published: 13 August 2014
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
J P. Ginsberg, Dorn VA Medical
J P. Ginsberg, Dorn VA Medical
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
EPIDEMIOLOGY AND DIAGNOSIS OF TRAUMATIC BRAIN
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
www.frontiersin.org 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.
HEART RATE VARIABILITY
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).
NEURAL RELATIONSHIP BETWEEN BRAIN AND HEART
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
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).
MECHANISM OF INJURY IN CONCUSSION
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
www.frontiersin.org 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
HRV AND EEG
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.
NEUROCOGNITIVE ENHANCEMENT AND REHABILITATION
WITH HRV BFB
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
SUMMARY AND CONCLUSION
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
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
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.
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
www.frontiersin.org 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.
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.
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.
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.
www.frontiersin.org August 2014 |Volume 5 |Article 890 |7