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55 results for “visual signal”
Data from "Robust sensory traits across light habitats: Visual signals but not receptors vary in centrarchids inhabiting distinct photic environments"
<p>Visual communication in fish is often shaped by the light environment they inhabit, influencing both sensory (e.g., eye size, opsin gene expression), and signaling traits (e.g., body reflectance). This study explores the phenotypic variation in the visual communication traits of six species of centrarchids (Centrarchidae) inhabiting two contrasting light environments. We measured morphological, molecular, and signaling traits to determine their responses to photic conditions. Our findings reveal significant interspecific variation in sensory traits but no consistent phenotypic variation between light environments. Centrarchids showed robust visual systems with red-green dichromatic vision, which was largely unaffected by the different light habitats. We also found significant molecular evolution in the visual opsin genes, although these changes were not associated with environmental conditions. However, body reflectance displayed species-specific responses to environmental conditions, suggesting that signaling traits may be more flexible than sensory traits. Overall, our results challenge the generality of the current paradigm in visual ecology, which portrays visual systems in fish as highly tunable owing to photic conditions. Our study highlights the potential evolutionary or developmental constraints on centrarchid visual systems and their implications for adaptability to various habitats and novel environmental threats.</p> <p>This dataset includes underwater light measurements, retinal transcriptomics, eye morphology, and spectral reflectance data to assess the effects of environment and species identity on eye size, opsin gene expression, chromophore usage, and body reflectance of centrarchids. Furthermore, we test for signatures of molecular evolution on the amino acid sequence of visual opsin genes across species and populations. By combining data on the visual ecology of different species from two distinct light environments, we ask i) do the visual traits of centrarchids vary across photic environments? and ii) are phenotypic responses to light conditions shared among species or are they species-specific? Overall, we found robust visual systems across species (no environmental effect) but variable body reflectance across species and environments (genotype-by-environment interaction, G × E). This suggests that divergent species-specific responses in signaling might help offset the lack of fine-tuning in the visual system of centrarchids. </p> <p>For more information see ReadMe file.</p>
Data supplementing Einhäuser, W., Neubert, C. R., Grimm, S., & Bendixen, A. (2024). High visual salience of alert signals can lead to a counterintuitive increase of reaction times. Scientific Reports, 14, 8858.
<p>These files supplement the publication <br>Einhäuser, W., Neubert, C. R., Grimm, S., & Bendixen, A. (2024). High visual salience of alert signals can lead to a counterintuitive increase of reaction times. <em>Scientific Reports, </em>14, 8858. https://doi.org/10.1038/s41598-024-58953-4</p> <p>The files data_expX.mat, where X is the experiment number (1-4), contain the data as described below. </p> <p>The files dataTraining_expX.mat contain the data of the first (training) block of each experiment. They are needed only for the supplemental material. </p> <p>To exemplify the usage, the functions figure2and3.m, figure4.m, figure5.m, figure6.m and Table1.m output the paper's figures and the data of Table 1, respectively; figureS2.m, figureS3.m, figureS4.m and figureS5.m output the figures of the supplemental material (figure S1 needs substantial amounts of external source code to compute the salience maps and is therefore not included).</p> <p><br>data_exp1.mat contains the following variables<br>For alert trials, variable of dimensions subjects x blocks x alert trials (20x10x64); note that only used participants and blocks with alert trials (2 through 11) are included in the data set:<br>alert_aud - the salience level of the alert tone (1-8, corresponding to 54dB(A) through 89 dB(A))<br>alert_vis - the salience level of the alert frame (1-8, corresponding to 0.10 to 8.50 Weber contrasts in logarithmic steps)<br>alert_side - the side on which the alert frame and the tone were presented (1-left, 2-right)<br>alert_fixOk - derived from eye movement data, was the first fixation closer to the alert square than to the center?<br>alert_primaryRT - primary-task reaction time (for alert trials)<br>alert_alertRT - alert-task reaction time <br>alert_correctAlert - was the response (up/down) to the alert correct?<br>alert_intrusionAlert - was there an intrusion (left/right pressed before up or down)?<br>alert_correctPrimary - was the primary task conducted correctly?<br>alert_intrusionPrimary - was there an intrusion for the primary task?<br>alert_timeToFixation - time to first fixation on alert square <br>alert_fixationToResp - time from beginning of fixation to response to the alert <br>alert_fixDur - duration of first fixation after trial onset</p> <p>For no-alert trials, variable of dimensions subjects x blocks x no-alert trials (20x10x448):<br>noalert_correctPrimary - was the primary task conducted correctly?<br>noalert_intrusionPrimary - was there an intrusion for the primary task? (i.e., up/down pressed before left/right)?</p> <p>For all trials, variable of dimensions subjects x blocks x no-alert trials (20x10x512):<br>all_correctPrimary - was the primary task conducted correctly?<br>all_intrusionPrimary - was there an intrusion for the primary task? (i.e., up/down pressed before left/right)?<br>all_RT - reaction time in the primary task<br>all_isAlertTrial - was the trial an alert trial? (useful to map no-alert trials and alert trials on all trials)</p> <p>In addition, there are some raw eye movement data for the alert blocks:<br>alert_eyeX, alert_eyeY - dimension 20 x 10 x 64 x 6000; x and y position in pixel coordinates relative to trial (and alert) onset, 1ms/sample, ends at conclusion of trials, filled up with NaN if duration was less than 6000ms <br>alert_eyeFixX, alert_eyeFixY, alert_eyeFixTon, alert_eyeFixDur - 20 x 10 x 64 x 15; x and y position, onset (in ms relative to trial onset) and duration of fixations during the trial (from onset to primary-task response), filled with NaN when less than 15 fixations were made. Note that the first entry of alert_eyeFixDur along the forth dimension will usually equal the alert_fixDur</p> <p><br>data_exp2.mat contains the same variables as data_exp1.mat with the following exceptions:<br>alert_vis - contains only two levels (1 and 2) corresponding to Weber contrasts of 0.10 and 2.39, respectively<br>alert_dur - the level of duration of the alert frame (1 through 8, corresponding to 25ms, 50ms, 100ms, 200ms, 300ms, 400ms, 600ms, 800ms)<br>alert_aud is not included (all tones were at 54 dB(A))<br>there are only 19 participants; hence the variables are of size 19 x ...<br>note: block 8 for subject 6 contains only 450 trials (57 alert trials), the remainder is filled with NaN.</p> <p><br>data_exp3.mat contains the same variables as data_exp1.mat with the following exceptions:<br>alert_aud - contains only two levels (1 and 2) corresponding to sound levels of 54 dB(A) and 79 dB(A) respectively<br>alert_dur - the level of duration of the alert tone (1 through 8, corresponding to 25ms, 50ms, 100ms, 200ms, 300ms, 400ms, 600ms, 800ms)<br>alert_vis is not included (all alert frames were at 0.10 contrast)</p> <p> </p> <p>data_exp4.mat contains the same variables as data_exp1.mat with the following exceptions:<br>alert_aud - contains only two levels (1 and 2) corresponding to sound levels of 54 dB(A) and 79 dB(A) respectively<br>alert_vis is not included and replaced by<br>alert_condBefore - alert frame contrast level before the saccade (1 - 0.10 contrast, 2 - 2.39 contrast)<br>alert_condAfter - alert frame contrast level after the saccade (1 - 0.10 contrast, 2 - 2.39 contrast)</p> <p><br>dataTraining_expX.mat contains for the first (training) block of experiment X (X being 1, 2, 3 or 4) the following variables of size 20x512 (participant x trial) [19x512 in case of Experiment 2]:<br>all_correctPrimary - was the primary task conducted correctly?<br>all_RT - reaction time in the primary task<br>[Note that there are no alert trials in this block and these data are only used in the supplementary material (part 4)]</p>
Data and code for Zheng et al. Contrasting coloured ventral wings are a visual collision avoidance signal in birds
<p>This repository contains codes and data for Zheng et al. Contrasting coloured ventral wings are a visual collision avoidance signal in birds. We have three folders, each containing one of the three datasets of contrast scores of avian ventral wings. These include the mean manual contrast ventral wing scores for 1780 species, a subset of 1745 diurnal species, 648 species with high-resolution museum ventral images, and the mean Root-Mean-Square (RMS) contrast ventral wing scores for the same 648 species. We tested the collision avoidance hypothesis for each dataset by assessing the relationships between the contrast scores and ecological traits. We used the Bayesian Generalized Linear Mixed Models in MCMCglmm with considering the phylogenetic relatedness among species and the uncertainties of 100 phylogenetic trees (downloaded in birdtree.org). We included body mass, flock size, coloniality (colonial vs. non-colonial breeding species), activity time (nocturnal vs. diurnal), the number of sympatric predators, and the interaction between coloniality and body mass as the predictors. In each folder, we included four files, including an R source file, a dataset containing the contrast scores and the ecological traits of the corresponding species, and a tree file containing 100 randomly sampled phylogenetic trees among these species. See the Methods of the paper for detail. </p>
Mate preferences act independently on different elements of visual signals in Heliconius butterflies
<p>Mating cues are often comprised of several elements, which can act independently, or in concert to attract a suitable partner. Individual elements may also function in other contexts, such as predator defence or camouflage. In <em>Heliconius</em> butterflies, wing patterns comprise several individual colour pattern elements, which advertise the butterflies' toxicity to predators. These wing patterns are also mating cues and males predominantly court females that possess the same wing pattern as their own. However, it is not known whether male preference is based on the full wing pattern or only individual pattern elements. We compared preferences of male <em>H. erato lativitta</em> between female models with the full wing pattern and those with some pattern elements removed. We found no differences in preference between the full wing pattern model and a model with pattern elements removed, indicating that the complete composition of all elements is not essential to the mating signal. Wing pattern preferences also contribute to pre-mating isolation between two other Heliconius taxa, <em>H. erato cyrbia</em> and <em>H. himera</em>, therefore, we next compared preferences for the same models in these species. <em>H. erato cyrbia</em> and <em>H. himera</em> strongly differed in preferences for the models, potentially providing a mechanism for how pre-mating isolation acts between these species. These findings suggest that contrasting levels of selective constraint act on elements across the wing pattern.</p>
Computational analyses of dynamic visual courtship display reveal diet-dependent and plastic male signaling in Rabidosa rabida wolf spiders
<p>It has long been a challenge to quantify the variation in dynamic motions to understand how those displays function in animal communication. The traditional approach is dependent on labor-intensive manual identification/annotation by experts. However, the recent progress in computational techniques provides researchers with toolsets for rapid, objective, and reproducible quantification of dynamic visual displays. In the present study, we investigated the effects of diet manipulation on dynamic visual components of male courtship displays of <em>Rabidosa</em> <em>rabida</em> wolf spiders using machine learning algorithms. Our results suggest that (i) the computational approach can provide an insight into the variation in the dynamic visual display between high- and low-diet males which is not clearly shown with the traditional approach and (ii) males may plastically alter their courtship display according to the body size of females they encounter. Through the present study, we add an example of the utilization of recent computational techniques for understanding the evolution of animal behaviors.</p>
Data for: Outcomes of multifarious selection on the evolution of visual signals
<p><span>Multifarious sources of selection shape visual signals and can produce phenotypic divergence. Theory predicts variance in warning signals should be minimal due to purifying selection, yet polymorphism is abundant. While in some instances divergent signals can evolve into discrete morphs, continuously variable phenotypes are also encountered in natural populations. Notwithstanding, we currently have an incomplete understanding of how combinations of selection shape fitness landscapes, particularly those which produce polymorphism. We modeled how combinations of natural and sexual selection act on aposematic traits within a single population to gain insights into what combinations of selection favor the evolution and maintenance of phenotypic variation. With a rich foundation of studies on selection and phenotypic divergence, we reference the poison frog genus <em>Oophaga</em> to model signal evolution. </span><span>Multifarious selection on aposematic traits created the topology of our model's fitness landscape by approximating different scenarios found in natural populations. </span><span>Combined, the model produced all types of phenotypic variation found in frog populations, namely monomorphism, continuous variation, and discrete polymorphism. </span><span>Our results afford advances into how multifarious selection shapes phenotypic divergence, which, along with additional modelling enhancements, will allow us to further our understanding of visual signal evolution.</span></p>
Mate preferences act independently on different elements of visual signals in Heliconius butterflies
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Data for: Outcomes of multifarious selection on the evolution of visual signals
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Data and code from: Computational analyses of dynamic visual courtship display reveal diet-dependent male signaling in <em>Rabidosa rabida</em> wolf spiders
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Computational analyses of dynamic visual courtship display reveal diet-dependent and plastic male signaling in Rabidosa rabida wolf spiders
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Nanoscale ultrastructures increase the visual conspicuousness of signalling traits in obligate cleaner shrimps
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Representations of language in a model of visually grounded speech signal: Data
<p>The set of datafiles to reproduce results from:</p> <ul> <li>Chrupała, G., Gelderloos, L., & Alishahi, A. (2017). Representations of language in a model of visually grounded speech signal. ACL. arXiv preprint: https://arxiv.org/abs/1702.01991</li> </ul>
Light environment interacts with visual displays in a species-specific manner in multimodal signaling wolf spiders
<p>Light availability is highly variable, yet predictable, over various timescales and the light environment is expected to play an important role in the evolution of visual signals. Courtship displays within the wolf spider genus Schizocosa always involve the use of substrate borne vibrations, however, there is substantial variation between species in the use of visual displays. We assessed the impact of light intensity on the courtship of four species of Schizocosa that vary in their use of visual signals during courtship. To examine the effects of the light environment on mating success and courtship effort in each species, we ran behavioral trials at three light intensities (bright, dim and dark). We also examined each species' circadian activity patterns. We found multiple effects of the light environment and these varied between species. Circadian activity patterns also differed between species and sexes. Our results suggest that dim-light might favor more conspicuous visual displays, while less conspicuous displays might be favored in bright light conditions. Additionally, we found evidence for light-dependent changes in selection on male traits, illustrating that short-term changes in light intensity have the potential for strong effects on the dynamics of sexual selection.</p>
Melanopsin-mediated amplification of cone signals in the human visual cortex
<p>The ambient daylight variation is coded by melanopsin photoreceptors and their luxotonic activity increases towards midday when colour temperatures are cooler, and irradiances are higher. Although melanopsin and cone photoresponses can be mediated via separate pathways, the connectivity of melanopsin cells across all levels of the retina enables them to modify cone signals. The downstream effects of melanopsin-cone interactions on human vision are however, incompletely understood. Here, we determined how the change in daytime melanopsin activation affects the human cone pathway signals in the visual cortex. A 5-primary silent-substitution method was developed to evaluate the dependence of cone-mediated signals on melanopsin activation by spectrally tuning the lights and stabilising the rhodopsin activation under a constant cone photometric luminance. The retinal (white noise electroretinogram, wnERG) and cortical responses (visual evoked potential, wnVEP) were simultaneously recorded with the photoreceptor-directed lights in 10 observers. By increasing the melanopsin activation, a reverse response pattern was observed with cone signals being supressed in the retina by 27% (p=0.03) and subsequently amplified by 16% (p=0.01) as they reach the cortex. We infer that melanopsin activity can amplify cone signals at sites distal to retinal bipolar cells to cause a decrease in the psychophysical Weber fraction for cone vision.</p>
Cholinergic input to mouse visual cortex signals a movement state and acutely enhances layer 5 responsiveness
<div>All raw data and Matlab code necessary to produce the figures of <a href="https://elifesciences.org/reviewed-preprints/89986">https://elifesciences.org/reviewed-preprints/89986</a></div> <div> <div> </div> </div>
ENST-Drums: an extensive audio-visual database for drum signals processing
<p>The <strong>ENST-Drums database</strong> is a large and varied research database for automatic drum transcription and processing:</p> <ul> <li>Three professional drummers specialized in different music genres were recorded.</li> <li>Total duration of audio material recorded per drummer is around 75 minutes.</li> <li>Each drummer played his own drum kit.</li> <li>Each sequence used either sticks, rods, brushes or mallets to increase the diversity of drum sounds.</li> <li>The drum kits themselves are varied, ranging from a small, portable, kit with two toms and 2 cymbals, suitable for jazz and latin music ; to a larger rock drum set with 4 toms and 5 cymbals.</li> </ul> <p>Each sequence is recorded on 8 individual audio channels, is filmed from two angles, and is fully annotated</p> <p>A large part of ENST-Drums is publicly available <strong>under some conditions</strong>. These conditions include:</p> <ul> <li>The use and exploitation of the database should be limited to <strong>research</strong> purposes. No commercial use is possible.</li> <li>The database is distributed under the licence "Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)"</li> <li>Any document describing a research work where ENST-Drums was used should include a reference to ENST-Drums and to the paper <em>Olivier Gillet and Gaël Richard. ENST-Drums: an extensive audio-visual database for drum signals processing, In Proc of ISMIR'06, Victoria, Canada, 2006.</em></li> </ul> <p> </p> <p><strong>Acknowledgements</strong></p> <p>We would like to thank:</p> <ul> <li>The 3 drummers: Louis Cavé, Bertrand Clouard and Frédéric Rottier.</li> <li>E. Thiévon (author) and Play Music Publishing (publisher) for the background accompaniment sequences.</li> </ul> <p>The authors wish to acknowledge the support of the French ministry of research (<a href="http://recherche.ircam.fr/equipes/analyse-synthese/musicdiscover">ACI-MusicDiscover</a> project) and of the European Commission under the <a href="http://www.k-space.eu/">FP6-027026-K-SPACE</a> contract.</p>
Data - "Suppressing feedback signals to visual cortex abolishes attentional modulation"
<p>Data associated with article "Suppressing feedback signals to visual cortex abolishes attentional modulation"</p>
Data from: Electroencephalography Responses to Simplified Visual Signals Reveal Explain Differences in Speech-in-Noise Comprehension
<p>Contents and Folder Structure:</p> <p><strong>EEG Experiment</strong></p> <ul> <li><strong>EEG_stimuli</strong>: these are the videos that were presented to participants in the EEG experiment, and the code that generates them from the original corpus (link)</li> <li><strong>data_2020>split_trials</strong>: contains the raw EEG data starting 1.995s before each trial and ending 1.995s after each trial with naming convention subXx_VV_YY_N.fif where X or Xx is the subject number, YY is the modality condition (AV for audiovisual and V0 for video only), N is the trial number (between 0 and 4 inclusive), and VV is the video condition (1e for the envelope dot, 1m is the mismatched dot, 4v is the cartoon, bw is the edge detection and nh is the natural condition). <ul> <li><strong>unprocessed>raw</strong>: contains the unprocessed raw EEG data <ul> <li><strong>processed>Fs-200>BP-1-80-ASR-INTP-AVR</strong>: contains the pre-processed raw EEG data: the output of <em>run_preprocessing.m</em></li> <li><strong>processed>Fs-200>BP-1-80-ASR-INTP-AVR-ICr</strong>: contains the pre-processed raw EEG data after ICA cleaning: the output of <em>run_reject_ICs.m</em></li> <li><strong>stim>stim_dwnspl</strong>: contains the aligned 200Hz envelopes of the presented speech used as features for the time-lagged models</li> </ul> </li> </ul> </li> <li><strong>EEG_analysis_code </strong>[note: please extract the contents of this folder to match paths] <ul> <li><strong>2_ICA_filt:</strong> this folder contains the MATLAB code that performs the pre-processing of the EEG data, including filtering, downsampling, ICA cleaning etc. The main functions are: <ul> <li><em>run_preprocessing.m: downsampling, filtering, ASR cleaning</em></li> <li><em>run_reject_ICs.m: ICLabel ICA cleaning</em></li> </ul> </li> <li><strong>3_analysis:</strong> this is the Python code that performs the TRF and backward modelling on the EEG data. The main functions are: <ul> <li><em>multisensory_bw.py</em>: backwards model</li> <li><em>multisensory_fw.py</em>: forwards model</li> </ul> </li> </ul> </li> </ul> <p><strong>Behavioural Experiment</strong></p> <ul> <li><strong>behavioural</strong> <ul> <li><strong>0_dataset</strong>: these are the videos that were presented to participants in the behavioural experiment, and the code that generates them from the original corpus (AV GRID corpus)</li> <li><strong>3_analysis</strong>: behavioural data analysis script <ul> <li>main function: <em>data_grid_v3.py</em></li> </ul> </li> </ul> </li> <li><strong>behavioural_data>data_grid</strong>: behavioural results </li> </ul>
Data from: Vomeronasal organ volume increases with body size and is dissociated with loss of a visual signal in Sceloporus lizards
<p>Many organisms communicate using signals in different sensory modalities (multicomponent or multimodal). When one signal or component is lost over evolutionary time, it may be indicative of changes in other characteristics of the signaling system, including the sensory organs used to perceive and process signals. <em>Sceloporus</em> lizards predominantly use chemical and visual signals to communicate, yet some species have lost the ancestral ventral color patch used in male-male agonistic interactions and exhibit increased chemosensory behavior. Here, we asked whether evolutionary loss of this sexual signal is associated with larger vomeronasal organ (VNO) volumes (an organ that detects chemical scents) compared to species that have retained the color patch. We measured VNO coronal section areas of 7–8 adult males from each of 11 <em>Sceloporus</em> species (4 that lost and 7 that retained the color patch), estimated sensory and total epithelium volume, and compared volumes using phylogenetic ANCOVA, controlling for body size. Contrary to expectations, we found that species retaining the ventral patch had similar relative VNO volumes as did species that have lost the ancestral patch, and that body size explains VNO epithelium volume. Visual signal loss may be sufficiently compensated for by increased chemosensory behavior, and the allometric pattern may indicate sensory system trade-offs for large-bodied species.</p>
Melanopsin-mediated amplification of cone signals in the human visual cortex
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