evaluate the performance of MRI-based radiomic features for diagnosing and grading chronic HE in adult patients affected by cirrhosis.</p> <p><strong>Methods: </strong>Adult patients with and without cirrhosis underwent brain MRI with identical imaging protocol on a 3T scanner. Patients without history of chronic liver disease were the control population. HE grading was based on underlying liver disease, severity of clinical manifestation, and number of encephalopathic episodes. Texture analysis was performed on axial T1-weighted images on bilateral lentiform nuclei at the level of the foramina of Monro. Diagnostic performance of texture analysis for the diagnosis and grading of HE was assessed by calculating the area under the receiver operating characteristics (AUROC) with 95% confidence interval (CI).</p> <p><strong>Results: </strong>The final study population consisted of 124 patients, 70 cirrhotic patients, and 54 non-cirrhotic controls. Thirty-eight patients had history of HE with 22 having an HE grade > 1. The radiomic features predicted the presence of HE with an AUROC of 0.82 (95% CI: 0.73, 0.90; P < .0001; 82% sensitivity, 66% specificity). Radiomic features predicted grade 1 HE (AUROC 0.75; 95% CI: 0.61, 0.89; P < .0001; 94% sensitivity, 60% specificity) and grade ≥ 2 HE (AUROC 0.82; 95% CI: 0.71, 0.93; P < .0001, 95% sensitivity, 57% specificity).</p> <p><strong>Conclusion: </strong>In cirrhotic patients, MR radiomic is effective in predicting the presence of chronic HE and in grading its severity.</p>
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.