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How ovarian hormones influence the behaviroal activation and inhibition system through the dopamine pathway
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Dataset for Activation of Glassy Carbon Surfaces by Alkaline Anodization Enhances Dopamine Adsorption and Electron-Transfer Kinetics
<p>This dataset provides the raw data to the manuscript</p><p><strong>"Activation of Glassy Carbon Surfaces by Alkaline Anodization Enhances Dopamine Adsorption and Electron-Transfer Kinetics"</strong></p><p>published in ChemElectroChem</p><p>Specifically, the following measurements are provided:</p><ul><li>Scanning electrochemical cell microscopy (SECCM). Cyclic voltammetry (E, i) data for each location across the sample. 5 cycles.</li><li>Chronoamperometry (i, t) for the anodization process.</li><li>Atomic Force Microscopy (AFM) topography.</li><li>Raman microscopy</li><li>X-ray photoelectron spectroscopy (XPS)</li><li>Scanning electron microscopy (SEM)</li></ul>
Variabilities of Dopamine (₯) I: Six Paper Collections in 2024
<ol> <li><a title="The Variabilities of Dopamine (₯) - PART V: MeSH: D005239 & NBO:0000209 (Fear Comes in to Play)" href="https://details-or-fragments.blogspot.com/2024/12/DAfear.html" target="_blank" rel="noopener"><strong>The Variabilities of Dopamine (₯) - PART V: MeSH: D005239 & NBO:0000209 (Fear Comes in to Play)</strong></a>: Do you still remember the 67-year-old dopamine girl in the history of dopamine science this year? She gradually became a spokesperson for happiness in her twenties. However, behind this happiness is actually a little fear. In the early stages of research, scientists used basic tools to explore dopamine's role, focusing on its relevance to psychosis and antipsychotic drugs. Initial claims that dopamine was involved in fear conditioning were dismissed due to the inadequacies of the drugs, tools, and techniques used. However, with the development of science, it turns out that the purple "Fear" in "Inside Out" also has some relationship with the dopamine girl. Let's do some brain teasers together this time! In "Dopamine at Forty," we learned that dopamine (DA) is more than just the "happy molecule" we once thought it was. Thanks to advancements in genetics, chemistry, and other technologies in the 21st century, scientists now understand dopamine and its interactions with neurons (DAN) and receptors much better. <a title="多變多巴胺&mdash;&mdash;第五部:恐懼也來湊一腳" href="https://case.ntu.edu.tw/blog/?p=44919" target="_blank" rel="noopener">CASE Science, Center for the Advancement of Science Education, National Taiwan (Chinese Publication)</a>, 2024-12-26 </li> <li><strong><a title="The Variabilities of Dopamine (₯) - PART IV: MeSH:D011954(Bound Receptors:D1~D5" href="https://details-or-fragments.blogspot.com/2024/12/dar.html" target="_blank" rel="noopener">The Variabilities of Dopamine (₯) - PART IV: MeSH:D011954(Bound Receptors:D1~D5</a>) : </strong>Dopamine is a pretty quirky character. Not only does it act as a neurotransmitter, but it also behaves differently depending on the "dopamine receptor" it binds to. Imagine these receptors as different doorways on the surface of a cell, each one changing how dopamine does its job. So, what's so special about these receptors? Well, think of them like the VIP passes that let dopamine into the cell club. You've probably heard about receptors because of the coronavirus (yep, the COVID-19 villain). The virus uses a special receptor called "ACE2" to sneak into our cells. Using this same idea, you can picture dopamine needing its own special receptors to get things done. In short, dopamine receptors are like the bouncers deciding who gets into the cell party, and without them, dopamine would just be left knocking on the door! <a title="多變多巴胺&mdash;&mdash;第四部:綁定的受體D1~D5" href="https://case.ntu.edu.tw/blog/?p=44815" target="_blank" rel="noopener">CASE Science, Center for the Advancement of Science Education, National Taiwan (Chinese Publication)</a>, 2024-11-14 <strong><br></strong></li> <li><strong><a title="The Variabilities of Dopamine (₯) - PART III: CL:0000700 & SIO:000823 (Curious detective DAN's aging)" href="https://details-or-fragments.blogspot.com/2024/09/curiosity.html" target="_blank" rel="noopener">The Variabilities of Dopamine (₯) - PART III: CL:0000700 & SIO:000823 (Curious detective DAN's aging)</a> : </strong>In the complex drama of the brain, there are many characters, but dopaminergic neurons (DAN) take the lead role. These neurons are always on the lookout for new things and solving puzzles, like a brainy Sherlock Holmes. Dopamine, the neurotransmitter, is their trusty sidekick, helping them stay curious and active. But, like in any good story, there's a twist. Over time, these once-energetic neurons start to lose their zest for new experiences. This decline in curiosity mirrors our own aging. It raises an important question: what happens in the brain to cause this loss? What makes our inner Sherlock Holmes lose interest in the unknown? <a title="多變多巴胺&mdash;&mdash;第三部:好奇偵探DAN的變老" href="https://case.ntu.edu.tw/blog/?p=44568" target="_blank" rel="noopener">CASE Science, Center for the Advancement of Science Education, National Taiwan (Chinese Publication)</a>, 2024-09-06 </li> <li><a title="The Variabilities of Dopamine (₯) - PART II: CL: 0000700" href="https://details-or-fragments.blogspot.com/2024/08/CL0000700.html"><strong>The Variabilities of Dopamine (₯) - PART II: CL: 0000700: </strong></a>What are dopaminergic neurons (DANs), the cells in your brain that help you do your job every day? Let’s give it a try . Let’s use the “Knowledge Manual” - the ontology. Starting from DAN’s ID, CL: 0000700, a few pictures will present the important relationship between DAN and dopamine. Once you have the concept of DAN-related knowledge graph, will it collide with the DAN and dopamine working in your mind to inspire a new cognitive world spark that belongs to you? | <a title="多變多巴胺&mdash;&mdash;第二部:工作細胞DAN " href="https://case.ntu.edu.tw/blog/?p=44411" target="_blank" rel="noopener">CASE Science, Center for the Advancement of Science Education, National Taiwan (Chinese Publication)</a>, 2024-08-04</li> <li><a title="The Variabilities of Dopamine (₯) - PART I:ChEBI:18243" href="https://details-or-fragments.blogspot.com/2024/06/ChEBI18243.html"><strong>The Variabilities of Dopamine (₯) - PART I:ChEBI:18243:</strong> </a>What is the specific image of the charming and changeable dopamine among scientists? What is the family tree of dopamine established by chemists and information scientists? What is so called ontology? Let us try to brief in common words, knowledge ontology (ontology for short) is a basic computing model compiled by scientific experts in a specific field and fed to computers. Today, we try to use the knowledge architecture of these computers to feed human readers in the context of popular science for writing and reading. This is an innovative creative experiment that uses dopamine to open a new chapter in popular science. It’s so exciting, so nervous for me. What are the benefits of learning about dopamine through Ontology? (1) Telling stories by the graphical structure of the basic knowledge summary, let people understand the information quickly and clearly at a glance. (2) Linking to specific knowledge bases, the information can be “tasted” briefly and deeply by human choices. (3) Are you in urgent need of inspiration tools? Why not try the ontological popular science for different creativity? | <a title="多變多巴胺&mdash;&mdash;第一部:ChEBI:18243" href="https://case.ntu.edu.tw/blog/?p=44277" target="_blank" rel="noopener">CASE Science, Center for the Advancement of Science Education, National Taiwan(Chinese Publication)</a>, 2024-06-27 </li> <li><a title="Variabilities of Dopamine (₯) - Prequel" href="https://details-or-fragments.blogspot.com/2024/04/polymorphic-dopamine-prequel.html" target="_blank" rel="noopener"><strong>Variabilities of Dopamine (₯) - Prequel:</strong> </a>Dopamine should be the most well-known neurotransmitter in the human body. After all, who doesn’t like the “happy molecule”? But you know what? Dopamine is not that simple! There are still divergent opinions about the role she plays in the human body, and it is often said that her actions and reactions affect us in unexpected ways. This article uses the theme of anthropomorphic scientific information to observe and understand the development process of dopamine in the history of science and the different characteristics discovered at different stages. It uses the growth process of a girl as a metaphor to observe and understand it as a leading story to understand the complete knowledge structure of dopamine. | <a href="https://case.ntu.edu.tw/blog/?p=44043">CASE Science, Center for the Advancement of Science Education, National Taiwan(Chinese Publication)</a>, 2024-04-24 </li> </ol>
Reward perseveration is shaped by GABAA-mediated dopamine pauses: Behavior Data
<p>Behavior assay data used to generate the following figures in the paper "Reward perseveration is shaped by GABAA-mediated dopamine pauses":</p> <ul> <li>Figure 2, all panels</li> <li>Figure 4, all panels</li> <li>Ext. Fig 3, panels a-c, e, f</li> <li>Ext. Fig 5, all panels</li> </ul> <p>Specifics of the data:</p> <ul> <li>ddHTP.zip contains the control raw data in MATLAB files</li> <li>HTP.zip contains the experimental raw data in MATLAB files</li> <li>The various Behavior_summary_data.csv files contain the subject details and extracted analyses, as detailed in each title.</li> <li>ddHTP_other_DART_pilots.zip and the corresponding .csv file hold the raw and analyzed data for the ddHTP controls of ongoing experiments shown in Ext. Fig 5c. </li> </ul>
Reward perseveration is shaped by GABAA-mediated dopamine pauses: Histology from Behavior Data Mice
<p>Histology images for the experimental +HTP behavior mice in the dataset 10.5281/zenodo.10903566. This histology was used to generate the following figures in the paper "Reward perseveration is shaped by GABAA-mediated dopamine pauses":</p> <ul> <li>Ext. Fig 3, panel d</li> </ul> <p>Specifics of the data:</p> <ul> <li>HTP_Histo_Cohort_VX.zip contains the raw images (Olympus .vsi files) and drawn ROIs and fluorescence analysis (MATLAB files) for each mouse/tissue section in cohort VX</li> <li>HTP_Histo_Cohort_VZ.zip contains the raw images (Olympus .vsi files) and drawn ROIs and fluorescence analysis (MATLAB files) for each mouse/tissue section in cohort VZ</li> <li>HTP_Histo_Cohort_VAJ.zip contains the raw images (Olympus .vsi files) and drawn ROIs and fluorescence analysis (MATLAB files) for each mouse/tissue section in cohort VAJ</li> <li>HTP_Histo_Cohort_VAK.zip contains the raw images (Olympus .vsi files) and drawn ROIs and fluorescence analysis (MATLAB files) for each mouse/tissue section in cohort VAK</li> <li> Behavior_summary_data_HTP_Histology.csv contains the summarized fluorescence quantification per animal</li> </ul>
Reward perseveration is shaped by GABAA-mediated dopamine pauses: Electrophysiology Data
<p>In vivo electrophysiological data, slice electrophysiological data, and HTP vs tyrosine hydroxylase immunohistochemistry data. These data were used to generate the following figures in the paper "Reward perseveration is shaped by GABAA-mediated dopamine pauses":</p> <ul> <li>Figure 1, panels c-f</li> <li>Ext. Fig 1, all panels</li> <li>Ext. Fig 2, all panels</li> </ul> <p>Specifics of the data:</p> <ul> <li>Slice_Ephys .csv files contain the summarized in vitro electrophysiology data.</li> <li>HTP_Mouse_*.7z and ddHTP_Mouse_*.7z are zipped folders with the raw data, sorted data, and extracted cells for each recording, grouped by mouse the recordings were obtained from.</li> <li>HTP final_grouped spiking analysis_n39.mat is the MATLAB data file with all the extracted firing metrics for all 39 +HTP cells.</li> <li>ddHTP final_grouped spiking analysis_n18.mat is the MATLAB data file with all the extracted firing metrics for all 18 ddHTP cells.</li> <li> Ephys_Summary_Data .csv files contain the summarized in vivo electrophysiology data.</li> <li>VHist4_HTP and TH.7z contains the raw histological images, drawn ROIs, and ilastik cell counting performed to compare tyrosine hydroxylase and HTP expression.</li> </ul>
Reward perseveration is shaped by GABAA-mediated dopamine pauses: Fiber Photometry Data
<p>Fiber photometry data. These data were used to generate the following figures in the paper "Reward perseveration is shaped by GABAA-mediated dopamine pauses":</p> <ul> <li>Figure 3, all panels</li> <li>Ext. Fig 4, all panels</li> </ul> <p>Specifics of the data:</p> <ul> <li>FiberPho_Cohort_*.zip files contain all of the raw fiber photometry and behavior data for each mouse, grouped by cohort.</li> <li>FiberPho_Histo_Cohort_*.zip files contain the histological images and ROIs for each mouse, grouped by cohort. </li> <li>HTP_grouped_data.zip contains the grouped analysis fiber photometry and behavior MATLAB files for the experimental group.</li> <li>ddHTP_grouped_data.zip contains the grouped analysis fiber photometry and behavior MATLAB files for the control group.</li> <li>The various .csv files contain the summarized mouse, cohort, and analysis details and data.</li> </ul> <p> </p>
Inhibition of striatal dopamine release by the L-type calcium channel inhibitor isradipine co-varies with risk factors for Parkinson's
<h3><strong>ABSTRACT</strong></h3> <p>Ca<sup>2+</sup> entry into nigrostriatal dopamine (DA) neurons and axons via L-type voltage-gated Ca<sup>2+</sup> channels (LTCCs) contributes respectively to pacemaker activity and DA release, and has long been thought to contribute to vulnerability to degeneration in Parkinson’s disease. LTCC function is greater in DA axons and neurons from substantia nigra pars compacta than from ventral tegmental area, but this is not explained by channel expression level. We tested the hypothesis that LTCC-control of DA release is governed rather by local mechanisms, focussing on candidate biological factors known to operate differently between types of DA neurons and/or be associated with their differing vulnerability to parkinsonism, including biological sex, α-synuclein, DA transporters (DATs), and calbindin-D28k (Calb1). We detected evoked DA release <em>ex vivo </em>in mouse striatal slices using fast-scan cyclic voltammetry, and assessed LTCC support of DA release by detecting the inhibition of DA release by the LTCC inhibitors isradipine or CP8. Using genetic knockouts or pharmacological manipulations we identified that striatal LTCC support of DA release depended on multiple intersecting factors, in a regionally and sexually divergent manner. LTCC function was promoted by factors associated with Parkinsonian risk, including male sex, α-synuclein, DAT, and a dorsolateral co-ordinate, but limited by factors associated with protection i.e. female sex, glucocerebrosidase activity, Calb1, and ventromedial co-ordinate. Together, these data show that LTCC function in DA axons, and isradipine effect, are locally governed and suggest they vary in a manner that in turn might impact on, or reflect, the cellular stress that leads to parkinsonian degeneration.</p> <p> </p> <h3><strong>FILE DESCRIPTIONS</strong></h3> <p>This repository contains the following files:</p> <ul> <li>Key Resources Table (.xlsx) - Table containing details on key lab materials (antibodies, mouse lines, and software), and the persistent identifiers for protocols and code used and generated in this study. </li> <li>Source Data (.xlsx) - Excel spreadsheet containing all tabular datasets plotted in Main Figures 1 to 5 (.xlsx).</li> <li>R_Scritps (.R) - Custom written R scripts to perform a classification tree analysis.</li> </ul>
Dataset for the manuscript "ExSTED microscopy reveals contrasting functions of dopamine and somatostatin CSF-c neurons along the central canal"
<p>Description: Dataset that supports the expansion-STED and light sheet microscopy methods in spinal cord and support the findings in the manuscript: ExSTED microscopy reveals contrasting functions of dopamine and somatostatin CSF-c neurons along the central canal (Elham Jalalvand, Jonatan Alvelid, Giovanna Coceano, Steven Edwards, Brita Robertson, Sten Grillner, Ilaria Testa).</p> <p>The software used to open the files and perform the analysis: Imspector v0.10_rev8575 and ImageJ 1.52i.</p> <p>The preprint of the manuscript can be found here: https://doi.org/10.1101/2021.08.17.456595</p>
Dataset: Insular cortex dopamine 1 and 2 receptors in methamphetamine conditioned place preference and aversion: Age and sex differences
<p>Dataset for Insular cortex dopamine 1 and 2 receptors in methamphetamine conditioned place preference and aversion: Age and sex differences</p>
A VTA to basal amygdala dopamine projection contributes to signal salient somatosensory events during fear learning
<p>This dataset represents the raw data that gave rise to the study by Tang et al., J. Neuroscience 2020 (DOI: 10.1523/JNEUROSCI.1796-19.2020). Please refer to the original publication regarding experimental design and methodological details of data acquisition and analysis. Below we supply information on the provided metadata files (which, in turn, refer to individual raw data files), and essential details on the specific data formats.</p> <ol> <li>raw data is organized in the datasets related to the Figs. 1H-L, 1M, 3B-C, 2, 4G-H, 5D-E, 5H-I of the paper (Tang et al., 2020);</li> <li>the metadata for each individual dataset, which lists individual data filenames from the respective dataset, are stored in separate “.csv” files, one per each dataset. Field separator: comma;</li> <li>individual metadata files for each dataset are described in the master metadata file “metadata_master.csv”. Field separator: comma;</li> <li>widefield fluorescent images of single coronal slices containing VTA (Fig. 1H-M) were converted from the proprietary format of Olympus slide scanning microscope into composite TIFF format readable by FIJI/ImageJ (<a href="https://fiji.sc/">https://fiji.sc/</a> or <a href="https://imagej.net/Fiji/Downloads">https://imagej.net/Fiji/Downloads</a>). Image stacks covering the injection area of CTB into BA are provided in single multi-plane TIFF files, one per animal. Unless specified in the metadata file, the information on pixel resolution is embedded inside the individual image files as TIFF metadata. Attribution of fluorescent probes to the color channels is given in the corresponding metadata files; AP positions refer to Franklin KB, Paxinos G (2016) The mouse brain in stereotaxic coordinates, Ed 4. San Diego: Elsevier/Academic;</li> <li>confocal fluorescent image stacks acquired from single coronal slices containing VTA (Fig. 3B-C) are provided in the original format “.lsm” written by a confocal software Zen (Carl Zeiss). Besides the original Zen software, this format can be readily imported into FIJI/ImageJ using built-in converters “LSM…” or “Bio-Formats”. All the metadata containing imaging parameters is embedded in this format and can be accessed from FIJI/ImageJ after importing the stack. Attribution of fluorescent probes to the color channels is given in the corresponding “.csv” metadata file; AP positions refer to Franklin and Paxinos (2016);</li> <li>video recordings of animal behavior are provided as “.wmv” files, unmodified from the original version created by the acquisition software VideoFreeze (MedAssociates Inc). Video stream parameters: wmv3 codec, color space yuv420p, 320x240 pixels, bitrate 300 kb/s, 30 fps;</li> <li>timing patterns of the sound (CS) and of the footshock (US) applications during each day of fear conditioning protocol are provided in the respective “.csv” files: “day1_CS_timing.csv”, “day2_CS_timing.csv”, “day2_US_timing.csv”, “day3_CS_timing.csv”. The timestamps in these files are expressed in seconds relative to the start of the VideoFreeze video recordings (see p. 4 above). These patterns are in common for all the video recordings done on respective training days in every data subset (Figs. 2, 4-5);</li> <li>extracellular optrode recording data (Fig. 2) were converted from the original proprietary “.mcd” format of the MC_Rack software (Multichannel Systems) into the open HDF5 format “.h5” using the Multi Channel DataManager software (Multichannel Systems). We provide both the continuous recording data acquired during behavior sessions on days 1-3 of the fear learning protocol, as well as recordings of light-evoked spiking acquired during the opto-tagging sessions on each experimental day. In the latter, each of 8-10 consequently recorded data files contains individual triggered sweeps (from -50 to +50 ms), each centered around a single laser pulse (t=0 ms);</li> <li>the raw unfiltered electrode data is stored as a 32-bit integer matrix 16xN (16 - number of electrodes, N - number of sampling points @ 40 kHz) in the container Data->Recording_0->AnalogStream->Stream_1->ChannelData of the HDF5 files. Conversion factor to the units of volts for the raw values is 1.25e-6. Correspondence of the rows of the data matrix to the electrodes “E1”-“E16” is indexed by the string array Data->Recording_0->AnalogStream->Stream_1->I_Label. The electrodes were physically arranged into four tetrodes in following groups: E1-E4, E5-E8, E9-E12, E13-E16;</li> <li>timestamps for the continuous recordings, or for each of the triggered sweeps in case of opto-tagging, are stored in the 2D floating point array Data->Recording_0->AnalogStream->Stream_1->ChannelDataTimeStamps; the timestamp values are in microseconds;</li> <li>the timing of CS and US stimuli produced by the VideoFreeze software (see p. 5 above) was sampled as input digital triggers by the amplifier for extracellular recordings for precise synchronization between the optrode- and video recordings. These signals are stored as single bit changes in the 32-bits integer N-samples array Data->Recording_0->AnalogStream->Stream_0->ChannelData of the corresponding HDF5 files.</li> </ol>
BRAIN Journal-Electrophysiological Neuroimaging using sLORETA Comparing 100 Schizophrenia Patients to 48 Patients with Major Depression -Figure 3. Resulting comparisons isolating the Dopamine D2 Mesolimbic Pathway
<p>Moreover, a study in Prague identified that Toxoplasmosis triggers schizophrenia in<br> predisposed subjects (Flegr et al., 2014). It may very well be that the Toxoplasmosis parasite<br> increasing dopamine secretions in the frontal lobes may very well lead to decreased cerebral<br> volumes. Cat feces, sexual contact, and eating raw or undercooked pork are well known transmitters<br> of the Toxoplasmosis parasite and may be advisable that patients take precautions of the possibility<br> of these triggering symptoms of psychosis with these possible routes of infection. Another adjunct to Atypical Antipsychotics may be to treat the potential cerebral Toxoplasmosis infection with<br> Cotrimoxazole or Pyrimethamine/Clindamycin.</p>
BRAIN Journal-Electrophysiological Neuroimaging using sLORETA Comparing 100 Schizophrenia Patients to 48 Patients with Major Depression -Figure 2. Resting State neuroimaging findings illustrating the action of atypical antipsychotics on postsynaptic dopamine D2
<p>Contrastingly, the results of the one-hundred males and females diagnosed with<br> Schizophrenia compared to the thirty-two females diagnosed with Major Depressive Disorder or<br> Depressive Episodes. The one-hundred male and female Schizophrenia patients had an average age<br> of 32-years-old and a Standard Deviation of 11.8-years. Whereas, the Depressive Episode and<br> Major Depressive Disorder females had an average age of 50-years old and a Standard Deviation of<br> 11.7-years. The statistically significant neuroimaging results identified the Delta (1.5–6 Hz)<br> frequency band at the neuroanatomical location of the region of the Superior Frontal Gyrus<br> (p=0.007; t=2.08, BA 10, X=25, Y=55, Z=30) with greater neuronal oscillations and synchrony in<br> the one-hundred males and females diagnosed with Schizophrenia than the thirty-two females<br> diagnosed with Depressive Episodes and Major Depressive Disorder.</p>
BRAIN Journal-Electrophysiological Neuroimaging using sLORETA Comparing 100 Schizophrenia Patients to 48 Patients with Major Depression -Figure 1. Group comparisons designed for isolating the mesolimbic Dopamine D2
<p>All patients diagnosed with Schizophrenia were medicated with atypical antipsychotics, Olanzapine (dose 5mg/day to 20mg/day) or Risperidone (dose 1mg/day to 4mg/day) blocking both Dopamine D2 and Serotonin 5-HT2 receptors. Whereas, all of the patients diagnosed with Major Depression or Depressive Episode were medicated with Sertraline (50mg/day to 200mg/day maximum dose) or Citalopram (20mg/day to 40mg/day maximum dose). This research protocol was approved by the Bioethical Commission of the Medical University of Lublin. </p>
Data set for "Dopamine dynamics in nucleus accumbens across reward-based learning of goal-directed whisker-to-lick sensorimotor transformations in mice"
<p>Data set for: Huang J, Crochet S, Sandi C, Petersen CCH (2024) Dopamine dynamics in nucleus accumbens across reward-based learning of goal-directed whisker-to-lick sensorimotor transformations in mice. Heliyon 10: e37831. https://doi.org/10.1016/j.heliyon.2024.e37831<br><br></p> <p>There are 2 files in this upload:</p> <p>1. The file named "2024_Huang_Heliyon.pdf" is the Open Access pdf of the online publication in Heliyon.</p> <p>2. The file named "Huang_data_code.zip" (~6 GB) is a zipped version of a folder "Huang_data_code" (~6 GB), which contains the data analysed in the study along with the Matlab codes used to generate the published figures. To access the data and codes, first unzip the file. You need to install the Matlab 'Signal Processing' and 'Curve Fitting' Toolboxes. In Matlab, add the path of the folder "Huang_data_code" and all subfolders. The main folder unzips into three subfolders: i) "Huang_dLight_data_code", which contains the dLight data; ii) "Huang_muscimol_data_code", which contains the behavioral data for muscimol inactivation experiments; and iii) "Huang_singletrial_example", which contains the data for the single trial example data shown in Figure 1C (note for this to run you first need to load the data file "JH056_190308_WD.mat"). In the folder "Huang_dLight_data_code", you can also find a "DataViewer" to visualise the data trial-by-trial, which you can run by executing "DataViewer.mlapp" directly from the subfolder "Huang_dLight_data_code" after loading the data "Huang_database.mat".</p>
Transgenic A53T mice have astrocytic a-synuclein aggregates in dopamine and striatal regions
<p>Quantification of astrocyte expression, co-expression of astrocytes with a-syn, and astrocyte morphological data (soma size and number of processes) from 6 month transgenic A53T PD mice.</p>
Dataset for: Dopamine neurons that inform Drosophila olfactory memory have distinct, acute functions driving attraction and aversion
<p>The brain must guide immediate responses to beneficial and harmful stimuli while simultaneously writing memories for future reference. While both immediate actions and reinforcement learning are instructed by dopamine, how dopaminergic systems maintain coherence between these two reward functions is unknown. Through optogenetic activation experiments, we showed that the dopamine neurons that inform olfactory memory in Drosophila have a distinct, parallel function driving attraction and aversion (valence). Sensory neurons required for olfactory memory were dispensable to dopaminergic valence. A broadly projecting set of dopaminergic cells had valence that was dependent on dopamine, glutamate, and octopamine. Similarly, a more restricted dopaminergic cluster with attractive valence was reliant on dopamine and glutamate; flies avoided opto-inhibition of this narrow subset, indicating the role of this cluster in controlling ongoing behavior. Dopamine valence was distinct from output-neuron opto-valence in locomotor pattern, strength, and polarity. Overall our data suggest that dopamine’s acute effect on valence provides a mechanism by which a dopaminergic system can coherently write memories to influence future responses while guiding immediate attraction and aversion.</p>
Dopamine transporter and synaptic vesicle sorting defects underlie auxilin-associated Parkinson's disease
<p>Auxilin participates in clathrin uncoating to facilitate presynaptic endocytosis. Loss-of-function mutations of auxilin (<em>PARK19</em>) cause Parkinson’s disease. Using auxilin KO mice, Vidyadhara et al. (2023) show that synaptic vesicle sorting deficits, cytoplasmic dopamine accumulation, dopamine transporter mistrafficking, and synaptic autophagic overload may lead to pathogenesis of Parkinson’s disease in <em>PARK19</em> patients. This file contains the data set used to generate all the main figures.</p>
Data for: Natural genetic variation in a dopamine receptor is associated with variation in female fertility in Drosophila melanogaster
<p>Fertility is a major component of fitness but its genetic architecture remains poorly understood. Using a full diallel cross of 50 <em>Drosophila</em> <em>melanogaster</em> Genetic Reference Panel inbred lines with whole genome sequences, we found substantial genetic variation in fertility largely attributable to females. We mapped genes associated with variation in female fertility by genome-wide association analysis of common variants in the fly genome. Validation of candidate genes by RNAi knockdown confirmed the role of the dopamine 2-like receptor (<em>Dop2R</em>) in promoting egg laying. We replicated the <em>Dop2R</em> effect in an independently collected productivity dataset and showed that the effect of the <em>Dop2R</em> variant was mediated in part by regulatory gene expression variation. This study demonstrates the strong potential of genome-wide association analysis in this diverse panel of inbred strains and subsequent functional analyses for understanding the genetic architecture of fitness traits.</p>
Dopamine mediates the pea aphid wing plasticity
<p><span>Many organisms exhibit phenotypic plasticity, in which developmental processes result in different phenotypes depending on their environmental context. We focus on the molecular mechanisms underlying that environmental response. Pea aphids (<em>Acyrthosiphon</em> <em>pisum</em>) show a wing dimorphism, in which pea aphid mothers produce winged or wingless daughters when exposed to a crowded or low-density environment, respectively. We investigated the role of dopamine in mediating this wing plasticity, motivated by a previous study that found higher dopamine titers in wingless- versus winged-producing aphid mothers. In this study, we found that manipulating dopamine levels in aphid mothers affected the number of winged offspring they produced. Specifically, asexual female adults injected with a dopamine agonist produced a lower percentage of winged offspring, while asexual females injected with a dopamine antagonist produced a higher percentage of winged offspring, matching expectations based on the titer difference. We also found that genes involved in dopamine synthesis, degradation, and signaling were not differentially expressed between wingless- and winged-producing aphids. This result indicates that titer regulation happens in a non-transcriptional manner or that we sampled non-relevant timepoints or tissue. Overall, our work emphasizes that dopamine is an important component of how organisms process information about their environments.</span></p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
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.