Abstract and Figures

METHODS Sixty-eight elderlies were paired in terms of age and gender and were equally distributed into depressed and nondepressed groups, according to their score on the Beck Depression Questionnaire. The participants performed the Grooved Pegboard Test placing and withdrawing pegs while execution time and error rate were measured. RESULTS This investigation revealed that depressive symptoms exert a broad effect upon motor control, although that the symptom intensity, as well as the interaction between aging and depression intensity, were exclusively correlated with withdrawal task, suggesting that there is a greater effect upon motor acts with higher frontal lobe requirements. CONCLUSION The discrimination of motor control aspects provides a valuable contribution for the understanding of the underlying neurophysiology of the interaction between aging and depression as it represents an indirect measure of cerebral dysfunction. Further, these findings may still have clinical implications, as they can promote more rational approaches to the elaboration of preventive measures that help maintain the functional capability of depressed elderlies.
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Motriz, Rio Claro, v.23, n.4, 2017, e1017110 DOI: http://dx.doi.org/10.1590/S1980-6574201700040005
Over the past few years, a growing body of evidence has
demonstrated that depression disorders are gaining relevance
in disease prevention and health promotion1,2. Specically, as
the population ages, the economic impact of neuropsychiatric
disorders is expected to grow signicantly3, posing a consider-
able public health problem4,5. Depression symptoms not only
include mood alterations but an array of other disorders, including
apathy, anedonia, vegetative symptoms and cognitive dysfunc-
tion, which can severely impact the quality of life of the elderly
and their ability to deal with many activities of daily living6,7.
It is common knowledge that aging impairs the mainte-
nance of functional capability as well as several domains of
the cognitive segment. However, the notion that depression
is also associated with alterations in regions of the brain that
are not related to mood control, was acknowledged only in the
last few decades
. Specically, neuroscience-based inquiries
have demonstrated depression inuences several areas of the
brain, such as the prefrontal and orbitofrontal cortices, anterior
cingulate, amygdala, and the hippocampus9,10. Consequently,
impairments over executive functions11-13, processing speed14-16,
and episodic memory may occur as a function of depression,
impairing everyday functioning12,17.
Most cognitive impairments associated with depression have
a strict relationship with motor control. These consequences,
usually termed as psychomotor abnormalities, encompass the
engagement of cognitive-control mechanisms into a motor act
and have been commonly explored by measures concerning
processing speed, such as reaction time or the control of spatial-
temporal parameters (see Bennabi, Ugrinowitsch, Apolinario-
Souza, Vieira, Albuquerque and Benda19 for a more detailed
review). These measures were included in different analyses,
such as gait
, drawing tasks
and eye movements
Because motor slowness was frequently reported in these stud-
ies, the impairments over motor control have been considered a
common feature of depressed individuals and comprises a great
focus of research in the last years. Summarily, these studies have
aimed to uncover the inuences of depression on motor control
in young adults, despite that some of them omitted the medica-
tion status of the sample20,26 or were under medication22, which
might have biased the intended behavior. To our knowledge,
Beheydt, Schrijvers, Docx, Bouckaert, Hulstijn and Sabbe
were the only who demonstrated that unmedicated depressive
older adults presented motor control impairments in comparison
to their nondepressed peers. Promising results were observed
as they revealed that the execution and initiation times were
signicantly impaired according to the manipulation of the
cognitive load of a gure copying task27.
The distinction of motor control aspects, on the other hand,
is extremely relevant to understand the issues related to the
interaction between aging and depression since it can provide
an indirect measure of different brain dysfunctions
. According
to the classic Woodworth concepts29, which are still followed by
several recent researches
, it is possible to discriminate motor
control aspects manipulating the required time on a motor task.
More precisely, ballistic motor actions don’t require much input
of sensory information and rely mainly on a pre-programmed
phase (planning; initial impulse phase) unlike movements that
are slower which engage high feedback processing (online
control of motor actions; current control phase). Therefore,
by manipulating different motor control requirements, we may,
indirectly, reveal impairments specically linked to different
brain areas.
Original Article (short paper)
Motor control assessment of community-dwelling
older adults with depressive symptoms
Lucas Eduardo Antunes Bicalho1, Maicon Rodrigues Albuquerque1, Jonas Jardim de Paula1, Guilherme Menezes
1Universidade Federal de Minas Gerais, UFMG, Belo Horizonte, MG, Brazil.
Abstract — Aims: The purpose of this study was to investigate how depressive symptoms mediate different motor
control requirements in elderlies and to assess the concurring effects fomented by the interaction between aging and
depressive symptoms, providing indirect measures of brain functionality. Methods: Sixty-eight elderlies were paired in
terms of age and gender and were equally distributed into depressed and nondepressed groups, according to their score
on the Beck Depression Questionnaire. The participants performed the Grooved Pegboard Test placing and withdrawing
pegs while execution time and error rate were measured. Results: This investigation revealed that depressive symptoms
exert a broad effect upon motor control, although that the symptom intensity, as well as the interaction between aging
and depression intensity, were exclusively correlated with withdrawal task, suggesting that there is a greater effect upon
motor acts with higher frontal lobe requirements. Conclusion: The discrimination of motor control aspects provides
a valuable contribution for the understanding of the underlying neurophysiology of the interaction between aging and
depression as it represents an indirect measure of cerebral dysfunction. Further, these ndings may still have clinical
implications, as they can promote more rational approaches to the elaboration of preventive measures that help maintain
the functional capability of depressed elderlies.
Keywords: aging, depression, psychomotor, psychiatric disorders, elderly, hand function.
2Motriz, Rio Claro, v.23, n.4, 2017, e1017110
Bicalho L.E.A. & Albuquerque M.R. & de Paula J.J. & Lage G.M.
Further, the estimation of the intensity of depression is also
of fundamental concern to the understanding of the interaction
between aging and depression since it has been reported as one
possible source of variation in the degree of cognitive impair-
ment27,34. Sex is another factor that might inuence the move-
ment planning and control of depressed elderlies. Specically,
Fernandes, Ugrinowitsch, Oliveira, Bicalho and Lage35 have
recently demonstrated that response strategies in aiming con-
trol are inuenced by sex in different task constraints. Still,
neurobiological differences (dimorphisms) have been observed
in many neurological domains (see Sacher, Sacher, Neumann,
Okon-Singer, Gotowiec and Villringer36 for a review) which
reveal that sex is also a relevant subject in the inquiries of
neuroscience and consequently, in motor control.
Overall, the discrimination of different aspects involved in
the motor control of elderlies with depressive symptoms can
bring useful information regarding the interaction between aging
and depression. Particularly, we expect to conrm that depressed
older adults present more prominent impairments in the most
complex task, (i.e., the peg placement task), and further, unravel
distinct associations with their motor performance.
Material and Methods
Older adults, who were originally participating in a social
project headed by the local city hall, were invited to participate
in this study. Firstly, the volunteers were submitted to a struc-
tured interview in order to exclude individuals with previous
history of psychiatric disorder, neurological disease, with
uncorrected or abnormal vision or using medication that
might impair motor control. Also, the level of education of
the volunteers was measured according to years of study. The
Edinburgh Handedness Inventory (EHI)37 was then applied to
determinate the participant’s laterality index and to exclude
individuals who presented a preference index of 70 points
or below. Subsequently, the Mini-Mental State Examination
(MMSE)38 was employed to screen dementia cases, exclud-
ing individuals who scored less than 24 points39 . The Beck
Depression Index (BDI)40 was then applied for the assessment
of depression symptoms and to allocate participants into two
groups, depressed elderlies (DE) or nondepressed elderlies
(NE), according to their score, following the cut-off point for
mild depression (10)41,42. The BDI is a self-evaluation scale
which is used worldwide in the general population and in
primary care43. Is easy to administer, is inexpensive44 and is
considered one of the most commonly used scales for identify-
ing the severity of depression symptoms.
After the exclusion of individuals who didn’t meet the
proposed criteria, 34 individuals (65.47 ± 3.14 years) with a
score equal to or higher than 10 (mild symptoms and above)
on the BDI were allocated into DE. Then, thirty-four indi-
viduals who paired in terms of level of education, age (65.35
± 5.13 years) and gender (4 males and 30 females) and pre-
sented a score lower than 10 on the BDI were allocated as
controls (Figure 1).
Figure 1. Flowchart overview of sample selection and experimental procedures.
Volunteers recruited from a
social project led by the city
Handedness Inventory
Mini-Mental State
Beck’s Depression
Sample pairing in terms
of gender and age
Depressed (n=36)
- 4 male, 30 females (65.79 ± 4.95 years)
Nondepressed (n=36)
- 4 male, 30 females (66.15 ± 2.99 years)
Pegboard Grooved Test
- Placement
- Removal
Motriz, Rio Claro, v.23, n.4, 2017, e1017110 3
Motor control and depressive symptoms
After the sample selection, all volunteers were oriented
regarding the experimental procedures and signed a consent
form before joining the study, which was conducted in ac-
cordance with the Declaration of Helsinki, and was approved
by the local Ethics Committee (CEP-FUMEC 03/2011). All
participants gave written consent for participation.
Experimental procedures
After the sample selection, the participants were oriented
concerning the experimental tasks procedures. Specically,
the participants were asked to take 25 pegs (1 mm diameter
and 25 mm length) placed on a receptacle, and place them in
the row of holes of the pegboard, or withdraw the pegs from
the pegboard to the receptacle as quickly as possible and in a
standardized, prescribed order (place and withdraw pegs from
left to right using their right hand). The Pegboard Grooved
Test (Lafayette Instruments # 32025) was then applied in both
groups to analyze the motor control of the volunteers (Figure
2). Each condition was repeated and the order of execution was
randomized. The tests and interviews were conducted in the
residences of the volunteers.
Figure 2. Schematic representation of the prescribed order of peg placement (a) and withdrawal (b) on the Grooved Pegboard Task. Adapted from
Salvador et al.54
With the assistance of a chronometer, participants were
timed during the GPT execution for both tasks (placement and
withdrawal). Specically, the time between the start stimulus
until the placement/withdrawal of the last peg was measured as
execution duration. Execution errors, which include attempts
in which the pins fell during placement/withdrawal, and order
errors, were also measured by the experimenter. Furthermore,
the association of motor control measures with depression
symptoms, depression intensity, and the interaction between
aging*depression intensity were determined with correlation
analysis performed in a statistical software package.
Statistical analysis
For all motor control variables, data from two trials of each
condition were averaged for each participant. Then, the ho-
mogeneity of variances was veried with a Shapiro-Wilks test
and subsequent tests were chosen accordingly. Mann-Whitney
U-tests were used to test overall group differences regarding
mean values of execution time and errors for both tasks, and
for sex differences. Spearman’s rank correlation coefcients
were computed to assess the association between the presence
of depressive symptoms, depression intensity, and the interac-
tion between aging and depression intensity with motor control
variables. Statistical analysis was conducted with SPSS 23.0 for
Windows (Statistical Package for Social Sciences, Chicago, IL,
USA) and α ≤ .05 was used as signicance criterion.
Sample characteristics
No differences in terms of age (F
=.127 p=.723), level of hand-
edness (EHI; F1,66=3.873, p=.053) and cognitive status (MMSE;
4Motriz, Rio Claro, v.23, n.4, 2017, e1017110
Bicalho L.E.A. & Albuquerque M.R. & de Paula J.J. & Lage G.M.
Pegs placement
According to the Mann-Whitney U-test, depressed older
adults presented a longer execution duration of peg placement
(MWU=349, Z=-2.810, p=.005) (Figure 3A) and a higher amount
of errors (MWU=383.0, Z=-2.472, p=.013) (Figure 3B) than
their non-depressed peers. Separate analysis revealed that the
results can’t be partially attributed to sex differences. Mann-
Whitney U-test analysis revealed no differences between males
and females regarding peg placement duration (MWU=152.5,
Z=-1.666, p=.096) and peg placement error (MWU=171.5,
Z=-1.344, p=.179) taking sex as factor. Spearman’s rank test
revealed a weak association between the presence of symptoms
and placement duration (r=0.296, p=.014) but, marginally, no
association with placement errors (r=0.233, p=.056). No signi-
cant correlations between scores of the depression rating (DBI)
with placement duration (r=0.238, p=.050) and placement errors
(r=0.085, p=.489) were revealed, either. However, a weak asso-
ciation between the interaction of aging*symptom intensity with
placement duration (r=0.260, p=.033) was observed, while no
associations with placement error (r=0.082, p=.506) were shown.
Withdrawal of pegs
The Mann-Whitney U-test also revealed that depressed older
adults present a higher withdrawal time (MWU=244.5, Z=-
4.099, p=.000) (Figure 3A) and withdrawal errors (MWU=426.5,
Z=-2.904, p=0.004) (Figure 3B) than their non-depressed coun-
terparts. The Mann-Whitney U-test analysis revealed no differ-
ences between males and females with and without depressive
symptoms regarding the duration of peg withdrawal (MWU=157,
Z=-1.584, p=.113) and withdrawal error (MWU=200, Z=-1.237,
p=.216). Correlation analysis revealed a weak association be-
tween the presence of depression symptoms and peg withdrawal
duration (r=0.472, p=.000) and with withdrawal errors (r=0.320,
p=.008). However, a moderate association between withdrawal
duration and symptom intensity (r=0.527, p=.000) (Figure 3C)
was revealed, as well as with the interaction of aging*symptom
intensity (r=0.531, p=.000). Regarding withdrawal errors,
Spearman’s rank test revealed a very weak association with
symptom intensity (r=0.242, p=.047) (Figure 3C) and a weak
association with the interaction of symptom intensity*aging
(r=0.441, p=.000).
F1,66=1.086, p=.301) were revealed between groups. In sum, non-
depressed older adults presented a range of 0 to 9 of depression
intensity on the BDI questionnaire, 80-100 on EHI, and 24-30
on MMSE; depressed elderlies presented a range of 10 to 50
on BDI, 80 to 100 on EHI, and 24-30 on MMSE. Descriptive
statistics for the entire sample are represented below on Table 1.
Table 1. Demographic characterization of depressed and non-depressed participants. Comparisons between groups were performed with univari-
ate analysis of variance (ANOVA). *p ≤ .05; **p ≤ .01
Nondepressed Depressed
Age (years) 66.15 ± 2.99 65.79 ± 4.95
Beck Depression Inventory 5.38 ± 2.24 ** 16.94 ± 9.46
Edinburgh Laterality Index 99.12 ± 3.79 97.94 ± 5.38
Gender 30 ♀ / 4 ♂ 30 ♀ / 4 ♂
Mini-Mental State Examination 29.03 ± 1.98 28.38 ± 1.61
Years of education 7.41 ± 4.44 7.94 ± 4.01
epressed elderlies (c). *p ≤ .05; **p ≤ .01
Figure 3. Mean (± SD) values of peg placement/withdrawal duration (a), errors (b) and a representation of the rate of change between peg with-
drawal duration/errors and depression intensity (BDI score) of depressed and nond
Duration (s)
Average of erros
Placement Withdrawal
Withdrawal Time
Withdrawal Error
Linear Fit
Linear Fit
-0.4 0 10 20 30 40 50
Withdrawal Time (s)
Withdrawal Errors (mean)
Depression Intensity (DBI Index)
Motriz, Rio Claro, v.23, n.4, 2017, e1017110 5
Motor control and depressive symptoms
The goal of this study was to (a) distinguish motor control
between older adults with and without depressive symptoms
based on different motor requirements (placement/withdrawal
of pegs) and (b) estimate the association between the presence
of depressive symptoms, depression intensity, and interaction
effects between aging and depression intensity, with motor
control. In sum, our results showed that depressed older adults
present a general worse performance than their nondepressed
peers and the depressive symptoms were correlated with motor
control, although its intensity and the interaction between aging
and depression intensity were correlated circumstantially. This
means that depression can impair both motor control require-
ments, although its intensity as the interaction between aging
and depression intensity is related with motor control contextu-
ally. Although we didn’t have enough samples to verify if the
classication of the symptoms of BDI can distinguish motor
performance of depressed older adults, the correlations, in turn,
revealed that the intensity of the symptoms, such as the interaction
between symptom intensity and aging, are strongly associated
with a greater slowness on withdrawal of pegs performance.
The GPT, originally, involves the analysis of the placement
of small shaped key-pegs which must be oriented correctly to
t in a hole with a random orientation. Assessing the with-
drawal of these pegs, Bryden and Roy45 suggested that we can
discriminate measures of visuomotor amplitude (placement) to
a simple measurement of motor speed (withdrawal). However,
since GPT measures how quickly the 25 pegs are placed and
withdrawn, it could be argued that these tasks, in fact, cover a
hybrid control phase, which consist of both initial impulse and
current control phases, although the current control is more
robust in the placement task as it demands more accuracy from
the participant28.
Withdrawal of pins from the instrument holes, therefore,
can be interpreted as the performance of a movement in a
ballistic form to the vicinity of a target that involves mainly a
pre-programmed phase without sufcient feedback processing,
while the placement of pegs into the holes incorporates higher
visual and proprioceptive information of the limb and the target
reference point. In this manner, the GPT enables the comparison
between the execution of two similar motor tasks with different
motor requirements; or more precisely, the distinction between a
higher feedback processing versus an effortless planning process,
and their respective brain associations.
Since the withdrawal task mainly involves a planning process,
these associations can be explained by the observed depression
consequences to the frontal lobe functioning46-48. Specically,
studies have demonstrated that damage to the inferior parietal
lobe, frontal lobes, or basal ganglia hamper the performance of
tasks that require more of a planning process32,49. Furthermore,
previous ndings have also demonstrated that individuals with
depressive symptoms increase the activation of frontostriatal
circuitry as an attempt to compensate cognitive failures
. These
observations lead us to hypothesize that a low involvement of
the frontal lobe (e.g. working memory) on the placement task
might be responsible for the absence of signicant associations.
Furthermore, the detrimental effects to the performance of tasks
that require, predominantly, a current control phase have been
usually associated with damage on the superior parietal lobe
or cerebellum32,49. In this manner, we can infer that depression
symptoms exert a broad effect upon motor control, although their
intensity as the interaction between aging*depression intensity
are only associated with motor acts that presents higher frontal
lobe requirements.
Apparently, our results and hypothesis corroborate with
the ndings of Pier, Pier, Hulstijn and Sabbe51 who observed
signicant associations between symptom intensity and motor
control only in the task that involved, mostly, pre-programmed
components of motor planning (r=0.28, p=0.046) and with the
highest complexity task that was guided, essentially, by feedback
control (r=0.41, p=0.005). Although these associations were
made with a different clinical scale, BDI correlations on this
study presented similar results, revealing positive associations
between different performance measures (initiation time: r=0.31,
p=0.032; movement time: r=0.34, p=0.020, and re-inspection
time: r=0.32, p=0.027) with symptom intensity exclusively in
the most complex task that involved, predominantly, a current
control phase. Following the hypothesis raised by our study, the
lack of association between motor control and symptom intensity
(BDI score) revealed in the ballistic task in their study can be
explained by the absence of the aging and depression interaction
effects, while the higher association in the most complex task
can be justied by high complexity implied by the number of
segments to be copied, and thus, the increased participation of
working memory.
Despite the evident biomechanical differences between
men and women, such as the size of their ngers relative to
the size of pegs, this study didn’t reveal sex-dependent effect
between depressed and nondepressed elderlies. Surprisingly,
the results of this study contrast with those of Briden and Roy45
who revealed performance differences between the sexes dur-
ing removal/placement of pegs. However, some confounding
variables such as menopause status and menstrual cycle phase
that can promote changes in woman physiology and further
inuence motor control response of elderly women was not
controlled in our study. Therefore, the sex differences analysis
of our study might be somewhat awed and could justify the
lack of signicant results. It might also be an interesting avenue
for further investigations.
In conclusion, our study provides the rst evidence of a motor
control-dependent effect on the interaction between depression
symptoms and aging. The results herein strengthen the need to
take careful considerations in dening the requirements of a task
into the assessment of motor control of depressed individuals
as there are indirect evidences that frontal lobe dysfunctions
present a considerable association with the interaction between
aging*depression intensity as well with depression intensity
itself. Furthermore, ours ndings may have clinical implications
since the determination of mechanisms that leads to disability in
aging are extremely important for the elaboration of preventive
measures to help maintain their functional capability
. It adds
evidence to support the claim that the progression of depressive
symptoms deserves a closer look when the disorder is established.
6Motriz, Rio Claro, v.23, n.4, 2017, e1017110
Bicalho L.E.A. & Albuquerque M.R. & de Paula J.J. & Lage G.M.
The present ndings revealed that depressive symptoms can
impair the motor control of elderlies and revealed contextual
associations between aging and illness intensity with motor
performance. The discrimination of motor control aspects raised
by this study provides a valuable contribution to the underlying
neurophysiology of the interaction between aging and depression
symptoms, suggesting the existence of a relevant association
between frontal lobe dysfunction and motor control impairments.
These indirect measures of cerebral dysfunction can also offer
a new path to more rational approaches aimed at assessing and
elaborating of preventive measures for depressed elderlies.
1. Almeida OP. Prevention of depression in older age.
Maturitas. 2014;79(2):136–141. http://doi.org/10.1016/j.
2. Mendelson T, Tandon SD. Prevention of Depression in Childhood
and Adolescence. Child Adolesc Psychiatr Clin N Am. Apr
2016;25(2):201-218. http://doi.org/10.1016/j.chc.2015.11.005
3. Smith K. Trillion-dollar brain drain. Nature. Oct 04
2011;478(7367):15. http://doi.org/10.1038/478015a
4. Haroz EE, Ritchey M, Bass JK, Kohrt BA, Augustinavicius
J, Michalopoulos L, et al. How is depression experienced
around the world? A systematic review of qualitative litera-
ture. Soc Sci Med. Dec 22 2016:1-12. http://doi.org/10.1016/j.
5. Ferrari AJ, Somerville AJ, Baxter AJ, Norman R, Patten SB, Vos
T, et al. Global variation in the prevalence and incidence of major
depressive disorder: a systematic review of the epidemiological
literature. Psychol Med. Mar 2013;43(3):471-481. http://doi.
6. Skoog I. Psychiatric disorders in the elderly. Can J Psychiatry. Jul
2011;56(7):387-397. http://doi.org/10.1177/070674371105600702
7. Kiosses DN, Alexopoulos GS, Murphy C. Symptoms of striato-
frontal dysfunction contribute to disability in geriatric depression.
Int J Geriatr Psychiatry. Nov 2000;15(11):992-999. http://doi.
8. Lohr JB, May T, Caligiuri MP. Quantitative assessment of mo-
tor abnormalities in untreated patients with major depressive
disorder. J Affect Disord. Mar 20 2012;146(1):84-90. http://doi.
9. Krishnan V, Nestler EJ. Linking molecules to mood: new
insight into the biology of depression. Am J Psychiatry.
Nov 2010;167(11):1305-1320. http://doi.org/10.1176/appi.
10. Murray EA, Wise SP, Drevets WC. Localization of dysfunction in
major depressive disorder: prefrontal cortex and amygdala. Biol
Psychiatry. Jun 15 2011;69(12):43-54. http://doi.org/10.1016/j.
11. Baudic S, Tzortzis C, Barba GD, Traykov L. Executive
decits in elderly patients with major unipolar depression. J
Geriatr Psychiatry Neurol. Dec 2004;17(4):195-201. http://doi.
12. Li W, Wang Y, Ward BD, Antuono PG, Li S, Goveas JS. Intrinsic
inter-network brain dysfunction correlates with symptom dimen-
sions in late-life depression. Journal of Psychiatric Research.
2016;87:71-80. http://doi.org/10.1016/j.jpsychires.2016.12.011
13. Morimoto SS, Gunning FM, Wexler BE, Hu W, Ilieva I, Liu J,
et al. Executive Dysfunction Predicts Treatment Response to
Neuroplasticity-Based Computerized Cognitive Remediation
(nCCR-GD) in Elderly Patients with Major Depression. Am
J Geriatr Psychiatry. Oct 2016;24(10):816-820. http://doi.
14. Brailean A, Comijs HC, Aartsen MJ, Prince M, Prina AM,
Beekman A, et al. Late-life depression symptom dimensions and
cognitive functioning in the Longitudinal Aging Study Amsterdam
(LASA). J Affect Disord. Sep 01 2016;201:171-178. http://doi.
15. Butters MA, Whyte EM, Nebes RD, Begley AE, Dew MA,
Mulsant BH, et al. The nature and determinants of neuro-
psychological functioning in late-life depression. Arch Gen
Psychiatry. Jun 2004;61(6):587-595. http://doi.org/10.1001/
16. Sheline YI, Barch DM, Garcia K, Gersing K, Pieper C, Welsh-
Bohmer K, et al. Cognitive function in late life depression:
relationships to depression severity, cerebrovascular risk factors
and processing speed. Biol Psychiatry. Jul 01 2006;60(1):58-65.
17. de Paula JJ, Bicalho MA, Avila RT, Cintra MT, Diniz BS,
Romano-Silva MA, et al. A Reanalysis of Cognitive-Functional
Performance in Older Adults: Investigating the Interaction
Between Normal Aging, Mild Cognitive Impairment, Mild
Alzheimer’s Disease Dementia, and Depression. Frontiers in psy-
chology. 2015;6:2061. http://doi.org/10.3389/fpsyg.2015.02061
18. Lage GM, Ugrinowitsch H, Apolinario-Souza T, Vieira
MM, Albuquerque MR, Benda RN. Repetition and variation
in motor practice: A review of neural correlates. Neurosci
Biobehav Rev. Oct 2015;57:132-141. http://doi.org/10.1016/j.
19. Bennabi D, Vandel P, Papaxanthis C, Pozzo T, Haffen E.
Psychomotor retardation in depression: a systematic review of di-
agnostic, pathophysiologic, and therapeutic implications. Biomed
Res Int. 2013;2013:158746. http://doi.org/10.1155/2013/158746
20. Hausdorff JM, Peng CK, Goldberger AL, Stoll AL. Gait
unsteadiness and fall risk in two affective disorders: a pre-
liminary study. BMC Psychiatry. Nov 24 2004;4:1-7. http://doi.
21. Lemke MR, Wendorff T, Mieth B, Buhl K, Linnemann M.
Spatiotemporal gait patterns during over ground locomotion in
major depression compared with healthy controls. J Psychiatr
Res. Jul-Oct 2000;34(4-5):277-283. http://doi.org/10.1016/
22. Pier MP, Hulstijn W, Sabbe BG. Psychomotor retardation in el-
derly depressed patients. J Affect Disord. Jul 2004;81(1):73-77.
23. Sabbea B, Hulstijn W, van Hoof J, Tuynman-Qua HG, Zitman
F. Retardation in depression: assessment by means of simple
motor tasks. J Affect Disord. Sep 1999;55(1):39-44. http://doi.
Motriz, Rio Claro, v.23, n.4, 2017, e1017110 7
Motor control and depressive symptoms
24. Winograd-Gurvich C, Georgiou-Karistianis N, Fitzgerald PB,
Millist L, White OB. Ocular motor differences between mel-
ancholic and non-melancholic depression. J Affect Disord. Jul
2006;93(1-3):193-203. http://doi.org/10.1016/j.jad.2006.03.018
25. Sweeney JA, Strojwas MH, Mann JJ, Thase ME. Prefrontal and
cerebellar abnormalities in major depression: evidence from
oculomotor studies. Biol Psychiatry. Apr 15 1998;43(8):584-594.
26. Stordal KI, Lundervold AJ, Egeland J, Mykletun A, Asbjornsen
A, Landro NI, et al. Impairment across executive functions in
recurrent major depression. Nord J Psychiatry. 2004;58(1):41-47.
27. Beheydt LL, Schrijvers D, Docx L, Bouckaert F, Hulstijn W,
Sabbe B. Psychomotor retardation in elderly untreated depressed
patients. Front Psychiatry. 2014;5:196. http://doi.org/10.3389/
28. Albuquerque MR, Malloy-Diniz LF, Romano-Silva MA, de
Paula JJ, Neves MC, Lage GM. Can eye xation during the
grooved pegboard test distinguish between planning and online
correction? Percept Mot Skills. 2016;124(0):380-392. http://doi.
29. Woodworth RS. The accuracy of voluntary movement. The
Psychological Review: Monograph Supplements, 1899.
30. Poletti C, Sleimen-Malkoun R, Lemaire P, Temprado JJ. Sensori-
motor strategic variations and sequential effects in young and older
adults performing a Fitts’ task. Acta Psychol. Jan 2016;163:1-9.
31. Elliott D, Helsen WF, Chua R. A century later: Woodworth’s
(1899) two-component model of goal-directed aim-
ing. Psychol Bull. May 2001;127(3):342-357. http://doi.
32. Glover S, Wall MB, Smith AT. Distinct cortical networks sup-
port the planning and online control of reaching-to-grasp in
humans. Eur J Neurosci. Mar 2012;35(6):909-915. http://doi.
33. Krigolson OE, Cheng D, Binsted G. The role of visual processing
in motor learning and control: Insights from electroencepha-
lography. Vision Res. May 2015;110(Pt B):277-285. http://doi.
34. Rogers MA, Kasai K, Koji M, Fukuda R, Iwanami A, Nakagome
K, et al. Executive and prefrontal dysfunction in unipolar depres-
sion: a review of neuropsychological and imaging evidence.
Neurosci Res. Sep 2004;50(1):1-11. http://doi.org/10.1016/j.
35. Fernandes LA, Ugrinowitsch H, Oliveira JRV, G. SM, Bicalho
LEA, LAGE GM. Comparison between manual aiming control
and sex in different task constraints. Motriz. (in press).
36. Sacher J, Neumann J, Okon-Singer H, Gotowiec S, Villringer A.
Sexual dimorphism in the human brain: evidence from neuroim-
aging. Magnetic resonance imaging. Apr 2013;31(3):366-375.
37. Oldeld RC. The assessment and analysis of handedness: the
Edinburgh inventory. Neuropsychologia. Mar 1971;9(1):97-113.
38. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A
practical method for grading the cognitive state of patients for
the clinician. J Psychiatr Res. Nov 1975;12(3):189-198. http://
39. Tombaugh TN, McIntyre NJ. The mini-mental state examination:
a comprehensive review. J Am Geriatr Soc. Sep 1992;40(9):922-
935. http://dx.doi.org/10.1111/j.1532-5415.1992.tb01992.x
40. Cunha JA. Manual da versão em português das Escalas Beck. São
Paulo, Casa do Psicólogo, 2001.
41. Beck AT, Steer A, Garbin MG. Psychomotor properties
of the Beck Depression Inventory: Twenty-Five years of
evaluation. Clin Psychol Rev. 1988;8:77-100. http://dx.doi.
42. Farrin L, Hull L, Unwin C, Wykes T, David A. Effects of de-
pressed mood on objective and subjective measures of attention.
J Neuropsychiatry Clin Neurosci. Winter 2003;15(1):98-104.
43. Kliem S, Mossle T, Zenger M, Brahler E. Reliability and valid-
ity of the Beck Depression Inventory-Fast Screen for medical
patients in the general German population. J Affect Disord. Mar
2014;156:236-239. http://doi.org/10.1016/j.jad.2013.11.024
44. Kung S, Alarcon RD, Williams MD, Poppe KA, Jo Moore M,
Frye MA. Comparing the Beck Depression Inventory-II (BDI-II)
and Patient Health Questionnaire (PHQ-9) depression measures
in an integrated mood disorders practice. J Affect Disord. Mar 05
2013;145(3):341-343. http://doi.org/10.1016/j.jad.2012.08.017
45. Bryden PJ, Roy EA. A new method of administering the Grooved
Pegboard Test: performance as a function of handedness and sex.
Brain Cogn. Aug 2005;58(3):258-268. http://doi.org/10.1016/j.
46. Chang CC, Yu SC, McQuoid DR, Messer DF, Taylor WD, Singh
K, et al. Reduction of dorsolateral prefrontal cortex gray matter
in late-life depression. Psychiatry Res. Jul 30 2011;193(1):1-6.
47. Fis k JE, Sharp CA. Age-related impairm ent in executi ve
functioning: updating, inhibition, shifting, and access. J
Clin Exp Neuropsychol. Oct 2004;26(7):874-890. http://doi.
48. Tupler LA, Krishnan KR, McDonald WM, Dombeck CB,
D’Souza S, Steffens DC. Anatomic location and lateral-
ity of MRI signal hyperintensities in late-life depression.
J Psychosom Res. Aug 2002;53(2):665-676. https://doi.
49. Glover S. Separate visual representations in the planning and
control of action. Behav Brain Sci. Feb 2004;27(1):3-24. http://
50. Naismith SL, Norrie LM, Mowszowski L, Hickie IB. The
neurobiology of depression in later-life: clinical, neuropsycho-
logical, neuroimaging and pathophysiological features. Prog
Neurobiol. Jul 2012;98(1):99-143. http://doi.org/10.1016/j.
51. Pier MP, Hulstijn W, Sabbe BG. Differential patterns of psychomo-
tor functioning in unmedicated melancholic and nonmelancholic
depressed patients. J Psychiatr Res. Jul-Aug 2004;38(4):425-435.
52. Gill TM, Williams CS, Richardson ED, Tinetti ME. Impairments
in physical performance and cognitive status as predisposing fac-
tors for functional dependence among nondisabled older persons.
8Motriz, Rio Claro, v.23, n.4, 2017, e1017110
Bicalho L.E.A. & Albuquerque M.R. & de Paula J.J. & Lage G.M.
J Gerontol A Biol Sci Med Sci. Nov 1996;51(6):283-288. http://
53. de Paula JJ, Albuquerque MR, Lage GM, Bicalho MA, Romano-
Silva MA, Malloy-Diniz LF. Impairment of ne motor dex-
terity in mild cognitive impairment and Alzheimers disease
dementia: association with activities of daily living. Revista
brasileira de psiquiatria. Jul-Sep 2016;38(3):235-238. http://doi.
54. Salvador GC, Ugrinowitsch H, Romano-Silva MC, Miranda
DM, Apolinário-Souza T, Lage GM. Transcranial direct current
stimulation and manual asymmetries: The effect of the stimula-
tion on the manual dextery. J. Phys. Educ. 2017;28(1). http://doi.
Corresponding author
Guilherme Menezes Lage
Department of Sports, School of Physical Education, Physiotherapy and Occupa-
tional Therapy, Universidade Federal de Minas Gerais, Av. Presidente Carlos Luz
6627, Pampulha - Belo Horizonte, MG - Brazil.
Email: menezeslage@gmail.com
Manuscript received on August 3, 2017
Manuscript accepted on October 1, 2017
Motriz. The Journal of Physical Education. UNESP. Rio Claro, SP, Brazil
- eISSN: 1980-6574 – under a license Creative Commons - Version 3.0
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AIMS This study aimed to investigate the comparison between sex and manual aiming control in different cognitive and motor constraints of the task. METHODS Eighty-four right-handed participants (42 women) performed 110 trials of a manual aiming task with a non-inking pen on a digitizing tablet. The aiming task required four different conditions of execution. The control condition appeared on the computer screen in 70% of the trials, and the other three conditions, (a) distractor, (b) inhibition of response and (c) higher index of difficulty, each appeared in 10% of the trials. RESULTS Compared with women, men produced shorter movement and response times, as well as higher peak velocity in the control and distractor conditions. When the index of difficulty of the task increased, men produced only higher peak velocity. Women produced more corrective movements to achieve the target only in the control condition. CONCLUSION Our results corroborate those of previous studies that indicate sex-specific response strategies when the sensory motor system is challenged by different task constraints.
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The aim of this study was to evaluate the effect of transcranial direct-current stimulation (tDCS) on the primary motor cortex (M1) in the manual performance asymmetries in a manual dexterity tasks. The sample consisted of 28 volunteers, righthanded, men and without neurological impairment. The task (Grooved Pegboard) consisted of inserting 25 pins in 25 receptacles, as soon as possible. The task was executed in the pretest with both hands to define the level of manual asymmetry. tDCS or Sham were applied a week after the pretest, then the subjects were evaluated in the post-test. The results revealed that the effects of tDCS in M1 did not reduce asymmetries in a manual dexterity task. However, only the tDCS group improved the performance from pretest to the posttest (p <0.05) in both hands. Stimulation of the right M1 may have generated benefits in the contralateral M1.
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The Grooved Pegboard Test can be used to assess motor performance in different contexts. A standard method for this test is well documented in the literature, but the recently revised methodology requires investigation. The aim of this study was to investigate whether the duration of fixation can predict the performance in different task conditions (Place and Remove) with the preferred and non-preferred hands. Fifty-two right-handed undergraduate students (33 male and 19 female), with a mean age of 22.22 (±3.57) years, performed the Grooved Pegboard Test. SMI Eye-Tracking Glasses were used during the task, with a binocular time resolution of 30 Hz. The videos were recorded in iView software, and data were analyzed using BeGaze software. The number of fixation and fixation duration were statistically different when preferred and non-preferred hands were used, as well as in Place task. In addition, simple linear regression using fixation duration was the predictor variable and movement time was the dependent variable in the Place task with the preferred hand (R² = 31%) and the non-preferred hand (R² = 41%), as well as in the Remove task with the preferred hand (R² = 11%) and the non-preferred hand (R² = 25%). Thus, our results show that the duration of fixation differentially predicted the performance in the Grooved Pegboard Test when preferred and non-preferred hands were used, as well as when different subtests were applied.
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Objectives: Executive dysfunction (ED) is a predictor of poor treatment response of late-life depression to pharmacotherapy. In response to the consistency of these findings, we designed neuroplasticity-based computerized cognitive remediation (nCCR-GD) intervention to target and improve ED in patients who failed to remit with antidepressant treatment. This study tests the hypothesis that ED at baseline will predict favorable treatment response to nCCR-GD. Methods: 11 elderly patients with treatment-resistant major depression were treated with a 30-hour, 4-week, unblinded, nCCR-GD treatment trial. Neuropsychological performance was assessed at baseline and after treatment ceased. Results: ED at baseline was associated with greater reduction in Montgomery-Asberg Depression Rating Scale score over the 4-week treatment β = -0.74, F(2,8) = 10.85, p = 0.009, R(2) = 0.55. Conclusions: ED predicts favorable treatment response to nCCR-GD in older adults suffering from major depression resistant to antidepressants. This finding is opposed to studies testing pharmacotherapy where ED predicts poorer treatment response.
Full-text available
Background: Depression often co-occurs in late-life in the context of declining cognitive functions, but it is not clear whether specific depression symptom dimensions are differentially associated with cognitive abilities. Methods: The study sample comprised 3107 community-dwelling older adults from the Longitudinal Aging Study Amsterdam (LASA). We applied a Multiple Indicators Multiple Causes (MIMIC) model to examine the association between cognitive abilities and latent dimensions of the Center for Epidemiologic Studies Depression Scale (CES-D), while accounting for differential item functioning (DIF) due to age, gender and cognitive function levels. Results: A factor structure consisting of somatic symptoms, positive affect, depressed affect, and interpersonal difficulties fitted the data well. Higher levels of inductive reasoning were significantly associated with lower levels of depressed affect and somatic symptoms, whereas faster processing speed was significantly associated with lower levels of somatic symptoms. DIF due to age and gender was found, but the magnitude of the effects was small and did not alter substantive conclusions. Limitations: Due to the cross-sectional context of this investigation, the direction of influence between depression symptom levels and cognitive function levels cannot be established. Furthermore, findings are relevant to non-clinical populations, and they do not clarify whether certain DIF effects may be found only at high or low levels of depression. Conclusions: Our findings suggest differential associations between late-life depression dimensions and cognitive abilities in old age, and point towards potential etiological mechanisms that may underline these associations. These findings carry implications for the prognosis of cognitive outcomes in depressed older adults.
In 1899, R. S. Woodworth published a seminal monograph, "The Accuracy of Voluntary Movement." As well as making a number of important empirical contributions, Woodworth presented a model of speed-accuracy relations in the control of upper limb movements. The model has come to be known as the two-component model because the control of speeded limb movements was hypothesized to entail both a central and a feedback-based component. Woodworth's (1899) ideas about the control of rapid aiming movements are evaluated in the context of current empirical and theoretical contributions.
To date global research on depression has used assessment tools based on research and clinical experience drawn from Western populations (i.e., in North American, European and Australian). There may be features of depression in non-Western populations which are not captured in current diagnostic criteria or measurement tools, as well as criteria for depression that are not relevant in other regions. We investigated this possibility through a systematic review of qualitative studies of depression worldwide. Nine online databases were searched for records that used qualitative methods to study depression. Initial searches were conducted between August 2012 and December 2012; an updated search was repeated in June of 2015 to include relevant literature published between December 30, 2012 and May 30, 2015. No date limits were set for inclusion of articles. A total of 16,130 records were identified and 138 met full inclusion criteria. Included studies were published between 1976 and 2015. These 138 studies represented data on 170 different study populations (some reported on multiple samples) and 77 different nationalities/ethnicities. Variation in results by geographical region, gender, and study context were examined to determine the consistency of descriptions across populations. Fisher's exact tests were used to compare frequencies of features across region, gender and context. Seven of the 15 features with the highest relative frequency form part of the DSM-5 diagnosis of Major Depressive Disorder (MDD). However, many of the other features with relatively high frequencies across the studies are associated features in the DSM, but are not prioritized as diagnostic criteria and therefore not included in standard instruments. Also, the DSM-5 diagnostic criteria of problems with concentration and psychomotor agitation or slowing were infrequently mentioned. This research suggests that the DSM model and standard instruments currently based on the DSM may not adequately reflect the experience of depression at the worldwide or regional levels.
Prior studies have demonstrated dysfunctions within the core neurocognitive networks (the executive control [ECN], default mode [DMN] and salience [SN] networks) in late-life depression (LLD). Whether inter-network dysfunctional connectivity is present in LLD, and if such disruptions are associated with core symptom dimensions is unknown. A cross-sectional resting-state functional connectivity magnetic resonance imaging investigation was conducted of LLD (n = 39) and age- and gender-equated healthy comparison (HC) (n = 29) participants. Dual regression independent component analysis approach was used to identify components that represented the ECN, DMN and SN. The intrinsic inter-network connectivity was compared between LLD and HC participants and the relationship of inter-network connectivity abnormalities with dimensional measures was examined. Relative to HC participants, LLD subjects showed decreased inter-network connectivity between the bilateral ECN and default mode subcortical (thalamus, basal ganglia and ventral striatum) networks, and the left ECN and SN insula component; and increased inter-network connections between the left ECN and posterior DMN and salience (dorsal anterior cingulate) network components. Distinct inter-network connectivity abnormalities correlated with depression and anxiety severity, and executive dysfunction in LLD participants. LLD subjects also showed pronounced intra-network connectivity differences within the ECN, whereas fewer but significant DMN and SN disruptions were also detected. Investigating the intrinsic inter-network functional connectivity could provide a mechanistic framework to better understand the neural basis that underlies core symptom dimensions in LLD. Inter-network connectivity measures have the potential to be neuroimaging biomarkers of symptom dimensions comprising LLD, and may assist in developing symptom-specific treatment algorithms.