DOI: 10.5061/dryad.h44j0zpwk
title: Data from: Frontal noradrenergic and cholinergic transients exhibit distinct spatiotemporal dynamics during competitive decision-making

description: Norepinephrine (NE) and acetylcholine (ACh) are crucial for learning and
 decision-making. In the cortex, NE and ACh are released transiently at
 specific sites along neuromodulatory axons, but how the spatiotemporal
 patterns of NE and ACh signaling link to behavioral events is unknown.
 Here, we use two-photon microscopy to visualize neuromodulatory signals in
 the premotor cortex (medial M2) as mice engage in a competitive matching
 pennies game. Spatially, NE signals are more segregated with choice and
 outcome encoded at distinct locations, whereas ACh signals can multiplex
 and reflect different behavioral correlates at the same site. Temporally,
 task-driven NE transients were more synchronized and peaked earlier than
 ACh transients. To test functional relevance, we stimulated
 neuromodulatory signals using optogenetics to find that NE, but not ACh,
 increases the animals’ propensity to explore alternate options.
 Altogether, the results reveal distinct subcellular spatiotemporal
 patterns of ACh and NE transients during decision-making in mice.
description: # Frontal noradrenergic and cholinergic transients exhibit distinct
 spatiotemporal dynamics during competitive decision-making [Access this
 dataset on Dryad](DOI: 10.5061/dryad.h44j0zpwk) Dataset includes: 1.
 2-photon recordings of NE and ACh in mice M2 cortex, and matching pennies
 behavior during the recordings. 2p imaging data were recorded with
 ScanImage5. Behavioral data were recorded with NBS Presentation.  2.
 matching pennies and simple 2-choice task behavior paired with
 optogenetics activation of M2 NE and ACh terminal. Behavioral data were
 recorded with NBS Presentation ## Description of the data and file
 structure ### 2p-NE/ACh (root) ``` │ ├── Data │ ├── Animal 910 │ │ ├──
 Session 1204 │ │ │ ├── cell1.mat % df/f data for ROI 1 │ │ │ ├── cell2.mat
 % df/f data for ROI 2 │ │ │ ├── cell3.mat % df/f data for ROI 3 │ │ │ └──
 ... │ │ │ └── {subject}-phase2_MP_2A_imaging.log (NBS Presentation
 logfile) │ │ │ │ └── stack_info.mat ``` ### MP\_STIM (root) ``` │ ├── 0.0
 mW (stimulation power) │ ├── data │ │ ├──
 {subject}-phase2_MP_2A_stim_{timestamp}.log (NBS Presentation logfile) │ │
 └── ... ├── 1.5 mW (stimulation power) ... ├── randomOutcome (behavior
 data of random outcome task) │ ├── chat (chat-cre animals) │ │ ├── data │
 │ │ ├── {subject}*random_outcome*{timestamp}.log (NBS Presentation
 logfile) ... │ ├── dbh (dbh-cre animals) │ │ ├── data │ │ │ ├──
 {subject}*random_outcome*{timestamp}.log (NBS Presentation logfile) ├──
 1Region (data of experiments with only one brain region stimulated) │ ├──
 LM2 (left M2) │ │ ├── data │ │ │ ├──
 {subject}*random_outcome*{timestamp}.log (NBS Presentation logfile) ... │
 ├── LV1 (left V1) │ ├── RM2 (right M2) │ ├── RV1 (right V1) ``` #### Data
 structure of cell.mat * bw: mask of the selected ROI * cellf: raw
 fluorescent traces of the ROI * neuropilf: fluorescent traces of the
 neuropil * substractmask: mask info used to substract neuropil signal ####
 Data structure of stack\_info.mat (not needed in analysis) * frameRate:
 frame rate * imageHeight/imageWidth: heigh and width of image in px *
 nChans: number of channels * nFrames: number of frames * rawFileName: file
 name of raw imaging * scim_header: header of scan image * tags:
 information of recordings * zoomFactor: factor of zoom ### Data structure
 of behavior.log file (A comprehensive explaination of variables can be
 found on NBS presentation website:
 [https://www.neurobs.com/presentation/docs/index_html](https://www.neurobs.com/presentation/docs/index_html)) Scenario: behavior task Logfile written: data and time of the session Subject: subject ID | Trial | The trials in a scenario are numbered sequentially starting with 1. If a trial is a feedback trial, it will be labeled by the number of the original trial which created the feedback trial plus a letter. Thus, the first feedback trial after trial 3 would be labeled 3A. Events that occur between trials will be assigned the trial number of the previous trial. If the scenario uses fMRI mode and contains only one trial, this column will indicate the main pulse number. | | :--------------------- | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Event Type | This is the type of the event. For example, "Picture", "Sound", or "Response". | | Code | For responses, this is the code provided by either the button\_codes or target\_button\_codes header parameters. For stimuli, this will be the user defined event code. Only stimuli that are given event codes will appear in the Analysis window and the logfile. | | \[custom properties] | (Optional) If you define the stimulus\_properties header parameter, extra columns containing the properties inside stimulus event codes will be inserted after the "Code" columns. | | Time | This is the time of occurrence of the event relative to the start of the scenario. See the section for each type of event for information on how to interpret this information. | | TTime | This is the same as 'Time' above except measured relative to the start of the trial the event is in. | | Uncertainty (Time) | This is the temporal uncertainty for the event (see Uncertainties.) | | Duration | For picture stimuli, this is the duration of the picture. Presentation does not monitor the durations of other stimuli. | | Uncertainty (Duration) | This is the uncertainty in the time given for the duration of a picture stimulus (see Uncertainties.) | | Req Time | This is the requested time of presentation given in the scenario file. Note that actual presentation times for picture stimuli are constrained by the monitor refresh and therefore should differ from requested times. | | Req Dur | For picture stimuli, this is the requested duration of presentation given in the scenario file. Note that picture stimuli durations are constrained by the monitor refresh. | ## Sharing/Access information Links to other publicly accessible locations of the data: * [https://github.com/Kwan-Lab/wangortega2024](http://...) For analysis and interpretation, see: * [https://www.biorxiv.org/content/10.1101/2024.01.23.576893v1.abstract](https://www.biorxiv.org/content/10.1101/2024.01.23.576893v1.abstract) ## Code/Software ``` ——— # for 2p imaging Data Requires the following MATLAB toolboxes: Optimization, Communications ``` Add all the subfoldersto the Path in MATLAB ``` To start portion on matching pennies: ``` Change the variable 'root_path_NE' and 'root_path_ACh' in line 8, 9 of master_MP_GRAB.m e.g. /Users/johndoe/Downloads/MP_GRAB_main/Data/ACh unzip the stack_info.7z inside each individual folder e.g. /Users/johndoe/Downloads/MP_GRAB_main/Data/ACh/910/0328stack_info.7z Run master_MP_GRAB.m estimated running time on demo: ~2 hours ``` To start portion on pupil and auditory control: ``` Change the variable 'root_path' in line 6 ofgrab_audi.m e.g. /Users/johndoe/Downloads/MP_GRAB_main/Data/ctrl Run grab_audi.m ``` Software dependencies: MATLAB 2021B Installation: ``` download the repository and unzip ``` # for optogenetics Data ## System Requirements * Tested on - Windows 10 \-- 12th Gen Intel(R) Core(TM) i9-12900K, 3200 Mhz, 16 Core, 24 Logical Processor \-- 65 GB RAM ## * MATLAB 2021b \-- Image processing toolbox (11.4) \-- Curve fitting toolbox (3.6) \-- Optimization toolbox (9.2) \-- Communications toolbox (7.6) \-- Statistics and machine learning toolbox (12.2) ## * Import and save files from GitHub ## Installation Guide * Install MATLAB and required add-ons ## * Data must be stored in the following structure \-- .....\level1\region\data \-- example '...\1Region\LM2\data' \-- 1Region must include folders for all regions to be analyzed ## ## Demo To create Fig 6 F&G * open 'master_MP_STIM_combine_animals.m' * change root_path (line 11) to one level above folders containing powers to be analyzed * run (will take ~20 minutes) To create Fig 6 I&J * open 'master_MP_STIM_combine_animals_1reg.m' * change root_path (line 11) to be one level above folders containing regions to be analyzed * run (will take ~10 minutes) To create Fig 7 H-I * open 'master_preference.m' * change root_path (line 7) to one level above powers to be analyzed on the simple choice task * run (will take ~1 minute) To create Fig 7 D-G * load session of interest * run 'plot_preference_single_session(trialData)' * will take &lt; 1 minute ```