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opencc-zeroJul 2020View details →

Data from: Control of adaptive action selection by secondary motor cortex during flexible visual categorization

Adaptive action selection during stimulus categorization is an important feature of flexible behavior. To examine neural mechanism underlying this process, we trained mice to categorize the spatial frequencies of visual stimuli according to a boundary that changed between blocks of trials in a session. Using a model with a dynamic decision criterion, we found that sensory history was important for adaptive action selection after the switch of boundary. Bilateral inactivation of the secondary motor cortex (M2) impaired adaptive action selection by reducing the behavioral influence of sensory history. Electrophysiological recordings showed that M2 neurons carried more information about upcoming choice and previous sensory stimuli when sensorimotor association was being remapped than when it was stable. Thus, M2 causally contributes to flexible action selection during stimulus categorization, with the representations of upcoming choice and sensory history regulated by the demand to remap stimulus-action association.

FIGURE 7 in Phylogenetic relationships and biological features reveal that male Ostrinia furnacalis (Lepidoptera: Crambidae) in Northeast China can be categorized into postmedial line-based clades

FIGURE 7. Host preference of clades of Ostrinia furnacalis 2015-2016. (Abbreviation: C=Corn, R=Rice, Sg=Sorghum, W=Weed, Sb=Soybean, G=Grape, V=Vegetation, CL=Corn-Larval (male from larval inside corn plants); I, II & III=Clade I-III). Note: IV in 2015 test represented males morphologically similar to males with postmedial line of IV clades, and was removed in 2016 test.

FIGURE 4 in Phylogenetic relationships and biological features reveal that male Ostrinia furnacalis (Lepidoptera: Crambidae) in Northeast China can be categorized into postmedial line-based clades

FIGURE 4. Phylogenic relationships within Ostrinia furnacalis: A: Phylogenic relationship within O. furnacalis clade I; B: Phylogenic relationship within O. furnacalis clade II; C: Phylogenic relationship within O. furnacalis clade III; D: Phylogenic relationship tree showing all typical taxa within O. furnacalis. A1 and A2 are outgroup O.nubilalis. Note: Maximum likelihood, Maximum parsimony, Bayesian posterior probabilities and Neighborjoining bootstrap values (%) are indicated above each branch in the format of ML/ MP/ BI/ NJ.

FIGURE 5 in Phylogenetic relationships and biological features reveal that male Ostrinia furnacalis (Lepidoptera: Crambidae) in Northeast China can be categorized into postmedial line-based clades

FIGURE 5. Life span of male Ostrinia furnacalis clades under different living conditions. Abbreviation: I~III=Clades I, II& III; N=none (no water provided); M = moisture (cotton ball full of water for air moisture, approximately 90% relative humidity); W=water (water was available); H=honey (5% honey was available); Comparision equals overall life span of the males under different conditions (captures from traps and sweep net were pooled); Life span equals life span of males captured just by traps. Note: right Y axis numbers are only used for the life span treatment.

FIGURE 2 in Phylogenetic relationships and biological features reveal that male Ostrinia furnacalis (Lepidoptera: Crambidae) in Northeast China can be categorized into postmedial line-based clades

FIGURE 2. The external appearance of male Ostrinia nubilalis and clades of male Ostrina furnacalis. A: terminology relating to postmedial line; a, b, c and d: four typical postmedial line; a-b, b-c and c-d: clades I, II, and III; e & f: Ostrinia nubilalis sex pheromone strains of General and New York.

opencc-zeroSep 2020View details →

Comparison of categorical color perception in two Estrildid finches

Sensory systems are predicted to be adapted to the perception of important stimuli, such as signals used in communication. Prior work has shown that female zebra finches perceive the carotenoid-based orange-red coloration of male beaks—a mate choice signal—categorically. Specifically, females exhibited an increased ability to discriminate between colors from opposite sides of a perceptual category boundary than equally-different colors from the same side of the boundary. The Bengalese finch, an Estrildid finch related to the zebra finch, is black, brown and white, lacking carotenoid coloration. To explore the relationship between categorical color perception and signal use, we tested Bengalese finches using the same orange-red continuum as in zebra finches, and also tested how both species discriminated among colors differing systematically in hue and brightness. Unlike in zebra finches, we found no evidence of categorical perception of an orange-red continuum in Bengalese finches. Instead, we found that the combination of chromatic distance (hue difference) and Michelson contrast (difference in brightness) strongly correlated with color discrimination ability on all tested color pairs in Bengalese finches. The pattern was different in zebra finches: this strong correlation held only when discriminating between colors from different categories, but not when discriminating between colors from within the same category. These experiments suggest that categorical perception is not a universal feature of avian, or even Estrildid finch, vision. Our findings also provide further insights into the mechanism underlying categorical perception and are consistent with the hypothesis that categorical perception is adapted for signal perception.

opencc-zeroOct 2020View details →

Code for: Threshold assessment, categorical perception, and the evolution of reliable signaling

Animals often use assessment signals to communicate information about their quality to a variety of receivers, including potential mates, competitors, and predators. But what maintains reliable signaling and prevents signalers from signaling a better quality than they actually have? Previous work has shown that reliable signaling can be maintained if signalers pay fitness costs for signaling at different intensities and these costs are greater for lower quality individuals than higher quality ones. Models supporting this idea typically assume that continuous variation in signal intensity is perceived as such by receivers. In many organisms, however, receivers have threshold responses to signals, in which they respond to a signal if it is above a threshold value and do not respond if the signal is below the threshold value. Here, we use both analytical and individual-based models to investigate how such threshold responses affect the reliability of assessment signals. We show that reliable signaling systems can break down when receivers have an invariant threshold response, but reliable signaling can be rescued if there is variation among receivers in the location of their threshold boundary. Our models provide an important step towards understanding signal evolution when receivers have threshold responses to continuous signal variation.

opencc-zeroDec 2014View details →

Data from: Rapid categorization of natural face images in the infant right hemisphere

Human performance at categorizing natural visual images surpasses automatic algorithms, but how and when this function arises and develops remain unanswered. We recorded scalp electrical brain activity in 4–6 months infants viewing images of objects in their natural background at a rapid rate of 6 images/second (6 Hz). Widely variable face images appearing every 5 stimuli generate an electrophysiological response over the right hemisphere exactly at 1.2 Hz (6 Hz/5). This face-selective response is absent for phase-scrambled images and therefore not due to low-level information. These findings indicate that right lateralized face-selective processes emerge well before reading acquisition in the infant brain, which can perform figure-ground segregation and generalize face-selective responses across changes in size, viewpoint, illumination as well as expression, age and gender. These observations made with a highly sensitive and objective approach open an avenue for clarifying the developmental course of natural image categorization in the human brain.

opencc-by-4.0Jul 2017View details →

Developmental Changes in the Categorical Processing of Positive and Negative Facial Expressions

Categorical biases in the processing of emotional facial expression have been the subject of much debate in the literature. Opposing views on this topic claim either that positive or negative facial expressions enjoy improved processing in the human brain. The developmental changes in the processing advantages of positive and negative facial expressions are also disputed, with studies using varying paradigms showing seemingly contradictory results. Therefore, to further investigate the development of categorical processing and extraction of emotional information from faces, we tested 6-, 9-, and 12-year-old children, as well as adults, on their ability to categorize various facial expressions as positive or negative as quickly as possible. This was a simplified paradigm designed to explicitly contrast the processing efficiency of positive and negative facial expressions on the broader level of those emotional valence categories, rather than specific single emotional expressions. Our results show an early age processing advantage for positive facial expressions, which disappears in adults who show no such differences in the case of response time measures. In the case of accuracy measures, the early advantage for positive facial expressions gradually disappears, and is reversed into a negativity advantage in adults. These findings demonstrate that category-based positive and negative processing advantages are strongly modulated by age over the course of development, and can exhibit opposite effects depending on the developmental stage of the participant. Here we archive the accuracy and and response time data used for our publication.

opencc-by-4.0Mar 2022View details →

Accompanying simulated data for "Go multivariate: recommendations on multilevel hidden Markov models with categorical data of varying complexity"

The multilevel hidden Markov model (MHMM) is a promising vehicle to investigate latent dynamics over time in social and behavioral processes. By including continuous individual random effects, the model accommodates variability between individuals, providing individual-specific trajectories and facilitating the study of individual differences. However, the performance of the MHMM has not been sufficiently explored. Currently, there are no practical guidelines on the sample size needed to obtain reliable estimates related to categorical data characteristics We performed an extensive simulation to assess the effect of the number of dependent variables (1-4), the number of individuals (5-90), and the number of observations per individual (100-1600) on the estimation performance of group-level parameters and between-individual variability on a Bayesian MHMM with categorical data of various levels of complexity. We found that using multivariate data generally alleviates the sample size needed and improves the stability of the results. Regarding the estimation of group-level parameters, the number of individuals and observations largely compensate for each other. Meanwhile, only the former drives the estimation of between-individual variability. We conclude with guidelines on the sample size necessary based on the complexity of the data and the study objectives of the practitioners. This repository contains data generated for the manuscript: "Go multivariate: recommendations on multilevel hidden Markov models with categorical data of varying complexity". It comprehends: (1) model outputs (maximum a posteriori estimates) for each repetition (n=100) of each scenario (n=324) of the main simulation, (2) complete model outputs (including estimates for 4000 MCMC iterations) for two chains of each repetition (n=3) of each scenario (n=324). Please note that the empirical data used in the manuscript is not available as part of this repository. A subsample of the data used in the empirical example are openly available as an example data set in the R package <a href="https://cran.r-project.org/web/packages/mHMMbayes/index.html">mHMMbayes on CRAN</a>. The full data set is available on request from the authors.

opencc-by-4.0Nov 2024View details →

IMAGES (jpg) from Lettuces categorized in 5 STARS of freshness state,

The file contains 2800 images taken with a DSLR camera , in jpg file format and limit 2mb per image. the resolution is the same at all, the backgound is white and the light is daylight. The images are categorized on 5 stars freshness category. the category 5 is the crop day and the category 1 is not for eating.  the categories are created using the food storage science and can be used as samples images for testing Algorithms and methods on analysing food freshness levels. The images are standarized at the same analysis (LENS,LUX,FFC,RESOLUTION)

opencc-by-4.0Nov 2021View details →

Explanations for "Defect Identification, Categorization, and Repair: Better Together"

Explanations for "Defect Identification, Categorization, and Repair: Better Together"

opencc-by-4.0Aug 2021View details →

Defect Identification, Categorization, and Repair:Better Together

CompDefect-replication-package This repository contains source code that we used to perform experiments in "Defect Identification, Categorization, and Repair: Better Together" paper. The paper is now under view. <a href="https://arxiv.org/pdf/2204.04856.pdf">https://arxiv.org/pdf/2204.04856.pdf</a>

opencc-by-4.0Sep 2022View details →

Scalable mixed model approaches for set-based association studies on large-scale categorical data analysis and its application to 450k exome sequencing data in UK Biobank

The ongoing release of large-scale sequencing data in the UK Biobank allows for identifying associations between rare variants and complex traits. SAIGE-GENE+ is a valid approach to conducting set-based association tests for quantitative and binary traits. However, for ordinal categorical phenotypes, applying SAIGE-GENE+ with treating the trait as quantitative or binarizing the trait can cause inflated type I error rates or power loss. In this study, we propose a novel method for rare-variant association tests, POLMM-GENE, in which a proportional odds logistic mixed model was used to characterize ordinal categorical phenotypes while adjusting for sample relatedness. POLMM-GENE fully utilizes the categorical nature of phenotypes and thus can well control type I error rates while remaining powerful. In the analyses of UK Biobank 450k whole exome-sequencing data for 5 ordinal categorical traits, POLMM-GENE identified 54 gene-phenotype associations.

opencc-by-4.0May 2024View details →

Dataset related to publication: Landcover-categorized fires respond distinctly to precipitation anomalies in the South-Central United States

Landcover-categorized fires respond distinctly to precipitation anomalies in the South-Central United States Kátia Fernandes and Sen g. Young doi: 10.3389/fenvs.2024.1433920 Abstract Satellite detection of active fires have contributed to advance our understanding of fire ecology, fire and climate dynamics, fire emissions and how to better manage the use of fires as a tool. In this study we use 12 years (2012-2023) of active fire data combined with landcover information in the South-Central United States to derive a monthly, open access dataset of categorized fires. This is done by calculating a fire predominance index used to rank fire prone land covers, which are then grouped into four main landscapes: grassland, forest, wildland and crop fires. County level aggregated analyses reveal spatial distributions, climatologies, and peak fire months that are particular to each fire type. Using the Standardized Precipitation Index (SPI), it is found that during climatological fire peak-month, SPI and fires exhibit an inverse relationship in forests and crops, whereas grassland and wildland fires show less consistent inverse or even direct relationship with SPI. This varied behavior is discussed in the context of landscapes’ responses to anomalies in precipitation, and fire management practices, such as prescribed fires and crop residue burning. In a case study of Osage County (OK) we find that large wildfires, known to be closely related to climate anomalies, occur where forest fires are located in the county and absent in areas of grassland fires. Weaker grassland fires response to precipitation anomalies can be attributed to the use of prescribed burning, which are normally planned under environmental conditions that facilitate control and thus avoided during droughts. Crop fires on the other hand, are set to efficiently burn residue and practiced more intensely in drier years than in wetter, explaining the consistently strong inverse correlation between fires and precipitation anomalies. In our increasingly volatile climate, understanding how fires, vegetation, and precipitation interact has become imperative to prevent hazardous fire conflagrations and to better manage ecosystems.