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Figure 1 from: Segovia JMG, Neco LC, Willemart RH (2018) On the habitat use of the Neotropical whip spider Charinus asturius (Arachnida: Amblypygi). Zoologia 35: 1-6. https://doi.org/10.3897/zoologia.35.e12874
Figure 1 Number of rocks observed without (white bars) and with (black bars) individuals of Charinus asturius per classes of sizes regarding the area (cm) close to the substrate. For the sake of clarity the size classes were divided 150cm2 ranges, except for the class (above 450cm2) in which the median was 670.4 cm2 and the values range from (459.2-2882.5 cm2).
Fig. 3 in Distribution, habitat use and plant associations of Moluchia brevipennis (Saussure, 1864) (Blattodea: Ectobiidae): an endemic cockroach from Chilean Mediterranean Matorral biome
Fig. 3. (A) Diagram of male M. brevipennis without left forewing, dorsal view. Abbreviations: PrN, Pronotum; MsN, Mesonotum; MtN, Metanotum; HW, Hind Wing; FW, Fore Wing; TeS, Tergal specialization; PtP, Proximal tergal pubescence; T2–T9, Tergites; SaP, Supra-anal plate; Cr, Cercus; SgP, Subgenital plate; St, Style. (B) Nymphs photographs; Blatta orientalis (left side) and Moluchia brevipennis (right side), scale bar correspond 1 cm. (C) Schematic drawing of nymphs tenth tergite left side drawing correspond to B. orientalis meanwhile right side to M. brevipennis.
Fig. 4 in Distribution, habitat use and plant associations of Moluchia brevipennis (Saussure, 1864) (Blattodea: Ectobiidae): an endemic cockroach from Chilean Mediterranean Matorral biome
Fig. 4. Maximum likelihood genera phylogenetic reconstruction within Blattodea family, excluding Termitidae, based on the mitochondrial gene cytochrome oxidase I (COI). Numbers indicate branch support based on 1000 bootstrap replicates.
Figure 1 in Diet and habitat use of the endangered Persian leopard (Panthera pardus saxicolor) in northeastern Iran*
Figure 1. Elevation profile of SNP, marking 4 distinct habitat types: plains; small undulating hills and rough terrain; mountainous areas; and high rocky, precipitous mountains.
Figure 2 in Diet and habitat use of the endangered Persian leopard (Panthera pardus saxicolor) in northeastern Iran*
Figure 2. Preferred habitat of the Persian leopard (mountainous areas and small undulating hills and rough terrain) in SNP.
Table ²: Comparison of the results of analysis of variance on the shape of scapulae (occlusal view) and pelvis (side view) in Rhipidomys mastacalis from three vegetation classes in Brazil. Correspondence asymmetry was the only method used for asymmetry analysis. in Morphological symmetry of Rhipidomys mastacalis (Mammalia, Rodentia, Cricetidae) in fragmented habitats of the Atlantic Forest in Northeastern Brazil: a study on the influence of the environment on an endemic species
<p><b>Table ²:</b> Comparison of the results of analysis of variance on the shape of scapulae (occlusal view) and pelvis (side view) in <i>Rhipidomys mastacalis</i> from three vegetation classes in Brazil. Correspondence asymmetry was the only method used for asymmetry analysis.</p><table><tbody><tr><th><b>Shape procrustes ANOVA</b></th></tr></tbody><tbody><tr><th><b>Effect Sum of squares</b></th><td><b>Mean squares</b></td><td><b>Degrees of freedom</b></td><td><i>F statistic</i></td><td><i>p -Value</i></td><td><b>Pillai tr.</b></td><td><i>p -Value</i></td></tr><tr><th><b>Scapulae</b></th></tr><tr><th><b>Forested vegetation</b></th></tr><tr><th>Individual</th><td>0.0941373400</td><td>0.0010459705</td><td>90</td><td>3</td><td><0.0001</td><td>–</td><td>–</td></tr><tr><th>Side</th><td>0.0100439600</td><td>0.0010043960</td><td>2.88</td><td>0.0037</td><td>0.0003</td><td>–</td><td>–</td></tr><tr><th>Individual × side</th><td>0.0314069500</td><td>0.0003489662</td><td>90</td><td>5.89</td><td><0.0001</td><td>4.91</td><td><0.0001</td></tr><tr><th>Error 1</th><td>0.0118544100</td><td>0.0000592721</td><td>200</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><th><b>Occupancy mosaics in forested areas</b></th></tr><tr><th>Individual</th><td>0.2064168200</td><td>0.0010320841</td><td>200</td><td>4.82</td><td><0.0001</td><td>7.15</td><td><0.0001</td></tr><tr><th>Side</th><td>0.0262808000</td><td>0.0026280796</td><td>10</td><td>12.28</td><td><0.0001</td><td>0.86</td><td>0.0022</td></tr><tr><th>Individual × side</th><td>0.0428160400</td><td>0.0002140802</td><td>200</td><td>2.68</td><td><0.0001</td><td>4.98</td><td><0.0001</td></tr><tr><th>Error 1</th><td>0.0335675700</td><td>0.0000799228</td><td>420</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><th><b>Cocoa plantations</b></th></tr><tr><th>Individual</th><td>0.2508635400</td><td>0.0009291242</td><td>270</td><td>4.07</td><td><0.0001</td><td>7.11</td><td><0.0001</td></tr><tr><th>Side</th><td>0.0256608100</td><td>0.0025660812</td><td>10</td><td>11.24</td><td><0.0001</td><td>0.87</td><td><0.0001</td></tr><tr><th>Individual × side</th><td>0.0616394000</td><td>0.0002282941</td><td>270</td><td>3.10</td><td><0.0001</td><td>5.72</td><td><0.0001</td></tr><tr><th>Error 1</th><td>0.0412323300</td><td>0.0000736292</td><td>560</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><th><b>Pelvis</b></th></tr><tr><th><b>Forested vegetation</b></th></tr><tr><th>Individual</th><td>0.0543411200</td><td>0.0004312787</td><td>126</td><td>4.63</td><td><0.0001</td><td></td><td></td></tr><tr><th>Side</th><td>0.0043155600</td><td>0.0003082544</td><td>14</td><td>3.31</td><td>0.0002</td><td></td><td></td></tr><tr><th>Individual × side</th><td>0.0117297800</td><td>0.0000930935</td><td>126</td><td>2.31</td><td><0.0001</td><td>6.07</td><td><0.0001</td></tr><tr><th>Error 1</th><td>0.0112943700</td><td>0.000040337</td><td>280</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><th><b>Occupancy mosaics in forested areas</b></th></tr><tr><th>Individual</th><td>0.1059661700</td><td>0.0003440460</td><td>308</td><td>4.42</td><td><0.0001</td><td>9.69</td><td><0.0001</td></tr><tr><th>Side</th><td>0.0049395300</td><td>0.0003528236</td><td>14</td><td>4.53</td><td><0.0001</td><td>0.85</td><td>0.0311</td></tr><tr><th>Individual × side</th><td>0.0239852500</td><td>0.0000778742</td><td>308</td><td>2.00</td><td><0.0001</td><td>6.64</td><td><0.0001</td></tr><tr><th>Error 1</th><td>0.0251368400</td><td>0.0000390324</td><td>644</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><th><b>Cocoa plantations</b></th></tr><tr><th>Individual</th><td>0.1292837500</td><td>0.0003420205</td><td>378</td><td>5.68</td><td><0.0001</td><td>10.51</td><td><0.0001</td></tr><tr><th>Side</th><td>0.0043550500</td><td>0.0003110747</td><td>14</td><td>5.17</td><td><0.0001</td><td>0.84</td><td>0.0016</td></tr><tr><th>Individual × side</th><td>0.0227608400</td><td>0.0000602139</td><td>378</td><td>2.24</td><td><0.0001</td><td>6.17</td><td><0.0001</td></tr><tr><th>Error 1</th><td>0.0210413800</td><td>0.0000268385</td><td>714</td><td>–</td><td>–</td><td>–</td><td>–</td></tr></tbody></table>
Table 1 in An updated distribution of the Andean swamp rat Neotomys ebriosus along the Peruvian Andes with notes on habitat use and taxonomy
<p><b>Table 1:</b> <i>Neotomys ebriosus</i> collection localities in Peru.</p><table><tbody><tr><th></th><th>Museum</th><th>Voucher #</th><th>Sex</th><th>Region</th><th>Elev</th><th>D Lat</th><th>D Long</th><th>Collection date</th></tr></tbody><tbody><tr><th><b>1</b></th><td>MUSM</td><td>23226</td><td>M</td><td>Ancash</td><td>4410</td><td>−8.1973°</td><td>−77.7866°</td><td>29 August 2004</td></tr><tr><th><b>2</b></th><td>MUSM</td><td>40068 −069</td><td>F M</td><td>Ancash</td><td>4240</td><td>−8.2595°</td><td>−77.7467°</td><td>06 May 2012</td></tr><tr><th><b>3</b></th><td>MUSM</td><td>45264</td><td>–</td><td>Ancash</td><td>4105</td><td>−9.4807°</td><td>−77.5972°</td><td>10 August 2012</td></tr><tr><th><b>4</b></th><td>MVZ</td><td>150167</td><td>−</td><td>Ancash</td><td>4230</td><td>−9.5433°</td><td>−77.6236°</td><td>07 August 1968</td></tr><tr><th><b>40</b></th><td>CORBIDI</td><td>466</td><td>M</td><td>Cusco</td><td>4110</td><td>−14.5068°</td><td>−71.7833°</td><td>11 August 2012</td></tr><tr><th><b>41</b></th><td>KUM</td><td>135132−135134</td><td>2F M</td><td>Cusco</td><td>4280</td><td>−14.478°</td><td>−71.007°</td><td>04 February 1975</td></tr><tr><th><b>42</b></th><td>MUSA</td><td>14014−14017</td><td>3M −</td><td>Arequipa</td><td>3770</td><td>−15.2802°</td><td>−72.3385°</td><td>24−26 September 2012</td></tr><tr><th><b>43</b></th><td>MUSA</td><td>18251, 18258</td><td>F M</td><td>Arequipa</td><td>3770</td><td>−15.2809°</td><td>−72.341°</td><td>03 February 2013</td></tr><tr><th><b>44</b></th><td>MUSA</td><td>17793, 17794</td><td>F M</td><td>Puno</td><td>4550</td><td>−14.2315°</td><td>−70.3115°</td><td>4−5 March 2014</td></tr><tr><th><b>45</b></th><td>MVZ</td><td>139591</td><td>F</td><td>Puno</td><td>3630</td><td>−14.1611°</td><td>−69.6946°</td><td>13 J uly 1970</td></tr><tr><th><b>46</b></th><td>MVZ</td><td>116196, 116197</td><td>2F</td><td>Puno</td><td>3500</td><td>−14.1622°</td><td>−69.6917°</td><td>10 August & 23 October 1951</td></tr><tr><th><b>47</b></th><td>MVZ</td><td>116198, 116199</td><td>F M</td><td>Puno</td><td>4110</td><td>−14.211°</td><td>−69.7303°</td><td>31 J uly and 01 August 1951</td></tr><tr><th><b>48</b></th><td>MVZ</td><td>114751−756; 116200−202</td><td>2F 7M</td><td>Puno</td><td>4350</td><td>−14.2546°</td><td>−69.7381°</td><td>08 J une−12 September 1951</td></tr><tr><th><b>49</b></th><td>MVZ</td><td>139590</td><td>M</td><td>Puno</td><td>4710</td><td>−14.2832°</td><td>−69.7694°</td><td>15 J uly 1970</td></tr><tr><th><b>50</b></th><td>MUSA</td><td>4184</td><td>F</td><td>Arequipa</td><td>4400</td><td>−15.822°</td><td>−71.4939°</td><td>26 February 2003</td></tr><tr><th><b>51</b></th><td>MVZ</td><td>174043</td><td>F</td><td>Arequipa</td><td>4250</td><td>−15.9825°</td><td>−71.3845°</td><td>08 J uly 1987</td></tr><tr><th><b>52</b></th><td>MUSA</td><td>1149</td><td>M</td><td>Arequipa</td><td>4580</td><td>−16.231°</td><td>−71.4896°</td><td>20 J anuary 2000</td></tr><tr><th><b>53</b></th><td>MUSA</td><td>7114</td><td>F</td><td>Arequipa</td><td>4200</td><td>−16.1827°</td><td>−71.0625°</td><td>07 March 2009</td></tr><tr><th><b>54</b></th><td>MVZ</td><td>115942−946</td><td>5M</td><td>Puno</td><td>4260</td><td>−15.8432°</td><td>−70.7997°</td><td>25 February−13 March 1952</td></tr><tr><th><b>55</b></th><td>MVZ</td><td>115947</td><td>M</td><td>Puno</td><td>3965</td><td>−15.8042°</td><td>−70.368°</td><td>19 February 1952</td></tr><tr><th><b>56</b></th><td>FMNH</td><td>49708</td><td>M</td><td>Puno</td><td>3910</td><td>−15.9561°</td><td>−69.99°</td><td>13 September 1939</td></tr><tr><th><b>57</b></th><td>MCZ</td><td>42865; 42868</td><td>M −</td><td>Puno</td><td>3960</td><td>−16.0667°</td><td>−69.5167°</td><td>15 and 21 J uly 1946</td></tr><tr><th><b>58</b></th><td>FMNH</td><td>51261−263</td><td>3F</td><td>Puno</td><td>3860</td><td>−16.3221°</td><td>−69.0399°</td><td>02 May 1940</td></tr><tr><th><b>59</b></th><td>FMNH</td><td>107842</td><td>M</td><td>Puno</td><td>3900</td><td>−16.4135°</td><td>−69.6628°</td><td>29 April 1976</td></tr><tr><th><b>60</b></th><td>MVZ</td><td>114747−750</td><td>2F 2M</td><td>Puno</td><td>3930</td><td>−16.431°</td><td>−69.665°</td><td>16 April 1951</td></tr><tr><th><b>61</b></th><td>MVZ</td><td>141616</td><td>M</td><td>Puno</td><td>3935</td><td>−16.4978°</td><td>−69.6471°</td><td>01 November 1971</td></tr><tr><th><b>62</b></th><td>MCZ</td><td>42866−867</td><td>F M</td><td>Puno</td><td>4760</td><td>−16.6191°</td><td>−70.0457°</td><td>13 August 1946</td></tr><tr><th><b>63</b></th><td>MUSM</td><td>49028</td><td>M</td><td>Moquegua</td><td>4500</td><td>−16.7393°</td><td>−70.3737°</td><td>08 October 2018</td></tr><tr><th><b>64</b></th><td>MCZ</td><td>42869</td><td>M</td><td>Puno</td><td>4180</td><td>−16.7632°</td><td>−69.8695°</td><td>28 J uly 1946</td></tr></tbody></table><p><b>Table 1:</b> (continued)</p><p>Color codes as shown in the distribution map. –, sex undetermined; †, 26 numbers inside the series; ††, 4 numbers inside the series; *, remains not deposited in museums until now. Museum acronyms: AMNH, American Museum of Natural History, New York; CORBIDI, Colección de Vertebrados del Centro de Ornitología y Biodiversidad, Lima; FMNH, Field Museum of Natural History, Chicago, Illinois; KUM, Kansas University Natural History Museum, Kansas; MCZ, Museum of Comparative Zoology, Harvard University, Massachusetts; MNHN, <b>Mus´eum National</b> d’ Histoire Naturelle, Paris, France; MUSA, Museo de Historia Natural,Universidad Nacional San Agustín,Arequipa;MUSM,Museo de Historia Natural,Universidad Nacional Mayor San Marcos,Lima; MVZ, Museum of Vertebrate Zoology, University of California; UMMZ, University of Michigan Museum of Zoology, Michigan.</p>
Data from: Identification of habitat-specific biomes of aquatic fungal communities using a comprehensive nearly full-length 18S rRNA dataset enriched with contextual data
Molecular diversity surveys have demonstrated that aquatic fungi are highly diverse, and that they play fundamental ecological roles in aquatic systems. Unfortunately, comparative studies of aquatic fungal communities are few and far between, due to the scarcity of adequate datasets. We combined all publicly available fungal 18S ribosomal RNA (rRNA) gene sequences with new sequence data from a marine fungi culture collection. We further enriched this dataset by adding validated contextual data. Specifically, we included data on the habitat type of the samples assigning fungal taxa to ten different habitat categories. This dataset has been created with the intention to serve as a valuable reference dataset for aquatic fungi including a phylogenetic reference tree. The combined data enabled us to infer fungal community patterns in aquatic systems. Pairwise habitat comparisons showed significant phylogenetic differences, indicating that habitat strongly affects fungal community structure. Fungal taxonomic composition differed considerably even on phylum and class level. Freshwater fungal assemblage was most different from all other habitat types and was dominated by basal fungal lineages. For most communities, phylogenetic signals indicated clustering of sequences suggesting that environmental factors were the main drivers of fungal community structure, rather than species competition. Thus, the diversification process of aquatic fungi must be highly clade specific in some cases.The combined data enabled us to infer fungal community patterns in aquatic systems. Pairwise habitat comparisons showed significant phylogenetic differences, indicating that habitat strongly affects fungal community structure. Fungal taxonomic composition differed considerably even on phylum and class level. Freshwater fungal assemblage was most different from all other habitat types and was dominated by basal fungal lineages. For most communities, phylogenetic signals indicated clustering of sequences suggesting that environmental factors were the main drivers of fungal community structure, rather than species competition. Thus, the diversification process of aquatic fungi must be highly clade specific in some cases.
Figure 3 in Activity patterns and habitat use of pudu deer (Pudu puda) in a mountain forest of south-central Chile
Figure 3. Picture of a pudu deer, obtained through camera trapping in Caramávida.
Figure 1 in Home range and habitat use by the roadside hawk, Rupornis magnirostris (Gmelin, 1788) (Aves: Falcaniformes) in southeastern Brazil
Figure 1. Area observation curves of five roadside hawks in southeastern Brazil.
Fig. 3 in Activity pattern and resource use of two Callosciurus species in different habitats in northeastern Thailand
Fig. 3. Proportion of observed behaviours of (a) Callosciurus finlaysonii and (b) C. caniceps throughout the day.
Fig. 5 in Habitat use and site fidelity of Irrawaddy dolphins (Orcaella brevirostris) in the coastal waters of Bago-Pulupandan, Negros Occidental, Philippines
Fig. 5. Non-metric Multidimensional Scaling of activity index in relation to geographic location. Straight lines indicate the degree of influence of each behaviour based on the distribution of clustered eigenvalues.
Fig. 1. Cicindelidia floridana, paratype. A in Determining Type Locality Habitat and Historic Land Use at Current Sites of the Miami Tiger Beetle, Cicindelidia floridana (Cartwright) (Coleoptera: Carabidae: Cicindelinae)
Fig. 1. Cicindelidia floridana, paratype. A) Dorsal habitus, B) Locality label.
Fig. 1 in Comparative feeding ecology and habitats use of Crenicichla species (Perciformes: Cichlidae) in a Venezuelan floodplain river
Fig. 1. Specimens of (a) Crenicichla lugubris (217 mm SL) and (b) C. aff. wallacii (51 mm SL) from the Cinaruco River, Venezuela.
Clinging performance on natural substrates predicts habitat use in anoles and geckos
<p>1. For arboreal lizards, the ability to cling or adhere to the substrate is critical for locomotion during prey capture, predator escape, thermoregulation, and social interactions. Thus, selection on traits related to clinging is likely strong. </p> <p>2. Correlations between morphology, performance, and habitat use have been documented in arboreal lizards, providing a framework for using functional traits to predict habitat use in the field.</p> <p>3. We tested the hypothesis that clinging performance predicts habitat use in an actively assembling community of introduced lizards in Hawaiʻi comprised of anoles (<i>Anolis carolinensis, A. sagrei</i>) and day geckos (<i>Phelsuma laticauda</i>).</p> <p>4. We measured morphological traits (toepad area and lamellae number) and tested clinging performance on two artificial and eight natural substrates in the lab. We measured habitat use in 10 m x 10 m outdoor enclosures where habitat availability was controlled and the lizard species assemblage was manipulated to reflect all species combinations. The enclosure experiment generated more than 9,000 habitat use observations from 360 lizards.</p> <p>5. Morphological traits that predict performance in <i>Anolis </i>were not predictive in <i>Phelsuma</i>, indicating that direct measures of performance are necessary for comparisons between the genera.</p> <p>6. Measuring clinging performance on multiple substrates provided key insights into patterns of habitat use. While all three species performed best on an artificial smooth substrate (acrylic), performance on natural substrates predicted which texture (rough vs. smooth) was most often used by each species. </p> <p>7. Performance predicted perch height use: species with the greatest clinging performance (<i>A. carolinensis </i>and <i>P. laticauda</i>) across substrates perched twice as high as <i>A. sagrei</i>.</p> <p>8. We did not observe habitat shifts in the height or texture of perches used by any species in response to experimental manipulation of the lizard species assemblage.</p> <p>9. Our results highlight the inextricable link between ecology, morphology, and performance, the importance of measuring functional traits in ecologically-relevant ways, and the potential for resource partitioning to be influenced by differences in the ability to attach to different substrates. </p>
Figure 6 from: Hawlitschek O, Brückmann B, Berger J, Green K, Glaw F (2011) Integrating field surveys and remote sensing data to study distribution, habitat use and conservation status of the herpetofauna of the Comoro Islands. ZooKeys 144: 21-79. https://doi.org/10.3897/zookeys.144.1648
Figure 6 - Species photographs. A Lycodryas sanctijohannis, male, ZSM 38/2010, Anjouan B Lycodryas sanctijohannis, female, ZSM 40/2010, Anjouan C Furcifer cephalolepis, male, Grand Comoro D Furcifer polleni, male, Anjouan E Furcifer cephalolepis, female, Grand Comoro F Furcifer polleni, female, Mayotte G Trachylepis comorensis, Mohéli H Trachylepis striata, ZSM 70/2010, Anjouan.
Figure 3 from: Hawlitschek O, Brückmann B, Berger J, Green K, Glaw F (2011) Integrating field surveys and remote sensing data to study distribution, habitat use and conservation status of the herpetofauna of the Comoro Islands. ZooKeys 144: 21-79. https://doi.org/10.3897/zookeys.144.1648
Figure 3 - Forest areas on the Comoros. For each level of altitude (in intervals of 100 m), the area occupied by forest is given as percentage of the total area occupied by all habitat classes in this level.
Figure 19 from: Hawlitschek O, Brückmann B, Berger J, Green K, Glaw F (2011) Integrating field surveys and remote sensing data to study distribution, habitat use and conservation status of the herpetofauna of the Comoro Islands. ZooKeys 144: 21-79. https://doi.org/10.3897/zookeys.144.1648
Figure 19 - Distribution maps, and distribution over habitat and altitude classes, for Trachylepis striata, Typhlops comorensis and Typhlops sp.
Figure 8 from: Hawlitschek O, Brückmann B, Berger J, Green K, Glaw F (2011) Integrating field surveys and remote sensing data to study distribution, habitat use and conservation status of the herpetofauna of the Comoro Islands. ZooKeys 144: 21-79. https://doi.org/10.3897/zookeys.144.1648
Figure 8 - Species photographs. A. Phelsuma nigristriata, Mayotte B Phelsuma comorensis, Grand Comoro C Phelsuma pasteuri, Mayotte D Phelsuma v-nigra anjouanensis, Anjouan E Phelsuma v-nigra comoraegrandensis, Grand Comoro F Phelsuma v-nigra v-nigra, Mohéli G Ebenavia inunguis, ZSM 68/2010, Anjouan H Paroedura sanctijohannis, ZSM 98/2010, Mayotte.
Figure 16 from: Hawlitschek O, Brückmann B, Berger J, Green K, Glaw F (2011) Integrating field surveys and remote sensing data to study distribution, habitat use and conservation status of the herpetofauna of the Comoro Islands. ZooKeys 144: 21-79. https://doi.org/10.3897/zookeys.144.1648
Figure 16 - Distribution maps, and distribution over habitat and altitude classes, for Phelsuma comorensis, Phelsuma dubia and Phelsuma laticauda.
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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.