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normalized histogram with single exponential decay function  (OriginLab corp)

 
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    OriginLab corp normalized histogram with single exponential decay function
    Normalized Histogram With Single Exponential Decay Function, supplied by OriginLab corp, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/normalized histogram with single exponential decay function/product/OriginLab corp
    Average 90 stars, based on 1 article reviews
    normalized histogram with single exponential decay function - by Bioz Stars, 2026-03
    90/100 stars

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    a, Schematic representation of the behavioral paradigm designed to evaluate olfactory and tactospatial WM (OWM and TSWM, respectively) in head-restrained mice. For each trial, both sample and target cues were presented for one second (see main text and methods for further details). b, Learning curves for OWM and TSWM tasks (fixed intercue delay of 5 and 1s, respectively; the number of mice is indicated; one-way repeated measures ANOVA). c, Change in performance between the first and the last 100 trials of the training phase shown in b for each mouse (black lines; paired t-test) and the mean population performance (colored bars). d, WM performances plotted as a function of the intercue delay duration (2WRM ANOVA, post-hoc Fisher’s test *: P < 0.05). e, Variability of WM performance across all individual animals shown for the D-prime parameter computed during the OWM task. Examples of <t>exponential</t> fit (used to calculate the amplitude at 0 delay and the half-life) of a few individual performance curves are illustrated (red dashed lines). f-h, Comparison of WM performance amplitude at 0 delay and half-life for OWM and TSWM tasks (unpaired t-test). i, Cumulative probability distribution of half-lives for OWM and TSWM tasks (Kolmogorov- Smirnov test). Data in b , d , f-h are presented as mean ± SEM. See Supplementary Table 1 for detailed statistics.
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    Image Search Results


    a, Schematic representation of the behavioral paradigm designed to evaluate olfactory and tactospatial WM (OWM and TSWM, respectively) in head-restrained mice. For each trial, both sample and target cues were presented for one second (see main text and methods for further details). b, Learning curves for OWM and TSWM tasks (fixed intercue delay of 5 and 1s, respectively; the number of mice is indicated; one-way repeated measures ANOVA). c, Change in performance between the first and the last 100 trials of the training phase shown in b for each mouse (black lines; paired t-test) and the mean population performance (colored bars). d, WM performances plotted as a function of the intercue delay duration (2WRM ANOVA, post-hoc Fisher’s test *: P < 0.05). e, Variability of WM performance across all individual animals shown for the D-prime parameter computed during the OWM task. Examples of exponential fit (used to calculate the amplitude at 0 delay and the half-life) of a few individual performance curves are illustrated (red dashed lines). f-h, Comparison of WM performance amplitude at 0 delay and half-life for OWM and TSWM tasks (unpaired t-test). i, Cumulative probability distribution of half-lives for OWM and TSWM tasks (Kolmogorov- Smirnov test). Data in b , d , f-h are presented as mean ± SEM. See Supplementary Table 1 for detailed statistics.

    Journal: bioRxiv

    Article Title: The claustrum is critical for maintaining working memory information

    doi: 10.1101/2024.10.28.620649

    Figure Lengend Snippet: a, Schematic representation of the behavioral paradigm designed to evaluate olfactory and tactospatial WM (OWM and TSWM, respectively) in head-restrained mice. For each trial, both sample and target cues were presented for one second (see main text and methods for further details). b, Learning curves for OWM and TSWM tasks (fixed intercue delay of 5 and 1s, respectively; the number of mice is indicated; one-way repeated measures ANOVA). c, Change in performance between the first and the last 100 trials of the training phase shown in b for each mouse (black lines; paired t-test) and the mean population performance (colored bars). d, WM performances plotted as a function of the intercue delay duration (2WRM ANOVA, post-hoc Fisher’s test *: P < 0.05). e, Variability of WM performance across all individual animals shown for the D-prime parameter computed during the OWM task. Examples of exponential fit (used to calculate the amplitude at 0 delay and the half-life) of a few individual performance curves are illustrated (red dashed lines). f-h, Comparison of WM performance amplitude at 0 delay and half-life for OWM and TSWM tasks (unpaired t-test). i, Cumulative probability distribution of half-lives for OWM and TSWM tasks (Kolmogorov- Smirnov test). Data in b , d , f-h are presented as mean ± SEM. See Supplementary Table 1 for detailed statistics.

    Article Snippet: The accuracy and D-prime values of the WM tasks at varying delay durations were modeled using an exponential decay function in GraphPad Prism 9.0.

    Techniques: Comparison