Three exciting pre-conference workshops will be offered at the 2024 SPR Annual Meeting in Prague. Registration fees for the workshops as well as online registration are available here.
Pre-Conference Workshop 1 (SOLD OUT)
Click here to be added to the waitlist.
Wednesday, October 23, 2024
9:00 a.m.-4:30 p.m.
Digital Signal Processing
J. Christopher Edgar, Gregory A. Miller, Tzvetan Popov, and Song Liu
This workshop discusses aspects of analog and digital signal acquisition and processing, including some fundamental principles and selected advanced topics, that are central to psychophysiology and a variety of other disciplines. It provides researchers with a better understanding of what happens when we use packaged software (e.g., filter settings) or when we call some common functions in code we write. The material has applications throughout the data pipeline, such as choosing a sampling rate or analysis epoch, and it applies to diverse psychophysiological measures (EEG, MEG, MRI, fMRI, fNIRS, EMG, pupillography, cardiovascular measures, etc.) and to other types of signals more generally, especially when signal frequency is of interest.
During the workshop, brief lectures will highlight data sampling and filtering topics. Most of the time will involve attendees completing shortened versions of the courseware sections listed below on their own laptops, with our individualized assistance (no need to bring your own data.) Attendees will leave the workshop with a better understanding of digital signal processing methods used to analyze brain and other data. Attendees will be well positioned to complete the full version of the free courseware, which will provide deeper understanding of signal processing in neuroscience research and beyond.
The workshop is based on and uses digital signal courseware written by some of us and is provided free to attendees (and anyone else). The workshop and the courseware don’t require much math background (e.g., no calculus needed). Attendees are asked to complete the first chapter of the courseware prior to the workshop (accessed online using Jupyter notebooks; no prior experience needed), so that the workshop can be very hands-on.
The workshop covers the following topics:
-
- Section 1 – Discussion of time series and spatial data, discussion of amplitude, frequency, and phase and their combination, such as adding sine waves, introduction to sine/cosine functions, and introduction to complex numbers and their use in signal processing.
- Section 2 – Discussion of the Nyquist sampling theorem and aliasing (time and spatial domains), multiplying sine waves, plotting complex numbers, and some applications.
- Section 3 – Discussion of convolution and, via convolution, filtering in the time domain, including high-pass and low-pass filters and gain functions. Use of convolution to filter time-domain datasets.
- Section 4 – Discussion of use of sine and cosine functions to compute the magnitude and phase of activity at different frequencies.
- Section 5 – _Discussion of the Fourier transform, with review (time permitting) of some of its limitations and ways to overcome some of them, including time-frequency transforms, and use of forward and inverse Fourier transforms to accomplish filtering.
Pre-Conference Workshop 2
Wednesday, October 23, 2024
9:00 a.m.-4:30 p.m.
Multiverse, Multilevel, and Bayesian Data Analysis in Psychophysiology
Tania Moretta, Giulia Calignano, Luca Menghini
The workshop “Multiverse, Multilevel, and Bayesian Data Analysis in Psychophysiology” will provide participants with a comprehensive introduction to the multiverse analysis framework, multilevel modeling, and Bayesian inference. Specifically, the first session of the workshop will provide participants with practical skills to systematically explore multiple pre-processing pathways, enhancing the robustness and reliability of their research findings. This hands-on session aims to improve transparency and reproducibility in psychophysiological data analysis. The second session will equip participants with the skills to analyze complex, ecological psychophysiological data using multilevel modeling techniques. This session allows for the examination of data with nested structures, capturing both within- and between-subject variability to better understand individual differences and dynamic processes. Lastly, the third session will provide participants with advanced tools for robust hypothesis testing and efficient variable selection. This session will enhance researchers’ ability to apply Bayesian methods in psychophysiological research, moving beyond the binary acceptance or rejection of null hypotheses to a more graded assessment of evidence and accounting for model and parameter uncertainty.
By the end of the workshop, attendees will have a general understanding of how to use these advanced statistical techniques in their own research, thereby improving the reliability, validity, and reproducibility of their findings. This workshop aims to foster a deeper appreciation for the power of modern statistical tools in addressing the unique challenges of psychophysiological research, ultimately contributing to more robust and insightful scientific discoveries.
Pre-Conference Workshop 3
Wednesday, October 23, 2024
9:00 a.m.-4:30 p.m.
From the Lab to the Real World: Challenges and Opportunities with Wearables
Lauren Bylsma and Varun Mishra
The ubiquitous presence of smartphones and wearable sensors offers an unprecedented ability to collect peripheral psychophysiological signals across diverse timescales, settings, populations, and modalities. Indeed, researchers have been increasingly using wearables to monitor and collect longitudinal data on a variety of health outcomes. However, the validity and reliability of psychophysiological signals from these wearables in comparison to gold-standard laboratory measures remain unclear. Further, researchers are confronted with an increasing number of devices and platforms for ambulatory assessment, with little guidance as to how to choose appropriate tools that match the aims of their research. In this workshop, we will explore the evolving landscape of ambulatory psychophysiology research, focusing on using wearable sensors for longitudinal real-world deployments, including integration of self-report data obtained from ecological momentary assessment (EMA). Participants will gain insights into the best practices for designing and conducting ambulatory psychophysiology studies, including selecting appropriate devices, setting up sampling designs, checking the validity of the psychophysiological data, and making critical data analytic decisions. The session will emphasize practical, hands-on approaches and real-world challenges, including data quality issues and the integration of multiple measures.
The workshop will feature a didactic component covering theoretical foundations and best practices, followed by a hands-on component where participants will use Python and interactive tools to analyze data from various wearable devices. This interactive workshop is ideal for researchers looking to enhance their understanding of wearable devices in psychophysiological research and to gain the knowledge and tools to address the challenges associated with real-world data collection and analysis.
Key topics will include:
-
- Selecting and evaluating wearable devices for psychophysiological data collection in ambulatory settings
- Addressing data quality challenges inherent to wearable technology
- Integrating physiological data with other behavioral and self-report measures (e.g., EMA)
- Navigating the complexities of data analysis in ambulatory settings
If you have any questions, please send an email to meetings@sprweb.org.