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Ki nesiolog y 52(2020)1:72- 84Grässler, B et al.: RESTING HEART RATE VARIABILITY AS A POSSIBLE MARKER...
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RESTING HEART RATE VARIABILITY AS A POSSIBLE
MARKER OF COGNITIVE DECLINE
Bernhard Grässler1, Anita Hökelmann1, and Richard Halti Cabral2
1Department of Sport Science, Ott-von-Guericke-University Magdeburg, Germany
2Tiradentes University, Aracaju, Brazil
Review
DOI: 10.26582/k.52.1.9
Abstract:
Cognition is a major subject to be addressed nowadays due to the increasing number of cognitively
affected people in most societies. Because of a lack of pharmaceutical therapies treating cognitive decline,
its indicators should be diagnosed before it becomes prevalent. Scientific evidence indicates a relationship
between cognition and the nervous system, especially its autonomic part. Heart rate variability (HRV)
as an indicator of the autonomic nervous system functioning has been studied as a biological marker for
the evaluation of cognitive performance. Therefore, HRV is a possible indicator of cognitive impairment.
The aim was to provide a systematic literature review about the association between resting HRV and the
cognitive performance. Five cognitive functions were analysed separately: executive functions, memory
and learning, language abilities, visuospatial functioning, and processing speed. Furthermore, the global
cognitive function evaluated with cognitive test batteries was considered too. An electronic database search
was conducted with five databases. Three search fields comprised HRV, cognitive performance, and adult
subjects. The final dataset consisted of 27 articles. Significant correlations in each cognitive function were
found, except for processing speed, suggesting a positive association between resting HRV and cognitive
performance. Mechanisms underlying this association between cardiovascular health and cognition are
discussed. For the future, HRV could be used in diagnostics as an indicator of cognitive impairment before
symptoms of dementia get apparent. With a timely diagnosis, preventative tools could be initiated at an early
stage of dementia.
Key words: autonomic nervous system, cognition, dementia diagnosis
Introduction
Cognition is a prerequisite to participate
successfully in social and everyday life. In fact,
cognitive functions usually decrease in late life
(Bugg, DeLosh, Davalos, & Davis, 2007; Wild-
Wall, Falkenstein, & Gajewski, 2011) and a very
strong decline leads to dementia in older age. One
of the biggest health problems in our future is the
increasing number of elderly people and concordant
increasing number of people with dementia. Medical
care of the population is based on early diagnosis,
treatment of reversible conditions in an attempt to
restore any mental function but, in many cases, it is
just a palliative care. So far, neither medications nor
drastic interventions can heal or prevent diseases
like dementia; except for some evidence pointing
out to physical activity (Blondell, Hammersley-
Mather, & Veerman, 2014). Then, prevention may
be a better option.
The heart rate variability (HRV) describes
the beat-to-beat variation of RR-intervals. It is a
common diagnostic tool to assess the cardiac auto-
nomic system and it has been used as a biolog-
ical indicator for recognizing emotions (Quintana,
Guastella, Outhred, Hickie, & Kemp, 2012). In
some other clinical situations, including diabetic
neuropathy and congestive heart failure, HRV is
used as a non-invasive diagnostic tool as well (Stein
& Kleiger, 1999; Sztajel, 2004). Beside genetic
factors (Singh, Larson, O’Donnell, Tsuji, Evans,
& Levy, 2001), the environment (Togo & Taka-
hashi, 2009), lifestyle (Valentini & Parati, 2009),
neuropsychological factors (Fatisson, Oswald, &
Lalonde, 2016), and age exert inuences on HRV
(Almeida-Santos, et al., 2016; Jandackova, Scholes,
Britton, & Steptoe, 2016). Regular physical exercise
has positive eects on HRV and can even attenuate
the age-induced decline (Hottenrott, Lauenroth, &
Schwesig, 2004; Melo, et al., 2005). In the context
of professional sports training, HRV is a popular
diagnostic tool to prevent overtraining (Makivić,
Nikić, & Willis, 2013).
In general, a high variation in heart rate reects
a good state of health. McCraty and Shaer (2015)
Grässler, B et al.: RESTING HEART RATE VARIABILITY AS A POSSIBLE MARKER... Ki nesiolog y 52(2020)1:72- 84
73
stated that “too little variation indicates age-related
system depletion, chronic stress, pathology, or
inadequate functioning in various levels of self-
regulatory control systems” but too much varia-
tion indicates “arrhythmias and nervous system
chaos [which] is detrimental to ecient physio-
logical functioning and energy utilization” (Stein,
Domitrovich, Hui, Rautaharju, & Gottdiene, 2005).
The heart-beat variations are the result of a
complex interaction between sympathetic and para-
sympathetic activity (Billman, 2011). Sympathetic
activity leads to a reduction of time between heart
beats and energy mobilization, whereas parasym-
pathetic activity has the opposite eect and is asso-
ciated with vegetative and restorative functions.
An optimal HRV reects a balanced state of the
autonomic nervous system (Thayer, Yamamoto,
& Brosschot, 2010). The Neurovisceral Integra-
tion Model appears to be an important framework
for understanding the mechanism underlying the
association between HRV and cognition (Kemp,
Koenig, & Thayer, 2017). According to that model,
neural structures responsible for aective, cogni-
tive, and physiological regulation are associated
with vagally mediated cardiac function, indexed
by HRV (Thayer, Hansen, Saus-Rose, & Johnsen,
2009). Especially the prefrontal cortex is associ-
ated, through its connection with the amygdala,
with the cardiovascular system (Thayer & Lane,
2009). Vagally mediated HRV is supposed to be
linked with “a set of neural structures that have
been implicated in cognitive, especially executive,
function” (Thayer, et al., 2009). Therefore, a greater
vagally mediated HRV reects a good prefrontal
neural function, leading to better executive func-
tioning.
A lot of dierent methods to measure the HRV
exist (Shaer, McCraty, & Zerr, 2014). Due to
the supposed relationship between vagally medi-
ated HRV and cognitive performance, the param-
eters HF (power in high frequency range, 0.15–0.4
Hz), HF nu (HF power in normalized units: HF
/ [Total Power – very low frequency] * 100) and
RMSSD (root mean square of successive dierences
between normal heart beats; in ms) are considered
in this review (Shaer, et al., 2014; Thayer, Åhs,
Fredrikson, Sollers III, & Wager, 2012). HF is also
called respiratory band because it corresponds to
the respiratory cycle. Changes in heart rate elicited
through respiration are known as respiratory sinus
arrhythmia (Shaer, et al., 2014). Parasympathetic
inuences on the heart rate are prevalent over all
possible frequency ranges but sympathetic inu-
ences are prevalent only up to 0.15Hz (Thayer, et
al., 2012). Therefore, the power in low frequency
range (LF, 0.04–0.15 Hz) cannot clearly be ascribed
to either the sympathetic or parasympathetic system
and were not considered in this review (Billman,
2013).
Alzheimer’s Disease (AD) is an increasing
problem for the health care system. Markers that
diagnose AD in preclinical stages are necessary to
initiate prevention at an early stage. Beside cogni-
tive performance tests, HRV could be such a diag-
nostic marker because of the previously mentioned
connections between cognition and heart rate regu-
lation. Although the knowledge of this connection
has existed for over 150 years (Thayer & Lane,
2009), research about the association between HRV
and cognitive performance only arose about 15 years
ago. For using HRV as a marker for mental health, a
relationship with the cognitive performance must be
conrmed. Thus, the aim of this review is to provide
an overview of the existing literature considering
the relationship between resting HRV and cogni-
tive performance.
Methods
Search strategy
A search request, consisting of three search
elds, was implemented to identify all relevant
studies. The search elds were connected with
AND. The terms within the elds were connected
with OR. This procedure guaranteed that at least
one term in each eld was found by the databases
search engines. The rst search eld comprised
terms relating to HRV. The second eld comprised
terms relating to cognition. The last eld specied
the subjects’ age characteristic to exclude studies
with infants or children. This reviewfollowed the
guidelines for writing systematic reviews (Moher,
Liberati, Tetzla, & Altman, 2009).
Search string
Search string: “heart rate variability“ OR
“HRV” OR “heart rate variance“ OR “cycle length
variability” OR “RR variability” OR “heart period
variability” OR “beat-to-beat variation” OR “beat-
to-beat variability” OR “cardiovascular uctuation”
OR “cardiovascular uctuations” OR “heart rate
oscillation” OR “heart rate oscillations”
AND
“cognition” OR “cognitive performance” OR
“cognitive function” OR “cognitive functions” OR
“memory” OR “executive function” OR “execu-
tive functioning“ OR “executive functions” OR
“cognitive state” OR “cognitive impairment” OR
“dementia” OR “Alzheimer” OR “cognitive neuro-
degeneration” OR “cognitive processing” OR
“cognitive process” OR “cognitive processes”
AND
“senior” OR “seniors” OR “elderly” OR “adult”
Search process
The search process was undertaken with elec-
tronic databases on August 18, 2017. Five databases
Ki nesiolog y 52(2020)1:72- 84Grässler, B et al.: RESTING HEART RATE VARIABILITY AS A POSSIBLE MARKER...
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were searched (Scopus, Pubmed, Web of Science,
Cochrane Library, Medline). In Scopus, the search
was limited to the categories title, abstract and
keywords. Articles were considered as a possible
document type and journal as a source type. Title
and abstract were used in Pubmed. In the Cochrane
Library, the search was undertaken in the catego-
ries title, abstract, and keyword, and was limited to
trials. No restrictions were possible in Medline and
Web of Science. All articles were downloaded in
the citation manager Citavi 5 and duplicates were
removed.
Inclusion and exclusion criteria
We considered all age groups except infants
and children. Studies with animals were excluded
as well. Articles published before 1980 were not
considered for this review. Further inclusion criteria
for eligible articles were the following:
• Measurement of HRV in resting state (short- or
long-term) but not during tasks
• Conduction and presentation of the results of at
least one cognitive task or comparison between
groups with divergent cognitive states
• Correlation analysis between HRV and cogni-
tion or comparison between groups with
different HRV levels
• Written in English language
• Full-text available
•
Studies that did not include depressive and/or
anxiety patients, or patients with psychiatric
illnesses
• No drug trials
• Intervention studies if HRV was measured pre-
and post-intervention and compared with cogni-
tive performance
•
Duplicates with the same study sample were
used only once
•
Only published original articles were consid-
ered, meaning we did not consider conference
papers, reviews, letters, articles in press and
notes
•
No beta blockers users nor persons with conges-
tive heart failure, myocardial infarction, or
cardiac arrhythmias.
All studies, 220 of them, that did not meet these
criteria were removed and excluded from further
analysis because they did not full the above
described criteria for eligibility. The cognitive tasks
were classied into the following cognitive func-
tions, based on a report of Levy (1994):
• Executive functions
• Memory and learning
• Language ability
• Visuospatial functioning
• Processing speed
• Global cognitive function.
This classication should ensure a presentation
of a broad spectrum of dierent cognitive abili-
ties. The global cognitive function was used as an
additional category because some studies presented
only the total score of a cognitive test battery (e.g.:
MMSE) without dierentiating between particular
cognitive functions. There are only a few cogni-
tive tasks measuring one specic cognitive func-
tion. Therefore, we assigned the cognitive tasks
to the function that was suggested as the primary
cognitive function by the study authors. If no
specic function was mentioned, or the task was
not described, we looked in the references of the
article and assigned it according to these references.
Data extraction
After reading the abstracts and method sections
of the 493 identied articles, 220 articles that did
not meet the inclusion criteria were excluded and
the full texts of the relevant articles were examined.
The cognitive tasks were then classied according
to their evaluated cognitive function. Figure 1
describes the search process. The ve databases
revealed 948 articles. After removing duplicates,
493 remained. Twenty-seven studies met the inclu-
sion criteria and were described in the tables with
the following data: rst author, year of publication,
characteristics of study sample (number of subjects,
mean age or age range with standard deviation,
if available, and state of health), measured HRV
parameters, cognitive tasks, and results.
Figure 1. Flow chart of the screening process (n=number of articles)
Identification
Records identified through database searching
(n=948):
Scopus: n=447
Cochrane Library: n=192
Web of Science: n=149
Medline: n=28
Pubmed: n=28
Screening
Included
Records after duplicates removed:
n=493
Eligible full-text articles included for review:
n=27
Eligibility
Assessment for eligibility:
Excluded records: 220
Figure 1. Flow chart of the screening process (n=number of
articles)
Grässler, B et al.: RESTING HEART RATE VARIABILITY AS A POSSIBLE MARKER... Ki nesiolog y 52(2020)1:72- 84
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Results
Executive functions
Table 1 summarizes all studies using executive
function tasks. A typical executive task is the task
Stroop. Positive correlations were found with HF
(Hovland, et al., 2012; Jennings, Allen, Gianaros,
Thayer, & Manuck, 2015), but two other studies
found no association with HF (Mathewson, et al.,
2010; Nonogaki, Umegaki, Makino, Suzuki, &
Kuzuya, 2017). Stenfors, Hanson, Theorell, and
Osika (2016) showed that the association with
RMSSD and HF diminished after considering age
and sex. Albinet, Abou-Dest, André, and Audiren
(2016) found no association with RMSSD and HF.
The study samples comprised young and healthy but
also elderly subjects and patients with AD. There-
fore, positive relations cannot be limited to specic
groups of people.
Two-back is another important executive task.
Three studies showed signicant associations with
HF and RMSSD (Hansen, Johnsen, & Thayer,
2003; Hansen, Johnsen, Sollers III, Stenvik, &
Thayer, 2004; Hansen, Johnsen, & Thayer, 2009),
but Albinet et al. (2016) and Stenfors et al. (2016) did
not nd any correlations for the same parameters.
WCST (Wisconsin Card Sorting Test) is a further
popular executive task. Two studies found positive
correlations: Albinet, Boucard, Bouquet, and Audif-
fren (2010) for RMSSD and HF, and Hovland et al.
(2012) for HF. In the Trail-Making-Test B, positive
associations (Kemp, et al., 2016) and no associa-
tions (Jennings, et al., 2015; Nicolini, et al., 2014;
Stenfors, et al., 2016) with HF were found. Positive
correlations were found for the CPT (Continuous
Performance Test) with HF and RMSSD (Hansen,
et al., 2003, 2004, 2009). A Psychomotor Vigilance
Task showed better results in a group with higher
RMSSD (Luque-Casado, Zabala, Morales, Mateo-
March, & Sanabria, 2013). HF and RMSSD were
positively associated with better results in a Flanker
Test (Williams, Thayer, & Koenig, 2016). However,
another version of the Flanker Test was not associ-
ated with HF (Alderman & Olson, 2014). No rela-
tionships were detected in some other familiar tasks
testing executive functions, e.g.: Raven Colored
Progressive Matrices (Incalzi, et al., 2009; Nicolini,
et al., 2014), d2 (Duschek, Muckenthaler, Werner,
& Reyes del Paso, 2009), Hayling-Test (Albinet,
et al., 2016) and Alice-Heim 4-I (Britton, Singh-
Manoux, Hnatkova, Malik, Marmot, & Shipley,
2008). Finally, Yang, Tsai, Hong, Yang, Hsieh, and
Liu (2008) detected positive relationships between
RMSSD and results of the CASI (Cognitive Abil-
ities Screening Instrument). Some other studies
showed no correlations between HRV parameters
and executive functions (Frewen, Finucane, Savva,
Boyle, Coen, & Kenny, 2013; Giuliano, Gatzke-
Kopp, Roos, & Skowron, 2017; Kimhy, et al., 2013).
Table 1. HRV parameters and executive functions
Author Ye ar
Participants (number/
age in M±SD or/and
range in years)
HRV parameters Cognitive task Result
Albinet et al. 2010 24/70.7±4.2; sedentary RMSSD, HF WCST ↑
Albinet et al. 2016 36/60 -75; sedentary RMSSD, HF Stroop ↔
RMSSD, HF Random Number Generation-Test ↔
Ha yli ng -Te st ↔
Spatial Running Span-Test ↔
2-back-Test ↔
Verbal Running Span-Test ↔
Dimension-switching-Test ↔
Plus-Minus-Test ↔
Digit-Letter-Test ↔
Alderman &
Olson
2014 56/18-25; healthy HF Eriksen Flanker-Test ↔
Britton et al. 2008 5375/55.5 (men), 55.8
(wo men)
HF Alice-Heim 4-I ↔
Duschek et al. 2009 60/24.5±3.7; healthy HF d2 ↔
Frewen et al. 2013 4763/61.7±8.3; healthy HF MOCA ↔
Giuliano et al. 2017 42 women/30.42±6.54;
stressed
HF visual change detect test ↔
Hansen et al. 2004 37 men/19.1; healthy HF CPT: executive functions ↑
2-back ↑
Ki nesiolog y 52(2020)1:72- 84Grässler, B et al.: RESTING HEART RATE VARIABILITY AS A POSSIBLE MARKER...
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Author Ye ar
Participants (number/
age in M±SD or/and
range in years)
HRV parameters Cognitive task Result
Hansen et al. 2003 53 men/23; healthy RMSSD CPT: executive functions ↑
2-back ↑
Hansen et al. 2009 65/23.1; healthy HF CPT: executive functions ↑
HF 2-back ↑
Hovland et al. 2012 36/18-50; panic
disorders
HF WCST ↑
Stroop ↑
Incalzi et al. 2009 5 4 /69 .1 ±7. 7; COP D HF nu Raven Coloured Progressive
Matrices
↔
Jennings et al. 2015 440/43±7.3; healthy HF Stroop ↑
WMS II + III: SP-BACK, DGT-BACK ↔
DIGVIG1+2 ↔
Trail-Making Test B ↔
Kemp et al. 2016 8114/51.17±8 .81; he althy RMSSD, HF Trail-Making Test B ↑
Kimhy et al. 2013 8 17/ 57.11±11.15; h eal thy HF Digits backward span ↔
Category fluency ↔
Number series ↔
SGST ↔
Luque-Casado
et al.
2013 26 men/19.5; fit & unfit
group
RMSSD Psychomotor vigilance task ↑
RMSSD Temporal orienting task ↔
RMSSD Duration discrimination task ↔
Mathewson et
al.
2010 76/30.6; healthy HF Pictorial Stroop ↔
Nicolini et al. 2014 80/78.6; 40 MCI, 40 CG HF nu digit cancellation and bell test ↔
digit span backward ↔
Trail-Making Test B ↔
Weigl’s colour-form sorting test ↔
Raven’s coloured progressive
matrices
↔
Letter fluency ↔
Nonogaki et al. 2017 78/77.1±6.2; AD HF Category fluency test ↔
Letter fluency test ↔
Wechsler: digit symbol subtest ↔
Clock drawing test ↔
Stroop ↔
Stenfors et al. 2016 119/47.98±10.4 9; 25 -66;
healthy
RMSSD, HF 2-back ↔
Trail-Making Test B ↔
Stroop
RMSSD, HF Letter Digit Substitution Task
Williams et al. 2016 104/19.25±1.43 healthy HF, RMSSD Modified flanker test ↑
Yang et al. 2008 63 men/78.3±3.9;
healthy
RMSSD CASI ↑
Note. AD – Alzheimer’s disease; CASI – Cognitive Abilities Screening Instrument; COPD – hypoxemic chronic obstructive pulmonar y
disease; CPT – continuous per formance test; DGT-BACK – digit span raw score; CG – control group; DIGVIG – digit vigilance; HF
– power in high frequency range; MCI – mild cognitive impaired; MOCA – Montreal Cognitive Assessment; nu – normalized units;
RMSSD – root of the mean square of the differences of successive intervals; SD – standard deviation; SGST – Stop & Go Switch Task;
SP-BACK – spatial span backward raw sc ore; WCST – Wisc onsin card sorting test; WMS – Wechsler Memory Scale. ↑: significant
positive correlation. ↔: no correlation detected.
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Memory and learning
Memory and learning seem hardly related to
HRV parameters (Table 2). There are some studies
that found no connections (Britton, et al., 2008;
Incalzi, et al., 2009; Jennings, et al., 2015; Nicolini,
et al., 2014; Stenfors, et al., 2016). Only one study
detected correlations: Nonogaki et al. (2017) showed
that the Wechsler Memory Tasks were related to HF.
There was a trend for HF in the verbal SRT (Selec-
tive Reminding Test) (Shah, et al., 2011).
Language ability
Language abilities were assessed in four studies
(Table 3). Two of them showed no correlations
(Britton, et al., 2008; Incalzi, et al., 2009). In the
study by Britton et al. (2008), HF of 5375 subjects
with a mean age of 55 years was measured. The
study of Incalzi et al. (2009) measured patients with
hypoxemic chronic obstructive pulmonary disease
(COPD) and used two language tasks. Frequency-
domain parameters did not correlate with task
performance. But the language part of two cognitive
test batteries showed correlations with HF: MOCA
(Montreal Cognitive Assessment) (Frewen, et al.,
2013) and CASI (Yang, et al., 2008). In both studies,
healthy elderly people were tested.
Visuospatial functioning
The relationship between HRV and visuospatial
functioning was investigated in three studies (Table
4). Frewen et al. (2013) found no association in 4763
healthy elderly subjects. Nicolini et al. (2014) found
no correlation either. Here, healthy elderly people
and subjects with MCI (mild cognitive impairment)
were investigated. On the other hand, Incalzi et al.
(2009) found a connection with frequency-domain
Table 2. HRV parameters and memory and learning
Author Ye ar
Participants (number/
age in M±SD or/and
range in years)
HRV parameters Cognitive task Result
Britton et al. 2008 5375/55.5 (men), 55.8
(wo men)
HF 20-word free recall test ↔
Incalzi et al. 2009 5 4 /69 .1 ±7. 7; COP D HF nu Rey auditory 15-word learning test ↔
Immediate visual memory ↔
Jennings et al. 2015 440/43±7.3; healthy HF 4WRD-STM ↔
Nicolini et al. 2014 80/78.6; 40 MCI, 40 CG HF nu Digit Span Forward ↔
Nonogaki et al. 2017 78/77.1±6.2; AD HF Wechsler Memory ↑
Shah et al. 20 11 416 men twins/55.1±2.9 HF SRT ↔
Visual SRT ↔
Stenfors et al. 2016 119/47.98±10.4 9; 25 -66;
healthy
RMSSD, HF Reading Span Task ↔
Note. 4WRD-STM – Four-Word Memory Test; CASI – Cognitive Abilities Screening Instrument; CG – control group; COPD – hypoxemic
chronic obstructive pulmonary disease; HF – power in high frequency range; MCI – mild cognitive impaired; nu – normalized units;
RMSSD – root of the mean square of the differences of successive inter vals; SRT – Verbal Selective Reminding Test. ↑: significant
positive correlation. ↔: no correlation detected.
Table 3. HRV parameters and language ability
Author Ye ar
Participants (number/
age in M±SD or/and
range in years)
HRV parameters Cognitive task Result
Britton et al. 2008 5375/55.5 (men), 55.8
(women); healthy
HF Mill Hill Vocabulary Test ↔
Phonemic fluency ↔
Semantic fluency ↔
Frewen et al. 2013 4763/61,7±8.3; healthy HF MOCA ↑
Incalzi et al. 2009 5 4 /69 .1 ±7. 7; COP D HF nu Verbal fluency test ↔
Sentence construction ↔
Yang et al. 2008 63 men/78.3±3.9;
healthy
HF CASI ↑
Note. CASI – Cognitive Abilities Screening Instrument; COPD – hypoxemic chronic obstructive pulmonary disease; HF – power in
high frequency range; MOCA – Montreal Cognitive Assessment; nu – normalized units; SD – standard deviation. ↑: significant positive
correlation. ↔: no correlation detected.
Ki nesiolog y 52(2020)1:72- 84Grässler, B et al.: RESTING HEART RATE VARIABILITY AS A POSSIBLE MARKER...
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HRV. Regarding visuospatial functioning, there are
too little studies to make any conclusions.
Processing speed
Six studies investigating the relationship
between processing speed and HRV (Table 5) were
identied. In none of them signicant correlations
between vagally mediated HRV and processing
speed were detected. Specically, there was no
correlation with the non-executive part of CPT
(Hansen, et al., 2003, 2004, 2009), Trail-Making
Test A (Nicolini, et al., 2014; Stenfors, et al., 2016),
and backward counting (Kimhy, et al., 2013).
Global cognitive functioning
Some authors did not dierentiate between
single cognitive functions but used general cogni-
tive tests or presented only the total score of a cogni-
tive test battery (Table 6). The MMSE (Mini Mental
Status Examination) is one of the most widespread
cognitive test batteries. One study showed positive
associations between the total score of MMSE and
RMSSD (Kim, et al., 2006). Associations with the
frequency-domain parameters were found in the
same study and a non-signicant trend in the study
by Mellingsæter, Wyller, Ranho, Bogdanovic, and
Wyller (2015), but not in the study by Allan et al.
Table 4. HRV parameters and visuospatial functioning
Author Ye ar
Participants (number/
age in M±SD or/and
range in years)
HRV parameters Cognitive task Result
Frewen et al. 2013 4763/61,7±8.3; healthy HF MOCA ↔
Incalzi et al. 2009 5 4 /69 .1 ±7. 7; COP D HF nu CDL ↓
Nicolini et al. 2014 80/78.6; 40 MCI, 40 CG HF nu Rey-Osterrieth complex figure-
delayed recall
↔
Note. CDL – copying of drawing landmarks; CG – control group; COPD – hypoxemic chronic obstr uctive pulmonary disease; HF –
power in high frequency range; MCI – mild cognitive impaired; MMSE – Mini-Mental-Status-Examination; MOCA – Montreal Cognitive
Assessment; nu – normalized units; SD – standard deviation. ↑: significant positive correlation. ↔: no correlation detected.
Table 5. HRV parameters and processing speed
Author Ye ar
Participants (number/
age in M±SD or/and
range in years)
HRV parameters Cognitive task Result
Hansen et al. 2004 37 men/19.1; healthy HF CPT ↔
Hansen et al. 2003 53 men/23; healthy RMSSD CPT ↔
Hansen et al. 2009 65/23.1; healthy HF CPT ↔
Kimhy et al. 2013 8 17/ 57.11±11.15; h eal thy HF Backward counting ↔
Nicolini et al. 2014 80/78.6; 40 MCI, 40 CG HF nu Trail-Making Test A ↔
Stenfors et al. 2016 119/47.98±10.4 9; 25 -66;
healthy
RMSSD, HF Trail-Making Test A ↔
Note. CG – control group; CPT – continuous performance test; HF – power in high frequency range; MCI – mild cognitive impaired;
nu – normalized units; RMSSD – root of the mean square of the dif ferences of successive intervals; SD – standard deviation. ↑:
significant positive correlation. ↔: no correlation detected.
Table 6. HRV parameters and global cognitive function
Author Ye ar Participants (number/age in M±SD or/
and range in years) HRV parameters Cognitive task Result
Allan et al. 2005 114/>65; 80 healthy, 14 AD, 20 VAD HF MMSE ↔
Allan et al. 2007 177/>65; 39 AD, 30 VAD, 30 DLB, 40 PDD,
38 CG
HF CAMCOG ↑
Kim et al. 2006 311 women/65-85 disabled HF, RMSSD MMSE ↑
Mellingsæter
et al.
2015 62/14 AD or MCI (73.6), 48 CG (72); >65 HF MMSE ↑
Note. AD – Alzheimer disease; CAMCOG – Cambridge Examination for Mental Disorders in the Elderly; CG – control group; DLB
– dementia with Lewy bodies; HF – power in high frequency range; MCI – mild cognitive impaired; MMSE – Mini-Mental-Status-
Examination; PDD – Parkinson’s disease dementia; RMSSD – root of the mean square of the differences of suc cessive inter vals; SD
– standard deviation; VAD – vascular Alzheimer disease. ↑: significant positive correlation. ↔: no correlation detected.
Grässler, B et al.: RESTING HEART RATE VARIABILITY AS A POSSIBLE MARKER... Ki nesiolog y 52(2020)1:72- 84
79
(2005). Allan et al. (2007) detected correlations
between HF and the total score of the test battery
CAMCOG (Cambridge Examination for Mental
Disorders in the Elderly) in 177 elderly people.
Discussion and conclusion
The purpose of the current review was to
summarize the existing literature exploring the
cross-sectional correlation between resting HRV
and cognitive functions. Possible reasons for both
the detected and not detected correlations are
presented.
HRV and executive functions
Executive functions comprise working memory,
inhibition and cognitive exibility (Albinet, et al.,
2016). Our results showed a partly relation between
executive performances and HRV levels. Some
studies detect associations with the vagally medi-
ated HRV parameters HF or RMSSD (Albinet, et
al., 2010; Hansen, et al., 2003, 2004, 2009; Hovland,
et al., 20012; Jennings, et al., 2015; Kemp, et al.,
2016; Luque-Casado, et al., 2013; Williams, et al.,
2016; Yang, et al., 2008), but others did not nd any
associations (Alderman & Olson, 2014; Britton, et
al., 2008; Duschek, et al., 2009; Frewen, et al., 2013;
Giuliano, et al., 2017; Incalzi, et al., 2009; Kimhy,
et al., 2013; Mathewson, et al., 2010; Nicolini, et al.,
2014; Nonogaki, et al., 2017; Stenfors, et al., 2016).
Hansen et al. (2003) justied their positive
results through the association between HRV and
“ecient attentional regulation and greater ability
to inhibit pre-potent but inappropriate responses”.
This statement underpins the supposed relation-
ship between HRV and the prefrontal cortex and
explains the positive association between vagally
mediated HRV and executive function tasks like
the task Stroop. Hansen et al. (2004) supposed
that the positive relationship was the result of the
increased eciency of prefrontal neural function
achieved through aerobic training. In particular,
physical training leads to cardiovascular improve-
ments and increased cerebral blood ow, which
improves prefrontal functioning.
One explanation for the lack of correlations in
other studies could be the big number of factors
playing their roles in the relationship between cogni-
tive performance and HRV (Alderman & Olson,
2014). Kimhy et al. (2013) mentioned a limited
instrument sensitivity of the working memory task
as one reason for the lack of correlation. Britton
et al. (2008) stated that their test battery did not
assess executive functions in detail. Nonogaki et al.
(2017) called the old age of their subjects to account
for the lack of correlations and maybe dementia
hid possible correlations. However, Holzman and
Bridgett (2017) noted that the relation between HRV
and top-down self-regulation is stronger in older
individuals. Nicolini et al. (2014) stated that auto-
nomic dysfunction is revealed only when the auto-
nomic system is challenged by changing from the
supine position to the standing one. In summary, the
results demonstrated a tendency of positive corre-
lations between typical executive function tasks
(Stroop and 2-back) and vagally mediated HRV.
HRV and memory learning
Memory was positively associated with vagally
mediated HRV in only one study with AD patients
(Nonogaki, et al., 2017). The authors argued that
some parts of the brain (insular cortex, amygdala,
hypothalamus and nucleus tractus solitarius)
regulate cardiac autonomic function and interact
with the medial temporal lobes. These regions are
responsible for memorizing things but get impaired
in case of a central autonomic dysfunction, which
is the case in AD. Karlamangla et al., (2014)
conrmed this by revealing a positive relationship
between cardiovascular function and memory. Shah
et al. (2011) mentioned an impaired baroreex as a
possible mechanism because it is responsible for the
cerebral blood ow and is an important component
of the autonomic nervous system. In summary, the
results indicate a weak connection between memory
a n d H RV.
HRV and language ability
Language ability includes comprehension and
word nding (Levy, 1994). In two studies, posi-
tive correlations with HF were detected (Frewen,
et al., 2013; Yang, et al., 2008). Frewen et al. (2013)
mentioned the fornix, a connective part for the
hippocampus in the brain, as a possible location
underlying the association between HRV and cogni-
tion. Moreover, the cholinergic anti-inammatory
pathway could explain this relationship as well.
HRV and visuospatial functioning
Regarding the visuospatial functioning, one
study detected signicant correlations. Incalzi et
al. (2009) explained their results with a dysfunction
of the right insular in COPD patients and concluded
that “neurogenic heart diseases” are an expression
of cardiac abnormalities related to problems in the
brain-heart connection.
HRV and processing speed
Processing speed was added as a non-execu-
tive function, measuring the reaction time in simple
choice tasks that do not require challenging cogni-
tive functions. None of the six relevant studies
found signicant correlations. There was at least a
trend in the Trail-Making Test A (Nicolini, et al.,
2014; Stenfors, et al., 2016). Stenfors et al. (2016)
suggested using the parameter QTVI (QT varia-
bility index) because it showed the best correlations
Ki nesiolog y 52(2020)1:72- 84Grässler, B et al.: RESTING HEART RATE VARIABILITY AS A POSSIBLE MARKER...
80
between HRV and cognitive functions. In the study
of Hansen et al. (2004), curiously, the low HRV
group had faster reaction times compared to the
high HRV group in a non-executive task.
HRV and global cognitive functions
In three out of four studies, positive correla-
tions between total cognitive scores and HRV were
detected. HF correlated signicantly with the scores
of the MMSE (Kim, et al., 2006; Mellingsæter, et
al., 2015) and the CAMCOG (Allan, et al., 2007).
Additionally, RMSSD showed a positive correlation
with the MMSE (Kim, et al., 2006). These results
implicate that HRV reects broad cognitive func-
tions and not only specic ones.
Mechanism linking HRV and cognitive
function
The role of the HRV as a possible biomarker
of the top-down self-regulatory mechanism was
well discussed in a recent meta-analysis (Holzman
& Bridgett, 2017). The present systematic review
focuses on the cognitive part of self-regulation.
Thayer et al. (2009) suggested that HRV served
as an index of the functional capacity of brain
structures “that support the eective and ecient
performance of cognitive executive-function tasks
including working memory and inhibitory control”.
Two theories are the basis for the considered
relation between HRV and top-down self-regu-
lation that comprises cognitive functions: the
Neurovisceral Integration Model (Thayer, et al.,
2009) and the Polyvagal Theory (Porges, 2003).
Both approaches stated a moderating role of the
parasympathetic-mediated nervous system. The
prefrontal cortex is supposed to play an important
role thereby. This part of the brain forms together
with cortical and subcortical brain structures an
interconnected network and controls the heart rate
being also responsible for the cognitive regulation
(Thayer & Lane, 2009). Thus, a declining prefrontal
activity leads to an increased sympathetic activity,
heart rate and hence reduced HRV (Thayer & Lane,
2009). This inhibition of prefrontal activity and
pronounced activation of the sympathetic system
was benecial for human survival in ancient
times. However, nowadays, a tonic inhibition of
the prefrontal cortex and a permanent sympathetic
state are contradictory to adaptation and self-regu-
latory processes (McCraty & Shaer, 2015). Thus,
an optimal level of vagally mediated HRV is neces-
sary for adaptation and cognitive functions.
The link between prefrontal cortex and cardiac
system was mentioned in some studies and called
upon as one explanation for the correlation between
HRV and cognition. The functional state of the
cardiac system depends on the level of brain perfu-
sion that can be improved through aerobic training
(Mahinrad, et al., 2016). Hansen et al. (2004) argued
that the relationship is “mediated by a common
set of neural circuits, the ecient functioning of
which have inhibitory processes”. Mahinrad et
al. (2016) considered an autonomic dysfunction
caused by dysregulation in cerebral perfusion as
the link between low HRV and cognitive impair-
ment. External factors like cardiovascular risk
factors could be responsible for the association as
well. Further, HRV could reect an early manifes-
tation of brain damage and future cardiovascular
events which lead to cognitive decline. The barore-
ex is another possible explanation for the relation
between HRV and cognition (Kim, et al., 2006). It
ensures proper blood ow through all organs and
is regarded an indicator for the autonomic nervous
system. High blood pressure variability is a sign
of baroreex disturbances and is associated with
cognitive impairment (Meyer, et al., 2017). The
relationship between blood pressure regulation and
dementia was recently reviewed by O’Callaghan
and Kenny (2016). They have described the
phenomenon of Neurocardiovascular Instability
(NCVI), which aects heart rate behaviour through
abnormal neural control and is more prevalent in
patients with MCI or AD. However, the direction
of causality is still unclear. Another reason for the
relationship may be a dysfunction of the cholinergic
system, which impairs cognitive and parasympa-
thetic system function (Frewen, et al., 2013; Yang,
et al., 2008). Incalzi et al. (2009) have mentioned
a dysfunction of the right insular as an additional
reason for the relationship because the insular
modulates sympathetic tone and is involved in inte-
grating cognitive and emotional aspects. Allan et
al. (2007) listed autonomic neuropathy as a possible
explanation because frequency-domain HRV was
lower in patients with Parkinson’s disease, who
showed higher prevalence of autonomic neuropathy.
Limitations
Some limitations have to be mentioned. First,
the studies used dierent HRV measurement tech-
niques and durations of recording the HRV. This
could lead to inconsistency in the results. Second,
dierent samples in terms of age-range and state
of health were compared. This was done to oer a
variety of studies with dierent sample character-
istics. Otherwise, the number of studies would have
been much smaller. And third, our classication of
cognitive functions was restricted in the way that a
lot of dierent tasks were used and therefore it was
dicult to classify and compare them.
Conclusions
A summary of studies investigating the asso-
ciation between resting-state HRV and cognitive
performance was provided. Theoretical models
Grässler, B et al.: RESTING HEART RATE VARIABILITY AS A POSSIBLE MARKER... Ki nesiolog y 52(2020)1:72- 84
81
proposed a positive connection between HRV and
cognitive performance through the link between
cardiovascular regulating processes in the brain
and cognition regulating processes located, espe-
cially, in the prefrontal cortex (McCraty, et al.,
2015; Shaer, et al., 2014; Thayer, et al., 2009).
Some studies could conrm this relationship (e.g.,
Albinet, et al., 2010; Hansen, et al., 2009; Hovland,
et al., 2012; Yang, et al., 2008), but others could not
(e.g., Britton, et al., 2008; Nicolini, et al., 2014). The
lack of a uniform measurement procedure, dierent
cognitive tasks, and dierent sample characteristics
(age, disorders) are possible reasons for the lack
of a stronger relation. To take a step forward in
diagnosing and preventing dementia, longitudinal
studies are recommended to evaluate HRV as an
indicator of cognitive impairment and to investi-
gate the development of and interaction between
HRV and cognitive performance throughout life.
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Submitted: July 18, 2018
Accepted: May 5, 2019
Published Online First: April 30, 2020
Correspondence to:
Bernhard Grässler, Ph.D.
Otto-von-Guericke-University Magdeburg,
Department of Sport Science
Germany
Phone: 0049 361 6756682
Fax: 0049 361 6746754
E-mail: bernhard.graesler@ovgu.de
