Respiration shapes response speed and accuracy with a systematic time lag

Sensory-cognitive functions are intertwined with physiological processes such as the heartbeat or respiration. For example, we tend to align our respiratory cycle to expected events or actions. This happens during sports but also in computer-based tasks and systematically structures the respiratory phase around relevant events. However, studies also show that trial-by-trial variations in the respiratory phase shape brain activity and the speed or accuracy of individual responses. We show that both phenomena, the alignment of respiration to expected events and the explanatory power of the respiratory phase on behaviour co-exist. In fact, both the average respiratory phase of an individual relative to the experimental trials and trial-to-trial variations in the respiratory phase hold significant predictive power on behavioural performance, in particular for reaction times. This co-modulation of respiration and behaviour emerges regardless of whether an individual generally breathes faster..., Respiration was recorded using a temperature-sensitive resistor that was inserted into disposable clinical oxygen masks (Littelfuse Thermistor No. GT102B1K, Mouser Electronics). This effectively captures the continuous temperature changes resulting from the respiration-related airflow. The voltage drop across the thermistor was recorded via the analogue input of an ActiveTwo EEG system (BioSemi BV; Netherlands) at a sampling rate of 500 or 1000 Hz. We verified that the voltage drop of the temperature sensor follows the respiratory air flow without time lag. For this, we combined the temperature probe with two short-latency airflow sensors (F1031V, Mass Airflow Sensor, Winsen) and confirmed that the temperature change tightly aligns with the directional change in airflow.
Compared to our previous work we improved the processing pipeline for respiratory data. The respiratory signals were filtered using 3-rd order Butterworth filters (high pass at 0.03 Hz, low pass at 6 Hz) and subsequentl..., , # Respiration shapes response speed and accuracy with a systematic time lag

[https://doi.org/10.5061/dryad.4mw6m90mz](https://doi.org/10.5061/dryad.4mw6m90mz)

## Description of the data and file structure

This repository contains the processed data and code required to reproduce the main results and figures. 

### Files and variables

#### Data files

**Dataset1.mat to Dataset_12.mat**

The main processed behavioural and respiratory data for each of the 12 datasets analysed in this study.

The numbers 1-12 map onto the 12 datasets explained in the Methods section: 

PARNAMES = {'Pitch1','Time','Visual shape','Emotion1','Emotion2','Pitch2','Arithm','Visual dots','Pitch3','Pitch4','Sound','Emotion3'};

Each file contains the following:

ARGglobal: multiple infos about dataset including information about preprocessing ARGglobal.Analysis

ARGout: further details about prepro.

ARGout.RespTraces{participant} epoch averaged respiratory trace for each participant. Visualizes the average res...