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103 results for “marmoset”
Functional MRI data from medetomidine-isoflurane anesthetized marmosets
<p>This dataset contains unprocessed <strong>functional MRI (fMRI)</strong> data acquired in <strong>common marmosets</strong> (<em>Callithrix jacchus</em>), The data were obtained during a continuous infusion of the sedative <strong>medetomidine</strong>, supplemented with a low concentration of <strong>isoflurane</strong>. All experiments were carried out in accordance with the guidelines from Directive 2010/63/EU of the European Parliament on the protection of animals used for scientific purposes.</p> <p><strong>Related paper</strong></p> <p>This dataset supplements the following <a href="https://www.biorxiv.org/content/10.1101/2023.11.21.568138v1.abstract">manuscript</a>.</p> <p><strong>Preserving functional network structure under anesthesia in the marmoset monkey brain</strong></p> <p>M Ortiz-Rios, N Sirmpilatze, J Koenig, S Boretius - bioRxiv, 2023</p> <p><strong>doi: <a href="https://doi.org/10.1101/2023.11.21.568138">https://doi.org/10.1101/2023.11.21.568138</a> </strong></p> <p><strong>Data structure</strong></p> <p>The main data files are organized into eight zipped folders - <em><strong>sub-02.tar.gz, .... sub-09.tar.gz </strong></em> - each constituting a dataset formatted according to the <a href="https://bids.neuroimaging.io/">Brain Imaging Data Structure</a> specifications (BIDS v1.6.0).</p> <ul> <li>Each BIDS-formatted dataset contains subfolders for individual sessions (e.g. <em><strong>ses-0001</strong>, </em>etc.).Additionally, a text file, <strong><em>participants.tsv</em></strong>, with some essential information about the subjects (e.g. age, weight, sex).</li> <li>Each subject-specific folder contains subfolders named <em><strong>func</strong> </em>and <strong><em>anat</em></strong>, storing fMRI and structural MRI data respectively. The (f)MRI data are provided in <a href="https://nifti.nimh.nih.gov/">NIfTI format</a> (suffixed with <strong><em>.nii.gz</em></strong>). </li> <li>The <em><strong>func</strong></em> files are named as <strong><em>{sub-id}_{ses-id}_{run-id}_{task-id}_bold.nii.gz. </em></strong>The task id is based on runs acquired for resting-state or during visual stimulation.</li> </ul> <p><strong>BIDS-formatted dataset</strong></p> <p>The basic characteristics of the datasets are given below. More details can be found in the <a href="https://www.biorxiv.org/content/10.1101/2023.11.21.568138v1.abstract">preprint</a>.</p> <ol> <li><em><strong>Marmoset</strong></em> <ul> <li><strong>Institution:<em> </em></strong>German Primate Center (Deutsches Primatenzentrum GmbH - Leibniz-Institut für Primatenforschung), Göttingen, Germany</li> <li><strong>MR system:</strong> Bruker BioSpec 9.4 T, equpped with B-GA 20S gradient</li> <li><strong>Anatomical MRI scan:</strong> Proton density-weighted (PDw) with magnetization transfer (MT) pulse, 1 per subject</li> <li><strong>fMRI scan:</strong> GE-EPI, several runs per subject (between 6 and 9 runs), duration 330 s for visual runs and 600 s for resting-state runs, all with a TR of 2 s and a resolution of 0.4 mm isotropic.</li> <li><strong>Subjects:</strong> 8 <em>Callithrix jacchus</em></li> <li><strong>Age range:</strong> 2.6 - 9.5 years</li> <li><strong>Weight range:</strong> 375 - 517 g</li> <li><strong>Sex:</strong> 5 males and 3 females</li> <li><strong>Ethics oversight:</strong> Lower Saxony State Office for Consumer Protection and Food Safety, Hannover, Germany (approval numbers 33.19-42502-04-17/2496)</li> </ul> </li> </ol>
Functional MRI data from isoflurane-anesthetized macaques, marmosets, and rats
<p>This dataset contains unprocessed task-free <strong>functional MRI (fMRI)</strong> data acquired in three different mammalian species: <strong>long-tailed macaques</strong> (<em>Macaca fascicularis</em>), <strong>common marmosets</strong> (<em>Callithrix jacchus</em>), and <strong>rats</strong> (<em>Rattus Norvegicus</em>, Wistar strain). The data were obtained during <strong>isoflurane anesthesia</strong>, with the animals intubated and mechanically ventilated. All experiments were carried out in accordance with the guidelines from Directive 2010/63/EU of the European Parliament on the protection of animals used for scientific purposes.</p> <p><strong>Related paper</strong></p> <p>This dataset supplements the following <a href="http://doi.org/10.7554/eLife.74813">manuscript</a>:</p> <p>Sirmpilatze N, Mylius J, Ortiz-Rios M, Baudewig J, Paasonen J, Golkowski D, Ranft A, Ilg R, Gröhn O, Boretius S. <em>Spatial signatures of anesthesia-induced burst-suppression differ between primates and rodents.</em> eLife 2022;11:e74813. DOI: https://doi.org/10.7554/eLife.74813</p> <p><strong>Data structure</strong></p> <p>The main data files are organized into four zipped folders - <em><strong>Macaque.zip, Marmoset.zip, Rat1.zip, Rat2.zip</strong></em> - each constituting a dataset formatted according to the <a href="https://bids.neuroimaging.io/">Brain Imaging Data Structure</a> specifications (BIDS v1.6.0).</p> <ul> <li>Each BIDS-formatted dataset contains subfolders for individual subjects (e.g. <em><strong>sub-01</strong>, <strong>sub-02</strong>,</em> etc.), as well as a tab-separated text file, <strong><em>participants.tsv</em></strong>, with some essential information about the subjects (e.g. age, weight, sex).</li> <li>Each subject-specific folder contains subfolders named <em><strong>func</strong> </em>and <strong><em>anat</em></strong>, storing fMRI and structural MRI data respectively. The (f)MRI data are provided in <a href="https://nifti.nimh.nih.gov/">NIfTI format</a> (suffixed with <strong><em>.nii.gz</em></strong>). Each NIfTI file is accompanied by a <strong><em>.json sidecar</em></strong> holding metadata.</li> <li>The <em><strong>func</strong></em> subfolders also include tab-separated text files named as <strong><em>{sub-id}_scans.tsv</em></strong> (e.g. <em><strong>sub-01_scans.tsv</strong></em>). These files provide additional information on the fMRI runs within the <em><strong>func</strong></em> subfolder, such as the isoflurane concentration during the acquisition of the fMRI run, duration of the run, etc.</li> <li>The column names in <em><strong>participants.tsv</strong></em> and <em><strong>{sub-id}_scans.tsv</strong></em> files are explained in accompanying <em><strong>participants.json </strong></em>and <em><strong>{sub-id}_scans.json</strong></em> files.</li> </ul> <p><strong>BIDS-formatted datasets</strong></p> <p>The basic characteristics of the datasets are given below. More details can be found in the <a href="https://www.biorxiv.org/content/10.1101/2021.10.15.464515">preprint</a>.</p> <ol> <li><em><strong>Macaque</strong></em> <ul> <li><strong>Institution:<em> </em></strong>German Primate Center (Deutsches Primatenzentrum GmbH - Leibniz-Institut für Primatenforschung), Göttingen, Germany</li> <li><strong>MR system:</strong> Siemens MAGNETOM Prisma 3T</li> <li><strong>Anatomical MRI scan:</strong> T1-weighted (MPRAGE), 1 per subject</li> <li><strong>fMRI scan:</strong> GE-EPI, 1 or 2 runs per subject, run duration 600 - 1200 s</li> <li><strong>Subjects:</strong> 13 <em>Macaca fascicularis</em></li> <li><strong>Age range:</strong> 6.8 - 19.8 years</li> <li><strong>Weight range:</strong> 3.6 - 8.1 kg</li> <li><strong>Sex:</strong> all females</li> <li><strong>Ethics oversight:</strong> Lower Saxony State Office for Consumer Protection and Food Safety, Hannover, Germany (approval number 33.19-42502-04-16/2278)</li> </ul> </li> <li><em><strong>Marmoset</strong></em> <ul> <li><strong>Institution:<em> </em></strong>German Primate Center (Deutsches Primatenzentrum GmbH - Leibniz-Institut für Primatenforschung), Göttingen, Germany</li> <li><strong>MR system:</strong> Bruker BioSpec 9.4 T, equpped with B-GA 20S gradient</li> <li><strong>Anatomical MRI scan:</strong> Proton density-weighted (PDw) with magnetization transfer (MT) pulse, 1 per subject</li> <li><strong>fMRI scan:</strong> GE-EPI, 1 run per subject, run duration 600 s (except for sub-21, containing 4 runs of 300 s duration each).</li> <li><strong>Subjects:</strong> 21 <em>Callithrix jacchus</em></li> <li><strong>Age range:</strong> 1.9 - 14.2 years</li> <li><strong>Weight range:</strong> 337 - 517 g</li> <li><strong>Sex:</strong> 11 females</li> <li><strong>Ethics oversight:</strong> Lower Saxony State Office for Consumer Protection and Food Safety, Hannover, Germany (approval numbers 33.19-42502-04-17/2496 and 33.19-42502-04-17/2535)</li> </ul> </li> <li><em><strong>Rat1</strong></em> <ul> <li><strong>Institution:<em> </em></strong>German Primate Center (Deutsches Primatenzentrum GmbH - Leibniz-Institut für Primatenforschung), Göttingen, Germany</li> <li><strong>MR system:</strong> Bruker BioSpec 9.4 T, equpped with B-GA 12S2 gradient</li> <li><strong>Anatomical MRI scan:</strong> T2-weighted (TurboRARE), 1 per subject</li> <li><strong>fMRI scan:</strong> GE-EPI, 6 runs per subject (except for sub-10: 4 runs), run duration 720 s</li> <li><strong>Subjects:</strong> 11 <em>Rattus norvegicus</em>, Wistar strain</li> <li><strong>Weight range:</strong> 350 - 450 g</li> <li><strong>Sex:</strong> all females</li> <li><strong>Ethics oversight:</strong> Lower Saxony State Office for Consumer Protection and Food Safety, Hannover, Germany (approval number 33.19-42502-04-15/2042)</li> </ul> </li> <li><em><strong>Rat2</strong></em> <ul> <li><strong>Institution:<em> </em></strong>A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland</li> <li><strong>MR system:</strong> Bruker PharmaScan 7 T</li> <li><strong>Anatomical MRI scan:</strong> NOT provided</li> <li><strong>fMRI scan:</strong> GE-EPI, 6 runs per subject (except for sub-10: 4 runs), run duration 720 s</li> <li><strong>Subjects:</strong> 6 <em>Rattus norvegicus</em>, Wistar strain</li> <li><strong>Weight range:</strong> 265 - 350 g</li> <li><strong>Sex:</strong> all males</li> <li><strong>Ethics oversight:</strong> Animal Ethics Committee of the Provincial Government of Southern Finland</li> </ul> </li> </ol> <p><strong>Example data</strong></p> <p>Before you commit to downloading the BIDS-formatted datasets, we encourage you to examine the example data that we provide in the root folder. These include one anatomical (stuctural MRI) and one functional (fMRI) scan from each of the four datasets (Rat2 contains functional scans only), with their respecitve <strong><em>.json sidecars</em></strong>. A preview of these example scans is provided by <em><strong>0_preview.pdf.</strong></em></p>
Dataset for "Intra-intestinal analysis of the functional activity of microbiomes and its application to the common marmoset intestine"
<p>Dataset:</p> <p>data1_ExpressionProfile.xlsx: gene expression profile</p> <p>data2_AnnotationProfile.xlsx: gene annotation profile</p>
Intra-intestinal analysis of the functional activity of microbiomes and its application to the common marmoset intestine
<p>Supplementary Table Captions:</p> <p>Table S7. Assignment of genes to unknown gene clusters</p> <p>Table S8. AUC used to determine parameters for covariation analysis by benchmarking</p> <p>Table S9. Linked unknown gene clusters</p> <p>Table S10. Information on common marmosets</p> <p>Table S11. Dual index sequences</p> <p>Table S12. Sequencing statistics</p> <p>Table S13. RIN score of total RNA samples</p> <p>Table S14. Top 20 bacterial species in taxonomic profiling</p> <p>Table S15. Number of genes covered by the nonchimaeric genome in each parameter at the assembly step</p> <p>Table S16. Number of genes covered by the nonchimaeric genome in each parameter at the merge step</p> <p>Table S17. Distance between intestinal sites</p>
Data from: A model of marmoset monkey vocal turn-taking
<p>Vocal turn-taking has been described in a diversity of species. Yet a model that captures the various processes underlying this social behavior across species has not been developed. To this end, here we recorded a large and diverse dataset of marmoset monkey vocal behavior in social contexts comprising one, two and three callers and developed a model to determine the keystone factors that affect the dynamics of these natural communicative interactions. While a coupled oscillator model failed to account for turn-taking in marmosets, our model alternatively revealed four key factors that encapsulate much of patterns evident in the behavior, ranging from internal processes, such as the state of the individual, to social context driven suppression of calling. In addition, we show that the same key factors apply to the meerkat, a carnivorous species, in a multicaller setting. These findings indicate that vocal turn-taking is affected by a broader suite of mechanisms than previously considered and our model provides a predictive framework with which to further explicate this natural behavior and for direct comparisons with the analogous behavior in other species.</p>
Common marmosets are sensitive to simple dependencies at variable distances in an artificial grammar
<p>Video data of each trial in a study with common marmoset monkeys.</p> <p>Its current title is "Common marmosets are sensitive to simple dependencies at variable distances in an artificial grammar".</p> <p>Abstract of the publication is as below.</p> <p>Recognizing that two elements within a sequence of variable length depend on each other is a key ability in understanding the structure of language and music. Perception of such interdependencies has previously been documented in chimpanzees in the visual domain and in human infants and common squirrel monkeys with auditory playback experiments, but it remains unclear whether it typifies primates in general. Here, we investigated the ability of common marmosets (<em>Callithrix jacchus</em>) to recognize and respond to such dependencies. We tested subjects in a familiarization-discrimination playback experiment using stimuli composed of pure tones that either conformed or did not conform to a grammatical rule. After familiarization to sequences with dependencies, marmosets spontaneously discriminated between sequences containing (‘consistent’) and lacking dependencies (‘inconsistent’), independent of stimulus length. Marmosets looked more often to the sound source when hearing sequences consistent with the familiarization stimuli, as previously found in human infants. Crucially, looks were coded automatically by computer software, avoiding risk of human bias. Our results support the hypothesis that the ability to perceive dependencies at variable distances was already present in the common ancestor of all anthropoid primates (<em>Simiiformes</em>).</p>
Fig. 1 in New insights into the taxonomy of the marmoset rats Hapalomys (Rodentia: Muridae)
Fig. 1. Map of localities. 1 – Myanmar, the type locality of Hapalomys longicaudatus; 2 – Thailand, locality of R5237 (Badenhorst et al., 2009); 3 – Laos, the type locality of Hapalomys pasquieri; 4 – Vietnam, Ha Tinh Province, Ke Go NR, locality of ZIN 103040; 5 – Vietnam, Kon Tum Province, Dakto, the type locality of Hapalomys delacouri; 6 – Vietnam, Binh Phuoc Province, Bu Gia Map NP; 7 – records of Hapalomys longicaudatus (after Musser, 1972); 8 – Malaysia, an approximate locality of the Hapalomys longicaudatus record from Yong et al. (1982).
Fig. 5 in New insights into the taxonomy of the marmoset rats Hapalomys (Rodentia: Muridae)
Fig. 5. Ventral, dorsal and lateral views of skull and lingual side of mandibles: A – Hapalomys suntsovi (holotype, ZIN 99487, Binh Phuoc Province, Vietnam); B – Hapalomys delacouri (ZIN 103040, Ha Tinh Province, Vietnam). Scale bar =10 mm.
Fig. 4 in New insights into the taxonomy of the marmoset rats Hapalomys (Rodentia: Muridae)
Fig. 4. General appearance of Hapalomys suntsovi based on a specimen ZIN 99484, collected from the Bu Gia Map NP, Vietnam, on 12 January 2010.
Fig. 2 in New insights into the taxonomy of the marmoset rats Hapalomys (Rodentia: Muridae)
Fig. 2. Maximum Likelihood phylogenetic tree (GTR+G+I) of Hapalomys spp. and relative murid taxa as inferred from the COI gene sequence. Posterior probabilities are indicated above the corresponding nodes.
Fig. 3 in New insights into the taxonomy of the marmoset rats Hapalomys (Rodentia: Muridae)
Fig. 3. Ungrouped morphometric separation (principal components analysis) drawn from the 19 specimens of Hapalomys spp. Red dots – H. longicaudatus; blue dots – H. delacouri; green dots – H. suntsovi from the Bu Gia Map NP (BGM), Binh Phuoc Province, Vietnam.
Preprocessed auditory task-fMRI files of common marmoset
<p>Preprocessed auditory task-fMRI files of common marmoset.</p> <p>Original data was acquired by https://doi.org/10.1016/j.jneumeth.2022.109737</p> <p>Related github repository is https://github.com/takuto-okuno-riken/oku2023dmn</p>
Fast prediction in marmoset reach-to-grasp movements for dynamic prey - Reach Data and Supplemental Video
<p>Supplemental video and data corresponding to Shaw, L., Wang, K.H., Mitchell, J. (2023) Fast prediction in marmoset reach-to-grasp movements for dynamic prey.</p> <p>1. Video Files</p> <p>MarmoReach 1 is an illustrative example.</p> <p>MarmoReach 2 illustrates the reaching trial shown in Figure 3D.</p> <p>MarmoReach 3-5 are example reach to grasps from grasp clusters found in Figure 2. </p> <p>2. Data</p> <p>marmo_reach_model.mat is a Matlab struct.</p> <p>2D position data of hand and cricket used for analyses related to Figure 3 and Figure 4. </p> <p>x.hand,y.hand = position data of the central hand marker for each trial.</p> <p>x.cricket,y.cricket = position data of the cricket marker for each trial.</p> <p>x.cricketexfull,y.cricketexfull = position data of the cricket marker preceding reach onset for delay analyses. </p> <p>To reconstruct cricket position from beginning to end with the inclusion of the exfull data (prior to reach to reach end) for the second reach, for example, [model.x.cricketexfull{2}' model.x.cricket{2}'].</p> <p> </p>
Supplementary Material for publication "Bifidobacteria Define Gut Microbiome Profiles of Golden Lion Tamarin (Leontopithecus rosalia} and Marmoset Callithrix sp. Metagenomic Shotgun Pools
<p>Supplementary Tables and Figure for the publication "Bifidobacteria Define Gut Microbiome Profiles of Golden Lion Tamarin <em>Leontopithecus rosalia</em> and Marmoset <em>Callithrix</em> sp. Metagenomic Shotgun Pools"</p>
Data and codes: Who is calling? Optimising source identification from marmoset vocalisations with hierarchical machine learning classifiers
<p>Data and codes that accompany the article titled "Who is calling? Optimising source identification from marmoset vocalisations with hierarchical machine learning classifiers".</p>
Data from: A model of marmoset monkey vocal turn-taking
Open the record for dataset details and reuse information.
Domestication phenotype linked to vocal behavior in marmoset monkeys
<p>The domestication syndrome refers to a set of traits that are the incidental by-products of artificial selection for increased tolerance towards humans. One hypothesis is that some species like humans and bonobos "self domesticated", that they have been under selection for that same suite of domesticated phenotypes. However, the evidence for this has been largely circumstantial. Here, we provide evidence that in marmoset monkeys, the size of a domestication phenotype—a white facial fur patch—is linked to their degree of affiliative vocal responses. During development, the amount of parental vocal feedback experienced by influences the rate of growth of this facial white patch and this suggests a mechanistic link between the two phenotypes, possibly neural crest cells. Our study provides evidence for links between vocal behavior and the development of morphological phenotypes associated with domestication in a nonhuman primate.</p>
Video data of spontaneous responses of common marmosets (Callithrix jacchus) on 3D and 2D cricket stimuli.
<p>The degree to which nonhuman animals recognize 2D images as representing the corresponding real objects remains debated. The common marmoset monkey (<em>Callithrix jacchus</em>) is often cited as a species which spontaneously shows natural behaviors to 2D images, e.g. grabbing behaviors to insects and fear responses to snakes. In this study, ten marmosets from two different groups were tested with a live cricket, a 3D plastic model, a monochrome image and two video recordings of the cricket.<br> The monkeys showed the grabbing behavior to the real cricket and the 3D plastic model, but to none of the 2D images. Our experiment suggests that depth information is the most important factor eliciting predatory behavior from the marmosets. In behavioral experiments, monkeys' responses toward 2D images of real objects should be carefully interpreted.</p> <p>All session videos are uploaded here with a 'LOG.txt' file which has sessions & timestamps when coded behaviors occurs.</p>
Data and Codes: Marmosets mutually compensate for differences in rhythms when coordinating vigilance
<p>Data and codes accompanying the article titled "Marmosets mutually compensate for differences in rhythms when coordinating vigilance".</p>
High plasticity in marmoset monkey vocal development from infancy to adulthood
<p>The vocal behavior of human infants undergoes dramatic changes across their first year, while becoming increasingly speech-like. Surprisingly, vocal development in nonhuman primates has been assumed to be largely predetermined and completed within the first postnatal months. Contradicting this assumption, we found a dichotomy between the development of call features and vocal sequences in marmoset monkeys suggestive of a role for experience. While changes in call features were related to physical maturation, sequences of and transitions between calls remained flexible until adulthood. As in humans, marmoset vocal behavior developed in stages correlated with motor and social development stages. These findings are evidence for a prolonged phase of plasticity during marmoset vocal development, a crucial primate evolutionary preadaptation for the emergence of vocal learning and speech.</p>
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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.