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52 results for “information content”
Data from: A chorus of color: hierarchical and graded information content of rapid color change signals in chameleons
Animals rely on information-rich signals to minimize costs associated with competition. If fighting ability is linked to stable individual attributes (e.g. morphology), the signals that communicate information about such ability should be relatively static. Conversely, the temporal variability of motivation should favor dynamic threat signals that indicate an animal's likelihood of escalating a contest. Though static colors are used by many animals to signal quality or fighting ability, the function of dynamic color change as a social signal has only recently begun to be investigated. Here, we examined the information content of rapid physiological color changes displayed by adult male veiled chameleons Chamaeleo calyptratus during agonistic interactions by conducting experimental trials between live chameleons and standardized, experimentally-controlled robochameleon models. Chameleons reliably communicated motivation with dynamic color displays – individuals that brightened were 14 times more likely to approach the robochameleon than non-brightening individuals. Additionally, chameleons with shorter latencies to maximum stripe brightness had stronger bites, and those displaying brighter, yellower stripes exhibited more aggression. The parallels between dynamic color changes and the vocalizations used to mediate aggressive interactions in other taxa are numerous. The use of particular vocalizations/color changes can signal motivation levels while specific signal elements (e.g. pitch, timing, brightness) may be linked to fighting ability. Because the complexity and potential information content of color signals increases markedly when organisms can display context-specific variation in the expression of these ornaments, the study of dynamic color signals is a field ripe for the investigation of complex visual and signaling strategies.
Data from: SNPs selected by information content outperform randomly selected microsatellite loci for delineating genetic identification and introgression in the endangered dark European honeybee (Apis mellifera mellifera)
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Data from: Hosts of avian brood parasites have evolved egg signatures with elevated information content
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Data from: Developmental timing of signals affects information content: song complexity but not consistency reflects innate immune strategy in male song sparrows
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Data from: Phylogeny inference under time-decaying migration and varying information content
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Data from: A chorus of color: hierarchical and graded information content of rapid color change signals in chameleons
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Dataset for: Physics-informed neural networks with monotonicity constraints for Richardson-Richards equation: Estimation of constitutive relationships and soil water flux density from volumetric water content measurements by Toshiyuki Bandai and Teamrat A. Ghezzehei
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Data from: Bayes factors unmask highly variable information content, bias, and extreme influence in phylogenomic analyses
As the application of genomic data in phylogenetics has become routine, a number of cases have arisen where alternative data sets strongly support conflicting conclusions. This sensitivity to analytical decisions has prevented firm resolution of some of the most recalcitrant nodes in the tree of life. To better understand the causes and nature of this sensitivity, we analyzed several phylogenomic data sets using an alternative measure of topological support (the Bayes factor) that both demonstrates and averts several limitations of more frequently employed support measures (such as Markov chain Monte Carlo estimates of posterior probabilities). Bayes factors reveal important, previously hidden, differences across six "phylogenomic" data sets collected to resolve the phylogenetic placement of turtles within Amniota. These data sets vary substantially in their support for well-established amniote relationships, particularly in the proportion of genes that contain extreme amounts of information as well as the proportion that strongly reject these uncontroversial relationships. All six data sets contain little information to resolve the phylogenetic placement of turtles relative to other amniotes. Bayes factors also reveal that a very small number of extremely influential genes (less than 1% of genes in a data set) can fundamentally change significant phylogenetic conclusions. In one example, these genes are shown to contain previously unrecognized paralogs. This study demonstrates both that the resolution of difficult phylogenomic problems remains sensitive to seemingly minor analysis details and that Bayes factors are a valuable tool for identifying and solving these challenges.
Data from: Discrimination of signal carotenoid content using multidimensional chromatic information
Red, orange and yellow carotenoid-based ornaments, which are widely used as sexual signals in many birds, fish and reptiles, are known to exhibit multidimensional chromatic variation as a result of both the concentration and relative proportions of different constituent carotenoids with differing spectral properties. This is thought to reflect intrinsic variation in signaller quality, making it a useful basis for female choice. However, whether females are able to discriminate relevant variation in carotenoid concentration and/or composition independently of each other, and of other phenotypic or behaviour traits, and if so, how this mediates their choice, is poorly understood. Here, female three-spined sticklebacks (Gasterosteus aculeatus) were presented with computer-animated courting males that varied exclusively in the appearance of their carotenoid-based colouration; specifically, each male's signal provided a perceptual match for carotenoid colouration expressed by live males with known underlying carotenoid content, thereby providing a biologically-relevant signal while precluding confounding traits influencing female choice. Females were able to discriminate between prospective mates solely on the basis of perceived variation in the allocation of carotenoids to males' sexual signals, and exhibited a strong preference for males with colouration indicative of higher concentrations of carotenoids in their signal, rather than in response to perceived variation in the relative proportion of constituent carotenoids. This has important implications for our understanding male signalling strategies and the information content of carotenoid-based sexual signals.
Data from: Assessing the potential information content of multicomponent visual signals: a machine learning approach
Careful investigation of the form of animal signals can offer novel insights into their function. Here, we deconstruct the face patterns of a tribe of primates, the guenons (Cercopithecini), and examine the information that is potentially available in the perceptual dimensions of their multicomponent displays. Using standardized colour-calibrated images of guenon faces, we measure variation in appearance both within and between species. Overall face pattern was quantified using the computer vision 'eigenface' technique, and eyebrow and nose-spot focal traits were described using computational image segmentation and shape analysis. Discriminant function analyses established whether these perceptual dimensions could be used to reliably classify species identity, individual identity, age and sex, and, if so, identify the dimensions that carry this information. Across the 12 species studied, we found that both overall face pattern and focal trait differences could be used to categorize species and individuals reliably, whereas correct classification of age category and sex was not possible. This pattern makes sense, as guenons often form mixed-species groups in which familiar conspecifics develop complex differentiated social relationships but where the presence of heterospecifics creates hybridization risk. Our approach should be broadly applicable to the investigation of visual signal function across the animal kingdom.
Data from: Information content is more important than sensory system or physical distance in guiding the long-term evolutionary relationships between signaling modalities in Sceloporus lizards
Long-term signal evolution is shaped by a variety of selective pressures including the need to convey additional information or to improve message transfer to specific receivers or through multiple environments. Here, we test the relative importance of information and sensory modality in shaping the long-term evolution of multimodal signals in Sceloporus lizards. To broadcast identity at territorial boundaries, male Sceloporus use both visual motion (headbob) and chemical signals, whereas they use color (blue belly patches) to signal aggression. Using modern phylogenetic comparative methods, we found a negative correlation between evolutionary changes in visual motion (headbobs) and chemical (femoral pore) signals, but only indirect ties between the evolution of color and motion signals (both of which are perceived visually) through viviparity, and no evidence of an evolutionary link between color and chemical signals. We also find a negative correlation between arboreality and chemical signals. Thus, information content (in this case, broadcasting individual identity versus signaling aggression) appears to play a more important role than sensory modality or physical distance in guiding long-term signal evolution. Additional insights into the underlying evolutionary processes are described, illustrating the utility of a phylogenetic approach.
Data from: Estimating Bayesian phylogenetic information content
Measuring the phylogenetic information content of data has a long history in systematics. Here we explore a Bayesian approach to information content estimation. The entropy of the posterior distribution compared to the entropy of the prior distribution provides a natural way to measure information content. If the data have no information relevant to ranking tree topologies beyond the information supplied by the prior, the posterior and prior will be identical. Information in data discourages consideration of some hypotheses allowed by the prior, resulting in a posterior distribution that is more concentrated (has lower entropy) than the prior. We focus on measuring information about tree topology using marginal posterior distributions of tree topologies. We show that both the accuracy and the computational efficiency of topological information content estimation improve with use of the conditional clade distribution, which also allows topological information content to be partitioned by clade. We explore two important applications of our method: providing a compelling definition of saturation, and detecting conflict among data partitions that can negatively affect analyses of concatenated data.
Data from: Markovian language model of the DNA and its information content
This work proposes a Markovian memoryless model for the DNA that simplifies enormously the complexity of it. We encode nucleotide sequences into symbolic sequences, called words, from which we establish meaningful length of words and groups of words that share symbolic similarities. Interpreting a node to represent a group of similar words and edges to represent their functional connectivity allows us to construct a network of the grammatical rules governing the appearance of groups of words in the DNA. Our model allows us to predict the transition between groups of words in the DNA with unprecedented accuracy, and to easily calculate many informational quantities to better characterize the DNA. In addition, we reduce the DNA of known bacteria to a network of only tens of nodes, show how our model can be used to detect similar (or dissimilar) genes in different organisms, and which sequences of symbols are responsible for most of the information content of the DNA. Therefore, the DNA can indeed be treated as a language, a Markovian language, where a 'word' is an element of a group, and its grammar represents the rules behind the probability of transitions between any two groups.
Supplementary material 1 from: Gavrilova A, Gavrilov G (2022) Assessment of morphological pharmacognostic characteristics of the content and label information of dried herbs marketed as food supplements in Bulgaria. Pharmacia 69(3): 865-872. https://doi.org/10.3897/pharmacia.69.e87549
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Development of a multi-excitation fluorescence (MEF) imaging method to improve the information content of benthic coral reef surveys
<p>Benthic surveys are a key component of monitoring and conservation efforts for coral reefs worldwide. While traditional image-based surveys rely on manual annotation of photographs to characterise benthic composition, automatic image annotation based on computer vision is becoming increasingly common. However, accurate classification of some benthic groups from reflectance images presents a challenge to local ecologists and computers alike. Most coral reef organisms produce one or a combination of fluorescent pigments, such as Green Fluorescent Protein (GFP)-like proteins found in corals, chlorophyll-a found in all photosynthetic organisms, and phycobiliproteins found in red macroalgae, crustose coralline algae (CCA) and cyanobacteria. Building on the potential of these pigments as a target for automatic image annotation, we developed a novel imaging method based on off-the-shelf components to improve classification of coral and other biotic substrates using a multi-excitation fluorescence (MEF) imaging system. We used RGB cameras to image the fluorescence emission of coral and algal pigments stimulated by narrow-waveband blue and green light, and then combined the information into 3-channel pseudocolour images. Using a set of <i>a priori</i> rules defined by the relative pixel intensity produced in different channels, the method achieved successful classification of organisms into three categories based on the dominant fluorescent pigment expressed, facilitating discrimination of traditionally problematic groups. This work provides a conceptual foundation for future technological developments that will improve the cost, accuracy and speed of coral reef surveys.</p>
Data from: Estimating Bayesian phylogenetic information content
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Data from: Markovian language model of the DNA and its information content
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Data from: Assessing the potential information content of multicomponent visual signals: a machine learning approach
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Development of a multi-excitation fluorescence (MEF) imaging method to improve the information content of benthic coral reef surveys
Open the record for dataset details and reuse information.
Data from: Information content is more important than sensory system or physical distance in guiding the long-term evolutionary relationships between signaling modalities in Sceloporus lizards
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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.