This Committee Report provides methodological, interpretive, and reporting guidance for researchers who use measures of heart rate (HR) and heart rate variability (HRV) in psychophysiological research. We provide brief summaries of best practices in measuring HR and HRV via electrocardiographic and photoplethysmographic signals in laboratory, field (ambulatory), and brain-imaging contexts to address research questions incorporating measures of HR and HRV. The Report emphasizes evidence for the strengths and weaknesses of different recording and derivation methods for measures of HR and HRV. Along with this guidance, the Report reviews what is known about the origin of the heartbeat and its neural control, including factors that produce and influence HRV metrics. The Report concludes with checklists to guide authors in study design and analysis considerations, as well as guidance on the reporting of key methodological details and characteristics of the samples under study. It is expected that rigorous and transparent recording and reporting of HR and HRV measures will strengthen inferences across the many applications of these metrics in psychophysiology. The prior Committee Reports on HR and HRV are several decades old. Since their appearance, technologies for human cardiac and vascular monitoring in laboratory and daily life (i.e., ambulatory) contexts have greatly expanded. This Committee Report was prepared for the Society for Psychophysiological Research to provide updated methodological and interpretive guidance, as well as to summarize best practices for reporting HR and HRV studies in humans.

Since its beginnings in the early 20th century, the psychophysiological study of human brain function has included research into the spectral properties of electrical and magnetic brain signals. Now, dramatic advances in digital signal processing, biophysics, and computer science have enabled increasingly sophisticated methodology for neural time series analysis. Innovations in hardware and recording techniques have further expanded the range of tools available to researchers interested in measuring, quantifying, modeling, and altering the spectral properties of neural time series. These tools are increasingly used in the field, by a growing number of researchers who vary in their training, background, and research interests. Implementation and reporting standards also vary greatly in the published literature, causing challenges for authors, readers, reviewers, and editors alike. The present report addresses this issue by providing recommendations for the use of these methods, with a focus on foundational aspects of frequency domain and time-frequency analyses. It also provides publication guidelines, which aim to (1) foster replication and scientific rigor, (2) assist new researchers who wish to enter the field of brain oscillations, and (3) facilitate communication among authors, reviewers, and editors.

A variety of psychological and physical phenomena elicit variations in the diameter of pupil of the eye. Changes in pupil size are mediated by the relative activation of the sphincter pupillae muscle (decrease pupil diameter) and the dilator pupillae muscle (increase pupil diameter), innervated by the parasympathetic and sympathetic branches, respectively, of the autonomic nervous system. The current guidelines are intended to inform and guide psychophysiological research involving pupil measurement by (1) summarizing important aspects concerning the physiology of the pupil, (2) providing methodological and data-analytic guidelines and recommendations, and (3) briefly reviewing psychological phenomena that modulate pupillary reactivity. Because of the increased ease and tractability of pupil measurement, the goal of these guidelines is to promote accurate recording, analysis, and reporting of pupillary data in psychophysiological research.

Pupillometry has been one of the most widely used response systems in psychophysiology. Changes in pupil size can reflect diverse cognitive and emotional states, ranging from arousal, interest and effort to social decisions, but they are also widely used in clinical practice to assess patients\' brain functioning. As a result, research involving pupil size measurements has been reported in practically all psychology, psychiatry, and psychophysiological research journals, and now it has found its way into the primatology literature as well as into more practical applications, such as using pupil size as a measure of fatigue or a safety index during driving. The different systems used for recording pupil size are almost as variable as its applications, and all yield, as with many measurement techniques, a substantial amount of noise in addition to the real pupillometry data. Before analyzing pupil size, it is therefore of crucial importance first to detect this noise and deal with it appropriately, even prior to (if need be) resampling and baseline-correcting the data. In this article we first provide a short review of the literature on pupil size measurements, then we highlight the most important sources of noise and show how these can be detected. Finally, we provide step-by-step guidelines that will help those interested in pupil size to preprocess their data correctly. These guidelines are accompanied by an open source MATLAB script (available at https://github.com/ElioS-S/pupil-size ). Given that pupil diameter is easily measured by standard eyetracking technologies and can provide fundamental insights into cognitive and emotional processes, it is hoped that this article will further motivate scholars from different disciplines to study pupil size.

Failing to consider psychometric issues related to reliability and validity, differential deficits, and statistical power potentially undermines the conclusions of a study. In research using event-related brain potentials (ERPs), numerous contextual factors (population sampled, task, data recording, analysis pipeline, etc.) can impact the reliability of ERP scores. The present review considers the contextual factors that influence ERP score reliability and the downstream effects that reliability has on statistical analyses. Given the context-dependent nature of ERPs, it is recommended that ERP score reliability be formally assessed on a study-by-study basis. Recommended guidelines for ERP studies include 1) reporting the threshold of acceptable reliability and reliability estimates for observed scores, 2) specifying the approach used to estimate reliability, and 3) justifying how trial-count minima were chosen. A reliability threshold for internal consistency of at least 0.70 is recommended, and a threshold of 0.80 is preferred. The review also advocates the use of generalizability theory for estimating score dependability (the generalizability theory analog to reliability) as an improvement on classical test theory reliability estimates, suggesting that the latter is less well suited to ERP research. To facilitate the calculation and reporting of dependability estimates, an open-source Matlab program, the ERP Reliability Analysis Toolbox, is presented.

Electromagnetic data collected using electroencephalography (EEG) and magnetoencephalography (MEG) are of central importance for psychophysiological research. The scope of concepts, methods, and instruments used by EEG/MEG researchers has dramatically increased and is expected to further increase in the future. Building on existing guideline publications, the goal of the present paper is to contribute to the effective documentation and communication of such advances by providing updated guidelines for conducting and reporting EEG/MEG studies. The guidelines also include a checklist of key information recommended for inclusion in research reports on EEG/MEG measures.

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A model for the functional and observable interrelation among the various components in a physical bioenergy system is presented. The analogy is made between electric circuits and electromagnetic interactions, and contact and noncontact bioenergy transfer. It is postulated that there exists some form of bioenergy that has the capacity to do work and that this energy behaves in a manner similar to electricity in that the physical concepts of electromotive force, current, and impedance have their equivalents in bioenergy. It is further postulated that these analogous components are related by an equivalent to Ohm\'s and other physical laws of electricity. This is extended to a conjecture that bioenergy healing is the transfer of information from a practitioner to a healee. Research guidelines for bioenergy measurements are presented, including basic measurement practices for electrical and electromagnetic systems through direct measurements and the use of indirect measurement experiments for detecting these or other forms of bioenergy transfer. The research guidelines are divided into 2 sections: those involving direct measurement of the physical electrical properties of a practitioner, in particular the difficulties associated with electrical measurements of extremely low-level signals outside of a Faraday shield or electromagnetic measurements outside of a radio frequency anechoic chamber; and those for conducting experiments in which the effects of bioenergy are being investigated on the healee or other target system without direct measurements of the means for bioenergy transfer.

Studies in psychophysiology and behavioral medicine have uncovered associations among psychological processes, behavior, and lung function. However, methodological issues specific to the measurement of mechanical lung function have rarely been discussed. This report presents an overview of the physiology, techniques, and experimental methods of mechanical lung function measurements relevant to this research context. Techniques to measure lung volumes, airflow, airway resistance, respiratory resistance, and airflow perception are introduced and discussed. Confounding factors such as ventilation, medication, environmental factors, physical activity, and instructional and experimenter effects are outlined, and issues specific to children and clinical groups are discussed. Recommendations are presented to increase the degree of standardization in the research application and publication of mechanical lung function measurements in psychophysiology.

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