cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.4210863.v195
title: Modality switch effects emerge early and increase throughout conceptual processing: Evidence from ERPs

description: Conference paper in <i>Proceedings of the 39th Annual Conference of the Cognitive Science Society.</i>Files: paper, poster, design overview, stimuli, EEG montage used, waveforms, window 1 close-ups, mean differences with 95% CIs, subtraction topographies, detailed waveforms, statistical results, fixed effects of final models, entire modeling, raw data. For best resolution, download file(s). Waveforms per participant and electrode (link). <b>OSF archive with all data and code (link).</b><b>Abstract </b>We tested whether conceptual processing is modality-specific by tracking the time course of the Conceptual Modality Switch effect. Forty-six participants verified the relation between property words and concept words. The conceptual modality of consecutive trials was manipulated in order to produce an Auditory-to-visual switch condition, a Haptic-to-visual switch condition, and a Visual-to-visual, no-switch condition. Event-Related Potentials (ERPs) were time-locked to the onset of the first word (property) in the target trials so as to measure the effect online and to avoid a within-trial confound. A switch effect was found, characterized by more negative ERP amplitudes for modality switches than no-switches. It proved significant in three typical time windows from 270 to 750 milliseconds post word onset, with greater strength in the Slow group, in posterior brain regions, and in the N400 window. These results suggest that conceptual processing may be modality-specific in certain tasks, but also that the early stage of processing is relatively amodal.<b></b><b></b><b></b><b></b><b></b><b></b>ReferencesCollins, J., Pecher, D., Zeelenberg, R., & Coulson, S. (2011). Modality switching in a property verification task: an ERP study of what happens when candles flicker after high heels click. <i>Frontiers in Psychology, 2.</i>Hald, L. A., Marshall, J.-A., Janssen, D. P., & Garnham, A. (2011). Switching modalities in a sentence verification task: ERP evidence for embodied language processing. <i>Frontiers in Psychology, 2.</i> Hauk, O. (2016). Only time will tell—Why temporal information is essential for our neuroscientific understanding of semantics. <i>Psychonomic Bulletin & Review, 23</i>.<i></i>Louwerse, M., & Connell, L. (2011). A taste of words: linguistic context and perceptual simulation predict the modality of words. <i>Cognitive Science, 35, </i>2, 381-98.Mahon, B.Z., & Hickok, G. (2016). Arguments about the nature of concepts: Symbols, embodiment, and beyond. <em>Psychonomic Bulletin & Review, 23, </em>941-958.
DOI: 10.7910/dvn/v1rjpf/jftzyf
title: cbb20151230_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/toda8v
title: cbb20150419_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/vvngxc
title: cbb20150220_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/ummucd
title: cbb20151213_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4210863.v198
title: Modality switch effects emerge early and increase throughout conceptual processing: Evidence from ERPs

description: Files: poster, paper, design overview, stimuli, EEG montage used, waveforms, window 1 close-ups, mean differences with 95% CIs, subtraction topographies, detailed waveforms, statistical results, fixed effects of final models, entire modeling, raw data. For best resolution, download file(s).<b>Abstract </b><b></b>We tested whether conceptual processing is modality-specific by tracking the time course of the Conceptual Modality Switch effect. Forty-six participants verified the relation between property words and concept words. The conceptual modality of consecutive trials was manipulated in order to produce an Auditory-to-visual switch condition, a Haptic-to-visual switch condition, and a Visual-to-visual, no-switch condition. Event-Related Potentials (ERPs) were time-locked to the onset of the first word (property) in the target trials so as to measure the effect online and to avoid a within-trial confound. A switch effect was found, characterized by more negative ERP amplitudes for modality switches than no-switches. It proved significant in three typical time windows from 270 to 750 milliseconds post word onset, with greater strength in the Slow group, in posterior brain regions, and in the N400 window. These results suggest that conceptual processing may be modality-specific in certain tasks, but also that the early stage of processing is relatively amodal.<br><b></b><b></b><b></b><b></b><b></b><b></b>ReferencesCollins, J., Pecher, D., Zeelenberg, R., & Coulson, S. (2011). Modality switching in a property verification task: an ERP study of what happens when candles flicker after high heels click. <i>Frontiers in Psychology, 2.</i>Hald, L. A., Marshall, J.-A., Janssen, D. P., & Garnham, A. (2011). Switching modalities in a sentence verification task: ERP evidence for embodied language processing. <i>Frontiers in Psychology, 2.</i> Hauk, O. (2016). Only time will tell—Why temporal information is essential for our neuroscientific understanding of semantics. <i>Psychonomic Bulletin & Review, 23</i>.<i></i>Louwerse, M., & Connell, L. (2011). A taste of words: Linguistic context and perceptual simulation predict the modality of words. <i>Cognitive Science, 35, </i>2, 381-98.Mahon, B.Z., & Hickok, G. (2016). Arguments about the nature of concepts: Symbols, embodiment, and beyond. <em>Psychonomic Bulletin & Review, 23, </em>941-958.<b>-</b> Web app for plotting waveforms in each data section (link).<br><b>- </b>OSF archive with all data and code (link).<b>- </b>Paper in <i>Proceedings of the 39th Annual Conference of the Cognitive Science Society.</i><br><br>Bernabeu, P., Willems, R. M., & Louwerse, M. M. (2017). Modality switch effects emerge early and increase throughout conceptual processing: Evidence from ERPs.<i> </i>In G. Gunzelmann, A. Howes, T. Tenbrink, & E. J. Davelaar (Eds.),<i> Proceedings of the 39th Annual Conference of the Cognitive Science Society </i>(pp. 1629-1634). Austin, TX: Cognitive Science Society.<br>
DOI: 10.7910/dvn/v1rjpf/v7efrw
title: cbb20150516_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4210863.v199
title: Modality switch effects emerge early and increase throughout conceptual processing: Evidence from ERPs

description: Files: poster, paper, design overview, stimuli, EEG montage used, waveforms, window 1 close-ups, mean differences with 95% CIs, subtraction topographies, detailed waveforms, statistical results, fixed effects of final models, entire modelling, raw data. For best resolution, download file(s).Abstract <b></b>We tested whether conceptual processing is modality-specific by tracking the time course of the Conceptual Modality Switch effect. Forty-six participants verified the relation between property words and concept words. The conceptual modality of consecutive trials was manipulated in order to produce an Auditory-to-visual switch condition, a Haptic-to-visual switch condition, and a Visual-to-visual, no-switch condition. Event-Related Potentials (ERPs) were time-locked to the onset of the first word (property) in the target trials so as to measure the effect online and to avoid a within-trial confound. A switch effect was found, characterised by more negative ERP amplitudes for modality switches than no-switches. It proved significant in three typical time windows from 270 to 750 milliseconds post word onset, with greater strength in the Slow group, in posterior brain regions, and in the N400 window. These results suggest that conceptual processing may be modality-specific in certain tasks, but also that the early stage of processing is relatively amodal.<br><b></b><b></b><b></b><b></b><b></b><b></b>ReferencesCollins, J., Pecher, D., Zeelenberg, R., & Coulson, S. (2011). Modality switching in a property verification task: an ERP study of what happens when candles flicker after high heels click. <i>Frontiers in Psychology, 2.</i>Hald, L. A., Marshall, J.-A., Janssen, D. P., & Garnham, A. (2011). Switching modalities in a sentence verification task: ERP evidence for embodied language processing. <i>Frontiers in Psychology, 2.</i> Hauk, O. (2016). Only time will tell—Why temporal information is essential for our neuroscientific understanding of semantics. <i>Psychonomic Bulletin & Review, 23</i>.<i></i>Louwerse, M., & Connell, L. (2011). A taste of words: Linguistic context and perceptual simulation predict the modality of words. <i>Cognitive Science, 35, </i>2, 381-98.Mahon, B.Z., & Hickok, G. (2016). Arguments about the nature of concepts: Symbols, embodiment, and beyond. <em>Psychonomic Bulletin & Review, 23, </em>941-958.Find more information on these links:<b>-</b> Interactive visualisation of waveforms in each data section (Shiny app).<br><b>- </b>OSF archive with all data and code.<b>- </b>Paper in <i>Proceedings of the 39th Annual Conference of the Cognitive Science Society</i><i>.</i>Bernabeu, P., Willems, R. M., & Louwerse, M. M. (2017). Modality switch effects emerge early and increase throughout conceptual processing: Evidence from ERPs.<i> </i>In G. Gunzelmann, A. Howes, T. Tenbrink, & E. J. Davelaar (Eds.),<i> Proceedings of the 39th Annual Conference of the Cognitive Science Society </i>(pp. 1629-1634). Austin, TX: Cognitive Science Society.<br>
DOI: 10.7910/dvn/v1rjpf/hq5lsw
title: cbb20150711_03.txt.gz

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DOI: 10.7910/dvn/v1rjpf/ymxbtu
title: cbb20150615_03.txt.gz

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DOI: 10.6084/m9.figshare.4206381
title: Microbiome Raw Sequence

description: Microbiome Raw Sequence
DOI: 10.7910/dvn/v1rjpf/zxpel4
title: cbb20151217_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4206381.v1
title: Microbiome Raw Sequence

description: Microbiome Raw Sequence
DOI: 10.7910/dvn/v1rjpf/uolgvn
title: cbb20150205_03.txt.gz

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DOI: 10.7910/dvn/v1rjpf/ydyvuo
title: cbb20151007_03.txt.gz

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DOI: 10.7910/dvn/v1rjpf/wfcjx5
title: cbb20150618_03.txt.gz

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DOI: 10.7910/dvn/v1rjpf/bf98ri
title: cbb20151028_03.txt.gz

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DOI: 10.7910/dvn/v1rjpf/scc1x1
title: cbb20151025_03.txt.gz

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DOI: 10.7910/dvn/v1rjpf/hqcbh2
title: cbb20150612_03.txt.gz

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DOI: 10.7910/dvn/v1rjpf/avcm8s
title: cbb20151002_03.txt.gz

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DOI: 10.7910/dvn/v1rjpf/7quxzo
title: cbb20150126_03.txt.gz

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DOI: 10.7910/dvn/v1rjpf/hg9asx
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DOI: 10.7910/dvn/v1rjpf/1sakzd
title: cbb20150602_03.txt.gz

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DOI: 10.6084/m9.figshare.4206294.v1
title: Dynamic Selection of Classifiers in Bug Prediction: an Adaptive Method

description: This files contains the online appendix of the TETCI submission of the paper named "Dynamic Selection of Classifiers in Bug Prediction: an Adaptive Method"
DOI: 10.7910/dvn/v1rjpf/oowmzh
title: cbb20150525_03.txt.gz

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DOI: 10.7910/dvn/v1rjpf/m2stop
title: cbb20150416_03.txt.gz

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DOI: 10.6084/m9.figshare.4206252
title: Heavy Minerals. A detrital record of the Nile River and its catchment

description: Supplementary item 4: Heavy Minerals
DOI: 10.6084/m9.figshare.4206255
title: Tracer isotope data. A detrital record of the Nile River and its catchment

description: Supplementary Item 12: Tracer isotope data.
DOI: 10.7910/dvn/v1rjpf/2ivvfp
title: cbb20150125_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4206255.v1
title: Tracer isotope data. A detrital record of the Nile River and its catchment

description: Supplementary Item 12: Tracer isotope data.
DOI: 10.6084/m9.figshare.4206252.v1
title: Heavy Minerals. A detrital record of the Nile River and its catchment

description: Supplementary item 4: Heavy Minerals
DOI: 10.6084/m9.figshare.4206246
title: U–Pb zircon data. A detrital record of the Nile River and its catchment

description: Supplementary Item 6: U–Pb zircon data
DOI: 10.7910/dvn/v1rjpf/jo3wli
title: cbb20150608_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4206246.v1
title: U–Pb zircon data. A detrital record of the Nile River and its catchment

description: Supplementary Item 6: U–Pb zircon data
DOI: 10.6084/m9.figshare.4206240
title: Sample Information. A detrital record of the Nile River and its catchment

description: Supplementary Item 1: Sample information
DOI: 10.6084/m9.figshare.4206243
title: Cenozoic zircon age calculations. A detrital record of the Nile River and its catchment

description: Supplementary Item 9: Cenozoic zircon age calculations.
DOI: 10.7910/dvn/v1rjpf/xt9yti
title: cbb20150425_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4206243.v1
title: Cenozoic zircon age calculations. A detrital record of the Nile River and its catchment

description: Supplementary Item 9: Cenozoic zircon age calculations.
DOI: 10.6084/m9.figshare.4206237
title: Additional U–Pb and Hf data from the Hammamat Formation. A detrital record of the Nile River and its catchment

description: Supplementary Item 8: additional U–Pb and Hf data from the Hammamat Formation
DOI: 10.7910/dvn/v1rjpf/kkyvjc
title: cbb20150609_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4206234
title: U–Pb rutile data. A detrital record of the Nile River and its catchment

description: Supplementary Item 10: U–Pb rutile data
DOI: 10.6084/m9.figshare.4206240.v1
title: Sample Information. A detrital record of the Nile River and its catchment

description: Supplementary Item 1: Sample information
DOI: 10.6084/m9.figshare.4206234.v1
title: U–Pb rutile data. A detrital record of the Nile River and its catchment

description: Supplementary Item 10: U–Pb rutile data
DOI: 10.7910/dvn/v1rjpf/xfu833
title: cbb20151010_03.txt.gz

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DOI: 10.6084/m9.figshare.4206225
title: Ar–Ar mica and plagioclase data. A detrital record of the Nile River and its catchment

description: Supplementary Item 11: Ar–Ar mica and plagioclase data
DOI: 10.7910/dvn/v1rjpf/pbxor7
title: cbb20150822_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4206225.v1
title: Ar–Ar mica and plagioclase data. A detrital record of the Nile River and its catchment

description: Supplementary Item 11: Ar–Ar mica and plagioclase data
DOI: 10.6084/m9.figshare.4206219
title: Major and trace element data. A detrital record of the Nile River and its catchment

description: Supplementary Item 5: Major and trace element data
DOI: 10.7910/dvn/v1rjpf/ej1qqm
title: cbb20151218_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4206219.v1
title: Major and trace element data. A detrital record of the Nile River and its catchment

description: Supplementary Item 5: Major and trace element data
DOI: 10.6084/m9.figshare.4206213
title: Lu–Hf zircon data. A detrital record of the Nile River and its catchment

description: Supplementary Item 7: Lu–Hf zircon data
DOI: 10.7910/dvn/v1rjpf/qjbsmh
title: cbb20150815_03.txt.gz

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DOI: 10.7910/dvn/v1rjpf/t0dtfj
title: cbb20150717_03.txt.gz

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DOI: 10.6084/m9.figshare.4206204
title: Petrography. A detrital record of the Nile River and its catchment

description: Supplementary Item 3: Petrography
DOI: 10.7910/dvn/v1rjpf/xe7rsn
title: cbb20150208_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4206204.v1
title: Petrography. A detrital record of the Nile River and its catchment

description: Supplementary Item 3: Petrography
DOI: 10.7910/dvn/v1rjpf/tbgoyz
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DOI: 10.6084/m9.figshare.4206186
title: Appendix S3. Indian Ocean whale shark database from The ecological connectivity of whale shark aggregations in the Indian Ocean: a photo-identification approach

description: Genetic and modelling studies suggest that seasonal aggregations of whale sharks (<i>Rhincodon typus</i>) at coastal sites in the tropics may be linked by migration. Here, we used photo-identification data collected by both citizen scientists and researchers to assess the connectedness of five whale shark aggregation sites across the entire Indian Ocean at timescales of up to a decade. We used the semi-automated programme I<sup>3</sup>S (Individual Interactive Identification System) to compare photographs of the unique natural marking patterns of individual whale sharks collected from aggregations at Mozambique, the Seychelles, the Maldives, Christmas Island (Australia) and Ningaloo Reef (Australia). From a total of 6519 photos, we found no evidence of connectivity of whale shark aggregations at ocean-basin scales within the time frame of the study and evidence for only limited connectivity at regional (100-1000km) scales. A male whale shark photographed in January 2010 at Mozambique was resighted eight months later in the Seychelles and was the only one of 1724 individuals in the database to be photographed at more than one site. On average, 35% of individuals were re-sighted at the same site in more than one year. A Monte Carlo simulation study showed that the power of this photo-ID approach to document patterns of emigration and immigration was strongly dependent on both the number of individuals identified in aggregations and the size of resident populations.
DOI: 10.7910/dvn/v1rjpf/b31xby
title: cbb20150304_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4206186.v1
title: Appendix S3. Indian Ocean whale shark database from The ecological connectivity of whale shark aggregations in the Indian Ocean: a photo-identification approach

description: Genetic and modelling studies suggest that seasonal aggregations of whale sharks (<i>Rhincodon typus</i>) at coastal sites in the tropics may be linked by migration. Here, we used photo-identification data collected by both citizen scientists and researchers to assess the connectedness of five whale shark aggregation sites across the entire Indian Ocean at timescales of up to a decade. We used the semi-automated programme I<sup>3</sup>S (Individual Interactive Identification System) to compare photographs of the unique natural marking patterns of individual whale sharks collected from aggregations at Mozambique, the Seychelles, the Maldives, Christmas Island (Australia) and Ningaloo Reef (Australia). From a total of 6519 photos, we found no evidence of connectivity of whale shark aggregations at ocean-basin scales within the time frame of the study and evidence for only limited connectivity at regional (100-1000km) scales. A male whale shark photographed in January 2010 at Mozambique was resighted eight months later in the Seychelles and was the only one of 1724 individuals in the database to be photographed at more than one site. On average, 35% of individuals were re-sighted at the same site in more than one year. A Monte Carlo simulation study showed that the power of this photo-ID approach to document patterns of emigration and immigration was strongly dependent on both the number of individuals identified in aggregations and the size of resident populations.
DOI: 10.7910/dvn/v1rjpf/bwf7ib
title: cbb20150503_03.txt.gz

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DOI: 10.6084/m9.figshare.4205898
title: Supplement 2 from The impact of cerebellar transcranial direct current stimulation (tDCS) on learning fine-motor sequences

description: Raw data
DOI: 10.7910/dvn/v1rjpf/tfqpkl
title: cbb20160727_03.txt.gz

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DOI: 10.6084/m9.figshare.4205898.v1
title: Supplement 2 from The impact of cerebellar transcranial direct current stimulation (tDCS) on learning fine-motor sequences

description: Raw data
DOI: 10.7910/dvn/v1rjpf/llg0hp
title: cbb20160609_03.txt.gz

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DOI: 10.6084/m9.figshare.4205760
title: Supplemental-File-1 from Evolution in eggs and phases: experimental evolution of fecundity and reproductive timing in <i>Caenorhabditis elegans</i>

description: To examine the role of natural selection on fecundity in a variety of Caenorhabditis elegans genetic backgrounds, we used an experimental evolution protocol to evolve 14 distinct genetic strains over 15-20 generations. We were able to generate 790 distinct genealogies, which provided information on both the effects of natural selection and the evolvability of each strain. Among these genotypes are a wild-type (N2) and a collection of mutants with targeted mutations in the daf-c, daf-d and AMPK pathways. Differences are observed in reproductive fitness along with related changes in reproductive timing. The majority of selective effects on fecundity occur during the first few generations of evolution, while the negative selection for reproductive timing occurs on longer time scales. In addition, positive selection on fecundity results in positive and negative strain-dependent selection on reproductive timing. A derivative of population size per generation called reproductive carry-over (RCO) may be informative in terms of developmental selection. While these findings transcend mutations in a specific gene, changes in the RCO measure may nevertheless be products of selection. In conclusion, the broader implications of these findings are discussed, particularly in the context of genotype-fitness maps and the role of uncharacterized mutations in individual variation and evolvability.