In the field of physiology, it is tempting to see the human body as a collection of independent systems performing a range of functions—converting food to energy, protecting us from harm and disease, and helping us react to and interact with our environments, to name a few. It is easy to overlook that these systems often work together and are interconnected. The field of network physiology does just that—look at how these systems (nervous, cardiovascular, muscular, etc.) work together, seeing them as part of a dynamic network rather than a collection of independent parts.
Researchers are exploring an array of ways to apply the concepts of network physiology, such as how stress affects both the brain and body. Medical researchers are looking into how to identify early warning signs of future health problems in how various physiological systems interact when developing treatments that address multiple bodily systems. While this may sound like the multimodal approach to physiology—collecting data simultaneously and synchronously from multiple systems—the two terms are not synonymous. Network physiology uses multimodal methods to collect data, but goes further by connecting the dots between the various systems.
A study by a team of researchers from the University of New York and the University of Houston demonstrated how combining data from different body systems can give a more complete picture of how the brain and body work together, specifically in response to music and mental effort. The study explored how different types of music—either calming or exciting—affect a person’s working memory (the ability to retain and use information for short periods) and overall brain and body arousal. During the experiment, participants completed memory tasks while listening to either calming or exciting music. Researchers collected detailed data from the body using a set of BIOPAC sensors and electrodes, including general-purpose electrodes for gathering electrocardiogram (ECG) signals, a respiratory effort transducer, a wireless skin temperature sensor, a wireless pulse transducer for photoplethysmogram (PPG) data, and electrodes to measure electrodermal activity (EDA), blood flow in the finger, and muscle activity in the shoulders. These multimodal signals were gathered using a BIOPAC data acquisition and analysis system. The data was collected at 2 kHz to capture even small changes in the body’s responses. The research team found that while the difficulty of the memory tasks didn’t significantly impact arousal levels, the type of music did. Exciting music helped participants feel more alert and even improved their performance on some tasks.
A 2024 South Korean study investigated how the autonomic nervous system (ANS) responds differently to social pain (such as emotional distress from losing a loved one) versus physical pain (like discomfort from a pressure cuff). Researchers used a BIOPAC 16-channel data acquisition and analysis system running AcqKnowledge software to collect a range of signals from 73 healthy young adult participants. The following signals were gathered synchronously using a variety of sensors and transducers: ECG electrodes placed on both wrists and the left ankle to monitor heart activity, EDA sensors attached to the index and middle fingers to assess skin conductance (indicating stress levels), PPG sensor on the thumb to measure blood volume changes, chest-wrapped sensor to track breathing patterns, and a temperature sensor on the ring finger to monitor peripheral temperature changes. Participants experienced social pain via a 60-second grief-themed film clip and physical pain through a blood pressure cuff inflated to 250 mmHg. Social pain increased heart rate and skin conductance, while lowering blood volume pulse, pulse transit time, breathing rate, and finger temperature, reflecting a mix of sympathetic and parasympathetic nervous system activity. Physical pain, on the other hand, raised heart rate variability and skin conductance, reduced blood volume pulse and pulse transit time, but left finger temperature unchanged, suggesting activation of the body’s stress response system. These distinct patterns show how different types of pain trigger unique responses across interconnected body systems.
A multimodal approach was employed in a study by researchers from several institutions including the University of Southern California, University of California, Irvine, Rutgers University, Vanderbilt University, and Wayne State University School of Medicine to examine how daily heart rate variability (HRV) biofeedback training influences brain function, emotional regulation, and physiological responses in both younger and older adults. In the study, 193 participants were randomly assigned to either increase or decrease their heart rate oscillations through daily biofeedback sessions over five weeks. Before and after the intervention, participants underwent various assessments, including MRI scans, psychological evaluations, and sleep monitoring using wristband sensors. During the MRI sessions, physiological data such as blood pressure, pulse, respiration (using a BIOPAC MRI-safe respiration transducer and module), and end-tidal CO₂ were continuously recorded. During stress tasks, blood pressure and hemodynamic measurements were taken using a noninvasive blood pressure monitor and transferred to a BIOPAC data acquisition and analysis system. The study’s findings suggest that HRV biofeedback can positively impact both brain function and physiological health, highlighting the interconnected nature of bodily systems, a central concept in network physiology.
These are just a few examples of how network physiology is being applied in research today. For more information on the topic, including links to related webinars, citations, and events, see our Network Physiology applications page.
Are you planning to integrate a range of signals for your next network physiology study? Our customer service specialists can help identify the best equipment and strategies for the synchronous collection of high-quality multimodal data.
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