ArticlePDF AvailableLiterature Review

Heart Rate Variability Interventions for Concussion and Rehabilitation

  • Carolina Neuropsychological Service


The study of heart rate variability (HRV) has emerged as an essential component of cardiovascular health, as well as a physiological mechanism by which one can increase the interactive communication between the cardiac and the neurocognitive systems (i.e., the body and the brain). It is well-established that lack of HRV implies cardiopathology, morbidity, reduced quality-of-life, and precipitous mortality. On the positive, optimal HRV has been associated with good cardiovascular health, autonomic nervous system (ANS) control, emotional regulation, and enhanced neurocognitive processing. In addition to health benefits, optimal HRV has been shown to improve neurocognitive performance by enhancing focus, visual acuity and readiness, and by promoting emotional regulation needed for peak performance. In concussed athletes and soldiers, concussions not only alter brain connectivity, but also alter cardiac functioning and impair cardiovascular performance upon exertion. Altered sympathetic and parasympathetic balance in the ANS has been postulated as a critical factor in refractory post concussive syndrome (PCS). This article will review both the pathological aspects of reduced HRV on athletic performance, as well as the cardiovascular and cerebrovascular components of concussion and PCS. Additionally, this article will review interventions with HRV biofeedback (HRV BFB) training as a promising and underutilized treatment for sports and military-related concussion. Finally, this article will review research and promising case studies pertaining to use of HRV BFB for enhancement of cognition and performance, with applicability to concussion rehabilitation.
published: 13 August 2014
doi: 10.3389/fpsyg.2014.00890
Heart rate variability interventions for concussion and
Robert L. Conder1* and Alanna A. Conder 2
1Department of Sports Neuropsychology, Carolina Neuropsychological Service, Raleigh, NC, USA
2Pediatric and Sports Neuropsychology, Carolina Neuropsychological Service, Raleigh, NC, USA
Edited by:
J P. Ginsberg, Dorn VA Medical
Center, USA
Reviewed by:
J P. Ginsberg, Dorn VA Medical
Center, USA
Paul Comper, University of Toronto,
Leah M. Lagos, Leah Lagos LLC, USA
Robert L. Conder, Department of
Sports Neuropsychology, Carolina
Neuropsychological Service, 1540
Sunday Drive, Suite 200, Raleigh,
NC 27609, USA
The study of heart rate variability (HRV) has emerged as an essential component of
cardiovascular health, as well as a physiological mechanism by which one can increase
the interactive communication between the cardiac and the neurocognitive systems (i.e.,
the body and the brain). It is well-established that lack of HRV implies cardiopathology,
morbidity, reduced quality-of-life, and precipitous mortality. On the positive, optimal HRV
has been associated with good cardiovascular health, autonomic nervous system (ANS)
control, emotional regulation, and enhanced neurocognitive processing. In addition to
health benefits, optimal HRV has been shown to improve neurocognitive performance
by enhancing focus, visual acuity and readiness, and by promoting emotional regulation
needed for peak performance. In concussed athletes and soldiers, concussions not
only alter brain connectivity, but also alter cardiac functioning and impair cardiovascular
performance upon exertion. Altered sympathetic and parasympathetic balance in the ANS
has been postulated as a critical factor in refractory post concussive syndrome (PCS).This
article will review both the pathological aspects of reduced HRV on athletic performance,
as well as the cardiovascular and cerebrovascular components of concussion and PCS.
Additionally, this article will review interventions with HRV biofeedback (HRV BFB) training
as a promising and underutilized treatment for sports and military-related concussion.
Finally, this article will review research and promising case studies pertaining to use of
HRV BFB for enhancement of cognition and performance, with applicability to concussion
Keywords: heart rate variability, concussion, mildTBI, biofeedback, neurofeedback, rehabilitation
Heart rate variability (HRV) has emerged as an essential com-
ponent for study, research and clinical applications in physiology
and psychophysiology (Moss et al., 2013). Research has shown
implications for HRV in physiology, pathophysiology, psychol-
ogy, psychopathology, cognition, and neurocognitive impairment
(Gevirtz, 2013). Within the physical domain, HRV has been
postulated as a measure of not only cardiac health, but of
cardiac pathology and as a marker of possible mortality from
cardiopathology (Bigger et al., 1995). Psychologically, given its
connections with the autonomic nervous system (ANS) and lim-
bic system, HRV can be a marker for anxiety disorders, such as a
generalized anxiety disorder (GAD), post-traumatic stress disor-
der (PTSD), or a general predisposition to react sympathetically
to external or internal stressors (Blechert et al., 2007). Cogni-
tively, persons with high HRV have shown superior performance
on neurocognitive measures of attention, concentration, working
memory, and executive functioning (Hansen et al., 2003). Alterna-
tively, HRV can be adversely affected by concussions or any degree
of traumatic brain injury (TBI; Goldstein et al., 1998). However,
there is research that HRV and HRV impairment can be mod-
ified and trained through exercise (Hedelin et al., 2001;Hansen
et al., 2004;Hautala et al., 2009), diet (Lima-Silva et al., 2010),
and biofeedback interventions (Lehrer et al., 2013). This article
will first review theoretical models of the heart–brain ANS inter-
action, with specific emphasis on the adverse effects of sport and
military concussions on HRV. Second, this article will review stud-
ies suggesting that heart rate variability biofeedback (HRV BFB)
is a promising intervention for treatment of sport and military
First, it is necessary to review the etiology and severity of TBI
to understand where concussions fall along the continuum of
severity of injury and how they may affect HRV. TBI is defined
as an injury to the brain resulting from blunt trauma to the
head or body, or acceleration or deceleration forces transmitted
to the brain (Barr and McCrae, 2011). TBI severity is classified
as Mild, Moderate, or Severe based on degree of injury severity,
including presence and length of loss of consciousness (LOC) and
number and degree of post-traumatic symptoms. These three cat-
egories are based on assessment with the Glasgow Coma Score
(GCS; Teasdale and Jeanette, 1974). The GCS measures a patient’s
level of functioning based on eye opening and verbal and motor
responses, resulting in a score ranging between 3 (minimum) and
15 (maximum). The Mild GCS group has a score of 13–15, and
typically will have minimal or no permanent neurologic seque-
lae, with typical recovery expected in 1–3 months (Levin et al.,
2012). The Moderate TBI group has a GCS score of 9–12 and
may have permanent sequelae impacting personal life, school or August 2014 |Volume 5 |Article 890 |1
Conder and Conder HRV interventions for concussion and rehabilitation
work; finally, the Severe TBI group has a GCS score of 8 and
below, and will almost always present with permanent neuro-
logic damage at a moderate level or greater, affecting all aspects
of life. It is the “Mild” group that is the primary focus of this
article, as these are the athletes and soldiers that most often will
be seen clinically and who may have cardiac correlates of con-
cussion sufficient to interfere with cognitive and cardiovascular
resources needed for athletic and military performance. Generally,
patients with a GCS in the 13–15 range will not have LOC, but may
have episodic cognitive confusion, transient amnesia, dizziness,
slow reaction time, and balance problems (McCrory et al., 2013).
When assessed in the Emergency Room, the traditional physical
neurologic exam will be negative and non-focal for pathology, as
will the Head CT. The traditional Emergency Room concussion
evaluation protocol may not elucidate underlying neuropathol-
ogy, which is being seen in controlled research studies of athletes
with sophisticated neuroimaging including magnetic resonance
spectroscopy, fMRI, or diffusion tensor imaging (DTI; Bluml and
Brooks, 2006;Pardini et al., 2011) or neuroelectrical assessment
including EEG and ERP (Broglio et al., 2009;McCrea et al., 2010;
Barr et al., 2012). If someone with a presumed Mild TBI does
present with greater neuropathology, such as a basilar skull frac-
ture, intracerebral bleed, or cerebral hematoma, then they are
generally referred to as a “complicated” Mild TBI and the sever-
ity of injury is noted, with implications for a more complicated
Giza and Hovda (2001) have elucidated an animal neu-
rometabolic model of mild TBI or concussion, in which there is
a significant mismatch between glucose metabolism and regional
cerebral blood flow, with a concomitant influx of glutamate and
other ionic changes in the cell membrane. Their studies have
repeatedly shown a return to baseline neurometabolism around
seven days post-injury, presumably without permanent cellular
damage. These animal studies have provided the basis for pre-
dicted return to baseline functioning in athletes in 7–10 days. This
neurometabolic model may be useful to explain the quick recov-
ery typical of non-refractory concussions. However, refractory
concussions (the focus of this article) may be better explained by
a model of neuronal deformation induced by the biomechanical
force of the injury (Abolfathi et al., 2009).
McCrory et al. (2013) postulate that concussions may overlap
with the lower end of the Mild TBI spectrum, and may extend to
a lesser degree of severity labeled Minimal TBI. The terms “con-
cussion” and “Minimal TBI” may be used interchangeably and as
an alternative to Mild TBI but “concussion” will be used in this
article, consistent with its usage in sports medicine.
Bigler (2008) points out that a concussion from a football
tackle, automobile accident or blast injury does not solely affect
the brain. The concussive forces can affect all organs, including
the heart (Cernak and Noble-Haeusslein, 2009). Cardiac seque-
lae of a primary blast injury may produce arrhythmias, ischemia
or a myocardial infarction (Garner and Brett, 2007), even in the
absence of cerebral concussion. For example, comotio cordis
is an unfortunate and often fatal cardiac event from a direct
blow to the chest wall, usually in baseball, and without a con-
comitant cerebral concussion. Additionally, Palma and Benarroch
(2014) reviewed non-traumatic cerebral illnesses which impair
HRV, including epilepsy, ischemic, and hemorrhagic stroke and
neurodegenerative diseases, such as Parkinson’s. They postulate
that these neuropathologies involve the insula, basal ganglia, and
brainstem and may impair HRV, leading to secondary cardiac
While there have been studies measuring actual G-force on the
playing field (Guskiewicz and Mihalik, 2011), few such studies have
been done for the most common cause of concussion in adults:
automobile accidents. In children, the most common cause of
concussion presenting at emergency departments is bicycle acci-
dents (Gilchrist et al., 2011), followed by sport-related injuries.
The change in momentum (impact) and transfer of kinetic energy
in low impact auto accidents can produce a concussion, and these
kinetics and V-max are presumed to produce greater forces than
those experienced on the playing field.
Other factors that can impact concussion recovery include pro-
tective health status and motivation. Athletes and soldiers tend to
have greater cardiovascular and aerobic fitness, which has been
postulated as a protective factor for recovery from complicated
concussion (Kontos et al., 2006), as opposed to the general, some-
times deconditioned, population. Psychosocial factors, such as
motivation, also can impact recovery trajectory. Ponsford et al.
(2000) tracked emergency room TBI admissions by mechanism
of injury (MOI). After three months, the athletes who presented
at the emergency room were significantly less symptomatic than
those who presented with a motor vehicle accident as their MOI.
Data is not currently available on quantification of blast injury for
soldiers in theater, or their outcomes regarding concussion. Never-
theless, typical sequelae of a refractory Mild TBI include problems
in attention, concentration, working memory, and executive func-
tioning. Even though the MOI is different between blast injuries
(Garner and Brett, 2007) and athletic injuries, the neuropsycho-
logical outcomes are similar (Belanger et al., 2009;Cooper et al.,
2012) and symptom differences may be due to PTSD in the mili-
tary group (Lippa et al., 2010). Tan etal. (2009) report a complex,
synergistic relationship between PTSD, pain, Mild TBI, and HRV
in OEF/OIF veterans.
As this article focuses on the relationship between HRV, cogni-
tion, and concussion, an explanation of HRV is necessary. While
a full explication of HRV assessment and treatment is beyond the
scope of this article, for our purposes we are interested in the mea-
sures traditionally cited in the research literature that are amenable
to measurement and intervention in the clinic and in exploring
the cardiac correlates of concussion. HRV is measured as part of
the cardiac QRS complex. The Inter-Beat Interval (IBI) measured
between R-waves is the basis for measurement of HRV. HRV was
initially felt to be more artifacts, but now is itself the focus of
intense study (Lehrer, 2013). HRV is also useful in that it can be
measured with minimal hardware and software. A traditional EKG
with as few as three chest leads or a three-lead wrist placement with
electrodes can be used (Thought Technology, Montreal, Canada).
A Blood Volume Pulse sensor (photoplethysmograph) attached
to the distal phalange of a finger or the earlobe can be used with
appropriate hardware and software to also calculate the IBI (Heart-
Math, Boulder Creek, CA, USA; StressEraser, New York, NY, USA).
Frontiers in Psychology |Psychology for Clinical Settings August 2014 |Volume 5 |Article 890 |2
Conder and Conder HRV interventions for concussion and rehabilitation
There are two standard metrics for measuring HRV for analysis
and treatment. One is the time domain (changes over time) and
the other is the frequency domain (measurement of a spectrum
of oscillatory components of the heart). While there are multi-
ple measures of time domain, the most common used statistical
method is measuring the Standard Deviation of the Normal-to-
Normal interval (SDNN). The SDNN is basically normalization
of the standard deviation of the R-to-R interval, with artifacts
removed. Comparisons of data should be with equal epochs, usu-
ally 5 min for SDNN. The power spectrum measurements are
fractionations of all the oscillatory frequencies contained within
a specific epoch. The frequencies are generally calculated over the
same epoch as the SDNN metric. There are three frequency sub-
bands of particular interest within HRV. The very low frequency
(VLF) is composed of frequencies less than 0.04 Hz. The low fre-
quency (LF) is composed of frequencies between 0.04 and 0.15 Hz.
The High Frequency (HF) band investigates frequencies between
0.15 and 0.4 Hz. There are both physiologic and cognitive cor-
relates of these frequency bands. The VLF band is considered
to reflect mainly sympathetic activity. The LF band is consid-
ered to show parasympathetic activity, as well as the baroreflex
and enhanced cognitive processing. The HF band is considered to
reflect respiratory sinus arrhythmia, and activity from the vagus
nerve (Combatalade, 2010).
These same hand-held HRV monitoring devices can provide
visual and/or auditory feedback to train HRV. HRV training begins
with breathing exercises to increase respiratory sinus arrhythmia,
and help one find their resonant frequency – the frequency at
which greatest HRV occurs. Breathing rates between 4.5 and 6.5
breaths per minute will produce the greatest HRV in most per-
sons. The biofeedback instruments can provide a visual pacer for
breathing rates and informs the person when they have achieved
the greatest coherence between respiratory rate and heart rate. A
more detailed training protocol is reported by Lehrer etal. (2000).
Thayer et al. (2009,2012) and Thayer and Lane (2009) have
postulated an intricate Neurovisceral model of the relationship
between the prefrontal cortex of the brain and the heart. In the
Thayer model, prefrontal brain areas, including the orbitofrontal
cortex and the medial prefrontal cortex tonically inhibit the amyg-
dala, with disinhibition of the central nucleus of the amygdala.
The deactivation of inhibitory nuclei leads to a net increase in
sympathetic activity which eventuates in decreased HRV and
increased heart rate. The central nucleus of the amygdala is
believed to be the major efferent source of modulation of auto-
nomic, endocrine, and cardiovascular responses. Three routes are
postulated. One involves the activation of tonically active sym-
pathoexcitatory neurons of the rostral ventrolateral medulla due
to decreased inhibition from neurons in the caudal ventrolateral
medulla, resulting in an increase in sympathetic activity. The sec-
ond involves inhibitory neurons in the nucleus of the solitary tract,
which can lead to a decrease in overall parasympathetic activity.
The third postulated pathway involves direct excitation of sympa-
thetic rostral ventrolateral medulla neurons, further leading to an
increase in sympathetic activity. The overall result, regardlessof the
pathway, would be an increase in sympathetic output and overall
heart rate, with a concomitant decrease in HRV.While these path-
ways have not been validated either electrophysiologically or with
physiologic staining techniques, Lane et al. (2007) used positron
emission tomography (PET) to measure medial prefrontal activity
along with simultaneous measurement of spectral HRV. In these
studies, subjects were shown film clips depicting emotional situa-
tions, involving happiness, sadness, or disgust. In all experimental
conditions, HF HRV was correlated with activation of the right
prefrontal cortex.
Thayer and Lane (2009) also elucidate hemispheric differences
in cardiac activation. Aron et al. (2004) postulate that the right
prefrontal cortex may have more potent input for cardiac mod-
ulation. This is not surprising, given the functional neurology of
the right prefrontal cortex involved in emotional regulation and
dysregulation. Nevertheless, the models propose that prefrontal
activity will modulate cardiac output, including general heart rate
and HRV. However, Mild TBI or concussion injuries are rarely
lateralized, typically being more diffuse in etiology and MOI.
Williamson et al. (2013) propose a similar model. They propose
a model of connections between the orbitofrontal cortex through
the uncinate fasciculus to the amygdala, terminating in the sympa-
thetic nervous system. The importance of these white matter tracts
for this model is that they communicate from the prefrontal cor-
tices to the brain stem, then to the heart. Disruption of the white
matter tracts may induce a loss of inhibitory control upon theANS.
Not only does this loss of inhibitory control result in impairment
of cognitive abilities, but it also can result in loss of emotional reg-
ulation, as seen in soldiers and civilians with PTSD. This review
cites similar neuroimaging studies to Thayer etal. (2009) as well
as citing neurotransmitter involvement.
Studies using DTI assess the integrity of the white matter tracts,
whereas typical MRI including T1, T2, and FLAIR protocols may
not show neuropathology in white matter. In DTI studies, frac-
tional anistrophy (FA) and mean diffusivity (MD) are measures
of white matter integrity noted to be impaired in concussion. Dis-
ruption may result in loss of neural transmission or in reduction
in transmission time due to neural deformation from physical
trauma (Bazarian et al., 2007).
As noted above, children from pre-school to senior high school are
most often injured in bicycle accidents. Among teen sports,Amer-
ican football is the next most frequent concussion generator. By
gender in this age group, American football is the greatest concus-
sion generator for males, while soccer is the greatest concussion
generator for females. Both sports can provide blunt trauma at
high velocity, either directly through head-to-head strikes, foot-
or knee-to-head strikes, or striking the ground or another object,
such as the goal. Due to the jagged cranial cavity, most often the
physical injury to the brain impacts the orbitofrontal and anterior
temporal areas. Linear forces are more often involved in head-
to-head contact of athletes and persons in motor vehicles with
straight-line acceleration, then impact, followed by rapid decel-
eration. In contrast, rotational injuries may be seen in open-field
tackles or checking or boarding on the ice of a hockey rink.
While traditional neuroimaging will not show white matter
attenuation, a recent study of Division I Ivy League football players August 2014 |Volume 5 |Article 890 |3
Conder and Conder HRV interventions for concussion and rehabilitation
with subconcussive injuries (not diagnosed with a formal con-
cussion) revealed changes in FA and MD DTI after a season of
play (McAllister et al., 2014). The groups compared contact sports,
such as American football and soccer versus non-contact sports,
including cross country and track and field. There were signifi-
cant changes in FA and MD in the contact sport group over the
course of a season. Long-term follow up is needed to ascertain if
these changes are reversible (some data points to this) or if they
are non-reversible. However, this does validate the concerns about
the integrity of white matter tracts as being the conduit between
the heart and brain.
Thompson and Hagedorn (2012) report alterations in HRV in
patients with concussion or mild TBI, including low amplitude
and poor rhythmicity. Decrease in HRV has been seen among
patients with all levels of TBI severity, from Severe TBI (Baugley
et al., 2006) to concussion (Goldstein et al., 1998;La Fountaine
et al., 2009). Disruption in cardiovascular reactivity was noted
after sports concussion, with interruptions of middle cerebral
artery blood velocity after oxidative stress (Len et al., 2011). Len
et al. (2011) studied HRV in Canadian Junior Hockey League play-
ers with and without concussion and matched for demographic
characteristics. In the resting condition, there were no differences
noted. However, upon exertion, there were significant differences
in total HRV, as well as LF and HF power for the concussed group.
This has implications for elite athletes who quickly need to respond
with greater cardiovascular output to perform well in their sport
(Gall et al., 2004). By extension, this cardiovascular output dys-
function may also hold true for soldiers concussed in IED blasts.
Similarly, Leddy et al. (2007) fully reviewed the ANS changes from
concussion, including “greater sympathetic and lower parasym-
pathetic activity ... and cerebrovascular dysregulation. These
concussive changes may affect multiple organ systems, includ-
ing pulmonary, hepatic, and renal. They suggest an individualized
aerobic exercise program that is below the threshold of symptom
As multiple models postulate a heart–brain connection in HRV,
measurement can empirically validate this neurovisceral relation-
ship. Searches of both Medline and PsychInfo revealed only a few
studies that addressed measurement of EEG changes with HRV
intervention. Sherlin et al. (2010) measured EEG variables dur-
ing HRV training. They assessed 19-channel QEEG and sLORETA
variables in a group of laboratory stressed-induced (non-injured)
subjects undergoing HRV training. Significant changes in either
alpha increase or beta decrease were found at Brodman’s areas 24,
30, and 31, all associated with the limbic system and cingulate
gyrus. The authors postulate these measured EEG changes from
HRV BFB reflect a decrease in autonomic arousal in brain areas
critical for stress regulation.
Prinloo et al. (2013) examined EEG correlates of HRV interven-
tion in stressed senior managers, further exposed to experimental
laboratory stress. In this study, five EEG sites were monitored. Two
frontal sites (Fp1 and Fp2) were monitored for muscular artifacts.
The important midline sites of Fz, Cz, and Pz were monitored,
as they are thought to reflect brain attention and arousal mech-
anisms. After a single session of HRV BFB, significant changes
were found with reduced beta and increased theta at all three
central sites. The authors suggest these EEG changes are reflec-
tive of “... increased relaxation, decreased anxiety and decreased
mental effort ...(p. 31).” These EEG changes were associated with
increases in LF and SDNN HRV variables.
Reid et al. (2013) assessed EEG changes in 40 clinical sub-
jects, half of whom were athletes undergoing optimal performance
training, including HRV BFB. For this study, only one EEG site was
utilized: Cz, the primary central site of the vertex, reflecting the
sensorimotor rhythm (SMR) at 12–15 Hz. Clients showing suc-
cessful HRV training (peak frequency heart rate between 0.05 and
0.15 Hz) also showed significant increases in SMR amplitude. The
authors conclude that the SMR increase reflects a state of relaxed
anticipatory focus (Sterman, 1966) useful for athletes who need to
perform better in stressful sport competitions, with greater flexi-
bility and regulation over their ANS. By extension, soldiers might
also benefit from this approach.
Collura (2009) developed a software and hardware proto-
col (BrainMaster, Bedford, OH, USA) that combined HRV and
Alpha EEG training. Each parameter could be trained indepen-
dently or simultaneously for greater HRV andAlpha enhancement.
Bazanova et al. (2013) trained high Alpha EEG (10–12 Hz) to mea-
sure its effect on HRV. They found that healthy male subjects with
low resting levels of Alpha who increased Alpha had lowered EMG,
greater HRV and showed increases in cognitive performance. They
also noted that these changes were not present in a control group
that did not receive any feedback, thus validating the need for
actual feedback for self-regulation.
To date, only case studies have been conducted on concussed
patients using either HRV or Neurofeedback interventions. Lagos
et al. (2013) used a 10-week HRV BFB protocol on an adult ath-
lete with post-concussion syndrome. At the end of treatment, the
patient showed greater HRV, and greater LF power, as well as sig-
nificant reduction in severity of post-concussion headaches and
overall post-concussive symptoms. Thompson et al. (2013) report
the case of an athlete who received a sport-related concussion
and was treated with a multi-modal intervention, including both
HRV BFB and neurofeedback. Bhandari et al. (2013) used both
HRV and neurofeedback to treat an adult male with a Severe TBI.
While this patient was much more severely injured than a person
with a concussion, after a lengthy course of treatment he showed
improvement on multiple QEEG parameters, as well as three HRV
parameters, and was able to function successfully in his personal
and work life. Lagos et al. (2012) provide a comprehensive ratio-
nale for HRV BFB in prolonged PCS from hyperactivation of the
sympathetic nervous system and hypoactivation of the parasym-
pathetic nervous system. In addition to changes in HRV as an
outcome measure for BFB intervention, they also recommend
multimodal measures, such as cardiovascular and neurovegetative
functioning, and quality of life indicators.
Several compelling studies have implicated HRV BFB in neu-
rocognitive enhancement, particularly executive functioning and
working memory. In studying non-injured persons, Hansen et al.
(2003) divided military personnel on the basis of low or high HRV
Frontiers in Psychology |Psychology for Clinical Settings August 2014 |Volume 5 |Article 890 |4
Conder and Conder HRV interventions for concussion and rehabilitation
groups and then assessed sustained attention and working mem-
ory. As would be expected, the higher HRV group had superior
performance on both measures. Other studies of executive func-
tioning, including the ability to make decisions, plan, and benefit
from feedback, have linked executive skills to high HRV. Murray
and Russoniello (2012) divided university students between exer-
cise or control groups. HRV including instantaneous changes of
heart rate and spectral analysis of HRV were measured. Results
indicated optimal performance with the peak inverted-U curve
for both the complex Trail Making B task and a four-choice reac-
tion timed complex test. Optimal neurocognitive performance was
obtained in the LF band. These studies suggest that HRV train-
ing may be a viable intervention to promote executive function
rehabilitation in PCS.
Collegiate basketball players with high-state anxiety levels were
given ten minutes of HRV training for ten days to increase coher-
ence and respiratory sinus arrhythmia (Paul and Garg, 2012).
The premorbidly anxious collegiate basketball players showed
improvement on objective measures of dribbling, passing, and
shooting with increases in HRV, especially the LF range. This study
has implications for HRV BFB training in the rehabilitation of
autonomic and emotional dysregulation as a critical component
in PCS recovery. In a study with military relevance (Saus et al.,
2006), Norwegian Police Academy cadets with higher HRV were
noted to have greater situational awareness, and to perform more
accurately in complex shooting drills requiring focused attention
and executive abilities. A compelling study not yet undertaken
would be to investigate whether pre-deployment training in HRV
could possibly reduce anxiety-related aspects of combat, including
In summary, this article has attempted to elucidate the relation-
ship between the brain, particularly the prefrontal cortices, the
ANS, and the heart. There can be top-down or bottom-up inter-
action to both, such that the prefrontal cortices’ judgment of
ambiguity for threat attenuates HRV. Similarly, baseline higher
levels of HRV, especially LF HRV, are associated with greater
performance on complex neurocognitive tasks of concentration,
working memory, and executive functioning, requiring prefrontal
integrity. Further, as sports-related and perhaps military-related
concussions interfere with optimal levels of HRV, interventions
to restore or increase these optimal HRV levels are needed. Diet,
endurance/cardiovascular exercise, and biofeedback are effective
interventions. Of these three, HRV BFB can be accomplished with
minimal hardware, software, time, cost, and effort constraints
upon an individual over a period of a few days. Additionally,
biofeedback provides real-time feedback for the attribute of inter-
est, allowing the athlete or soldier to exercise cognitive control over
their physiology.
Future research is needed to assess the EEG correlates of HRV
intervention on randomized, controlled groups of symptomatic
post-concussion athletes and soldiers. As Tan et al. (2013) noted,
HRV intervention can be more acceptable for veterans with PTSD
than the emotionally charged psychotherapies, and this same logic
may hold true for athletes and soldiers with PCS. Data currently
available regarding HRV BFB efficacy raise a compelling argument
for the need for further empirical validation, not only for treatment
of refractory sport and military concussions, but possibly pre-
deployment stress inoculation training for soldiers, and pre-game
training for athletes.
The authors wish to sincerely thank Ms. Lauren Conder and the
Library of the University of North Carolina at Chapel Hill for their
research assistance.
Abolfathi, N., Naik, A., Sotudeh Chafi, M., Karami, G., and Ziejewski, M. (2009). A
micromechanical procedure for modelling the anisotropic mechanical properties
of brain white matter. Comput. Methods Biomech. Biomed. Engin. 12, 249–262.
doi: 10.1080/10255840802430587
Aron, A. R., Robbins, T. W., and Poldrack, R. A. (2004). Inhibition and
the right inferior prefrontal cortex. Trends Cogn. Neurosci. 8, 170–177. doi:
Barr, W. B., and McCrae, M. (2011). “Diagnosis and assessment of concussion,” in
The Handbook of Sport Neuropsychology, ed. F. M. Webbe (New York: Springer),
Barr, W. B., Prichep, L. S., Chabot, R., Powell, M. R., and McCrea, M. (2012). Mea-
suring brain electrical activity to track recovery from sport-related concussion.
Brain Inj. 26, 58–66. doi: 10.3109/02699052.2011.608216
Baugley, I. J., Heriseanu, R. E., Felmingham, K. L., and Camerson, I. D. (2006).
Dysautonomia and heart rate variability following severe traumatic brain injury.
Brain Inj. 20, 437–444. doi: 10.1080/02699050600664715
Bazanova, O. M., Balioz, N. V., Mauravleva, K. B., and Skoraya, M. V. (2013). Effect
of voluntary EEG Alpha power increase training on heart rate variability. Hum.
Physiol. 39, 86–97. doi: 10.1134/S0362119712060035
Bazarian, J. J., Zhong, J., Blyth, B., Zhu, T., Kavicic, V., and Peterson, D. (2007).
Diffusion tensor imaging detects clinically important axonal damage after mild
traumatic brain injury: a pilot study. J. Neurotrauma 24, 1447–1459. doi:
Belanger, H. G., Kretzmer, T., Yoash-Gantz, R., Pickett, T., and Tupler, L. A. (2009).
Cognitive sequelae of blast-related versus other mechanisms of brain injury. J.
Int. Neuropsychol. Soc. 15, 1–8. doi: 10.1017/S1355617708090036
Bhandari, T., Thompson, L., and Reid-Chung, A. (2013). Treating postconcus-
sion syndrome using neurofeedback: a case study. Biofeedback 41, 172–182. doi:
Bigger, J. T., Fleiss, J. L., Steinman, R. C., Rolnitzky, L. M., Schneider, W. J., and
Stein, P. K. (1995). R-R variability in healthy, middle-aged persons compared
with patients with chronic coronary heart disease or recent acute myocardial
infarction. Circulation 91, 1936–1943. doi: 10.1161/01.CIR.91.7.1936
Bigler, E. D. (2008). Neuropsychology and clinical neuroscience of persis-
tent post-concussive syndrome. J. Int. Neuropsychol. Soc. 14, 1–22. doi:
Blechert, J., Michael, T., Grossman, P., Lajtman, M., and Wilhelm, F. H. (2007). Auto-
nomic and respiratory characteristics of post traumatic stress disorder and panic
disorder. Psychosom. Med. 69, 935–943. doi: 10.1097/PSY.0b013e31815a8f6b
Bluml, S., and Brooks, W. M. (2006). “Magnetic resonanace spectroscopy of trau-
matic brain injury and concussion,”in Foundations of Sport-Related Brain Injuries,
eds S. Slobounov and W. Sebastianelli (New York, NY: Springer), 197–220. doi:
Broglio, S., Pontifex, M. B., O’Connor, P., and Hillman, C. H. (2009). The persistent
effects of concussion on neuroelectric indices of attention. J. Neurotrauma 26,
1463–1470. doi: 10.1089/neu.2008.0766
Cernak, I., and Noble-Haeusslein,L. J. (2009). Traumatic brain injury: an overview
of pathobiology with emphasis on military populations. J. Cereb. Blood Flow
Metab. 30, 255–266. doi: 10.1038/jcbfm.2009.203
Collura, T. F. (2009). Combining EEG with heart rate training for brain/body
optimization. Neuroconnections 1, 8–11.
Combatalade, D. (2010). Basics of Heart Rate Variability Applied to Psychophysiology.
Montreal: Thought Technology.
Cooper, D. B., Chau, P. M., Armistead-Jehle, P., Vanderploeg, R. D., and Bowles,
A. O. (2012). Relationship between mechanism of injury and neurocognitive August 2014 |Volume 5 |Article 890 |5
Conder and Conder HRV interventions for concussion and rehabilitation
functioning in OEF/OIF service members with mild traumatic brain injuries.
Mil. Med. 177, 1157–1160. doi: 10.7205/MILMED-D-12-00098
Gall, B., Parkhouse,W., and Goodman, D. (2004). Heart rate variability of recently
concussed athletes at rest and exercise. Med. Sci. Sports Exerc. 36,1269–1274. doi:
Garner, J., and Brett, S. J. (2007). Mechanisms of injury by explosive devices.
Anesthesiol. Clin. 25, 147–160. doi: 10.1016/j.anclin.2006.11.002
Gevirtz, R. (2013). The promise of heart rate var iability biofeedback: evidence-based
applications. Biofeedback 41, 110–120. doi: 10.5298/1081-5937-41.3.01
Gilchrist, J., Thomas, K. E., Xu, L., McGuire, L. C., and Coronado, V. G. (2011).
Nonfatal sports and recreation related traumatic brain injuries among children
and adolescents treated in emergency departments in the United States, 2001–
2009. MMWR 60, 1337–1342.
Giza, C. G., and Hovda,D. A. (2001). The neurometabolic cascade of concussion. J.
Athl. Train. 36, 228–235.
Goldstein, B., Toweill, D., Susanna, L., Sonnenthal, K., and Kimberly, B. (1998).
Uncoupling of the autonomic and cardiovascular systems in acute brain injury.
Am. J. Physiol. 275(4 Pt 2), R1287–R1292.
Guskiewicz, K. P., and Mihalik, J. P. (2011). Biomechanics of sport concussion:
quest for the elusive injury threshold. Exerc. Sport Sci. Rev. 39, 4–11. doi:
Hansen, A. L., Johnsen, B. H., Sollers, J. J., Sand Thayer, J. F. (2004). Heart rate
variability training and its relation to prefrontal cognitive function: the effects of
training and detraining. Eur. J. Appl. Physiol. 93, 263–272. doi: 10.1007/s00421-
Hansen, A. L., Johnsen, B. H., and Thayer, J. F. (2003). Vagal influence in the
regulation of attention and working memory. Int. J. Psychophysiol. 48, 263–274.
doi: 10.1016/S0167-8760(03)00073-4
Hautala, A. J., Kiviniemi, A. M., and Tulppo, M. (2009). Individual responses to
aerobic exercise: the role of the autonomic nervous system. Neurosci. Biobehav.
Rev. 33, 107–115. doi: 10.1016/j.neubiorev.2008.04.009
Hedelin, R., Bjerle, P., and Henriksson-Larsen, K. (2001). Heart rate variability in
athletes: relationship with central and peripheral performance. Med. Sci. Sport
Exerc. 33, 1394–1398. doi: 10.1097/00005768-200108000-00023
Kontos, A., Elbin, R., and Collins, M. (2006). “Aerobic fitness and concussions
outcomes in high school football,” in Foundations of Sport-Related Brain Injuries,
eds S. Slobounov and W. Sebastianelli (New York, NY: Springer), 315–340. doi:
La Fountaine, M. F., Heffernan, K. S., Gossett, J. D., Bauman, W. A., and De
Meersman, R. E. (2009). Transient suppression of heart rate complexity in con-
cussed athletes. Auton. Neurosci. 148, 101–103. doi: 10.1016/j.autneu.2009.03.001
Lagos, L., Bottiglieri, T., Vaschillo, B., and Vaschillo, E. (2012). Heart rate vari-
ability biofeedback for postconcussion syndrome: implications for treatment.
Biofeedback 40, 150–153. doi: 10.5298/1081-5937-40.4.05
Lagos, L., Thompson, J., and Vaschillo, E. (2013). A preliminary study: heart rate
variability biofeedback for treatment of postconcussive syndrome. Biofeedback
41, 136–143. doi: 10.5298/1081-5937-41.3.02
Lane, R. D., McRae, K., Reiman, E. M., Ahern, G. L., and Thayer, J. F. (2007). Neural
correlates of vagal tone during emotion. Psychom. Med. 69, 1–8.
Leddy,J. J., Kozlowski, K., Fung, M., Pendergast,D. R., and Willer, B. (2007). Regula-
tory and autoregulatory physiological dysfunction as a primary characteristic of
post concussion syndrome: implications for treatment. NeuroRehabilitation 22,
Lehrer, P. (2013). History of heart rate variability biofeedback research: a per-
sonal and scientific voyage. Biofeedback 41, 88–97. doi: 10.5298/1081-5937-41.
Lehrer,P. M.,Vaschillo, E., and Vaschillo, B. (2000). Resonant frequency biofeedback
training to increase cardiac variability: rationale and manual for training. Appl.
Psychophysiol. Biofeedback 25, 177–191. doi: 10.1023/A:1009554825745
Lehrer, P., Vaschillo, B., Zucker, T., Graves, J., Katsamanis, M., Aviles, M., et al.
(2013). Protocol for heart rate variability biofeedback training. Biofeedback 41,
98–109. doi: 10.5298/1081-5937-41.3.08
Len, T., Nearly, J., Asmundson, G., Goodman, D., Bjornson, B., and Bhambhani, Y.
(2011). Cerebrovascular reactivity impairment after sport-induced concussion.
Med. Sci. Sports Exerc. 43 , 2241–2248. doi: 10.1249/MSS.0b013e3182249539
Levin, H. S., Li, X., McCauley, S. R., Hanten, G.,Wilde, E. A., and Swan, P.
(2012). Neuropsychological outcome of mTBI: a principal components analysis
approach. J. Neurotrauma 30, 625–632. doi: 10.1089/neu.2012.2627
Lima-Silva, A. E., Bertuzzi, R., Dalquano, E., Nogueira, M., Casarini, D., Kiss, M. A.,
et al. (2010). Influence of high- and low-carbohydrate diet following glycogen-
depleting exercise on heart rate variability and plasma catecholamines. Appl.
Physiol. Nutr. Metab. 35, 541–547. doi: 10.1139/H10-043
Lippa, S. M., Pastorek, N. J., Benge, J. F., and Thornton, G. M. (2010). Postconcus-
sive symptoms after blast and nonblast-related mild traumatic brain injuries in
Afghanistan and Iraq war veterans. J. Int. Neuropsychol. Soc. 16, 856–866. doi:
McAllister, T. W., Ford, J. C., Flashman, L. A., Maerlender, A., Greenwald, R.
M., Beckwith, J. G., et al. (2014). Effects of head impacts on diffusivity mea-
sures in a cohort of collegiate contact sport athletes. Neurology 82, 1–7. doi:
McCrea, M., Prichep, L., Powell, M. R., Chabot, R., and Barr, W. B. (2010). Acute
effects and recovery after sport-related concussion: a neurocognitive and quan-
titative brain electrical activity study. J. Head Trauma Rehabil. 25, 283–292. doi:
McCrory, P., Meeuwisse, W., Aubry, M., Cantu, B., Dvorák, J., Echemendia, R. J.,
et al. (2013). Consensus statement on concussion in sport: the 4th International
conference on concussion in sport held in Zurich, November 2012. Br. J. Sports
Med. 47, 250–258. doi: 10.1136/bjspor ts-2013-092313
Moss, D., Lagos, L., and Shaffer, F. (2013). Don’t add or miss a beat: a special issue
on current evidence and current practice in heart rate variability biofeedback.
Biofeedback 41, 83–84. doi: 10.5298/1081-5937-41.3.09
Murray, N. P., and Russoniello, C. (2012). Acute physical activity on cognitive
function: a heart rate variability examination. Appl. Psychophysiol. Biofeedback
37, 219–227. doi: 10.1007/s10484-012-9196-z
Palma, J., and Benarroch, E. E. (2014). Neural control of the heart. Neurology 83,
261–271. doi: 10.1212/WNL.0000000000000605
Pardini, J., Henry, L. C., and Fazio, V. C. (2011). “Neuroimaging techniques and
sports-related concussion,” in The Handbook of Sport Neuropsychology, ed. F. M.
Webbe (New York: Springer), 113–130.
Paul, M., and Garg, K. (2012). The effect of heart rate variability biofeedback on
performance psychology of basketball players. Appl. Psychophysiol. Biofeedback
37, 131–144. doi: 10.1007/s10484-012-9185-2
Ponsford, J., Willmott, C., Rothwell, A., Cameron, P., Kelly, A., Nelms, R., et al.
(2000). Factors influencing outcome following mild traumatic brain injury in
adults. J. Int. Neuropsychol. Soc. 6, 568–579. doi: 10.1017/S1355617700655066
Prinloo, G. E., Rauch, H. G., Karpul, D., and Derman, W. E. (2013). The effect of
a single session of short duration heart rate variability biofeedback on EEG: a
pilot study. Appl. Psychophysiol. Biofeedback 38, 45–56. doi: 10.1007/s10484-012-
Reid, A., Nihon, S., Thompson, L., and Thompson, M. (2013). The effects of heart
rate variability training on sensorimotor rhythm: a pilot study. J. Neurother. 17,
43–48. doi: 10.1080/10874208.2013.759020
Saus, E. R., Johnsen, B. H., Eid, J., Riisem, P. K., Andersen, R., and Thayer, J. (2006).
The effect of brief situational awareness training in a police shooting simulator:
an experimental study. Mil. Psychol. 18,3–21. doi: 10.1207/s15327876mp1803s_2
Sherlin, L., Muench, F., and Wyckoff, S. (2010). Respiratory sinus arrhythmia
feedback in a stressed population exposed to a brief stressor demonstrated by
quantitative EEG and sLORETA. Appl. Psychophysiol. Biofeedback 35, 219–228.
doi: 10.1007/s10484-010-9132-z
Sterman, B. (1966). Physiological origins and functional correlates of EEG rhythmic
activities: implications for self-regulation. Biofeedback Self Regul. 21, 3–33. doi:
Tan, G., Fink, B., Dao, T. K., Hebert, R., Farmer, L. S., Sanders, A., et al. (2009).
Associations among Pain, PTSD, mTBI, and heart rate variability in veterans of
operation enduring and Iraqi freedom: a pilot study. Pain Med. 10, 1237–1245.
doi: 10.1111/j.1526-4637.2009.00712.x
Tan, G., Wang, P., and Ginsberg, J. (2013). Heart rate variability and post traumatic
stress disorder. Biofeedback 41, 131–135. doi: 10.5298/1081-5937-41.3.05
Teasdale, G., and Jeanette, B. (1974). Assessment of coma and impaired conscious-
ness: a practical scale. Lancet 2, 81–84. doi: 10.1016/S0140-6736(74)91639-0
Thayer, J. F., Ahs, F., Fredirkson, M., Sollers, J. J., and Wager, T. D. (2012). A meta-
analysis of heart rate variability and neuroimaging studies: implications for heart
rate variability as a marker for stress and health. Neurosci. Biobehav. Rev. 36,
747–756. doi: 10.1016/j.neubiorev.2011.11.009
Thayer,J. F., Hansen, A. L., Saus-Rose,E., and Johnsen, B. H. (2009). Heart rate vari-
ability, prefrontal neural function, and cognitive performance: the neurovisceral
Frontiers in Psychology |Psychology for Clinical Settings August 2014 |Volume 5 |Article 890 |6
Conder and Conder HRV interventions for concussion and rehabilitation
integration perspective on self-regulation, adaptation, and health. Ann. Behav.
Med. 37, 141–153. doi: 10.1007/s12160-009-9101-z
Thayer,J. F.,and Lane, R. D. (2009). Claude Bernard and the heart-brain connection:
further elaboration of a model of neurovisceral integration. Neurosci. Biobehav.
Rev. 33, 81–88. doi: 10.1016/j.neubiorev.2008.08.004
Thompson, J., and Hagedorn, D. (2012). Multimodal analysis: new approaches to
the concussion conundrum. J. Clin. Sport Psychol. 6, 22–46.
Thompson, M., Thompson, L., Reid-Chung, A., and Thompson, J. (2013).
Managing traumatic brain injury: appropriate assessment and a rationale for
using neurofeedback and biofeedback to enhance recovery in postconcussion
syndrome. Biofeedback 41, 158–173. doi: 10.5298/1081-5937-41.4.07
Williamson, J. B., Heilman, K. M., Porges, E. C., Lamb, D. G., and Porges, S. W.
(2013). A possible mechanism for PTSD symptoms in patients with traumatic
brain injury: central autonomic network disruption. Front. Neuroeng. 6:13. doi:
Conflict of Interest Statement: The authors declare that the research was conducted
in the absence of any commercial or financial relationships that could be construed
as a potential conflict of interest.
Received: 01 June 2014; accepted: 27 July 2014; published online: 13 August 2014.
Citation: Conder RL and Conder AA (2014) Heart rate variability interventions for
concussion and rehabilitation. Front. Psychol. 5:890. doi: 10.3389/fpsyg.2014.00890
This article was submitted to Psychology for Clinical Settings, a section of the journal
Frontiers in Psychology.
Copyright © 2014 Conder and Conder. This is an open-access article distributed under
the terms of the Creative Commons Attribution License (CC BY). The use, distribution
or reproduction in other forums is permitted, provided the original author(s) or licensor
are credited and that the original publication in this journal is cited, in accordance with
accepted academic practice. No use, distribution or reproduction is permitted which
does not comply with these terms. August 2014 |Volume 5 |Article 890 |7
... Collision casque vs casque Coup de bâton à la tête Réception de projectile sur la tête Coups portés au menton ou à la mâchoire « Tackle » Mise en échec Arrêt brusque du corps d'un adversaire l'empêchant d'aller dans la direction où il se dirigeait Accélération et freinage brusque en voiture (Conder & Conder, 2014;Ellemberg, 2013;Gerberich et al., 1983;Guskiewicz & Mihalik, 2011) Étant donné qu'une accélération rapide se produit suite à un impact, plusieurs chercheurs ont tenté de trouver un seuil d'accélération minimale menant à une commotion cérébrale et les résultats sont plutôt variés. Il a été suggéré par Pellman et al. qu'il fallait atteindre un seuil minimal de 70-75 g (le g étant une unité gravitationnelle permettant de quantifier une accélération et non g pour gramme) pour se blesser (Broglio et al., 2010). ...
... En effet, la VRC pourrait être utile pour le suivi des commotions puisque celle-ci permet d'observer la relation entre le cerveau et le coeur et donc, le contrôle du SNA (Bishop et al., 2017;Conder & Conder, 2014). Il a été démontré que cette mesure est suffisamment sensible pour détecter les changements physiologiques chez des patients asymptomatiques considérés comme guéris, cela en fait donc potentiellement un outil pour évaluer la récupération physiologique de l'athlète (Dobney et al., 2018). ...
Full-text available
Objectif: Rechercher systématiquement et regrouper tous les articles publiés depuis la dernière recherche systématique sur le sujet, mais avec des critères d’inclusion précis pour faciliter les comparaisons et offrir une vision explicite des méthodologies employées et des résultats. Ceci permettra une présentation globale du comportement de la variabilité du rythme cardiaque au repos et à l’effort suite à une commotion cérébrale chez des adultes. Méthodologie: Une recherche systématique a été conduite en utilisant la méthode du PRISMA en décembre 2019 au travers des bases de données PubMed, Scopus et SPORTDiscus. Une recherche manuelle a été conduite au travers des références de tous les articles inclus. La fiabilité de la recherche systématique a été assurée par un deuxième auteur qui a entièrement répété le processus de sélection d’articles. Résultats: 15 articles ont été sélectionnés suite à la recherche systématique. Les résultats de ces études démontrent une altération de la variabilité du rythme cardiaque à l’effort suite à une commotion cérébrale, des études très hétérogènes avec un manque de contrôle des facteurs confondants et, seulement environ 50% des résultats démontraient une différence entre le groupe contrôle et le groupe avec commotion. Conclusion: Les recherches futures devraient tenter de standardiser les méthodes d’acquisition de VRC en contrôlant davantage les facteurs confondants pour faciliter les comparaisons futures et, éventuellement permettre le développement d’une méta-analyse.
... For example, SPB may improve executive functions and working memory which have been associated to analytic processing of the information in different models of DM (Kennedy & Parker, 2019;Kim et al., 2013). Thus, a concomitant beneficial effect could be observed on DM: a direct effect through the potential strengthening of visceral traffic (Asadi-Pooya et al., 2019;Conder & Conder, 2014;Forte et al., 2021;Ram ırez et al., 2015), and an indirect effect through the regulation of the emotional state (Lerner et al., 2015;Lerner & Keltner, 2000). ...
Impairments in decision-making have been reported in brain-damaged (stroke/traumatic brain injury) patients with a wide range of lesion sites. Here, we propose that the performances of patients in complex sequential decision-making (DM) tasks can be explained by their negative affectivity, leading to deliberative processing associated with poor DM performances. We assumed that a slow-paced breathing (SPB) training, by reducing negative affectivity would improve performances in a complex DM task. For 24 days, 34 brain-damaged patients (16 males and 18 females; 12 had a hemorrhagic stroke, 17 with an ischemic stroke and 5 with a TBI), practiced either daily SPB or sham trainings for five min, three times a day. Before and after training, we assessed their vagal tone (electrocardiogram-ECG), affectivity (Positive and Negative Affect Schedule-PANAS) and certainty level (Dimensional Ratings Questionnaire-DRQ) and their performance on the Iowa Gambling Task. All participants showed initial weak performance, which improved only for patients in the SPB training condition. These results suggest that DM disorders in brain-damaged patients can be the consequence of their poor information processing strategy rather than an impairment in their DM abilities. Second, we showed that SPB could be efficient to normalize DM processes in brain injury patients.
... This research has documented significant negative effects on brain and cardiac physiology [1][2][3][4][5][6][7][8][9][10][11][12][13]. The acute physiological effects include altered cerebrovascular reactivity [10,14,15], cerebral oxygenation [16], baroreflex sensitivity [5,17], blood pressure variability [5,18], heart rate variability [3,[19][20][21], dynamic cerebral autoregulation [22][23][24], and cardiac mechanics [25]. Furthermore, some research has shown that changes in functional connectivity are found in athletes with post-concussion syndrome [16,[26][27][28], but not all research supports this contention [29]. ...
Full-text available
(1) Background: Cerebral autoregulation is altered during acute mild traumatic brain injury, or concussion. However, it is unknown how a history of concussion can impact cerebral haemodynamic activity during a task that elicits an autoregulatory response. (2) Methods: We assessed cerebral haemodynamic activity in those with a history of three or more concussions. The study included 44 retired athletes with concussion history and 25 control participants. We recorded participants’ relative changes in right and left pre-frontal cortex oxygenation collected by near-infrared spectroscopy and continuous beat-to-beat blood pressure measured by finger photoplethysmography. Participants completed a 5-min seated rest followed by a 5-min repeated squat (10-s) stand (10-s) maneuver (0.05 Hz) to elicit a cerebral autoregulatory response. Wavelet transformation was applied to the collected signals, allowing separation into cardiac interval I (0.6 to 2 Hz), respiratory interval II (0.145 to 0.6 Hz), and smooth muscle cell interval III (0.052 to 0.145 Hz). (3) Results: Significant increases at cardiac interval I were found for the wavelet amplitude of oxy-haemoglobin and haemoglobin difference at the right pre-frontal cortex. No significant difference was found at the left pre-frontal cortex or the blood pressure wavelet amplitudes. (4) Conclusion: Contributions from cardiac activity to the pre-frontal cortex oxygenation are elevated when eliciting dynamic cerebral autoregulation in those with a history of three or more concussions.
... 2 A systematic review from 2018 concluded that autonomic dysfunction might contribute to postconcussion symptoms and cardiovascular dysregulation. 3 The cardiac system responds flexibly to stressors, such as physical exertion or relaxation by respectively increasing or decreasing the heart rate resulting in shortened or lengthened R-R intervals. Heart rate variability (HRV) measures the variation in time between 2 consecutive heartbeats or R-R intervals of a cardiac cycle, [3][4][5] provides insight into the connection between the autonomic and cardiac systems, 6 and is a reliable marker of autonomic dysfunction. [7][8][9] Because of the effect of concussion on the autonomic system and the resulting cardiovascular dysregulation, decreasing its flexibility in response to stress, HRV has been proposed as a useful metric following a SRC and for return-toplay (RTP) decisions. ...
Clinical scenario: Recent systematic reviews show conflicting information regarding the effect of concussion on cardiac autonomic function. Controlled aerobic exercise is the most popular intervention for those recovering from a concussion. There is a gap in the literature supporting the utility of objective metrics during exertional return to play protocols and rehabilitation. Clinical question: Can heart rate variability (HRV) during physical exertion be a reliable biomarker over time for those who suffered a sport-related concussion? Summary of key findings: A literature search produced 3 studies relevant to the clinical question. One, a prospective-matched control group cohort study, reported disturbances in HRV during physical exertion in those with a history of concussion, and identified persistent HRV dysfunction after resolution of subjective complaints, return to play, and with multiple concussive events. Second, a cross-sectional cohort study found an HRV difference in those with and without a history of concussion and in HRV related to age and sex. Finally, the prospective longitudinal case-control cohort study did not find sex or age differences in HRV and concluded that, although postconcussion HRV improved as time passed, resting HRV was not as clinically meaningful as HRV during exertional activities. Clinical bottom line: There is emerging evidence to support the use of HRV as an observable biomarker, over time, of autonomic function during physical exertion following a sport-related concussion. However, the meaningfulness of HRV data is not fully understood and the utility seems individualized to the level of athlete, age, and sex and, therefore, cannot be generalizable. In order to be more clinically meaningful and to assist with current clinical decision making regarding RTP, a preinjury baseline assessment would be beneficial as an individualized reference for baseline comparison. Strength of recommendation: Although HRV is not fully understood, currently, there is grade B evidence to support the use of individualized baseline exertional HRV data as comparative objective metric to assess the autonomic nervous system function, over time, following a concussive event.
... A recent meta-analysis revealed an effect size of Hedges' g = 0.83 for comparing HRVB (ranges 1-50 sessions) to other control interventions on improving adaption to real-world stressors (e.g., perceived stress and anxiety trait and state) [17]. Although RFB has not been tested in groups at risk for dementia, HRVB using RFB training improves resting HRV, executive function, and anxiety in traumatic brain injury [20,21] and older adults [22]. HRVB also improves HRV response to cognitive stress [23]. ...
Full-text available
Importance Cognitive training with components that can further enhance the transferred and long-term effects and slow the progress of dementia is needed for preventing dementia. Objective The goal of the study is to test whether improving autonomic nervous system (ANS) flexibility via a resonance frequency breathing (RFB) training will strengthen the effects of a visual speed of processing (VSOP) cognitive training on cognitive and brain function, and slow the progress of dementia in older adults with mild cognitive impairment (MCI). Design Stage II double-blinded randomized controlled trial. The study was prospectively registered at, with registration approved on 21 August 2020 (No. NCT04522791). Setting Study-related appointments will be conducted on-site at University of Rochester Medical Center locations. Data collection will be conducted from August 2020 to February 2025. Participants Older adults with MCI ( n = 114) will be randomly assigned to an 8-week combined intervention (RFB+VSOP), VSOP with guided imagery relaxation (IR) control, and a IR-only control, with periodical booster training sessions at follow-ups. Mechanistic and distal outcomes include ANS flexibility, measured by heart rate variability, and multiple markers of dementia progress. Data will be collected across a 14-month period. Discussion This will be among the first RCTs to examine in older persons with MCI a novel, combined intervention targeting ANS flexibility, an important contributor to overall environmental adaptation, with an ultimate goal for slowing neurodegeneration. Trial registration NCT04522791 . Registered on 21 August 2020 Protocol version: STUDY00004727; IRB protocol version 2, approved on 30 July 2020.
... A number of patients in our study underwent biofeedback therapy in conjunction with their CBT treatment. Although biofeedback has not been previously described in the medical literature for the treatment of PPPD, it has been shown to have significant benefits in the treatment of anxiety, depression, autonomic dysfunction, syncope, post-concussion syndrome, headaches, chronic pain disorders, and overall stress management including adjustment to chronic illnesses (41,(48)(49)(50)(51)(52)(53)(54)(55)(56). These symptoms and diagnoses frequently present concurrently in PPPD patients. ...
Objective: Persistent postural-perceptual dizziness (PPPD) is a recently defined diagnostic syndrome characterized by chronic symptoms of dizziness, unsteadiness, and/or non-spinning vertigo. Although PPPD has been studied in adults, reports in the pediatric population are few. The goal of this study was to describe the presentation and treatment of PPPD in a group of pediatric patients. Study design: Retrospective chart review. Setting: Tertiary referral center. Patients: ≤21 years old, who met Bárány Society consensus criteria for a diagnosis of PPPD and were followed for ≥6 months or until symptom resolution. Main outcome measuress: Patient demographics, comorbidities, symptom chronicity, and response to treatment(s). Results: Of the 53 patients identified, 44 (83.0%) were women. Mean age at the time of initial evaluation was 14.6 years old. Common diagnoses in addition to PPPD included benign paroxysmal positional vertigo (64.2%), vestibular migraine (56.6%), and anxiety (28.3%). A high proportion of patients (43.4%) reported initially missing school or work due to their symptoms. Eighteen patients (34.0%) reported symptom resolution ranging from 2 to 48 months after diagnosis (median 9 mo). Of these patients, 15 of 18 attended physical therapy (PT), 11 of 18 attended cognitive behavioral therapy (CBT) and/or biofeedback therapy, and 10 of 18 took selective serotonin reuptake inhibitor (SSRI) medications, and 7 of 18 (40%) did a combination of all three therapies. Conclusion: PPPD can impact patients at a young age, and prolonged symptoms present a significant burden to children and adolescents, many of whom are unable to attend school. Treatments such as PT, CBT, and SSRI medication may be effective.
... The ratio of these frequencies (LF/HF) is considered a clinical index of ANS regulation of target organs. Decreased HRV, indicating sympathetic dominance, is reported in patients with all levels of TBI (87). Importantly, correction of dysautonomia in TBI patients is an emerging therapeutic target with early administration of propranolol having beneficial effects on TBI in a prospective randomized clinical trial (88). ...
Traumatic brain injury (TBI) is a chronic and progressive disease, and management requires an understanding of both the primary neurological injury and the secondary sequelae that affect peripheral organs, including the gastrointestinal (GI) tract. The brain-gut axis is composed of bidirectional pathways through which TBI-induced neuroinflammation and neurodegeneration impact gut function. The resulting TBI-induced dysautonomia and systemic inflammation contribute to the secondary GI events, including dysmotility and increased mucosal permeability. These effects shape, and are shaped by, changes in microbiota composition and activation of resident and recruited immune cells. Microbial products and immune cell mediators in turn modulate brain-gut activity. Importantly, secondary enteric inflammatory challenges prolong systemic inflammation and worsen TBI-induced neuropathology and neurobehavioral deficits. The importance of brain-gut communication in maintaining GI homeostasis highlights it as a viable therapeutic target for TBI. Currently, treatments directed toward dysautonomia, dysbiosis, and/or systemic inflammation offer the most promise.
Full-text available
The field of concussion research is vast but lacking in uniformity when implementing or recommending evaluative protocols. Of the pathological characteristics associated with concussion, autonomic dysfunction includes but is not limited to a dysregulation of autonomic afferent and efferent pathways in both cortical and medullary regions, resulting in impaired intrinsic autoregulatory function influencing inotropic and chronotropic aspects of myocardial contractility, as well as vascular smooth muscle regulation (1,2). Popular methods of assessing autonomic function in the wake of a concussion include heart rate variability (HRV) analysis, blood pressure variability analysis (BPV), and spontaneous baroreceptor sensitivity (SBRS). This project aims to examine the impact of concussive trauma on cardioautonomic functioning and multilevel cardioautonomic integration across two studies in 65 otherwise healthy college-aged athletes, with a focus on heart rate variability, blood pressure variability, and the multilevel autonomic integration required for cardiac baroreflex functioning across six time epochs (baseline, days 1-3, days 4-7, days 8-11, days 12-15, and days 16+) using rest and rhythmic breathing portions (0.1 Hz) of the Neary Protocol. Two within-subject repeated-measures multilevel modelling approaches were used for statistical analysis to address non-equidistant sampling intervals present in the data set, with a Sidak post-hoc test for pairwise comparisons with alpha set at p<0.05. I conclude that rhythmic breathing is the preferred methodology to assess cardioautonomic dysfunction in the wake of a concussion, integrate heart rate variability and baroreceptor sensitivity values, and speculate about a potential mechanism responsible for patterns of cardioautonomic dysfunction to paint a picture of the multilevel autonomic integration that can be readily evaluated to diagnose concussion.
Background Preliminary evidence suggests that individuals with persistent post-concussion symptoms (PPCS) have a dysfunctional stress response, consisting of the autonomic nervous system (ANS) and hypothalamic pituitary adrenal-axis (HPA-axis). Objectives This review aims to explore the extent of evidence for dysfunction of the stress response in individuals with PPCS by individually mapping the literature surrounding quantifiable changes of the (1) ANS and (2) HPA-axis using non-invasive and clinical tools, and highlighting any (3) knowledge gaps. Methods Nine electronic databases and grey literature were searched on the 1st of June 2021 and 4th of October 2021. Studies were included if their population was classified with PPCS, and their study stated at least one quantifiable marker of the ANS or HPA-axis using non-invasive and clinical tools. Relevant studies were screened, and data extracted. Results A total of 37 articles were included in this scoping review. The majority of studies assessed quantifiable markers of the ANS (n = 34), in comparison to the HPA-axis (n = 2), and ANS and HPA-axis (n = 1). The most common quantifiable markers of the ANS included heart rate (n = 20), blood pressure (n = 16), and heart rate variability (n = 10). Cortisol was the only included quantifiable marker of the HPA-axis (n = 2). Conclusions Most of the evidence in this review supports quantifiable dysfunction of the ANS in those with PPCS. Further research is required investigating quantifiable dysfunction of the HPA-axis, and subsequently ANS and HPA-axis in unison, in those with PPCS.
Das Gesundheitssystem steht aufgrund der alternden Bevölkerung vor großen medizinischen und gesellschaftlichen Herausforderungen. Ein wesentliches Hilfsmittel für die adäquate Vorsorge und Behandlung der zunehmenden chronischen Krankheiten ist das kontinuierliche Langzeitmonitoring von relevanten Vitalparametern. Während primäre Parameter wie der Herzschlag von großer Bedeutung sind, um akute Gesundheitsänderungen zu erkennen, weist ein daraus abgeleiteter Parameter, die Herzratenvariabilität (HRV), sowohl auf chronische als auch psychische Krankheiten hin. Etablierte Messgeräte wie der Elektrokardiograph haben den essentiellen Nachteil, dass ein permanenter Körperkontakt zur untersuchten Person erforderlich ist. Dies hat nicht nur einen immens hohen Personal- und Materialaufwand zur Folge, sondern schränkt vor allem beim Langzeitmonitoring die Selbstständigkeit und den Komfort der untersuchten Person ein. Wünschenswert wäre eine berührungslose und somit belastungsfreie Lösung. Die Radartechnologie als Verfahren der Abstandsmessung hat sich in den letzten Jahren als ein vielversprechendes Verfahren präsentiert. Es gab bislang jedoch nur unzureichende Untersuchungen zur Messbarkeit der HRV mittels Radar. Eine wesentliche Herausforderung stellt hierbei die benötigte Genauigkeit bei der Detektion einzelner Herzschläge dar, welche mit der bis dato analysierten Pulswellenkomponente nur schwer zu erreichen ist. In einer Vorarbeit konnte jedoch nachgewiesen werden, dass auch Herztöne mittels Radar messbar sind, welche durch ihre markante Charakteristik eine hohe Genauigkeit bei der Segmentierung versprechen. In dieser Arbeit wird erstmalig untersucht, ob eine berührungslose Messbarkeit der HRV mittels der mit Radar aufgezeichneten Herztonsignale möglich ist. Hierfür werden zunächst anhand von detaillierten theoretischen Vorüberlegungen die Aspekte ermittelt, welche für die Durchführung dieses Verfahrens notwendig sind. Dies umfasst neben der Erforschung eines Algorithmus für die automatisierte Qualitätsbestimmung des Herztonsignals auch ein Verfahren für die präzise Segmentierung und Detektion einzelner Herzschläge sowie eine nachfolgende Artefaktkorrektur und die Bestimmung der HRV-Parameter. Um die Umsetzbarkeit auch im praktischen Umfeld nachzuweisen, wurden zusammen mit dem Universitätsklinikum Erlangen umfangreiche Studien mit zahlreichen Probanden durchgeführt. Die daraus gewonnenen Messdaten, welche in ihrem Umfang und ihrer Art einzigartig sind, wurden anschließend für die Validierung der implementierten Verfahren und Algorithmen verwendet. Mittels Ensemble Learning und Gaußprozess-Regression konnten für die Qualitätsbestimmung der Herztöne F1-Scores von über 92 Prozent sowie Korrelationen von über 95 Prozent erreicht werden. Bei der Herztonsegmentierung konnte ein mehrschichtiges bidirektionales LSTM-Netzwerk die höchsten F1-Scores von 94 bis 98 Prozent erzielen. Im letzten Schritt wurden bei der HRV-Bestimmung mit dieser Architektur geringe Abweichungen von der Referenz im einstelligen Prozentbereich realisiert. Zudem wurde dies nicht nur in einem statischen Setting nachgewiesen, sondern es konnten auch die Verläufe bei sich dynamisch und abrupt ändernden Szenarien nachgebildet werden. Die in ihrer Art erstmaligen Untersuchungen in dieser Arbeit sowie die vielversprechenden Ergebnisse weisen auf ein enormes Potential der vorgestellten Technologie hin und stellen einen substantiellen Schritt in Richtung einer verbesserten Patientenversorgung mittels eines belastungsfreien Langzeitmonitorings dar.
Full-text available
This paper describes a five-visit heart rate variability (HRV) biofeedback protocol we have used both clinically and in research. This protocol was refined in a study of biofeedback therapy for treating asthma. Similar, longer methods have been used for treating various conditions involving pain, anxiety, depression, and other psychophysiological disorders.
Full-text available
The psychophysiology of posttraumatic stress disorder (PTSD) points towards autonomic dysregulation—specifically, elevated sympathetic response and attenuated parasympathetic response. In view of this, heart rate variability (HRV) biofeedback has been applied and tested as a treatment for PTSD. Review of existing published research suggests that HRV biofeedback seems promising as a treatment for PTSD, both in significantly alleviating the symptoms and in improving cognition for those suffering from PTSD. Drop-out rate is low, and inexpensive and portable HRV biofeedback devices such as the Stress Eraser make it a viable alternative to traditional treatment such as prolonged exposure therapy (PET), cognitive behavior therapy (CBT) and cognitive processing therapy (CPT). More recent research has also shown that combining HRV biofeedback with CBT, PET, and Acceptance and Commitment Therapy (ACT) improved the efficacy of these therapies in treating PTSD. More larger-scale and rigorous controlled trials are needed to confirm these outcomes.
Full-text available
Heart rate variability (HRV) biofeedback (BFB) can be used to reduce activation of the sympathetic nervous system (SNS) and increase activation of the parasympathetic nervous system (PNS). A growing body of research suggests that increased arousal of the SNS contributes to the sustained state of postconcussion syndrome (PCS). It has also been postulated that underactivation of the PNS may also play a role in the postinjury state of autonomic dystonia, wherein the autonomic nervous system is in a state of imbalance and does not return to normal. In addition to autonomic imbalance, patients who are generally advised not to engage in physical exertion until asymptomatic from concussion, are known to experience secondary symptoms of fatigue and reactive depression. Recent research has established that such symptoms can delay the recovery from concussion indefinitely. By addressing both autonomic dysfunction and the secondary symptoms of depression and anxiety, HRV BFB may be an effective treatment for PCS by ...
Full-text available
This paper reviews the history of heart rate variability biofeedback. Interest in the method has evolved from several directions, eventually mutually influencing each other, and often through workshops provided by the Association for Applied Psychophysiology and Biofeedback. My own work was influenced by long-term use of the technique in Russia, and from research by Evgeny Vaschillo using transfer function analysis among heart rate, respiration, and blood pressure, to show how the technique stimulates the baroreflex; also by Richard Gevirtz in frequent workshops given together. Work at the HeartMath Institute independently evolved from experience with music relaxation and “heartfelt emotion,” and other research evolved from American psychophysiological research. Brief descriptions of the development of interest and work in this field are provided by Richard Gevirtz, Rollin McCraty (HeartMath), Fredric Shaffer, and Robert Nolan, as well as myself.
Full-text available
Heart Rate Variability (HRV) Biofeedback is used to restore balance in the activity of the sympathetic and parasympathetic branches of the autonomic nervous system by increasing or reducing the activity of either. Researchers have postulated that a fundamental cause of refractory postconcussion syndrome (PCS) is physiologic dysfunction that fails to return to normal after concussion. The primary physiologic issues identified have been altered autonomic function and impaired cerebral autoregulation. Evidence has shown that aerobic exercise training increases parasympathetic activity, reduces sympathetic activation, and improves cerebral blood flow so it may, therefore, help to reduce concussion-related physiological dysfunction. The authors hypothesize that HRV biofeedback training will ameliorate PCS by improving autonomic balance as well as cerebral autoregulation, and that there will be a relationship between increased interval variability and postconcussion symptom reduction.
Sports-related concussions are complex injuries with biomechanical and biochemical etiology that present with central and autonomic nervous system dysfunction. Current methods for assessing concussions and basing return-to-play decisions rely on symptom resolution, rating scales, and neuropsychological testing, all of which are indirect measures of injury severity and detect functional capabilities but do not directly measure injury location or severity. In addition, these downstream measures are susceptible to false negatives because compensatory mechanism, such as unmasking and redundancies in brain circuitry can return functional capabilities before injury resolution. The multifactorial nature of concussion necessitates rapid, inexpensive, and easily applied multimodal analysis methods that can offer greater sensitivity and specificity. This article discusses how new approaches utilizing electrophysiology (e.g., QEEG, ERP, ECG, HRV), quantified balance measures, and biochemistry are necessary to advance the science of concussion assessment, treatment, recovery projections, and return-to-play decisions. These additional assessment tools offer a more direct window into the severity and location of the injury, real-time measures of brain function, and the ability to measure the multiple body systems negatively affected by concussion.
Heart rate variability (HRV) training and EEG Biofeedback are techniques used to improve neurological disorders in both clinical and optimal performance populations. HRV training uses combined respiration and heart rate biofeedback to achieve synchrony between the changes in breathing and heart rate. This specific signature of synchronization of breathing and heart rate changes appears to correlate with a relaxed state and cognitive clarity. HRV may provide a promising index for both physical and emotional stress. Improvements in mental processing (Thayer, Hansen, Saus-Rose, & Johnson, 20099. Thayer , J. , Hansen , A. , Saus-Rose , E. , & Johnson , B. H. ( 2009 ). Heart rate variability, prefrontal neural function, and cognitive performance: The neurovisceral integration perspective on self-regulation, adaptation, and health . Annals of Behavioral Medicine Publication of the Society of Behavioral Medicine , 37 ( 2 ), 141 – 153 . [CrossRef], [PubMed]View all references) and emotional stability (Applehans & Lueken, 20061. Applehans , B. , & Lueken , L. ( 2006 ). Attentional processes, anxiety, and regulation of cortisol reactivity . Anxiety, Stress & Coping , 19 , 81 – 92 . [Taylor & Francis Online], [Web of Science ®]View all references) have been demonstrated as a result of HRV training. A similar mental state is the target of EEG biofeedback training when parameters are set to increase sensorimotor rhythm (SMR). SMR is usually trained using the frequency band 12–15 Hz. These frequencies are called SMR only when they are produced across the sensorimotor strip (C3, Cz, C4). In other locations, 12–15 Hz is simply called beta. SMR production has been closely linked to a state of calm, relaxed focus (Sterman, 19968. Sterman , M. ( 1996 ). Physiological origins and functional correlates of EEG rhythmic activities: Implications for self-regulation . Biofeedback and Self-Regulation , 21 , 3 – 33 . [CrossRef], [PubMed]View all references). This article proposes that HRV training may be associated with increased levels of SMR. Preliminary data have been collected for 40 clients. Twenty clients were athletes training to improve performance, and 20 clients were from a clinical population aiming to increase SMR as a part of their program. A 3-min sample of EEG baseline data was compared to a 3-min sample of EEG data collected during HRV training. Mean microvolt values were collected for SMR during both the baseline recording and during the HRV training. T-test results show that there was a statistically significant increase in SMR during HRV training as compared to baseline (p < .001). This suggests that increased HRV leads to increases in production of SMR.