DOI: 10.5061/dryad.9ghx3ffpx
title: Data from: A model of marmoset monkey vocal turn-taking

description: Vocal turn-taking has been described in a diversity of species. Yet a
 model that captures the various processes underlying this social behavior
 across species has not been developed. To this end, here we recorded a
 large and diverse dataset of marmoset monkey vocal behavior in social
 contexts comprising one, two and three callers and developed a model to
 determine the keystone factors that affect the dynamics of these natural
 communicative interactions. While a coupled oscillator model failed to
 account for turn-taking in marmosets, our model alternatively revealed
 four key factors that encapsulate much of patterns evident in the
 behavior, ranging from internal processes, such as the state of the
 individual, to social context driven suppression of calling. In addition,
 we show that the same key factors apply to the meerkat, a carnivorous
 species, in a multicaller setting.  These findings indicate that
 vocal turn-taking is affected by a broader suite of mechanisms than
 previously considered and our model provides a predictive framework with
 which to further explicate this natural behavior and for direct
 comparisons with the analogous behavior in other species.
description: Data was collected using multiple directional microphones. For
 each context (1 animal, 2 animals, 3 animals), the call times were
 extracted from the raw audio files and collated into a single cell
 array. For the models in Fig 2, additionally the
 spectral features were extracted for each call and collated across calls
 in one .mat file.
description: # Data from: A model of vocal turn-taking
 [https://doi.org/10.5061/dryad.9ghx3ffpx](https://doi.org/10.5061/dryad.9ghx3ffpx) ## Description of the data and file structure Main data files are divided across 3 folders, each folder contains files for one context (1, 2 or 3 animals). Each file contains a 1 x n_animals cell array, where each cell contains a list of individual animals' calls (start time, end time). The file name (in the case of 2 monkey, the folder name) indicates the names of the recorded animals and the recording date (in YYYYMMDD). A last folder contains collated metadata, including the animal's names, sex, age, cage mate status and recording details: **familial_connection** This contains two arrays (sheets) with each row and each column being an animal ID. In the first sheet, if the animal in the row is the parent of the column animal, this is indicated with a TRUE value, otherwise the value is FALSE. In the second sheet, if the animal in the row is the sibling of the column animal, this is indicated with a TRUE value, otherwise the value is FALSE. **fps** This text file contains the downsampled fps at which all recordings were taken. **monkey_data_per_session_v2** This file shows for each of the two monkey recording sessions the age of each monkey in days, whether they were cagemates (cm), whether they were bonded partners (partners), whether they were a parent/child pair (parent-child), whether the animals were siblings (sibling), whether animal 1 was the parent of animal 2 (is_parent), and the time of day the recordings was taken, rounded to the nearest hour, in 24h notation. **Monkey_list** This file contains a list of monkey names and their index in the code. This file can be used to crossreference data from the file names and the other metadata files. **Monkey_sex** This file contains the monkey indices and the sex of the monkey (0=Female, 1=Male). **'Fig_2_features.mat' ('Fig_2_features.csv')** This file contains the features included in the model for each call across all 2 animal recordings. Note that not all calls have a valid value for all features. Specifically, the first call of each session will be missing a value for whether it was a response or not, as this could not be determined (a call may have been made prior to the start of the session). If no prior calls were made in a conversation, the monkey ICI and/or target ICI will be missing. Lastly, if the end frequency of a call was the same as the maximum frequency, no value for slope could be calculated. All missing values are indicated as NaNs. ## Code/Software Two sets of code are included with the data. First, the MATLAB (using MATLAB 2020a) code to perform all analysis described in the manuscript, ordered by figure. Next, a set of R (v4.3.1) code to make the particular figures based on the extracted data.