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Psychedelic drug effects on reactivity of the paraventricular nucleus of the hypothalamus and threat responding behavior

Cite this dataset

Effinger, Devin (2024). Psychedelic drug effects on reactivity of the paraventricular nucleus of the hypothalamus and threat responding behavior [Dataset]. Dryad. https://doi.org/10.5061/dryad.3ffbg79qr

Abstract

Psychedelics have experienced renewed interest following studies suggesting potential therapeutic effects in patients with affective disorders. While clinical results look promising, the neurobiological mechanisms underlying acute and prolonged effects of psychedelics remain unclear. Many psychiatric disorders involve hypothalamic-pituitary-adrenal (HPA) axis dysfunction. The paraventricular nucleus of the hypothalamus (PVN) is a midline hypothalamic nucleus that plays an integral role in HPA stress reactivity, autonomic functioning, social behavior, and many other affective processes. We investigated the effect of psilocin, the psychoactive metabolite of psilocybin, on PVN reactivity in Sprague Dawley rats. Psilocin increased stimulus-independent activity as measured by c-Fos expression in the PVN of male and female rats. Psilocin also increased PVN reactivity (ΔF/F) to an aversive air-puff stimulus in males but not females. PVN reactivity was restored at 2- and 7-days post-injection with no group differences. Additionally, we found that prior psilocin injection did not affect PVN reactivity following acute restraint stress. Experimental groups were sub-classified by baseline threat responding and psilocin-induced increases in male PVN reactivity were found to be driven by baseline active threat responders. Overall, these data demonstrate that the PVN is a significant site of psychedelic drug action with implications for threat responding behavior.

README: Psychedelic drug effects on reactivity of the paraventricular nucleus of the hypothalamus and threat responding behavior

https://doi.org/10.5061/dryad.3ffbg79qr

Data set includes data files, Matlab structures, and Matlab scripts used to generate data structures containing values used in a currently submitted manuscript. These experiments included the use of an air-puff in conjunction with fiber photometry to track changes in reactivity within the PVN at acute and prolonged time points.

Description of the data and file structure

Throughout all data structures, there is a Psilocin and Vehicle structure. If you open them you will see further organization based on the condition/day of recording. If you click on that you will see various data values that contain data points for each subject. In all data folders the rows correspond to values for an individual subject.

Data files:

  1. COHORT 7 DARTERS_revision.xlsx: includes lists of subjects that were subclassified into active (darter) vs. passive responders
  2. Cohort7_restraint: prism file containing the stats for the male subjects following acute restraint stress
  3. Cohort7_stats (revision): prism file containing the main stats for male subjects to include binned trace plots, peak point (PP), Area under curve (AUC), and active vs. passive responder proportions across time
  4. Cohort9_restraint.prism: prism file containing the stats for the female subjects following acute restraint stress
  5. Devin PVN CORT.prism: prism file containing stats for the corticosterone assay statistics
  6. Paper Figures_updated extra animals.prism: prism file containing the male and female velocity and post-air puff distance traveled figures and stats following addition of new subjects added in revision
  7. PVN BOOTSTRAP CI.xlsx: containing the raw data from upper and lower bound confidence interval (CI) resulting from a bootstrapping CI assay to determine which points along time in the binned trace analyses display a significant increase from baseline. Colors highlighted in red are points of significance corresponding to a significant increase from baseline at that particular time bin. These red cells correspond to the lines above the fiber photometry plots.
  8. PVN c-Fos paper stats: prism file containing stats for the c-Fos histological analyses for both male and females for vehicle and psilocin conditions.
  9. PVN_Females Behavior pre revision: prism file containing the behavior for females that is included in supplementary figures for distance traveled, time immobile, time spent in center, and other metrics that were not included in the paper.
  10. PVN_HEATMAPS.pzfx: prism file containing data points used in the binned trace plots. Each row represents the average trace for each individual subject. These data were used for heatmaps that are located to the right of the binned trace plots seen throughout the paper.
  11. PVN_Males Behavior Analysis_Final: prism file containing the behavior for males that is included in supplementary figures for distance traveled, time immobile, time spent in center, and other metrics that were not included in the paper.
  12. PVN_Males Behavior Analysis_passive v active only (1).prism: prism file containing time spent in center and immobility time plots that are featured in supplementary figures for males between the active and passive responders.
  13. PVN_cohort7and9combined: prism file that contains data for both males and females that are combined based on an earlier reviewer comment. The only plot that made it into the paper from this file is the baseline responding demonstrating a difference between males and females in PVN reactivity and justifying maintaining separation by sex throughout the paper.
  14. Source Data_UPDATED.xlsx: spreadsheet containing the data for each plot featured in the paper
  15. Cohort7_corrected_Final_revision052324.mat: Matlab structure containing raw data for males calculated from the raw TDT files. In the workplace click either the Psilocin or Vehicle structure to find data stored by condition (Baseline, treatment, etc.). Data from this structure was used to generate prism files. 
  16. Cohort7_Passive_Final_Revision052324.mat: Matlab structure containing raw data for passive males calculated from the raw TDT files. In the workplace click either the Psilocin or Vehicle structure to find data stored by condition (Baseline, treatment, etc.). Data from this structure was used to generate prism files.
  17. Cohort7_Active_Final_Revision052324.mat: Matlab structure containing raw data for active males calculated from the raw TDT files. In the workplace click either the Psilocin or Vehicle structure to find data stored by condition (Baseline, treatment, etc.). Data from this structure was used to generate prism files. 
  18. Cohort9_FINAL_revision052224.mat: Matlab structure containing raw data for females calculated from the raw TDT files. In the workplace click either the Psilocin or Vehicle structure to find data stored by condition (Baseline, treatment, etc.). Data from this structure was used to generate prism files. 

Matlab Scripts:

  1. Cohort7_structurebuild.m: Will build a matlab structure provided you have raw TDT Syapse data files organized in the way in which this script is designed to locate them. Example file path: (cohort 9->baseline->individual subject data files corresponding to baseline). I used data folder names that correspond to the subject name and condition (e.g. PVG14baseline).
  2. Cohort9_structurebuild.m: Will build a matlab structure provided you have raw TDT Syapse data files organized in the way in which this script is designed to locate them. Example file path: (cohort 9->baseline->individual subject data files corresponding to baseline). I used data folder names that correspond to the subject name and condition (e.g. PVG14baseline).
  3. New_Structure_Analysis_Loop.m: This is an add on script to be done after utilizing scripts 1 or 2 above. This script will look for folders beginning with either "V" or "P" and will then create two structures, one for "vehicle" and the other for "psilocin", respectively. Within these structures you will find multiple different data points such as area under curve, peak point, binned trace plots, CI (results from bootstrapping Confidence interval assay), etc. Each row corresponds to the average for an individual subject. Specific corresponding subject names can be found in the "subjects" structure for each condition (baseline, treatment, etc.) and the row location corresponds to the row location in data points.

Sample/Test of script

  • You will need your own raw TDT Synapse data files to do this
  • Also you will need to label some data files so that they begin with "p_filename" and "v_filename". I did this as a way to organize data such that I could tell Matlab how to easily split data by group ( in this case v= vehicle and p= psilocin

Using Matlab R2023a

-Open the 'Structure_Build_Script.m'
-Adjust location for the TDTSDK folder in the SDKPATH command. You can download TDTSDK folder from TDT at https://www.tdt.com/docs/sdk/offline-data-analysis/offline-data-matlab/getting-started/
-Adjust directory by changing address following 'cd'
-Adjust location of Files to match where you place the 'BASELINE' folder you want to analyze within one of the cohorts RAW DATA folders.
-Run the first section of the script and ensure that the line item within the 'Conditions' cell within your workplace reads BASELINE. If it doesn't check the ConditionNames to locate where in that cell BASELINE is located.
-Once you are sure that the first line of the Conditions cell is BASELINE and the File designation leads to the BASELINE folder you are ready to progress to the next level of the code.
-Run the next section and Matlab will begin to analyze the raw data. After that is done, open the 'New_Structure_Analysis_Loop.m' and run the entire script.
-This will populate a psilocin and vehicle structure.
-Within this structure you will find various data types. If you click on the data, Corrected_bins for example, you will see data organized by condition (baseline in this case, but full data set would include all time points). The rows correspond to average for each subject and the columns (in this case) are 1-30 of the time bins used for fiber trace comparison and heat maps.

Methods

Data were collected using TDT RZ5 real time processor and Anymaze.

Funding

National Institutes of Health