Cholinergic interneurons and dopamine in the nucleus accumbens
Data files
Abstract
Motivation to work for potential rewards is critically dependent on dopamine (DA) in the nucleus accumbens (NAc). DA release from NAc axons can be controlled by at least two distinct mechanisms: 1) action potentials propagating from DA cell bodies in the ventral tegmental area (VTA), and 2) activation of β2* nicotinic receptors by local cholinergic interneurons (CINs). How CIN activity contributes to NAc DA dynamics in behaving animals remains unclear. We monitored DA release in the NAc Core of awake, unrestrained rats while simultaneously monitoring or manipulating CIN activity at the same location. CIN stimulation rapidly evoked DA release, and in contrast to slice preparations, this DA release showed no indication of short-term depression or receptor desensitization. The sound of food delivery evoked a brief joint increase in CIN population activity and DA release, with a second joint increase as rats approached the food. In an operant task, we observed fast ramps in CIN activity during approach behaviors, either to start the trial or to collect rewards. These CIN ramps co-occurred with DA release ramps, without corresponding changes in the firing of VTA DA neurons. Finally, we examined the effects of blocking CIN influence over DA release through local NAc infusion of DHβE, a selective antagonist of nicotinic receptors. DHβE dose-dependently interfered with motivated approach decisions, mimicking the effects of a DA antagonist. Our results support a key influence of CINs over motivated behavior via the local regulation of DA release.
README: Accumbens cholinergic interneurons dynamically promote dopamine release and enable motivation
--- This readme file provides instructions on reproducing the results presented in the research article titled "Accumbens cholinergic interneurons dynamically promote dopamine release and enable motivation\," published by Mohebi et al. in eLife\, 2023. The article can be accessed at https://elifesciences.org/articles/85011.
Description of the data and file structure
The dataset included in this repository follows the standard format used by the Berke lab. It contains the necessary files and data required to replicate the experiments and findings described in the research article. Additionally, we have provided MATLAB code that can be utilized to read and interpret the data, as well as generate figures related to our results.
The dataset consists of four *.zip files corresponding to four figures in the paper. Each zip file contains MATLAB scripts and data files required to reproduce the graphs in each figure. Following is the description for each data file.
Fig_1.zip
Fig1_Data.mat: Contains data from n=4 experiments described in Fig1 with the following fields. Use Fig1d.m, Fig1e.m scripts to reproduce Fig1a-e.
Fs: Sampling Frequency (Hz)
boxts: timestamp of laser onset (s)
stimData:
width: laser pulse width (ms)
interpulse: interpulse interval (ms)
count: Number of pulses in each trial
Repeat: Number of trials of each type
ISI: interstimulus interval (ms)
sig: photometry signal, sampled at Fs
ref: control photometry signal. Sampled at Fs
Fig1F_Data.mat: Use Fig1f.m script to reproduce the graph in Fig1f.
response: average photometry trace
x_axis: time(s)
Fig_2.zip
Fig2_Data.mat: Contains data from n=5 experiments described in Fig2 with the following fields. Use Fig2.m script to reproduce the graphs in Fig2.
Fs: Sampling Frequency (Hz)
ACh: Acetylcholine signal
DA: Dopamine signal
boxts: timestamp for events
FoodLine: Food port occupancy
ratConditioning: Conditioning task parameters
Fig_3.zip
Fig3_Data.mat: Contains data from n=5 experiments described in Fig2 with the following fields. Use Fig3.m script to reproduce the graph in Fig3. plotSEM.m is a helper script used inside the Fig3.m script.
Fs: Sampling Frequency (Hz)
boxts: timestamp of event onset (s)
behavData: performance measure in the bandit task
sig: photometry signal, sampled at Fs
ref: control photometry signal. Sampled at Fs
Fig_4.zip
Multiple nested folders. Each folder corresponds to one experimental condition, specified in the folder name, and contains behavioral reports for each subject. Subjects are named IM-1442,...,IM-1447. There are four different conditions as described in the paper: baseline, DHBE_15UG, DHBE_30UG, VEH. Use Fig4_Hazard.m script to reproduce the results in Fig4. bandit_performance_Results.m is a helper function. Each behavioral file contains behavioral measurements during the bandit task. Each line corresponds to one trial and contains the following keys:
Subject: Name of the subject
Date: Date of the experiment
Time: Time of the trial
Attempt: Attempt number
Trial: Trial number
Food: Binary variable reporting whether a trial was rewarded
Block: Block number
Block trial: Trial number within the block
Center: Number of the center poke for each trial
Port poked: Number of the poked port
RT: Reaction Time (ms)
MT: Movement Time (ms)
PreT: Pre Tone period (ms)
ResponseLimit: Response limit time (ms)
TrPerBlock: maximum number of trials per block
FalseStart: Number of false starts
WrongStart: Number of failed starts
FailureToRespond: Number of failures to start a trial
Prob Left: Probability of reward on the left side
Prob Right: Probability of reward on the right side
Target Poke: Poked port
CNI Latency: Latency to initiate the task (ms)
SI Duration: Side-in duration (ms)
ITI: Intertrial Interval (ms)
TTR: Time to Reward (ms)
Session Type: Type of the session (string, note)
Number of pulses: Number of laser pulses
Pulse width: Width of laser pulse
Amplitude: Amplitude of the laser pulse
Laser Active: Binary variable representing whether a trial was rewarded.
Sharing/Access information:
For further details and access to the dataset, please refer to the Dryad Digital Repository, where Mohebi, Collins, and Berke have made their data available under the following citation: Mohebi A, Collins VL, Berke JD (2022) Cholinergic Interneurons and Dopamine in the Nucleus Accumbens. Dryad Digital Repository, doi:10.7272/Q68P5XST. The dataset can be accessed at https://dx.doi.org/10.7272/Q68P5XST. Please follow the instructions below to replicate the results and findings of the study.
Methods
Refer to the methods section of Mohebi et al, eLife, 2023
Usage notes
MATLAB