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322 results for “dopaminergic”
Neurothreads: development of supportive carriers for mature dopaminergic neuron differentiation and implantation
<p>Raw data for the publication:</p> <p><strong>Neurothreads: development of supportive carriers for mature dopaminergic neuron differentiation and implantation</strong></p>
BIDS Data for "A Whole-Brain Map and Assay Parameter Analysis of Mouse VTA Dopaminergic Activation"
<p>Base data package for the “"A Whole-Brain Map and Assay Parameter Analysis of Mouse VTA Dopaminergic Activation” article, formatted corresponding to the Brain Imaging Data Structure.</p>
Original single session datasets from "Slowly evolving dopaminergic activity modulates the moment-to-moment probability of reward-related self-timed movements."
<p>This archive contains the original single-session recording datasets associated with the paper "Slowly evolving dopaminergic activity modulates the moment-to-moment probability of reward-related self-timed movements" by Allison E Hamilos, Giulia Spedicato, Ye Hong, Fangmiao Sun, Yulong Li, and John A Assad (https://doi.org/10.1101/2020.05.13.094904). Files can be loaded and collated with code from our GitHub repository to reproduce all analyses (https://www.github.com/harvardschoolofmouse).</p>
Raw dataset and additional data for article "Nonmotor symptoms associated with progressive loss of dopaminergic neurons in a mouse model of Parkinson's disease"
<p>Dataset from the project investigating the presence of nonmotor symptoms of Parkinson's disease in a mouse model of progressive loss of dopaminergic neurons (namely,TIF-IADATCreERT2 strain). Mice were tested for executive and cognitive functions (males: Operant Sensation Seeking test, OSS; females: Probabilistic Reversal Learning Task in Intellicages), olfactory acuity (males: buried food test), saccharin preference (males and females), and motor performance (males and females: test using CatWalk apparatus).</p><p>The dataset includes files used to perform statistical analyses but their names may vary from the ones used in the scripts. For the purpose of recreating our analyses, please refer to the GitHub page, where both scripts and input data file names (in 'Raw data files' section) are compliant: https://github.com/annaradli/tif-pd-behavior.</p><p><strong>Description of files:</strong></p><p><i>Raw data files:</i></p><ul><li>animals_info.csv - animals data: genotype, sex, age, Intellicage tag identifier</li><li>catwalk_run_statistics_all_females.csv - data recorded in CatWalk apparatus for females</li><li>catwalk_run_statistics_all_males.csv - data recorded in CatWalk apparatus for males</li><li>females_weight_raw_data_revised.csv - females' body weight (revised for containing Polish words)</li><li>intellicage_raw_data.csv - data recorded in IntelliCage exported to .csv format</li><li>intellicage_raw_data_R.RData - data recorded in IntelliCage in .RData format</li><li>males_weight_raw_data.csv - males' body weight</li><li>olfactory_time_digging_raw_data.csv - time to start digging at the right place in the buried food test</li><li>olfactory_time_retrieve_raw_data.csv- time to retrieve cracker in the buried food test</li><li>oss_raw_data.csv - data recorded in the OSS test</li><li>saccharin_preference_males_raw_data.csv - saccharin preference test results for males</li><li>snvta_cells_count.csv - number of TH+ cells in SN and VTA in male mice (3+3) 14 weeks after tamoxifen treatment</li></ul><p><i>Additional data files:</i></p><ul><li>all_anova.xlsx - summary of two-way ANOVAs of all behavioral tests and weight measurements for males and females</li><li>catwalk_complete.xlsx - CatWalk complete dataset with datapoints</li><li>catwalk_correlation_between_paws.xlsx - correlation coefficients of CatWalk parameters between the left and right paws</li><li>catwalk_reduced.xlsx - CatWalk parameters used in linear regression model reduction of data</li><li>intelli.xlsx - IntelliCage data summarized in bins</li><li>oss.xlsx - operant sensation-seeking data</li></ul><p>v2 contains the corrected 'animals_info.csv' file without an unnecessary column.</p><p>v3 has a revised version of file containing females' weight measurements and also added a file with midbrain cell counts</p><p>v4 has a whole section of 'Additional data files' added</p>
Electrophysiological data of the paper 'Serotonergic and dopaminergic neurons in the dorsal raphe are differentially altered in a mouse model for parkinsonism'
<p>This excel data set contains the electrophysiological data presented in the paper including figure 1I, 1J, figure 3, figure 5, suppl. figure 2A, suppl. figure 3, suppl. figure 6E, 6G, 6L & 6N.</p> <p> </p> <p>More information about how the data was extracted can be found in the materials and methods section of the paper. </p>
Figure 4 in Perinatal exposure to a high-fat diet alters proopiomelanocortin, neuropeptide Y and dopaminergic receptors gene expression and the food preference in offspring adult rats
Figure 4. Body weight on the 120th offspring from mothers submitted the control diet or the high-fat diet. Values are presented as mean ± SEM using two-way ANOVA followed by the Bonferroni multiple-comparison test. *p<0,05; **p<0,005.
Figure 3 in Perinatal exposure to a high-fat diet alters proopiomelanocortin, neuropeptide Y and dopaminergic receptors gene expression and the food preference in offspring adult rats
Figure 3. Body weight on the second day life's of offspring from mothers submitted the control diet (C) or the high-fat diet (H). Values are presented as mean + SEM using Student t-test. C: n = 23; H: n = 23.
Figure 2 in Perinatal exposure to a high-fat diet alters proopiomelanocortin, neuropeptide Y and dopaminergic receptors gene expression and the food preference in offspring adult rats
Figure 2. Pomc (A) and npy (B) gene expression in the hypothalamus of offspring exposed or not to a control diet or high-fat diet during perinatal and/or postnatal period. Values are presented as mean ± SEM using two-way ANOVA followed by the Bonferroni multiplecomparison test. Level of significance: *p<0,05; "a": compared to CC, "b": compared to CH; "c": compared to HC; "d": compared to HH.
Figure 1. Drd1 in Perinatal exposure to a high-fat diet alters proopiomelanocortin, neuropeptide Y and dopaminergic receptors gene expression and the food preference in offspring adult rats
Figure 1. Drd1 (A) and drd2 (B) gene expression in the nucleus accumbens of offspring exposed or not to a control diet or high-fat diet during perinatal and/or postnatal period. Values are presented as mean ± SEM using two-way ANOVA followed by the Bonferroni multiplecomparison test. Level of significance: *p<0,05; "a": compared to CC, "b": compared to CH; "c": compared to HC; "d": compared to HH.
Data from: Loss of primary cilia and dopaminergic neuroprotection in pathogenic LRRK2driven and idiopathic Parkinson’s disease
Open the record for dataset details and reuse information.
Data from: Developmental Dieldrin exposure alters DNA methylation at genes related to dopaminergic neuron development and Parkinson's disease in mouse midbrain
Human and animal studies have shown that exposure to the organochlorine pesticide dieldrin is associated with increased risk of Parkinson's disease (PD). Despite previous work showing a link between developmental dieldrin exposure and increased neuronal susceptibility to MPTP toxicity in male C57BL/6 mice, the mechanism mediating this effect has not been identified. Here, we tested the hypothesis that developmental exposure to dieldrin increases neuronal susceptibility via genome-wide changes in DNA methylation. Starting at 8 weeks of age and prior to mating, female C57BL/6 mice were exposed to 0.3 mg/kg dieldrin by feeding (every 3 days) throughout breeding, gestation, and lactation. At 12 weeks of age, pups were sacrificed and ventral mesencephalon, containing primarily substantia nigra, were microdissected. DNA was isolated and dieldrin-related changes in DNA methylation were assessed via reduced representation bisulfite sequencing (RRBS). We identified significant, sex-specific differentially methylated CpGs (DMCs) and regions (DMRs) by developmental dieldrin exposure (FDRNr4a2 and Lmx1b genes, which are involved in dopaminergic neuron development and maintenance. Developmental dieldrin exposure had distinct effects on the male and female epigenome. Together, our data suggest that developmental dieldrin exposure establishes sex-specific poised epigenetic states early in life. These poised epigenomes may mediate sensitivity to subsequent toxic stimuli and contribute to the development of late-life neurodegenerative disease, including PD.
Synaptic vesicle glycoprotein 2C enhances vesicular storage of dopamine and counters dopaminergic toxicity
<p>Dopaminergic neurons of the substantia nigra exist in a persistent state of vulnerability resulting from high baseline oxidative stress, high energy demand, and broad unmyelinated axonal arborizations. Impairments in the storage of dopamine compound this stress due to cytosolic reactions that transform the vital neurotransmitter into an endogenous neurotoxicant, and this toxicity is thought to contribute to the dopamine neuron degeneration that occurs Parkinson's disease. We have previously identified synaptic vesicle glycoprotein 2C (SV2C) as a modifier of vesicular dopamine function, demonstrating that genetic ablation of SV2C in mice results in decreased dopamine content and evoked dopamine release in the striatum. Here, we adapted a previously published in vitro assay utilizing false fluorescent neurotransmitter 206 (FFN206) to visualize how SV2C regulates vesicular dopamine dynamics and identified that SV2C promotes the uptake and retention of FFN206 within vesicles. In addition, we present data indicating that SV2C enhances the retention of dopamine in the vesicular compartment with radiolabeled dopamine in vesicles isolated from immortalized cells and from mouse brain. Further, we demonstrate that SV2C enhances the ability of vesicles to store the neurotoxicant 1-methyl-4-phenylpyridinium (MPP+) and that genetic ablation of SV2C results in enhanced 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced vulnerability in mice. Together, these findings establish that SV2C functions to enhance storage of dopamine and toxicants and helps maintain the integrity of dopaminergic neurons.</p>
The Cellular and Extra-Cellular Proteomic Signature of Human Dopaminergic Neurons Carrying the LRRK2 G2019S Mutation
<p>The provided data sets were generated during the work described in "The Cellular and Extra-Cellular Proteomic Signature of Human Dopaminergic Neurons Carrying the LRRK2 G2019S Mutation" published in Frontiers in Neuroscience, 2024.</p> <p>They contain the results from our differential expression analysis of our raw DIA Protemic Data as well as a list of input data for GO analyses.</p>
Medial prefrontal cortex and anteromedial thalamus interaction regulates motivation related behavior and dopaminergic neuron activity: Animal Behavior
<p>The excel Source DATA file contains the data described in Figures 2c, 2d, 2f, and 3b and Supplementary Figure 3b and 3c. The fiber photometry data described in Supplementary Figure 9 are found in the CSV files. The CSV file names reflect animal IDs. </p>
Source data for "Ca2+ channels couple spiking to mitochondrial metabolism in substantia nigra dopaminergic neurons"
<p><strong>Fig.1Aa-c.tif</strong></p> <p>2PLSM images (Fura-2 filled neuron) used for the reconstruction in Fig.1A</p> <p> </p> <p><strong>Fig1CDJ.xlsx</strong></p> <p>Numerical data for the charts in Fig. 1C, Fig.1D, Fig.1J</p> <p> </p> <p><strong>Fig.1F_GCEPIA1er.tif</strong></p> <p>Confocal image (green channel, G-CEPIA1er) for Fig. 1F</p> <p> </p> <p><strong>Fig.1F_TH.tif</strong></p> <p>Confocal image (blue channel, anti-TH immunostaining) for Fig. 1F</p> <p> </p> <p><strong>Fig.1G_GCEPIA1er.tif</strong></p> <p>Confocal image (green channel, G-CEPIA1er) for Fig. 1G</p> <p> </p> <p><strong>Fig.1G_CRT.tif</strong></p> <p>Confocal image (magenta channel, anti-CRT immunostaining) for Fig. 1G</p> <p> </p> <p><strong>Fig.1H_GCEPIA1er.tif</strong></p> <p>Confocal image (green channel, G-CEPIA1er) for Fig. 1H</p> <p> </p> <p><strong>Fig.1H_TH.tif</strong></p> <p>Confocal image (blue channel, anti-TH immunostaining) for Fig. 1H</p> <p> </p> <p><strong>Fig. 2B_mitoGCaMP6.tif</strong></p> <p>Confocal image (green channel, mito-GCaMP6) for Fig. 2B</p> <p> </p> <p><strong>Fig.2B_TH.tif</strong></p> <p>Confocal image (blue channel, anti-TH immunostaining) for Fig. 2B</p> <p> </p> <p><strong>Fig. 2C_mitoGCaMP6.tif</strong></p> <p>Confocal image (green channel, mito-GCaMP6) for Fig. 2C</p> <p> </p> <p><strong>Fig.2C_COXIV.tif</strong></p> <p>Confocal image (magenta channel, anti-COXIV immunostaining) for Fig. 2C</p> <p> </p> <p><strong>Fig. 2D_mitoGCaMP6.tif</strong></p> <p>Confocal image (green channel, mito-GCaMP6) for Fig. 2D</p> <p> </p> <p><strong>Fig.2D_TH.tif</strong></p> <p>Confocal image (blue channel, anti-TH immunostaining) for Fig. 2D</p> <p> </p> <p><strong>Fig.2FGJL.xlsx</strong></p> <p>Numerical data for the charts in Fig. 2F, Fig.2G, Fig.2J, Fig.2L</p> <p> </p> <p><strong>Fig.3BDE.xlsx</strong></p> <p>Numerical data for the charts in Fig. 3B, Fig.3D, Fig.3E</p> <p> </p> <p><strong>Fig.3C_Alexa.tif</strong></p> <p>MAX Projection of z-stack of 2PLSM images (magenta channel, Alexa 594 dye) used to generate Fig.3C top panel</p> <p> </p> <p><strong>Fig.3C_mitoGCaMP6.tif</strong></p> <p>MAX Projection of z-stack of 2PLSM images (green channel, mito-GCaMP6) used to generate Fig.3C top panel</p> <p> </p> <p><strong>Fig.3C_inset_dendritic_mitoGCaMP6.tif</strong></p> <p>2PLSM image (green channel, mito-GCaMP6) for Fig.3C bottom left panel</p> <p> </p> <p><strong>Fig.3C_inset_soma_mitoGCaMP6.tif</strong></p> <p>2PLSM image (green channel, mito-GCaMP6) for Fig.3C bottom right panel</p> <p> </p> <p><strong>Fig. 4A_PercevalHR.tif</strong></p> <p>Confocal image (green channel, PercevalHR) for Fig.4A</p> <p> </p> <p><strong>Fig.4A_TH.tif</strong></p> <p>Confocal image (blue channel, anti-TH immunostaining) for Fig.4A</p> <p> </p> <p><strong>Fig. 4B_PercevalHR.tif</strong></p> <p>Confocal image (green channel, PercevalHR) for Fig.4B</p> <p> </p> <p><strong>Fig.4B_TH.tif</strong></p> <p>Confocal image (blue channel, anti-TH immunostaining) for Fig.4B</p> <p> </p> <p><strong>Fig.4G.xlsx</strong></p> <p>Numerical data for the charts in Fig.4G</p> <p> </p> <p><strong>Fig.5BDFHI.xlsx</strong></p> <p>Numerical data for the charts in Fig.5B, Fig.5D, Fig.5F, Fig.5H, Fig.5I</p> <p> </p> <p><strong>Fig.6ADEFJKLN.xlsx</strong></p> <p>Numerical data for the charts in Fig.6A, Fig.6D, Fig.6E, Fig.6F, Fig.6J, Fig.6K, Fig.6L, Fig.6N</p> <p> </p> <p><strong>Fig.6H_mitoroGFP.tif</strong></p> <p>2PLSM image (green channel, mito-roGFP) for Fig.6H</p> <p> </p> <p><strong>Fig.6M_MCU-KO.tif</strong></p> <p>Combined EM micrographs used to generate Fig. 6M right side</p> <p> </p> <p><strong>Fig.6M_wildtype.tif</strong></p> <p>Combined EM micrographs used to generate Fig. 6M left side</p> <p> </p> <p><strong>Fig.7CEFG.xlsx</strong></p> <p>Numerical data for the charts in Fig.7C, Fig.7E, Fig.7F, Fig.7G</p> <p> </p> <p><strong>Fig.8CEHJK.xlsx</strong></p> <p>Numerical data for the charts in Fig.8C, Fig.8E, Fig.8H, Fig.8J, Fig.8K</p> <p> </p> <p><strong>Fig.S1A_bottom.tif</strong></p> <p>2PLSM image (green channel, G-CEPIA1er) for Fig.S1A bottom panel (low Ca2+)</p> <p> </p> <p><strong>Fig.S1A_top.tif</strong></p> <p>2PLSM image (green channel, G-CEPIA1er) for Fig.S1A top panel (high Ca2+)</p> <p> </p> <p><strong>Fig.S1B.xlsx</strong></p> <p>Numerical data for the chart in Fig.S1B</p> <p> </p> <p><strong>Fig.S2A_baseline.tif</strong></p> <p>2PLSM image (green channel, mito-GCaMP6) for Fig.S2A middle panel (baseline)</p> <p> </p> <p><strong>Fig.S2A_MAX.tif</strong></p> <p>2PLSM image (green channel, mito-GCaMP6) for Fig.S2A top panel (high Ca2+)</p> <p> </p> <p><strong>Fig.S2A_min.tif</strong></p> <p>2PLSM image (green channel, mito-GCaMP6) for Fig.S2A bottom panel (low Ca2+)</p> <p> </p> <p><strong>Fig.S2C_baseline.tif</strong></p> <p>2PLSM image (green channel, mito-GCaMP6) for Fig.S2C middle panel (baseline)</p> <p> </p> <p><strong>Fig.S2C_MAX.tif</strong></p> <p>2PLSM image (green channel, mito-GCaMP6) for Fig.S2C top panel (high Ca2+)</p> <p> </p> <p><strong>Fig.S2C_min.tif</strong></p> <p>2PLSM image (green channel, mito-GCaMP6) for Fig.S2C bottom panel (low Ca2+)</p> <p> </p> <p><strong>Fig.S2E_baseline.tif</strong></p> <p>2PLSM image (green channel, mito-GCaMP6) for Fig.S2E bottom left panel (baseline)</p> <p> </p> <p><strong>Fig.S2E_end.tif</strong></p> <p>2PLSM image (green channel, mito-GCaMP6) for Fig.S2E bottom right panel</p> <p> </p> <p><strong>Fig.S2E_peak.tif</strong></p> <p>2PLSM image (green channel, mito-GCaMP6) for Fig.S2E bottom center panel</p> <p> </p> <p><strong>Fig.S2F.xlsx</strong></p> <p>Numerical data for the chart in Fig.S2F</p> <p> </p> <p><strong>Fig.S3ABC.xlsx</strong></p> <p>Numerical data for the charts in Fig.S3A, Fig.S3B, Fig.S3C</p> <p> </p> <p><strong>Fig.S4CD.xlsx</strong></p> <p>Numerical data for the charts in Fig.S4C, Fig.S4D</p> <p> </p> <p><strong>Fig.S5ABC.xlsx</strong></p> <p>Numerical data for the charts in Fig.S5A, Fig.S5B, Fig.S5C</p> <p> </p> <p><strong>Fig.S7A.tif</strong></p> <p>2PLSM image (green channel, GCaMP6) for Fig.S7A</p> <p> </p> <p><strong>Fig.S7CEFGH.xlsx</strong></p> <p>Numerical data for the charts in Fig.S7C, Fig.S7E, Fig.S7F, Fig.S7G, Fig.S7H</p> <p> </p> <p><strong>Fig.S8ABCDEF.xlsx</strong></p> <p>Numerical data for the charts in Fig.S8A, Fig.S8B, Fig.S8C, Fig.S8D, Fig.S8E, Fig.S8F</p> <p> </p> <p><strong>Fig.S9AHIJK.xlsx</strong></p> <p>Numerical data for the charts in Fig.S9A, Fig.S9H, Fig.S9I, Fig.S9J, Fig.S9K</p> <p> </p> <p><strong>Fig.S9B_wildtype_DLStr.tif</strong></p> <p>Confocal image of dorso-laterateral striatum in wildtype mouse (red channel, anti-TH immunostaining) for Fig.S9B</p> <p> </p> <p><strong>Fig.S9C_MCU-KO_DLStr.tif</strong></p> <p>Confocal image of dorso-laterateral striatum in MCU-KO mouse (red channel, anti-TH immunostaining) for Fig.S9C</p> <p> </p> <p><strong>Fig.S9D_wildtype_SN.tif</strong></p> <p>Confocal image of midbrain in wildtype mouse (red channel, anti-TH immunostaining) for Fig.S9D</p> <p> </p> <p><strong>Fig.S9E_MCU-KO_SN.tif</strong></p> <p>Confocal image of midbrain in MCU-KO mouse (red channel, anti-TH immunostaining) for Fig.S9E</p> <p> </p> <p><strong>Fig.S9F_wildtype_openfield.png</strong></p> <p>Open field path tracked for wildtype mouse for Fig.S9F</p> <p> </p> <p><strong>Fig.S9G_MCU-KO_openfield.png</strong></p> <p>Open field path tracked for MCU-KO mouse for Fig.S9G</p> <p> </p> <p><strong>Fig.S10A.xlsx</strong></p> <p>Numerical data for the charts in Fig.S10A</p>
Table 2 in Perinatal exposure to a high-fat diet alters proopiomelanocortin, neuropeptide Y and dopaminergic receptors gene expression and the food preference in offspring adult rats
<p><b>Table 2.</b> Relative food intake of the high-fat diet and control diet during the food preference study in offspring exposed or not a control diet or high-fat diet during perinatal and/or postnatal period.</p><table><tbody><tr><th></th><th><i>High-fat diet (g/100 g body weight)</i></th><th></th></tr></tbody><tbody><tr><th></th><td><i>102º day</i></td><td><i>110º day</i></td><td><i>116º day</i></td></tr><tr><th><i>CC</i></th><td>12.6 ± 0.6</td><td>11.3 ± 0.2</td><td>11.1 ± 0.7</td></tr><tr><th><i>CH</i></th><td>12.8 ± 0.6</td><td>12.4 ± 0.3</td><td>11.4 ± 0.4</td></tr><tr><th><i>HC</i></th><td>16.7 ± 1.1 <b>a.b*</b></td><td>13.7 ± 0.9</td><td>10.0 ± 0.5</td></tr><tr><th><i>HH</i></th><td>15.3 ± 0.7 <b>a.b*</b></td><td>11.7 ± 0.9</td><td>10.7 ± 0.5</td></tr><tr><th></th><td><i>Control diet (g/100 g body weight)</i></td><td></td></tr><tr><th></th><td><i>102º day</i></td><td><i>110º day</i></td><td><i>116º day</i></td></tr><tr><th><i>CC</i></th><td>1.4 ± 0.2</td><td>1.1 ± 0.1</td><td>1.1 ± 0.3</td></tr><tr><th><i>CH</i></th><td>2.1 ± 0.2</td><td>1.5 ± 0.3</td><td>0.9 ± 0.1</td></tr><tr><th><i>HC</i></th><td>1.8 ± 0.2</td><td>1.0 ± 0.3</td><td>1.0 ± 0.3</td></tr><tr><th><i>HH</i></th><td>1.9 ± 0.2</td><td>1.1 ± 0.2</td><td>0.7 ± 0.1</td></tr></tbody></table><p>Values are presented as mean + SEM using two-way ANOVA followed by the Bonferroni multiple-comparison test. *p<0,005; “a”: compared to CC, “b”: compared to CH; “c”: compared to HC; “d”: compared to HH.</p>
Table 1 in Perinatal exposure to a high-fat diet alters proopiomelanocortin, neuropeptide Y and dopaminergic receptors gene expression and the food preference in offspring adult rats
<p><b>Table 1.</b> Experimental design. The rats were fed commercial standard diet for rodents control diet or high-fat diet during pregnancy, lactation and post-weaning (up to 100 days of life).During the feeding period, rats consumed both diets (control diet and high-fat diet). The numbers in parentheses indicate the animals number in each nutritional group.</p><table><tbody><tr><th><b>Experimental Design</b></th></tr></tbody><tbody><tr><th><b>Genitors (n)</b></th><td><b>Gestation and lactation</b></td><td><b>Offspring during lactation (n)</b></td><td><b>Offspring (n)</b></td><td><b>Post-weaning (21-100° life’s day)</b></td><td><b>Food preference (102-116º life’s day)</b></td></tr><tr><th></th><td></td><td></td><td>CC (12)</td><td>Control diet</td><td>Control diet</td></tr><tr><th></th><td></td><td></td><td></td><td></td><td>High-fat diet</td></tr><tr><th>GC (5)</th><td>Control diet</td><td>C (23)</td><td>CH (11)</td><td>High-fat diet</td><td>Control diet</td></tr><tr><th></th><td></td><td></td><td></td><td></td><td>High-fat diet</td></tr><tr><th></th><td></td><td></td><td>HC (11)</td><td>Control diet</td><td>Control diet</td></tr><tr><th></th><td></td><td></td><td></td><td></td><td>High-fat diet</td></tr><tr><th>GH (5)</th><td>High-fat diet</td><td>H (23)</td><td>HH (12)</td><td>High-fat diet</td><td>Control diet</td></tr><tr><th></th><td></td><td></td><td></td><td></td><td>High-fat diet</td></tr></tbody></table>
Action Prediction Error: a value-free dopaminergic teaching signal that drives stable learning - Behavioral dataset
<p>Behavioral data to reproduce figures of this paper: https://doi.org/10.1101/2022.09.12.507572</p> <p>See Github repository: https://github.com/HernandoMV/APE_paper</p>
An unbiased, automated platform for scoring dopaminergic neurodegeneration in C. elegans
<p><em><span>Caenorhabditis elegans</span></em><span> (<em>C. elegans</em>) has served as a simple model organism to study dopaminergic neurodegeneration, as it enables quantitative analysis of cellular and sub-cellular morphologies in live animals. These isogenic nematodes have a rapid life cycle and transparent body, making high-throughput imaging and evaluation of fluorescently tagged neurons possible. However, the current state-of-the-art method for quantifying dopaminergic degeneration requires researchers to manually examine images and score dendrites into groups of varying levels of neurodegeneration severity, which is time-consuming, subject to bias, and limited in data sensitivity. We aim to overcome the pitfalls of manual neuron scoring by developing an automated, unbiased image processing algorithm to quantify dopaminergic neurodegeneration in <em>C. elegans</em>. The algorithm can be used on images acquired with different microscopy setups and only requires two inputs: a maximum projection image of the four cephalic neurons in the <em>C. elegans</em> head and the pixel size of the user's camera. We validate the platform by detecting and quantifying neurodegeneration in nematodes exposed to rotenone, cold shock, and 6-hydroxydopamine using 63x epifluorescence, 63x confocal, and 40x epifluorescence microscopy, respectively. Analysis of tubby mutant worms with altered fat storage showed that, contrary to our hypothesis, increased adiposity did not sensitize to stressor-induced neurodegeneration. We further verify the accuracy of</span><span> the</span><span> algorithm by comparing code-generated, categorical degeneration results with manually scored dendrites of the same experiments. The platform, which detects 19 different metrics of neurodegeneration, can provide comparative insight into how each exposure affects dopaminergic neurodegeneration patterns. </span></p>
Dopaminergic Modulation of Brain Activation Using Simultaneous PET/Pharmacological MRI
ClinicalTrials.gov study NCT03326245. IPD Sharing: NO. Countries: 1. Publications: 4.
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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.