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FIGURE 3 in Taxonomic re-assessment of the Australian and New Guinean green-eyed treefrogs Litoria eucnemis, L. genimaculata and L. serrata (Anura: Hylidae)
FIGURE 3. Bayesian majority rule consensus tree of 12S rRNA nucleotide sequences from 77 pelodryadid hylid frogs from Australia and New Guinea. Numbers at nodes indicate Bayesian posterior probabilities and maximum likelihood non-parametric bootstrap proportions.
FIGURE 1 in Taxonomic re-assessment of the Australian and New Guinean green-eyed treefrogs Litoria eucnemis, L. genimaculata and L. serrata (Anura: Hylidae)
FIGURE 1. Map showing locations of samples used for the molecular genetic analyses (numbered sites) and morphological comparisons (lower case letters). Site labels are listed in Appendix I and also referred to in Figure 2.
FIGURE 2 in Taxonomic re-assessment of the Australian and New Guinean green-eyed treefrogs Litoria eucnemis, L. genimaculata and L. serrata (Anura: Hylidae)
FIGURE 2. Neighbour-joining phylogram based on Cavalli-Sforza chord allozyme allele frequency distances between OTUs. OTU numbers are listed in Table 1 and Appendix I.
Figure 3. A in Phylogenetic relationships and biogeographic range evolution in cat-eyed snakes, Boiga (Serpentes: Colubridae)
Figure 3. A, BioGeoBEARS geographic range evolution of Boiga under the highest supported model scheme (biogeographic model = DIVALIKE+J, dispersal direction = unconstrained and dispersal rates = faunal similarity). Pie charts at internal nodes indicate the posterior estimate of ancestral geographic distributions and rectangles at tips indicate modern geographic distributions. B, model scheme AIC score (red bar) and corresponding null distribution of AIC scores (grey bars) for each of the five model schemes with biogeographic model = DIVALIKE+J (dispersal rate multipliers either: all equal, random or proportional to faunal similarity; dispersal direction either: constrained or unconstrained). Null AIC distributions and P-values are from permutation tests of dispersal rate multipliers; P <0.05 indicates significantly better model fit under the alternative model scheme compared to permutation set of model schemes; see Supporting Information, Figures S1–5 for results under the other biogeographic models.
Figure 2 in Phylogenetic relationships and biogeographic range evolution in cat-eyed snakes, Boiga (Serpentes: Colubridae)
Figure 2. Bayesian inference (BI) time-tree of Boiga. Horizontal bars centred at internal nodes indicate 95% highest posterior density for clade age. Circles indicate posterior probability (PP) and ultrafast bootstrap support (UFBoot) for clades that were not highly supported by BI and/or ML analyses (PP <0.95 and/or UFBoot <95); nodes without circles indicate clades that were highly supported in both BI and ML analyses (PP ≥ 0.95 and UFBoot ≥ 95). Photos: Ishan Agarwal (Boiga beddomei, B. trigonata and B. ochracea), Kin Onn Chan (Boiga melanota, B. drapiezii, B. cynodon and B. cyanea) and Perry L. Wood, Jr (Boiga multomaculata).
Predicting readers' prototypical eye-movement behavior using MASC, a model of Attention in the Superior Colliculus: Stimulus materials, model code, data, and statistical analyses.
<p>The goal of the present research was to determine the role of rudimentary visuo-motor pathways, from the retina and the primary visual cortex to the superior colliculus (SC), in the guidance of human eye movement during reading. To this end, we used MASC, our model of Attention in the Superior Colliculus (Adeli et al., Journal of Neuroscience 2017), a model that relies on well-established saccade-programming principles in the SC. MASC predicts sequences of fixations over an input image by spatially integrating incoming signals in the space of the SC.</p> <p>Here, MASC computed the distribution of luminance contrast over sentences' images (visual-saliency map), after blurring it proportional to retinal eccentricity (retina transformation). It then projected the visual-saliency map into SC space, using a logarithmic afferent-mapping function (magnification factor). Input signals were averaged over retinotopically organized populations of neurons (point images) of constant size, first in the visual map and then in a spatially-registered motor map. The most active population was identified through a winner-take-all process. After jitter applied to the winning population, the next fixation location was determined using inverse efferent mapping. This sequence of events was then repeated to predict following fixation locations, but inserting after each saccade an inhibitory spatial tag (Inhibition of Saccade Return; ISR -referred to as IOR in the uploaded files). All MASC's parameters, but one, were biologically determined, using electrophysiological data in macaque; the ISR window was the one fit parameter.</p> <p>MASC was tested by comparing its predicted sequences of fixations over sentences from the French-Sentence Corpus (FSC) to the eye-movement behavior of 40 French-native speakers reading the same sentences for comprehension (Albrengues et al., Plos One 2019). Then, MASC was dissected to determine the crucial processing steps enabling prediction of human behavior (10 comparison models -see the general README file). Finally, to address crucial issues in the reading literature, i.e., the role of inter-word spacing and character print size in eye-movement guidance, MASC was additionally tested in four additional display conditions: the same sentences from the FSC, but with blank spaces between words being either filled or removed, or with the screen width angle being multiplied by 2 or 4, such that characters were larger in angular size (0.5° and 1°) than in the original experiment (0.25°). MASC's predicted effects of inter-word spacing and print size were compared to previously published data.</p> <p>All material relevant to the project is reported here, including the FSC materials (bitmap and information text files), the Matlab code for our MASC model, raw simulation data for MASC and all our comparison models, as well as MASC's simulations in the different display conditions, the scripts we developed in R to transform raw simulation data into data matrices for statistical analyses of (word-based) eye-movement behavior, the resulting data matrices for all models as well as the data matrix for FSC readers, the R-scripts for statistical comparison of oculomotor behavior between data sets and conditions, literature-review tables of previously published data (for comparison with MASC's predictions), and the R-scripts generating the figures summarizing our results.</p> <p>Further information can be found in the general README file as well as in the README files attached to each folder. The authors' respective contributions to the project, the licence attached to the included materials and their condition of use are listed in the general README file.</p> <p>A manuscript reporting and discussing these modeling data is in preparation (Vitu, F., Adeli, H. & Zelinsky, G. J.); A reference will be provided here when the manuscript appears in a journal.</p> <p>Other references to be cited:</p> <p>- For the model code: Adeli, H., Vitu, F., & Zelinsky, G. J. (2017). A model of the superior colliculus predicts fixation locations during scene viewing and visual search. Journal of Neuroscience, 37(6), 1453-1467. http://www.jneurosci.org/content/37/6/1453</p> <p>- For FSC materials and data: Albrengues, C., Lavigne, F., Aguilar, C., Castet, E., & Vitu, F. (2019). Linguistic processes do not beat visuo-motor constraints, but they modulate where the eyes move regardless of word boundaries: Evidence against top-down word-based eye-movement control during reading. PLoS ONE 14(7): e0219666. https://doi.org/10.1371/journal.pone.0219666<br> </p>
Fig. 1 in Further Evidence for Pre-metamorphosis Larval Eye Reduction in the Holometabola (Insecta: Mecoptera: Panorpa vulgaris Imhoff & Labram, 1836).
Fig. 1: SEM side view of a 3rd instar larvae head and eye, notice the well defined rows of ommatidia. Figure annotations: 1: eye; 2: antenna; 3: mandible.
Fig. 2 in Further Evidence for Pre-metamorphosis Larval Eye Reduction in the Holometabola (Insecta: Mecoptera: Panorpa vulgaris Imhoff & Labram, 1836).
Fig. 2: A–D: A: eye segment of a transversal section through the first puppal stage head of Panorpa vulgaris, upper half of the picture dorsal, lower half ventral; B: TEM overview of the area of the pigment spot from the same specimen; C: detailed TEM picture of a degrading rhabdomer; D: detailed TEM picture of a developing rhabdomer.
Fig. 3 in Further Evidence for Pre-metamorphosis Larval Eye Reduction in the Holometabola (Insecta: Mecoptera: Panorpa vulgaris Imhoff & Labram, 1836).
Fig. 3: Means of all four instars shown as Boxplots, significances are denoted as following * significant (a<0,05), ** highly significant (a<0,01).
Figure 10 in New genera records of split-eyed owlflies (Neuroptera: Myrmeleontidae: Ascalaphinae) from Colombia
Figure 10. Collecting records of Ameropterus, Cordulecerus, and Fillus from Colombia.
Distinct type II opsins in the eye decode light properties for background adaptation and behavioural background preference
<p>Crypsis increases survival by reducing predator detection. <i>Xenopus laevis</i> tadpoles decode light properties from the substrate to induce two responses: A cryptic coloration response where dorsal skin pigmentation is adjusted to the colour of the substrate (background adaptation) and a behavioural crypsis where organisms move to align with a specific colour surface (background preference). Both processes require organisms to detect reflected light from the substrate. We explored the relationship between background adaptation and preference and the light properties able to trigger both responses. We also analysed which retinal photosensor (type II opsin) is involved. Our results showed that these two processes are segregated mechanistically, as there is no correlation between the preference for a specific background with the level of skin pigmentation, and different dorsal retina-localized type II opsins appear to underlie the two crypsis modes. Indeed, inhibition of melanopsin affects background adaptation but not background preference. Instead, we propose pinopsin is the photosensor involved in background preference. <i>pinopsin</i> mRNA is co-expressed with mRNA for the <i>sws1</i> cone photopigment in dorsally-located photoreceptors. Importantly, the developmental onset of pinopsin expression aligns with the emergence of the preference for a white background, but after the background adaptation phenotype appears. Furthermore, white background preference of tadpoles is associated with increased <i>pinopsin</i> expression, a feature that is lost in pre-metamorphic froglets along with a preference for a white background. Thus, our data show a mechanistic dissociation between background adaptation and background preference, and we suggest melanopsin and pinopsin, respectively, initiate the two responses.</p>
Multiple sequence alignments and phylogenetic trees from: Co-option of the limb patterning program in cephalopod eye development
<p>Background</p> <p><span>Across the Metazoa, similar genetic programs are found in the development of analogous, independently evolved, morphological features. The functional significance of this reuse and the underlying mechanisms of co-option remain unclear. Cephalopods have evolved a highly acute visual system with a cup shaped retina and a novel refractive lens in the anterior, important for a number of sophisticated behaviors including predation, mating and camouflage. Almost nothing is known about the molecular-genetics of lens development in the cephalopod.</span></p> <p><span>Results</span></p> <p><span>Here we identify the co-option of the canonical bilaterian limb pattering program during cephalopod lens development, a functionally unrelated structure. We show radial expression of transcription factors <i>SP6-9/sp1, Dlx/dll, </i><i>Pbx/exd, Meis/hth, </i>and a <i>Prdl</i> homolog in the squid <i>Doryteuthis pealeii</i>, similar to expression required in <i>Drosophila</i> limb development.<i> </i>We assess the role of Wnt signaling in the cephalopod lens, a positive regulator in the developing <i>Drosophila </i>limb, and find the regulatory relationship reversed, with ectopic Wnt signaling leading to lens loss. </span></p> <p><span>Conclusion</span></p> <p><span>This regulatory divergence suggests that duplication of SP6-9 in cephalopods may mediate the co-option of the limb patterning program. Thus our study suggests that the limb network could perform a more universal developmental function in radial pattering and highlights how canonical genetic programs are repurposed in novel structures.</span></p>
Data to accompany: Rapid body color change provides lizards with facultative crypsis in the eyes of their avian predators
<p>Color change serves many antipredator functions and may allow animals to better match environments or disrupt outlines to prevent detection. Rapid color change could potentially provide camouflage to animals that frequently move among microhabitats. Determining the adaptiveness of whole-animal rapid color changes in natural habitats with respect to predator visual systems would greatly broaden our fundamental understanding of the evolution of rapid color change. We tested whether whole-body color change provides water anoles (<i>Anolis aquaticus</i>) with camouflage against avian predators, and whether these rapid changes allow them to shift between environment matching and edge disruption. We manipulated <i>A. aquaticus</i> placement in natural microhabitats and used digital image analysis to quantify color matching, pattern matching, and edge disruption produced by microhabitat-induced color change. Color change reduced lizard detectability to predators in microhabitat-specific ways. Environment matching was favored when lizards were in solid-colored microhabitats, regardless of exposure to predators. Edge disruption was instead induced by high exposure and varied by body region. We provide the first evidence that rapid color change permits a tetrapod to flexibly employ the most optimal camouflaging strategy by form (e.g., color matching vs. edge disruption) to minimize detection in the eyes of its predators.</p>
FIGURES 23–29. Sinella gei n in Contribution to study of eyed species of Sinella (Collembola: Entomobryidae), with a key to this group of species from China
FIGURES 23–29. Sinella gei n. sp.: 23–25, abdominal chaetotaxy: 23, Abd. I–III; 24, Abd. IV; 25, Abd. V; 26–27, ventral tube: 26, anterior face; 27, posterior face and lateral flap; 28, manubrial plaque; 29, mucro.
FIGURES 1–9. Sinella sunae n in Contribution to study of eyed species of Sinella (Collembola: Entomobryidae), with a key to this group of species from China
FIGURES 1–9. Sinella sunae n. sp.: Ant. III organ; 2, labrum; 3, lateral process of labial palp; 4, maxillary outer lobe; 5, setae on ventral side of the head; 6, dorsal cephalic chaetotaxy; 7, thoracic chaetotaxy; 8, trochanteral organ; 9, hind claw.
FIGURES 43–48. S. umesaoi Yosii, 1940 in Contribution to study of eyed species of Sinella (Collembola: Entomobryidae), with a key to this group of species from China
FIGURES 43–48. S. umesaoi Yosii, 1940: 43, chaetotaxy of Abd. IV; 44, chaetotaxy of Abd. V; 45–47, ventral tube: 45, anterior face; 46, posterior face; 47, lateral flap; 48, manubrial plaque.
FIGURES 17–22. Sinella gei n in Contribution to study of eyed species of Sinella (Collembola: Entomobryidae), with a key to this group of species from China
FIGURES 17–22. Sinella gei n. sp.: 17, lateral process of labial palp; 18, setae on ventral side of head; 19, dorsal cephalic chaetotaxy; 20, thoracic chaetotaxy; 21, trochanteral organ; 22, hind claw.
FIGURES 10–16. Sinella sunae n in Contribution to study of eyed species of Sinella (Collembola: Entomobryidae), with a key to this group of species from China
FIGURES 10–16. Sinella sunae n. sp.: 10–12, abdominal chaetotaxy: 10, Abd. I–III; 11, Abd. IV; 12, Abd. V; 13–14, ventral tube: 13, anterior face; 14, posterior face and lateral flap; 15, manubrial plaque; 16, mucro.
FIGURES 38–42. S. umesaoi Yosii, 1940 in Contribution to study of eyed species of Sinella (Collembola: Entomobryidae), with a key to this group of species from China
FIGURES 38–42. S. umesaoi Yosii, 1940: 38, inner differentiated tibiotarsal setae and claw of hind leg; 39, inner outstanding tibiotarsal seta; 40–42, abdominal chaetotaxy: 40, Abd. I; 41, Abd. II; 42, Abd. III.
FIGURES 31–37. S. umesaoi Yosii, 1940 in Contribution to study of eyed species of Sinella (Collembola: Entomobryidae), with a key to this group of species from China
FIGURES 31–37. S. umesaoi Yosii, 1940: 31, Ant. III organ; 32, lateral process of labial palp; 33, ventral side of the head; 34, dorsal cephalic chaetotaxy; 35–36, thoracic chaetotaxy: 35, Th. II; 36, Th. III; 37, trochanteral organ.
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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.