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openNov 2022View details →

Embodiment of virtual feet correlates with motor performance in a target-stepping task

Dataset for the human factors experiment of "Embodiment of virtual feet correlates with motor performance in a target-stepping task".

opencc-zeroDec 2022View details →

Published correlational effect sizes in social and developmental psychology

The distribution of effect sizes may offer insights about the research done and reported in a scientific field. We have evaluated 12,412 manually collected correlation effect sizes (Sample 1) and 31,157 computer-extracted correlation effect sizes (Sample 2) published in journals focused on social or developmental psychology. Sample 1 consisted of 243 studies from 6 journals published in 2010 and 2019. Sample 2 consisted of 5,012 papers published in 10 journals between 2010–2019. The 25th, 50th and 75th effect size percentiles were 0.08, 0.17 and 0.33, and 0.17, 0.31, and 0.52 in Samples 1 and 2, respectively. Sample 2 percentiles were probably larger because Sample 2 only included effect sizes from the text but not from tables. In text, authors may have emphasized larger correlations. Large sample sizes were associated with smaller reported correlations. In Sample 1 about 70% of studies specified a directional hypothesis. In 2010, no papers had power calculations while in 2019, 14% of papers had power calculations. These data offer empirical insights into the distribution of reported correlations and may inform the interpretation of effect sizes. They also demonstrate the importance of computation of statistical power and highlight potential reporting bias.

opencc-zeroDec 2022View details →

Different proxies, different stories? Imperfect correlations and different determinants of fitness in bighorn sheep

Measuring individual fitness empirically is required to assess selective pressures and predict evolutionary changes in nature. There is, however, little consensus on how fitness should be empirically estimated. As fitness proxies vary in their underlying assumptions, their relative sensitivity to individual, environmental, and demographic factors may also vary. Here, using a long-term study, we aimed at identifying the determinants of individual fitness in bighorn sheep (Ovis canadensis) using seven fitness proxies. Specifically, we compared four-lifetime fitness proxies: lifetime breeding success, lifetime reproductive success, individual growth rate, and individual contribution to population growth, and three multi-generational proxies: number of granddaughters, individual descendance in the next generation, and relative genetic contribution to the next generation. We found that all proxies were positively correlated, but the magnitude of the correlations varied substantially. Longevity was the main determinant of most fitness proxies. Individual fitness calculated over more than one generation was also affected by population density and growth rate. Because they are affected by contrasting factors, our study suggests that different fitness proxies should not be used interchangeably as they may convey different information about selective pressures and lead to divergent evolutionary predictions. Uncovering the mechanisms underlying variation in individual fitness and improving our ability to predict evolutionary change might require the use of several, rather than one, proxy of individual fitness.

opencc-by-4.0Dec 2022View details →

archive_image_correlation_robust_geometrical_design_of_2D_sequential_interlocking_assemblies

Archive containing the X and Y deformation, obtained by image correlation, of several laser cut samples of assemblies generated using the method described in the article Robust geometrical design of 2D sequential interlocking assemblies (not published yet)

opencc-zeroDec 2022View details →

Data for: Limited host availability disrupts the genetic correlation between virulence and transmission

Virulence is expected to be linked to parasite fitness via transmission. However, it is not clear whether this relationship is genetically determined, nor if it differs when transmission occurs continuously during, or only at the end of, the infection period. Here, we used inbred lines of the macro-parasitic spider mite Tetranychus urticae to disentangle genetic vs non-genetic correlations among traits, while varying parasite density and opportunities for transmission. A positive genetic correlation between virulence and the number of transmitting stages produced was found under continuous transmission. However, if transmission occurred only at the end of the infection period, this genetic correlation disappeared. Instead, we observed a negative relationship between virulence and the number of transmitting stages, driven by density dependence. Thus, within-host density dependence caused by reduced opportunities for transmission may hamper selection for higher virulence, providing a novel explanation as to why limited host availability leads to lower virulence.

opencc-by-4.0Dec 2021View details →

Data for: Neural correlates of individual odor preference in Drosophila

Data associated with: Neural correlates of individual odor preference in Drosophila Abstract: Behavior varies even among genetically identical animals raised in the same environment. However, little is known about the circuit or anatomical origins of this individuality. We show individual Drosophila odor preferences (odor-vs-air and odor-vs-odor) are predicted by idiosyncratic calcium dynamics in olfactory receptor neurons (ORNs) and projection neurons (PNs), respectively. Variation in ORN presynaptic density also predicts odor-vs-odor preference. The ORN-PN synapse appears to be a locus of individuality where microscale variation gives rise to idiosyncratic behavior. Finally, simulating microscale stochasticity in ORN-PN synapses of a 3,062-neuron model of the antennal lobe recapitulates patterns of variation in PN calcium responses matching experiments. Our results demonstrate how physiological and microscale structural circuit variations can give rise to individual behavior, even when genetics and environment are held constant.

opencc-by-4.0Aug 2022View details →

cross-correlations of seismic data nodes Lipari 2018

Stacked cross-correlation functions of the continuous seismic data recorded at the nodes installed at Lipari in 2018. Data in SAC format. All details about stations (name, latitude longitude, elevation) and data ( sampling rate, starting and ending time, etc) are in the HEADER of each file.

opencc-zeroJan 2023View details →

Data from: Female and male plumage brightness is positively correlated among populations of the dichromatic Variable Seedeater

Because studies of plumage coloration often focus on highly elaborate and conspicuous males, little is known about the factors driving the evolution of drab plumage in females of dichromatic species. We explored variation in the color properties of drab female plumage across subspecies of the Variable Seedeater (Sporophila corvina), and found a correlation between plumage brightness of male and female plumage patches. This correlation is consistent with the hypothesis that differences in plumage brightness among females result, at least partially, from a genetic correlation or shared developmental pathway with the more conspicuous male plumage traits that are shaped by sexual selection. Further, we modeled the perception of female plumage using the avian visual system and found that most of the variation in color among females is mostly undetectable by birds; therefore, it is unlikely for such variation to have evolved via direct sexual selection as a signal for recognition or assortative mating. Together, these results suggest that variation in S. corvina female color result from non-adaptive processes. However, we found a reduced variation on color of dorsal patches compared with that of ventral patches among females, which could be explained by natural selection operation on crypsis, reducing the variation on dorsal patches. Finally, we found little differences in plumage color between adult females and juveniles, which suggest selection for juveniles to resemble adult females possibly to reduce aggression from adult males. Additional within-population studies and behavioral experiments are needed to discern the evolutionary factors driving variation on S. corvina female color and its function.

Correlated k coefficients for H2-He atmospheres; 196 spectral windows and 1460 pressure-temperature points

There are 108 correlated k-coefficients datasets, using the naming convention sonora_2020_fehxxxx_co_yyy.data.196.tar.gz (78 models) or sonora_2020_fehxxxx_co_yyy_noTiOVO.data.196.tar.gz (78 models), where xxxx is the metallicity in 10x dex relative to solar, and yyy is the 100x C/O ratio relative to solar, as a multiplication factor. For example a metallicity of +000 and a C/O ratio of 100 indicates solar abundances, feh+070 should be read as a metallicity of +0.7 dex, feh-100 as -1.0 dex, co_025 should be read as 0.25x C/O relative to solar, and co_200 as 2x C/O relative to solar. We use the Lodders et al. 2010 value for the solar C/O=0.458. The files with “noTiOVO” in the filename contain the correlated k-coefficients calculated without the opacity of TiO and VO. The rest of the molecular abundances and opacities are the same as the equilibrium chemistry values in the regular files. These files are useful for calculating models without any TiO- and VO-induced temperature inversion in the atmosphere. The correlated-k coefficients are calculated using pre-mixed opacities, with abundances given by equilibrium chemistry for each metallicity-C/O combination, as described in Marley et al. 2021. There are 13 Fe/H values: 0.0, 0.3, 0.5, 0.7, 1.0, 1.3, 1.5, 1.7, 2.0, -0.3, -0.5, -0.7, and -1.0; and 6 C/O values: 0.25, 0.5, 1.0, 1.5, 2.0 and 2.5. The k-coefficients are calculated for a grid of 1460 pressure-temperature points, from10^−6 to 3000 bar and from 75 to 4000 K, listed in the file 1460_layer_list, and can be read in using the IDL script read_k_coefficients.pro. The spectral windows are listed in the file 196_windows.txt (intervals defined as starting at lambda1 and ending at lambda2). NB Please note that for metallicities between 1.3 and 2.0 the value of max_windows has changed from 200 to 1000. The opacity sources included in the calculations are: C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, Fe, FeH, H2, H3+, H2O, H2S, HCN, LiCl, LiF, LiH, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The corresponding high resolution opacities for these atoms and molecules can be found in the Zenodo repository 10.5281/zenodo.6600976. The references for the line lists used in these opacity calculations are listed in the file Opacity_references_2021.pdf. Please include these references, as well as the reference to this Zenodo repository when publishing your paper. Each dataset contains the following files: ascii_data: the correlated k coefficients file in ascii format. This can be read by the included IDL code. binary_data: the correlated k coefficients file in binary format full_abunds: the relative abundances for all the species from the chemistry files, on the 1460-point pressure-temperature grid sum_in_atoms: relative abundances for the alkali metals sum_in_layer: relative abundances for all molecules included in the correlated k-coefficients calculations Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.

Correlated k coefficients for H2-He atmospheres; 180 spectral windows and 1460 pressure-temperature points

There are 108 correlated k-coefficients datasets, using the naming convention sonora_2020_fehxxxx_co_yyy.data.196.tar.gz (78 models) or sonora_2020_fehxxxx_co_yyy_noTiOVO.data.196.tar.gz (78 models), where xxxx is the metallicity in 10x dex relative to solar, and yyy is the 100x C/O ratio relative to solar, as a multiplication factor. For example a metallicity of +000 and a C/O ratio of 100 indicates solar abundances, feh+070 should be read as a metallicity of +0.7 dex, feh-100 as -1.0 dex, co_025 should be read as 0.25x C/O relative to solar, and co_200 as 2x C/O relative to solar. We use the Lodders et al. 2010 value for the solar C/O=0.458. The files with “noTiOVO” in the filename contain the correlated k-coefficients calculated without the opacity of TiO and VO. The rest of the molecular abundances and opacities are the same as the equilibrium chemistry values in the regular files. These files are useful for calculating models without any TiO- and VO-induced temperature inversion in the atmosphere. The correlated-k coefficients are calculated using pre-mixed opacities, with abundances given by equilibrium chemistry for each metallicity-C/O combination, as described in Marley et al. 2021. There are 13 Fe/H values: 0.0, 0.3, 0.5, 0.7, 1.0, 1.3, 1.5, 1.7, 2.0, -0.3, -0.5, -0.7, and -1.0; and 6 C/O values: 0.25, 0.5, 1.0, 1.5, 2.0 and 2.5. The k-coefficients are calculated for a grid of 1460 pressure-temperature points, from10^−6 to 3000 bar and from 75 to 4000 K, listed in the file 1460_layer_list, and can be read in using the IDL script read_k_coefficients.pro. The spectral windows are listed in the file 180_windows.txt (intervals defined as starting at lambda1 and ending at lambda2). NB Please note that for metallicities between 1.3 and 2.0 the value of max_windows has changed from 200 to 1000. The opacity sources included in the calculations are: C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, Fe, FeH, H2, H3+, H2O, H2S, HCN, LiCl, LiF, LiH, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The corresponding high resolution opacities for these atoms and molecules can be found in the Zenodo repository 10.5281/zenodo.6600976. The references for the line lists used in these opacity calculations are listed in the file Opacity_references_2021.pdf. Please include these references, as well as the reference to this Zenodo repository when publishing your paper. Each dataset contains the following files: ascii_data: the correlated k coefficients file in ascii format. This can be read by the included IDL code. binary_data: the correlated k coefficients file in binary format full_abunds: the relative abundances for all the species from the chemistry files, on the 1460-point pressure-temperature grid sum_in_atoms: relative abundances for the alkali metals sum_in_layer: relative abundances for all molecules included in the correlated k-coefficients calculations Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.

Correlated k coefficients for H2-He atmospheres; 11 spectral windows and 1460 pressure-temperature points

There are 108 correlated k-coefficients datasets, using the naming convention sonora_2020_fehxxxx_co_yyy.data.196.tar.gz (78 models) or sonora_2020_fehxxxx_co_yyy_noTiOVO.data.196.tar.gz (78 models), where xxxx is the metallicity in 10x dex relative to solar, and yyy is the 100x C/O ratio relative to solar, as a multiplication factor. For example a metallicity of +000 and a C/O ratio of 100 indicates solar abundances, feh+070 should be read as a metallicity of +0.7 dex, feh-100 as -1.0 dex, co_025 should be read as 0.25x C/O relative to solar, and co_200 as 2x C/O relative to solar. We use the Lodders et al. 2010 value for the solar C/O=0.458. The files with “noTiOVO” in the filename contain the correlated k-coefficients calculated without the opacity of TiO and VO. The rest of the molecular abundances and opacities are the same as the equilibrium chemistry values in the regular files. These files are useful for calculating models without any TiO- and VO-induced temperature inversion in the atmosphere. The correlated-k coefficients are calculated using pre-mixed opacities, with abundances given by equilibrium chemistry for each metallicity-C/O combination, as described in Marley et al. 2021. There are 13 Fe/H values: 0.0, 0.3, 0.5, 0.7, 1.0, 1.3, 1.5, 1.7, 2.0, -0.3, -0.5, -0.7, and -1.0; and 6 C/O values: 0.25, 0.5, 1.0, 1.5, 2.0 and 2.5. The k-coefficients are calculated for a grid of 1460 pressure-temperature points, from10^−6 to 3000 bar and from 75 to 4000 K, listed in the file 1460_layer_list, and can be read in using the IDL script read_k_coefficients.pro. The spectral windows are listed in the file 11_windows.txt (intervals defined as starting at lambda1 and ending at lambda2). NB Please note that for metallicities between 1.3 and 2.0 the value of max_windows has changed from 200 to 1000. The opacity sources included in the calculations are: C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, Fe, FeH, H2, H3+, H2O, H2S, HCN, LiCl, LiF, LiH, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The corresponding high resolution opacities for these atoms and molecules can be found in the Zenodo repository 10.5281/zenodo.6600976. The references for the line lists used in these opacity calculations are listed in the file Opacity_references_2021.pdf. Please include these references, as well as the reference to this Zenodo repository when publishing your paper. Each dataset contains the following files: ascii_data: the correlated k coefficients file in ascii format. This can be read by the included IDL code. binary_data: the correlated k coefficients file in binary format full_abunds: the relative abundances for all the species from the chemistry files, on the 1460-point pressure-temperature grid sum_in_atoms: relative abundances for the alkali metals sum_in_layer: relative abundances for all molecules included in the correlated k-coefficients calculations Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.

Correlated k coefficients for H2-He atmospheres; 30 spectral windows and 1460 pressure-temperature points

There are 108 correlated k-coefficients datasets, using the naming convention sonora_2020_fehxxxx_co_yyy.data.196.tar.gz (78 models) or sonora_2020_fehxxxx_co_yyy_noTiOVO.data.196.tar.gz (78 models), where xxxx is the metallicity in 10x dex relative to solar, and yyy is the 100x C/O ratio relative to solar, as a multiplication factor. For example a metallicity of +000 and a C/O ratio of 100 indicates solar abundances, feh+070 should be read as a metallicity of +0.7 dex, feh-100 as -1.0 dex, co_025 should be read as 0.25x C/O relative to solar, and co_200 as 2x C/O relative to solar. We use the Lodders et al. 2010 value for the solar C/O=0.458. The files with “noTiOVO” in the filename contain the correlated k-coefficients calculated without the opacity of TiO and VO. The rest of the molecular abundances and opacities are the same as the equilibrium chemistry values in the regular files. These files are useful for calculating models without any TiO- and VO-induced temperature inversion in the atmosphere. The correlated-k coefficients are calculated using pre-mixed opacities, with abundances given by equilibrium chemistry for each metallicity-C/O combination, as described in Marley et al. 2021. There are 13 Fe/H values: 0.0, 0.3, 0.5, 0.7, 1.0, 1.3, 1.5, 1.7, 2.0, -0.3, -0.5, -0.7, and -1.0; and 6 C/O values: 0.25, 0.5, 1.0, 1.5, 2.0 and 2.5. The k-coefficients are calculated for a grid of 1460 pressure-temperature points, from10^−6 to 3000 bar and from 75 to 4000 K, listed in the file 1460_layer_list, and can be read in using the IDL script read_k_coefficients.pro. The spectral windows are listed in the file 30_windows.txt (intervals defined as starting at lambda1 and ending at lambda2). NB Please note that for metallicities between 1.3 and 2.0 the value of max_windows has changed from 200 to 1000. The opacity sources included in the calculations are: C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, Fe, FeH, H2, H3+, H2O, H2S, HCN, LiCl, LiF, LiH, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The corresponding high resolution opacities for these atoms and molecules can be found in the Zenodo repository 10.5281/zenodo.6600976. The references for the line lists used in these opacity calculations are listed in the file Opacity_references_2021.pdf. Please include these references, as well as the reference to this Zenodo repository when publishing your paper. Each dataset contains the following files: ascii_data: the correlated k coefficients file in ascii format. This can be read by the included IDL code. binary_data: the correlated k coefficients file in binary format full_abunds: the relative abundances for all the species from the chemistry files, on the 1460-point pressure-temperature grid sum_in_atoms: relative abundances for the alkali metals sum_in_layer: relative abundances for all molecules included in the correlated k-coefficients calculations Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.

opencc-zeroJan 2023View details →

Mapping the correlations and gaps in studies of complex life histories

For species with complex life histories, phenotypic correlations between life-history stages constrain both ecological and evolutionary trajectories. Studies that seek to understand correlations across life history differ greatly in their experimental approach: some follow individuals ("individual longitudinal"), while others follow cohorts ("cohort longitudinal"). Cohort longitudinal studies risk confounding results through Simpson's Paradox, where correlations observed at the cohort-level do not match that of the individual-level. Individual longitudinal studies are laborious in comparison, but provide a more reliable test of correlations across life-history stages. Our understanding of the prevalence, strength and direction of phenotypic correlations depends on the approaches that we use, but the relative representation of different approaches is unknown. Using marine invertebrates as a model group, we used a formal, systematic literature map to screen 17,000+ papers studying complex life histories, and characterized the study type (i.e. cohort longitudinal, individual longitudinal or single stage), as well as other factors. For 3,315 experiments from 1,716 articles, most (67.4%) focused on a single stage, and just 1.7% used an individual longitudinal approach. While life-history stages have been studied extensively, we suggest that the field prioritize individual longitudinal studies to understand the phenotypic correlations among stages.

opencc-zeroJan 2023View details →

Spatial genetic differentiation correlates with species assemblage turnover across tropical reef fish lineages

Aim: Evaluating the similarity of diversity patterns across micro- to macroevolutionary scales in natural communities, such as species-genetic diversity correlations (SGDC), may inform on processes shaping community assembly. However, whether SGDCs not only hold across communities but also across lineages has never been explored so far. Here we investigated SGDCs across co-distributed taxa for different spatial components (α, β, γ), and formally tested the influence of dispersal traits on β SGDCs. Location: Western Indian Ocean Time period: 2016–2017 Major taxa studied: Tropical reef fish species with contrasting dispersal traits Methods: Using ddRADseq single nucleotide polymorphism (SNP) data for 20 tropical reef fishes and distribution data of 2,446 species belonging to 12 families, we analysed the correlations between within-species genetic diversity and within-family species diversity (i.e., lineage diversity) for the three spatial components (α, β, γ SGDCs). We then related the strength of β-SGDCs per species to proxies of larval dispersal abilities. Results: We detected positive and significant lineage-based SGDC only for the β component, i.e., the families showing the greatest level of species turnover among sites contains the species with the greatest levels of genetic differentiation. We showed that the Monsoon drift mainly explained the β diversity patterns at both intraspecific and interspecific levels. Higher β-SGDCs were found for species with short pelagic larval duration and weak larval swimming capacity. Main conclusions: Our study reveals a strong correlation between genetic and species β diversity, a result explained by the presence of a 'soft' barrier and mediated by larval dispersal processes. This suggests that vicariance and dispersal limitation are major processes shaping β-diversity patterns from microevolutionary to macroevolutionary scales in tropical reef fishes.

opencc-by-4.0Feb 2023View details →

SourceData for "Correlating the charge transfer gap to the maximum transition temperature in Bi2Sr2Can-1CunO2n+4+x"

SourceData for "Correlating the charge transfer gap to the maximum transition temperature in Bi2Sr2Can-1CunO2n+4+x"

opencc-zeroFeb 2023View details →

Data for: Phylogenetically controlled life history trait meta-analysis in cetaceans reveals unexpected negative brain size and longevity correlation

The identification of patterns in trait evolution is essential to understand the interaction of evolutionary forces, and provides useful information for species management. Cetaceans are a phylogenetically well-resolved infraorder that exhibit distinct trait variation across behavioural, molecular and life history dimensions, yet few researchers have applied a meta-analytic or comparative approach to these traits. To understand cetacean trait evolution, we used a phylogenetic generalised least squares approach to examine the cognitive buffer hypothesis (CBH). A large brain should buffer individuals against environmental challenges through increasing survival rates, and a longer lifespan should buffer individuals against the cost of extended development for larger brains according to the CBH, leading to an expected positive correlation between brain size and lifespan. In contrast to this expectation, previously observed in taxa including primates, we found a negative correlation between brain size and lifespan in cetaceans. This suggests cetaceans experience selective pressures different from most other mammals in these traits but may be more similar to some social mammalian carnivores that display alloparenting. We also provide a comprehensive dataset to explore additional aspects of trait evolution but which would greatly benefit from studies on behavioural ecology across cetaceans and increased focus on data-deficient species.

opencc-zeroFeb 2023View details →

Acoustic activity of bats at power lines correlates with relative humidity: A potential role for corona discharges

With the ever-increasing dependency on electric power, electrical grid networks are expanding worldwide. Bats exhibit a wide diversity of foraging and flight behaviours, and their sensitivity to anthropogenic stressors suggests this group is very likely to be affected by power lines in a myriad of ways. Yet the effects of power lines on bats remain unknown. Here we assessed the responses of insectivorous bats to very-high-voltage power lines (>220 kV, VHVPL). We implemented a paired sampling design and monitored bats acoustically at 25 pairs, one pair consisting of one forest edge near to VHVPL matched with one control forest edge. Relative humidity mediates the effects of power lines on bats: we detected bat attraction to VHVPL at high relative humidity levels and avoidance of VHVPL by bats at low relative humidity levels. We argue that the former could be explained by insect attraction to the light emitted by VHVPL due to corona discharges while the latter may be due to the physical presence of pylons/cables at foraging height and/or because of electromagnetic fields. Our work highlights the response of bats to power lines at foraging habitats, providing new insight into the interactions between power lines and biodiversity.

opencc-by-4.0Feb 2023View details →

Aerogel Spring-Back Correlates with Strain Recovery: Effect of Silica Concentration and Aging - Dataset

Dataset corresponding to the scientific publication: Sivaraman, Deeptanshu, Shanyu Zhao, Subramaniam Iswar, Marco Lattuada, and Wim J. Malfait. "Aerogel Spring‐Back Correlates with Strain Recovery: Effect of Silica Concentration and Aging." Advanced Engineering Materials 23, no. 10 (2021): 2100376. <a href="https://doi.org/10.1002/adem.202100376">https://doi.org/10.1002/adem.202100376</a> This project was funded by the Swiss National Science Foundation through grant 200021_179000 (W.J.M). S.I. acknowledges the Flemish agency “Agentschap Innoveren en Ondernemen” (VLAIO) for providing financial support of this research through subvention IWT 130668.

opencc-by-4.0Dec 2021View details →

Data for: Neural correlates of individual odor preference in Drosophila

Data associated with: Neural correlates of individual odor preference in Drosophila Behavior varies even among genetically identical animals raised in the same environment. However, little is known about the circuit or anatomical origins of this individuality. We show individual Drosophila odor preferences (odor-vs-air and odor-vs-odor) are predicted by idiosyncratic calcium dynamics in olfactory receptor neurons (ORNs) and projection neurons (PNs), respectively. Variation in ORN presynaptic density also predicts odor-vs-odor preference. The ORN-PN synapse appears to be a locus of individuality where microscale variation gives rise to idiosyncratic behavior. Finally, simulating microscale stochasticity in ORN-PN synapses of a 3,062-neuron model of the antennal lobe recapitulates patterns of variation in PN calcium responses matching experiments. Our results demonstrate how physiological and microscale structural circuit variations can give rise to individual behavior, even when genetics and environment are held constant.