[00:00:00] Speaker A: Welcome, friends, to the Heart Rate Variability Podcast. This week in Heart Rate Variability Edition. Each week we commit ourselves to a journey. It is a journey through the dense, often complex, but incredibly rewarding forest of scientific literature. We explore the latest research and news in heart rate variability, autonomic physiology, trauma recovery, and biofeedback. We do this not just to accumulate facts, but to understand the language of the human nervous system. We do it to translate the cold, hard data of the laboratory into the warm, beating reality of our daily lives. Before we begin our deep dive, a brief and important medical disclaimer. This podcast is for educational and informational purposes only. It is not medical advice. Nothing in this episode is intended to diagnose, treat, cure, or prevent any disease. The human body is complex and individual physiology varies wildly. What works for a generalized population in a study may not apply to your specific biology. Please consult your physician or a qualified healthcare professional before making change to your health routines, medications, exercise plan, or mental health care. If you are experiencing a medical emergency, please seek immediate medical help. All right, let's take a breath together.
[00:01:01] Speaker B: I want you to really settle in for this one. Not because we're going to do a breathing protocol right now, but because this week's research is exceptionally rich. It deserves our full, unhurried attention. We're going to step out of the shallow end of the pool and swim into the deep waters of autonomic function.
[00:01:14] Speaker A: Today, we will spend equal time on six studies that demonstrate how HRV is used across the spectrum of human experience, from cardiovascular medicine and neuroscience to developmental challenges in children and the aging process, and even into the future of human connection and virtual reality. Here's what I want you to listen for as we move through these papers. I want you to listen past the numbers. I want you to listen past the P values. Please listen to the concept of the window. We often talk about HRV as a number, a metric, a score to be optimized. But today's research shows that HRV is a window. It is a window into autonomic flexibility, the ability to bend without breaking. A window into biological vulnerability, where the cracks in the foundation are forming a window into physiological resilience, how quickly we bounce back. And sometimes, perhaps most importantly, it is a window into what is happening in the body's basement, the autonomic subfloor, long before symptoms show up in the living room of our conscious awareness. As always, I'm Matt Bennett, co founder of Optimal hrv, and this is this Week in Heart Rate Variability. Let's begin with the bedrock of HRV Research Cardiovascular Medicine the first paper we're discussing today is a major review article published in Frontiers in Cardiovascular Medicine. The title is Heart Rate Variability and Cardiovascular Disease Diagnosis, Prognosis, and Management. The authors are Brian Xiangzhi Wang, Ella Brennan, Pierre Lepage, and Andrew RJ Mitchell. Their affiliations include the Department of Medicine at Jersey General Hospital in St. Helier, Jersey, and the Department of Medicine at John Radcliffe Hospital, Oxford University Hospitals in Oxford, United Kingdom. Now this is the kind of paper that is incredibly easy to oversimplify. In our field, there's strong, seductive narrative High HRV is good. Low HRV is bad. Therefore, if you have heart disease, your HRV is low, and if you fix it, you're cured. It's a clean story. It sells devices. But biology is rarely that binary. Biology is messy, and Wong and his colleagues are careful. They do not oversell. They do not dismiss. They do what good reviews are supposed to do. They map the landscape. They tell us where the ground is solid, where the ground is shaky, and where we need to build new roads. Let's start with the fundamentals, because this paper does a beautiful job of resetting the baseline heart rate variability is the variation in intervals between consecutive heartbeats. Clinically, we usually talk about RR intervals or NN intervals, normal to normal beats. These variations result from a constant dynamic tug of war, or perhaps better described as a dance, between branches of the autonomic nervous system that act on the sinoatrial node, the heart's natural pacemaker. In simplified terms, sympathetic activation. The fight or flight response typically increases heart rate and reduces beat to beat variability. It functions as a metronome, regularizing the rhythm to ensure consistent output. Under stress. It floods the pacemaker cells with norepinephrine, increasing the firing rate and tightening the timing. Parasympathetic activation, largely mediated by the vagus nerve, which releases acetylcholine, tends to slow the heart and increase beat to beat variability. It acts like a jazz drummer, adding syncopation in space, allowing the heart to respond to the breath. It creates the pause between the beats. But in the context of cardiovascular disease, the the sympathetic versus parasympathetic balance model is too simple. It's incomplete. It implies that the only thing changing is the signal coming from the brain. When we look at a patient with cardiovascular disease, we aren't just seeing a shift in nerve traffic. We are seeing changes in reflexes, specifically the baroreceptor reflex, which manages blood pressure. We are seeing changes in cardiac conduction, the electrical wiring of the heart itself. We are seeing systemic inflammation, which irritates the nervous system and alters receptor sensitivity. We are seeing changes in sleep architecture, changes in breathing mechanics, and the influence of powerful medications such as beta blockers and ACE inhibitors. And crucially, we are often seeing changes in the heart muscle itself. Remodeling of the tissue if the heart muscle becomes stiff or scarred from a previous heart attack, it may not respond to the vagus nerve signal, even if the nerve is shouting. So when we say HRV changes in cardiovascular disease, we mean HRV is sensitive to these changes. That sensitivity is what makes HRV potentially useful.
It picks up on the system's noise when it captures the aggregate chaos. But that sensitivity is also what makes HRV difficult to use as a standalone diagnostic tool. Because if a metric is sensitive to everything from inflammation to scarring to stress, it can be very hard to know exactly what it is telling you about the specific patient sitting in front of you. The review starts by noting that reduced HRV has been linked to a who's who of cardiac arrhythmias, heart failure, and ischemic heart disease. But they note that the findings are mixed across studies. They use a key phrase. The prognostic value remains debated. That phrase matters remains debated why? In the 1980s and 90s, following the well known CAST and Atrami studies, HRV was regarded as a breakthrough risk marker. We thought we had found the crystal ball of cardiology. We thought we could predict exactly who would survive a heart attack and who wouldn't. And then as larger, more controlled, multicenter work emerged, the signal became somewhat noisier. We found that HRV sometimes added only modest predictive value beyond established risk factors such as ejection fraction or diabetes status. So what does HRV do well in cardiovascular care today? According to this review, one of HRV's strongest promises is that it serves as an early marker of autonomic dysfunction before structural disease is evident. This is the canary in the coal mine concept. Before the echocardiogram shows a stiff heart wall, before the angiogram shows a blocked artery, the autonomic control of the heart may begin to drift. The beat to beat. Responsiveness begins to dull. The system becomes rigid. That rigidity matters because cardiovascular disease is not just a plumbing problem. It is not just cholesterol clogging a pipe. It is not just blood pressure bursting a hose. It is also a failure of neurocardiac regulation. It is a failure of the software that runs the hardware. Wang and colleagues review evidence that HRV can predict outcomes such as sudden cardiac death and recurrent myocardial infarction heart attacks. They highlight post MI risk, the period after a heart attack where reduced HRV has been associated with a significantly higher risk of mortality and arrhythmic events. This is not new science, but the framing is vital. They frame HRV as capturing autonomic instability. When the autonomic nervous system is unstable, the electrical threshold for an arrhythmia drops. It becomes easier for the heart to slip into a fatal rhythm like ventricular fibrillation. HRV measures the stability of the safety net that prevents slippage. They also discuss HRV and heart failure. Heart failure is a condition where the heart cannot pump enough blood to meet the body's needs. To compensate, the body cranks up the sympathetic nervous system. It screams at the heart to beat faster, to contract harder. This works for a while. It's an adaptive mechanism, but eventually it burns out the receptors and further damages the heart. It's like driving a car with the pedal to the floor constantly. Eventually the engine blows. In heart failure, the parasympathetic system is almost completely withdrawn. The result? Extremely low variability, a flat line of adaptability. In this context, HRV correlates with disease severity and perhaps more importantly for treatment, it can track recovery or worsening. If a heart failure patient's HRV starts dropping further, it may be a warning sign of decompensation days before they end up in the ER with fluid in their lungs. Now we should pause to address an important nuance the authors raise. HRV is not one metric. It is a family of metrics, each looking at the data through a different lens. We have the time domain sdnn, the standard deviation of all bead intervals, rmssd, the root mean square of successive differences. We have the frequency domain, high frequency power, low frequency power and the LF HF ratio. We use nonlinear measures Poincare plots, entropy and detrended fluctuation analysis to assess the signal's complexity and chaos. One major theme of this review and a frustration for the field is that measurement variability and lack of standardization remain massive barriers.
Think about it. Different studies use different recording durations. Some use short term five minute recordings in a clinic. Some use 24 hour Holter recordings to capture circadian rhythms. Some use sleep only windows to avoid movement artifacts. Some use active challenge tests such as standing up or deep breathing. Different studies focus on different metrics. One paper builds its conclusion on sdnn. The next paper builds its conclusion on LF power. Different devices capture different signal qualities. Different pre processing pipelines remove artifacts differently. One algorithm might throw out a bead as an error, while another algorithm keeps it as a premature contraction. This cleaning process can fundamentally change the results. All of that creates what we might call method noise. So when the review says findings are mixed, it's not always because the physiology is inconsistent. Sometimes it's because the methodology is a mess. It's like trying to listen to a whisper in a hurricane. If your microphone isn't perfect, or if you record for five minutes instead of 24 hours, you might miss the message entirely. Another important contribution of this review is its discussion of comorbid conditions, specifically heart failure and depression. This connection is fascinating and tragic. Depression is associated with reduced hrv. We know this from psychiatric literature. But depression is also associated with worse cardiovascular outcomes. People with depression are more likely to get heart disease, and people with heart disease who get depressed are more likely to die. This suggests that HRV may be a shared pathway, a shared marker of system dysregulation. A low HRV might indicate a brain struggling to regulate mood and a heart struggling to regulate rhythm. They are not two separate problems. They are one problem of regulation manifesting in two different organs. It reinforces the idea that we cannot treat the heart without considering the mind. The review also highlights advances in wearable technology and machine learning. And I want to slow down here because this is where HRV is heading. For decades, getting an HRV reading meant a trip to the hospital, sticky electrodes and a 24 hour box strapped to your waist. Wearable devices now enable continuous, non invasive HRV monitoring. We aren't just getting a snapshot, we are getting a movie. We are seeing the trend. We are seeing the trajectory and machine learning. AI may enhance the predictive power of HRV by finding patterns that humans don't easily see. And AI might look at 24 hours of heartbeat data and see nonlinear patterns of chaos and subtle shifts in entropy that predict an arrhythmia better than simple SDNN ever could. It might see the risks texture.
However, Wang and colleagues are again careful. They acknowledge that these innovations may facilitate tailored treatment plans. But they state clearly clinical utility requires validation in larger prospective trials. That's the key. We can't jump from our smartwatch can capture HRV to HRV should guide cardiac care without a bridge. And that bridge is a good trial. We need to prove that acting on the data actually saves lives. Not just that the data is interesting that they also highlight that HRV often has limited incremental prognostic value over established risk factors, which is a respectful academic way of saying if you already know someone's ejection fraction is 20%, their blood pressure is 180 over 100, they are 80 years old, they have diabetes and their lipids are sky high. Knowing their HRV is low doesn't really tell you anything new. You already know they are high risk. But and this is an important but even modest incremental value can matter in certain clinical contexts, especially when you're trying to stratify borderline cases. The person who looks okay on paper but feels terrible, or the person who had a heart attack and seems to be recovering but their nervous system is silently crashing. That is where HRV shines. How do we translate this comprehensive review into a practical message? Here's how I would say it. HRV is not a replacement for traditional cardiovascular risk factors. It does not replace the blood pressure cuff or the lipid panel. But HRV may be our best early signal of autonomic impairment. HRV may help track the invisible trajectory of recovery after cardiac events. HRV may help monitor the stress related and mood related burden that often accompanies cardiovascular disease. As we standardize measurement and refine our algorithms, HRV may finally graduate from a promising marker to a standard vital sign in cardiology. Now we're going to shift gears. We are moving from the specific pathology of cardiovascular disease to the broader systemic concept of load.
Our second paper is titled Linking Allostatic Load, Heart Rate Variability, and Brain Functional Networks and Structures in Healthy Men. The authors are Juan Mesolano dejordua, Gabriel Castrillon Jazmin Echis Suarez Revello, Juan de Sanchez Lopez, Daniel Alvargastejada Joaquins, Caicedo Valentina, Juan Calderon, Jaime Galavillegas, Yedzel V. Ospina Serrano, Juan D. Caicedo Jamillo, and Ana L. Miranda Angulo from institutions in Colombia. This paper was published in Psychoneuroendocrinology. The key concept here is allostatic load. If you listen to this podcast, you've heard this term, but let's define it precisely and give it some weight. Homeostasis is the principle that the body seeks to remain stable. Constant temperature, constant ph, constant oxygen. Allostasis, a term coined by Sterling and Iyer, is the process of achieving stability through change. You encounter a stressor, a deadline, an argument, a virus. You respond. You mobilize energy. You change cardiovascular tone. You release hormones such as cortisol and adrenaline through the HPA axis. You change immune activity. This is allostasis. It is good. It keeps you alive. It allows you to run from the tiger or finish the project.
But allostatic load is the price you pay for that adaptation. It is the cumulative physiological wear and tear that results when the cycle is repeated too frequently is inefficient or recovery is incomplete. Think of it like revving your car's engine. Revving is necessary to merge onto the highway. But if you rev the engine in the driveway every morning for an hour, the engine wears out. You burn through the gaskets, you stress the pistons. That wear is allostatic load, and that wear can be measured. Allostatic load indices typically include markers across systems cardiovascular blood pressure resting heart rate metabolic glucose cholesterol Waist circumference, which indicates visceral fat and systemic inflammation Inflammatory C reactive protein Neuroendocrine cortisol DHEAS in this study, the Researchers worked with 88 healthy men aged 21 to 40 in Medellin, Colombia.
Note that age range these are young healthy men. They aren't sick patients. This is a study of healthy physiology under invisible pressure. They calculated two allostatic load indices, an index with four biomarkers, Ali 4 and an index with seven biomarkers, Ali 7. They used a quartile based risk summation method in plain English for each biomarker. If you were in the top 25% of bad scores, even if you were technically in the normal range, you got a point. Then they added the points up. This captures subclinical dysfunction, the problems that aren't yet problems. The participants also had 24 hour Holter recordings. That's important.
As discussed in the previous paper, 24 hour HRV. It includes sleep. It includes daily activity. It includes the circadian dip at night. It shows how the system recovers when the lights go out.
And this is the cool part. The participants had neuroimaging functional mri, FMRI and structural mri. Why include the brain? Because chronic stress affects the brain. The brain regulates the autonomic nervous system, the central autonomic network, the prefrontal cortex, the anterior cingulate, the amygdala, the insula. These structures tell the heart what to do. They are the command center. So the question is not just does allostatic load relate to hrv? The question is the does the brain moderate this relationship? Do differences in brain networks change how stress burden maps to autonomic regulation? They examined the functional connectivity strength of three specific networks. First, they looked at the Default Mode network, which is active when we are resting, daydreaming or ruminating. This network is often overactive in anxiety and depression. Second, they analyzed the Salience network, the System that decides what is important right now, switches between internal and external focus and scans for danger. Finally, they examined the control subnetworks, which are involved in executive function and regulation, essentially acting as the adult in the room of the brain. They also examined cortical thickness, the thickness of the gray matter and the volumes of subcortical structures. Now, what did they find? The headline finding a higher allostatic load was associated with lower HRV. Specifically, the 7 biomarker index ALI7 was positively associated with the LF over HF ratio. They report a beta of 0.09 and p 0.004 and and a confidence interval from 0.03 to 0.15. In plain language, as the cumulative wear and tear on the body allostatic load increases, the autonomic balance shifts. The LF HF ratio increases. Commonly interpreted as a shift towards sympathetic dominance or reduced parasympathetic influence. The body appears to be under stress even when resting. The engine is idling high. Now, we should also be cautious. The LF HF ratio is controversial. It is not a pure scale in which one side is sympathetic and the other is parasympathetic. LF power is messy. It includes sympathetic activity, parasympathetic activity and baroreflex activity. HF power is cleaner and typically reflects vagus nerve activity and respiration. But in a broad population analysis like this, an elevated LF HF ratio generally indicates a strained system, a system that is revving to maintain stability. The finding is consistent with the hypothesis that chronic physiological stress burden is linked to reduced autonomic flexibility. But what about the brain? They explored interactions. They wanted to see if the brain protected the heart or made it worse. They found exploratory interactions suggesting that Ali7's association with SDNN overall variability might be moderated by the functional connectivity strength in the posterior default mode network and by cortical thickness in the anterior salience network. That sounds exciting. It suggests that how your brain is wired might determine how much stress damages your heart rate variability. Maybe a strong salience network protects you. Maybe an efficient default mode network allows you to drop the load faster.
However, and this is why we read the fine print, none of these interactions remain significant after false discovery rate correction. What is that? When you test 100 different brain regions, you're bound to find a few significant correlations just by random chance. It's like rolling dice. Eventually you roll double sixes. Corrections like Bonferroni or false discovery rate are statistical penalties you apply to make sure you aren't seeing ghosts. It's a statistical speeding ticket. When they applied the penalty, the brain findings disappeared. That matters. It means we cannot confidently claim that brain parameters moderated the relationship in this specific sample. We can't say a thicker cortex protects your HRV from stress based on this data. So what is the take home? The authors conclude that in healthy men, higher allostatic load was associated with a higher LF HF ratio. They suggest the allostatic load index might serve as an early marker of morbidity and mortality risk. And they call for larger studies, including women, to clarify the predictive value and effects on brain connectivity. Clinically, this paper is relevant even if you're not in research because it reinforces something many of us see in practice. People can look healthy. Their doctor says your labs are mostly fine, glucose is a little high, blood pressure is borderline, but you're fine. But their allostatic load is accumulating. The wear and tear is happening. Their sleep is suffering, their inflammation is creeping up. And where does it show up? First, it often shows up in the hrv. In this case, HRV is functioning as the summation of the load. The check engine light comes on before the engine starts smoking. It tells us the cost of the lifestyle before the lifestyle causes the disease. I want to connect Paper one and paper two before we move on. In cardiovascular disease, HRV may reflect early autonomic dysfunction within the heart, a localized failure in chronic stress. HRV reflects cumulative physiological burden across the whole body, a systemic overload. These are not separate topics because chronic stress contributes to cardiovascular risk. So HRV sits at the intersection. It is an autonomic marker, and autonomic regulation is the highway through which stress travels to the heart. Now let's move to a study that connects autonomic dysfunction to a very real world dangerous outcome in the elderly falling. Our third paper is titled Assessment of Heart Rate Variability and Occurrence of Falls in Alzheimer's Disease An Exploratory Study. The authors are Ivlizia Antunes Rodriguez Alin, Roberta da Naga, Echini Ferrate, Serge Carvalho, Carlos Alberto Santos Filo Jose Burgos Ponce, Alessandro Ferrari Jacinto from Brazil. This paper is available in PubMed Central and published in Archivos de Niro Secretaria. The authors begin with a basic but essential Aging is associated with an increasing incidence of dementia.
Alzheimer's disease is the leading cause of dementia. And here's the critical link. Alzheimer's disease impairs autonomic function. That is a point that is often underappreciated when people Think about Alzheimer's, they think about the cortex, they think about memory loss, they think about getting lost in the neighborhood, they think about forgetting names. But Alzheimer's is a neurodegenerative condition that affects the whole brain, including the brain stem and the central autonomic network. The plaques and tangles don't stop at the hippocampus. They also infiltrate regions that control blood pressure and heart rate. So autonomic impairment is part of the disease and HRV is our marker for that function. However, findings in Alzheimer's have been conflicting. Some studies show massive autonomic failure, others show very little. And there is scanned information on the association of HRV with falls in dementia patients. Falls matter. They matter immensely. Falls are a major cause of morbidity and mortality in older adults. A hip fracture in an 80 year old with dementia is a life altering, often life ending event. Falls lead to hospitalizations, loss of independence, a cycle of fear, post fall syndrome and a massive increase in caregiver burden. So the question is practical. Does autonomic dysfunction as reflected by HRV relate to fall risk?
The study design was straightforward. They assessed older adults with mild to moderate Alzheimer's disease and they recruited older adults without dementia as controls. They measured HRV using a heart rate monitor on a single day. But they didn't just measure it while resting. They did an orthostatic challenge. They measured 10 minutes in the supine position lying down. Then the participants stood up and they measured 10 minutes in the orthostatic position, standing. Why do this? Standing up is a major stress test for the autonomic nervous system.
Gravity is a relentless force. When you stand up, gravity immediately pulls about 500 to 800 milliliters of blood into the legs and splanchnic bed. That's a lot of blood leaving the head and heart. The blood pressure drops. The baroreceptors in the neck and aortic arch sense this drop. Instantly. They scream to the brain stem. The brain stem inhibits the vagus nerve, taking the break off the heart and excites the sympathetic nervous system hitting the gas. Heart rate goes up. Blood vessels in the legs constrict to push blood back up. Blood pressure stabilizes.
[00:22:24] Speaker B: If this system is working, you stand up and you feel fine. You don't even notice it happening. If this system is broken, if there is autonomic failure, you stand up, the blood stays in your legs.
[00:22:33] Speaker A: The brain doesn't get enough oxygen and you get dizzy, you get orthostatic hypotension or you wobble or you fall. They assessed HRV components in time and frequency domains, and they collected fall history over the past three years. The groups were similar in demographics, mostly female. Average ages were around 81 for the Alzheimer's group and 79 for the control group. In both groups, shifting from supine to standing reduced the RR interval, which makes sense. Heart rate increases when you stand. Everyone's heart sped up. But here's the difference. The Alzheimer's group showed reduced parasympathetic activity in the orthostatic position compared with controls. In frequency domain terms, they observed a reduction in high frequency power, the vagal break, and increases in low frequency power, and increases in the LF HF ratio. Wait, didn't we just say increased LF HF means more sympathetic? Yes.
So Alzheimer's patients showed greater sympathetic activation when standing. It suggests a system struggling to compensate. The system is pushing too hard to maintain pressure but lacks the parasympathetic fine tuning needed to stabilize it. It's a rigid, frantic response rather than a flexible, controlled one. Or it suggests that the parasympathetic withdrawal is excessive, leaving the heart vulnerable to instability. The Alzheimer's group had significantly more falls, and fall incidence was associated with these HRV components. The the authors conclude that Alzheimer's disease was associated with worse autonomic dysfunction, increased sympathetic dominance, greater parasympathetic impairment upon standing, a high incidence of falls, and an interaction between HRV values and fall history. This is an exploratory study, but it is clinically meaningful because it suggests that HRV might help identify which Alzheimer's patients are at higher risk of falls. Now, I want to be careful here. This study does not prove that improving HRV will reduce falls. It does not prove that HRV causes falls. Correlation is not causation, but it provides a plausible physiological pathway where Alzheimer's pathology first damages the central autonomic network. This damage leads to autonomic dysfunction, which subsequently causes orthostatic instability, dizziness upon standing. That instability, in turn leads to falls. If you're a clinician, this paper suggests you might want to pay attention to autonomic symptoms in dementia patients. Do they get dizzy when they stand? Is their blood pressure label? Do they have temperature regulation issues? If you're a researcher, it suggests a pathway for intervention trials. Can autonomic training, gentle exercise, or HRV biofeedback improve orthostatic response and help these patients stay on their feet? Can we reteach the baroreflex? If you're a caregiver, it suggests practical strategies slow Transitions count to 10 before walking after standing up. Hydration, which boosts blood volume.
Monitoring medications that affect blood pressure. For all of us, it's a reminder that brain health is body health. You cannot separate the memory from the blood pressure. You cannot separate the mind from the mechanics of standing upright. Now, after three heavy studies on disease and degeneration, it's time for our mid episode break. This week in HRV is sponsored by Optimal hrv.
[00:25:27] Speaker B: You know, reading these studies about cardiovascular disease, about stress load, about dementia and it can feel overwhelming. It can feel like the nervous system is fragile, constantly under attack and degrading. But at Optimal HRV we believe the nervous system is also capable of profound learning, neuroplasticity and recovery.
[00:25:43] Speaker A: But to learn, feedback is needed.
[00:25:45] Speaker B: It needs a mirror.
[00:25:46] Speaker A: Optimal HRV provides trauma informed research based HRV biofeedback tools for clinicians, researchers and individuals. Our goal is to make nervous system regulation measurable, trainable and accessible. If you're a clinician, Optimal HRV supports both individual client work and and program level implementation. You can use our mobile app to take HRV assessments, guide clients through paced breathing exercises and track their trends over weeks and months. You can see if that intervention, that therapy, that meditation, that exercise is actually shifting their baseline physiology. You can use our educational resources to strengthen your foundation and applied psychophysiology. If you're an individual, Optimal HRV helps you turn HRV into a practical signal, not something to obsess about. We don't want you waking up and panicking because your score dropped five points. We want you to use it as a signal, a reflection of recovery, a reflection of stress load, a reflection of regulation. It's a tool for self compassion, not self judgment. It allows you to say my body is tired today. I will respect that instead of I am lazy. You can learn
[email protected] and now I have a very special event announcement to share with you. The Biofeedback Federation of Europe BFE is hosting the 24th BFE Meeting from March 23 to March 28, 2026 in Szechen, Poland. This is not just a conference, this is a gathering of the tribe. It is a six day meeting with immersive workshops, a full day scientific program and networking events designed to spark collaboration. It is where the science meets the practice. One of the featured workshop presenters is a longtime friend of the field, Dr. Ina Kazan. If you know Dr. Kazan's work, you know she brings a rare combination of scientific rigor and clinical practicality. She wrote the book literally on clinical biofeedback. She is one of the clearest voices in HRV biofeedback, especially in the context of mindfulness and acceptance based therapies act the BFE meeting features hands on workshops led by experts including Inna, several past guests of this podcast, and other recognized leaders. If you've been waiting for a reason to invest in your skills, your network and your inspiration. If you've been considering visiting Poland, this is it. Registration is ongoing and space is limited for the workshops, so register now. You can find details on the Meeting website, visit bfemeeting.org that's bfemeeting.org alright, let's get back to the research. Our fourth study takes HRV out of the hospital and into the future, into a domain that feels very current for anyone who works remotely. Remote Collaboration, Virtual Presence and Physiological Synchrony the title is Remote Collaboration in Virtual Reality induces physiological synchrony comparable to face to face Interaction. The authors are Stefan Strieber, Sarah Rogula, Maria Alejandra Quiros Ramirez, and and Jens Prisner. This was published in Scientific Reports, which is a Nature portfolio journal. The key concept here is physiological synchrony. What is that? It refers to the temporal alignment of bodily signals between individuals during social interaction. When you have a deep conversation with a friend, your heart rate often begins to oscillate in a similar rhythm. Your breathing may align, your skin conductance responses may mirror each other. This isn't magic, it's biology. It's rooted in our evolution as pack animals. It reflects implicit processes, shared attention, shared emotion, shared rhythm of speech. It is the physiological basis of empathy. Synchrony has been linked to social cohesion. High synchrony often predicts better rapport, better team performance, and more effective therapy. It's the biological substrate of being on the same wavelength.
Traditionally, synchrony is studied in face to face contexts. Why? Because physical proximity provides the sensory inputs we need. We see the micro expressions, we hear the subtle intake of breath. We feel the presence of the other via mirror neurons. We unconsciously mimic posture. But we now live in the era of zoom, the era of slack, the era of remote work, video conferencing, remote teams, distance learning, and telehealth. The central question for sociology and psychology is can remote interactions support the same deep physiological connection, or are we just exchanging information without the biological resonance? Are we just talking heads? This study compares three conditions. The first is face to face collaboration, the first the gold standard involving real people in a real room. The second is remote collaboration via video conferencing, such as Zoom or Microsoft Teams, which is the current standard. The third condition is remote collaboration using immersive virtual reality headsets representing a futuristic alternative. Participants worked in triads, groups of three. They performed a collective creativity task. They had to design something together. The researchers measured three things. The creative outcome, essentially asking how good the idea was, social presence or how much they felt like they were together and HRV synchrony, the mathematical coupling of their heart rate variability signals. The findings are fascinating because they show a dissociation. First, creative performance and social presence were highest in face to face.
No surprise there. Humans are evolved to be together. Both measures were reduced in VR and video. People felt less there and were slightly less creative. But look at the physiology. HRV synchrony was strong and face to face. HRV synchrony was also strong in virtual reality. In fact, it was comparable to face to face. But HRV synchrony was significantly weaker in the video condition. That is a profound finding. It suggests that subjective feelings and objective physiology are not always telling the same story. The participants reported feeling less present in VR than in face to face interactions. But their bodies were syncing up in the video. They were looking at each other's faces, but their bodies were disconnected. They were biologically isolated. What explains this? Why would cartoon avatars in VR create a more biological connection than a high definition video of a real face?
One possibility is embodied interaction. In VR you share a 3D space. You have spatial orientation. If I stand to your left, you hear me on your left. If I point at an object, we both look at that object. In 3D space, we have joint attention on a shared environment.
We move our heads. We use our hands. Video calls flatten the interaction. We are all heads in boxes. Eye contact is impossible. If I look at your eyes, I'm not looking at the camera. There is no shared space. I am in my room, you are in yours. I cannot see what you are looking at. The authors suggest that the shared spatial environment in VR enables natural movement and spatial cues that the autonomic nervous system interprets as being together. It triggers the ancient systems of proximity. Video eliminates these cues. Video forces us to stare at ourselves. The mirror anxiety effect, which keeps us self focused rather than other focused. It's this matters. It matters for clinicians, telehealth is here to stay. But if video calls reduce physiological synchrony, does that affect the therapeutic alliance? Does it make CO regulation harder?
Maybe it matters for educators. Is remote learning failing because students can't sync with the teacher? It matters for organizations. If you want a team to bond. A zoom happy hour may not be enough. Maybe, and I can't believe I'm saying this, a VR meeting might be better. If VR supports physiological synchrony, it might support a deeper kind of unconscious connection. The kind that supports trust, the kind that supports CO regulation. It suggests that our nervous systems need space and movement to connect, not just pixels of a face. So the take home VR may better support physiological CO regulation than video conferencing. An HRV is not only an individual marker inside your own skin, it is a social marker. It is a bridge between bodies. It is the invisible thread that connects us that transitions beautifully into our fifth study Our fifth study focuses on HRV and performance, but in a very different population children and a very specific type of performance attention. The fifth paper is titled Heart Rate Variability and MOXO d CPT Relationship in Children with Attention Deficit Hyperactivity Disorder. The authors are Sultan Tarlacha and Yaren Kayatopal. Published in Applied Psychophysiology and Biofeedback. This is a case control study involving 52 children aged 6 to 12. A DHD diagnosis was confirmed by a child psychiatrist according to DSM 5 criteria. They were careful to exclude comorbidities like anxiety or oppositional defiant disorder, which could confuse the HRV data. They stratified them into an ADHD group, 33 children and a control group, 19 children. They used the MOXO DCPT to characterize performance. The MOXO is a continuous performance test. It measures attention, timing, impulsivity and hyperactivity. But unlike older tests that are just boring white screens with letters like the tova, the MOXO introduces visual and auditory distractors. It simulates the real world. It flashes cartoons. It plays sounds. It tries to annoy the child while they are trying to focus. It tests attention under load. They recorded resting state HRV for five minutes. They analyzed time domain SDNNRMSSD and frequency domain VLF LF HF measures. Now what did they find? The strongest findings were for two metrics, VLF power, very low frequency and the SNS index Sympathetic Nervous system index. Finding 1. The good performance group on the test demonstrated significantly lower VLF power compared to the weak performance group. They report an eta squared of 0.176. That's a decent effect size. Finding 2. The SNS Index was significantly higher in the group with weak hyperactivity scores, meaning they were more hyperactive. They reported Cohen's D of 0.49. That's a medium effect size. Interestingly, they observed non significant trends For SDNN and rmssd, the standard parasympathetic markers showed no significant difference between the groups. Let's interpret this first, vlf, very low frequency power is a mysterious metric. In short recordings 5 minutes VLF is physiologically dubious. It is usually thought to reflect thermoregulation, the renin angiotensin system, hormonal blood pressure control and perhaps slow sympathetic rhythms. High VLF in a short recording is often interpreted as instability or baseline wandering. It suggests the system is drifting. Children who performed worse showed more of this erratic slow wave instability. Their biological baseline was fluctuating wildly. Second, the SNS index. This metric is derived from the shape of the Poincare plot. A higher SNS index indicates the heartbeat is highly rhythmic and metronomic children who were more hyperactive had a more sympathetic heart rhythm, more fight or flight. Their bodies were revved up, making it hard to sit still, hard to inhibit the impulse to move. Their conclusion VLF and the SNS index were the most robust HRV metrics associated with impulsivity and hyperactivity.
The lack of findings in rmssd, the vagal break, is interesting. In ADHD research, HRV findings have historically been mixed. Some studies show reduced vagal tone, some show no differences. Why the confusion? One reason is heterogeneity. A DHD is not one thing. There is the inattentive type, the hyperactive type, the combined type. There are kids who are sluggish and kids who are wired high arousal. Lumping them together might obscure the HRV averages. Another reason is the measurement context. Asking an ADHD child to sit still for 5 minutes to measure HRV is in itself a stress test. The measurement might be capturing their frustration with sitting still rather than their baseline physiology. From a clinical standpoint, however, the SNS finding aligns with the regulation framing. Many ADHD symptoms can be interpreted as dysregulation a nervous system that is more easily activated, a sympathetic system that is too quick to trigger, a braking system that is inconsistent. Now we must be cautious. HRV is not a diagnostic tool for adhd. This study does not claim that you cannot distinguish an ADHD child from a non ADHD child just by looking at their heart rate.
It suggests that autonomic markers may relate to performance profiles. This could matter for monitoring if a child undergoes behavioral therapy, if they start medication, if they do exercise interventions, if they do biofeedback, does their HRV profile change? Does the SNS index drop? Does the VLF stabilize? HRV can be valuable here not as a label but as a training Feedback signal. It helps us see if the intervention is reaching the nervous system. Now our final study. We have looked at the heart, the stressed body, the aging brain, the virtual connection and the developing mind. Now we look at the earliest whisper of decline, the twilight zone between healthy aging and dementia. The sixth study is titled Cognitive Changes in Emotional Heart Rate Variability Dynamics in Subjective Cognitive Decline. An Exploratory Longitudinal Neuropsychophysiological Study. The authors are Giuseppina Elena Cipriani, Francesca Borghesi, Pietro Cipresso, Nicola Canessa, Sara Molfese, Cristiano Manco, Alicia Cirico, Gloria Simoncini, Mateo Anselmino and Martina Amancio from Italy. Published in Acta Psychologica, this study focuses on subjective cognitive decline. SCD. SCD is a fascinating and somewhat scary concept. It refers to individuals who go to the doctor and say, doc, my memory is slipping. I'm not as sharp as I was. I can't find the right word. But when the doctor runs the tests, the scores are normal. They pass the exams. Historically, doctors told these people, you're fine, it's just stress, it's just aging. Go home.
But we now know that SCD can be a pre clinical stage of Alzheimer's. The patient notices the change before the test can measure it. Their brain is compensating, working harder to get the same result. The cognitive reserve is masking the damage. Not everyone with SCD progresses to dementia, but as a group, they are at higher risk. The question is, can we identify physiological markers that indicate which of these people are truly vulnerable? Can we see the cracks in the foundation before the house starts to lean? This study uses HRV as a psychophysiological marker. They studied 21 participants meeting SCD criteria. This is a longitudinal study. They assessed them at baseline and again approximately 12 months later. Each session included comprehensive neuropsychological testing. Memory, language, executive function. And this is key. They recorded continuous HRV during an affective storm. They showed the participants a series of emotionally evocative images from the IAPS database. Positive images, a smiling baby, a sunset. Negative images, a pointed gun, a crying face. Neutral images, a chair. They wanted to see how the heart reacts to emotion. Why emotion? Because the brain areas that process emotion, amygdala, medial, prefrontal cortex, are the same areas that regulate the heart. And they are often the areas affected early in neurodegeneration. If the prefrontal cortex, the regulator, is weakening, the emotional response should become dysregulated. Now, here's the finding at the group level, averaged across all participants. There were no significant changes over the 12 month period. The group didn't get statistically worse. At the individual level. Longitudinal variations in HRV were associated with cognitive performance.
Specifically, changes in global cognition, verbal fluency and visuospatial working memory were correlated with changes in HRV indices. Participants whose HRV flexibility declined over the year tended to show steeper cognitive decline. Participants whose HRV remained robust tended to maintain their cognition.
What does this mean? It suggests that dynamic autonomic responses to emotional stimulation may reflect subtle correlates of cognitive functioning. The authors invoke the Neurovisceral integration model.
This model proposes that the prefrontal cortex acts as a conductor. It inhibits the amygdala. It regulates the heart, keeping HRV high. It focuses attention, keeping cognition sharp. If the prefrontal cortex starts to fail due to early disease, the inhibition lifts. The heart becomes less variable, less regulated. Emotion becomes less regulated. Cognition becomes less sharp. They are all downstream effects of the same upstream failure. The conductor has left the podium and the orchestra is falling apart. This is an exploratory study. Small sample, 21 people. We cannot generalize this to the whole world yet, but conceptually it is important. It suggests HRV can be part of early screening. Imagine a future checkup. You don't just do a memory test. You watch a sad movie clip while wearing a heart monitor. The doctor assesses how your system recovers. That recovery curve might tell them as much about your brain health as the memory test does. It also suggests that emotional regulation and autonomic flexibility are tied to cognitive resilience.
Keeping the heart flexible might, just might, help keep the mind flexible. Now we've covered all six studies. That was a lot of science, a lot of methodology. Let's take a breath and let's synthesize.
What is the story here. We looked at cardiovascular disease and the pump itself. We explored allostatic load and the cost of stress. We examined Alzheimer's falls and the mechanism of autonomic failure. We analyzed VR synchrony and the concept of the social body. We investigated ADHD performance and the dysregulated child. Finally, we discuss subjective cognitive decline as an early warning signal. One theme appears again and again. HRV reflects flexibility and the loss of HRV reflects rigidity in cardiovascular disease. HRV reflects the rigidity of a sick heart and a remodeled nervous system. It warns of the lack of reserve, the inability to handle a shock like an arrhythmia. It is the stiff tree that breaks in the wind. In allostatic load HRV reflects the rigidity caused by constant pressure. The system is stuck and on. The flexibility of the off switch is eroding. The engine is redlining. In Alzheimer's disease, that rigidity becomes literal instability. The system cannot adjust blood pressure fast enough. When standing up, gravity wins. The person falls. The flexibility to adapt to posture is gone. In virtual reality, we see that flexibility is social. We sync with others to form a flexible shared unit. And VR might support that biological handshake better than video, allowing our bodies to resonate in a shared space. In adhd, we see a system that is too labile or paradoxically rigid. In its sympathetic arousal, the child struggles to flexibly shift between states of play and focus. The rhythm is disrupted. In subjective cognitive decline, we see that the loss of autonomic flexibility mirrors the loss of cognitive flexibility. The mind and the heart narrow together. The window of tolerance shrinks.
So what are the takeaways? For clinicians, HRV is a contextual tool. It is not a magic wand. It doesn't diagnose a specific disease. However, it provides information about the patient's condition. It indicates whether they are brittle. It indicates whether they are loaded. It can support case conceptualization. It can help track regulation. It can reveal patterns that are invisible in symptom checklists. But it must be interpreted carefully. Standardized protocols matter. Don't compare a 5 minute sitting test to a 24 hour lying down test. An HRV should complement, not replace, clinical judgment. For researchers, these studies highlight both promise and massive methodological challenges. We need larger samples. 21 people are a start, but we need 2,000. We need longitudinal designs. We need to follow people for 10 years to see if the HRV drop really predicts a dementia. We need better standardization. We need to agree on how to clean the data. We need a careful interpretation of the metrics. We need to stop fighting about lf, HF and start looking at the whole picture. For individuals, HRV is feedback. It is not a grade. You're not a C minus human being because your HRV is low today. It is not your worth. It is a signal. A signal of recovery. Did I sleep well? A signal of stress load. Am I over training? A signal of adaptability. Am I ready for a hard conversation? Use it to learn about yourself. Use it to be kind to yourself. If your HRV is low, don't beat yourself up. Rest, breathe, recover. Listen to the window. And for all of us, this week's research reinforces a core idea. Your nervous system is not separated into compartments. Cardiovascular health, stress physiology, cognitive aging, child attention. Social connection. These are not different books, they are different chapters in the same book. And hrv. HRV is the index. It helps us find where the story is going. Thank you for joining us on the Heart Rate Variability podcast. I know this was a long one, I know it was dense, but I hope it was valuable. If you found this episode helpful, please subscribe.
Leave a Review it really helps people find the show and share it with someone who cares about mind, body, health. Share it with a cardiologist. Share it with a therapist. Share it with a teacher. We'll see you next time. Until then, take good care of your nervous system. One breath, one beat, one moment at a time.
