Behavioural Neurology

Behavioural Neurology / 2015 / Article
Special Issue

Ageing and Neurodegenerative Disorders

View this Special Issue

Clinical Study | Open Access

Volume 2015 |Article ID 287843 |

Hellen Livia Drumond Marra, Martin Luiz Myczkowski, Cláudia Maia Memória, Débora Arnaut, Philip Leite Ribeiro, Carlos Gustavo Sardinha Mansur, Rodrigo Lancelote Alberto, Bianca Boura Bellini, Adriano Alves Fernandes da Silva, Gabriel Tortella, Daniel Ciampi de Andrade, Manoel Jacobsen Teixeira, Orestes Vicente Forlenza, Marco Antonio Marcolin, "Transcranial Magnetic Stimulation to Address Mild Cognitive Impairment in the Elderly: A Randomized Controlled Study", Behavioural Neurology, vol. 2015, Article ID 287843, 13 pages, 2015.

Transcranial Magnetic Stimulation to Address Mild Cognitive Impairment in the Elderly: A Randomized Controlled Study

Academic Editor: Liana Palermo
Received14 Nov 2014
Revised05 Feb 2015
Accepted01 Apr 2015
Published16 Jun 2015


Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation technique with potential to improve memory. Mild cognitive impairment (MCI), which still lacks a specific therapy, is a clinical syndrome associated with increased risk of dementia. This study aims to assess the effects of high-frequency repetitive TMS (HF rTMS) on everyday memory of the elderly with MCI. We conducted a double-blinded randomized sham-controlled trial using rTMS over the left dorsolateral prefrontal cortex (DLPFC). Thirty-four elderly outpatients meeting Petersen’s MCI criteria were randomly assigned to receive 10 sessions of either active TMS or sham, 10 Hz rTMS at 110% of motor threshold, 2,000 pulses per session. Neuropsychological assessment at baseline, after the last session (10th) and at one-month follow-up, was applied. ANOVA on the primary efficacy measure, the Rivermead Behavioural Memory Test, revealed a significant group-by-time interaction , favoring the active group. The improvement was kept after one month. Other neuropsychological tests were heterogeneous. rTMS at 10 Hz enhanced everyday memory in elderly with MCI after 10 sessions. These findings suggest that rTMS might be effective as a therapy for MCI and probably a tool to delay deterioration.

1. Introduction

Mild cognitive impairment (MCI) is an intermediary status between normal aging and very early dementia [1], wherein individuals have subjective cognitive deficits and objective memory impairment, without affecting their daily activities [2].

MCI is not necessarily a prodrome of Alzheimer’s disease (AD), although evidence suggests that patients with the amnesic subtype (a-MCI) are likely to progress to AD [1, 37]. Episodic memory decline is the most frequent impairment in patients who will progress to AD (MCI due to AD) [8, 9]. Patients with MCI typically show impairment in delayed recall [10]. A combination of multivariate episodic memory tests increases the prediction of AD converters and identifies the profile associated with each MCI subtype [11]. Likewise, everyday memory, which includes episodic memory, is impaired [12]. Difficulties in episodic memory are common in healthy aging [13], and studies revealed that the Rivermead Behavioural Memory Test (RBMT), a brief battery test for everyday memory, is able of differentiate between individuals with MCI, AD, and healthy controls [12, 14].

Even though some older adults perform as well as young adults [15], memory processing declines with senescence, particularly in episodic memory tasks, which involve encoding and retrieval of information. Episodic memory processes is dependent on the integrity of the medial temporal lobe and the interaction with lateral prefrontal cortex (PFC) [13, 16]. The posterior parietal cortex is also involved in this network [3, 4, 17]. Imaging studies have evidenced that neural activity reductions occur primarily in the left PFC and temporooccipital regions during encoding, and right PFC was important for retrieval [1821]. This rationale is clinically consistent with the HERA (hemispheric encoding/retrieval asymmetry) model, which predicts that the younger adults’ left PFC specializes in encoding and the right PFC specializes in retrieval [15, 18, 19, 21]. In normal aging, PFC activation tends to be less asymmetric during memory tasks, as indicated by the HAROLD (hemispheric asymmetry reduction in older adults) model. Cabeza et al. [15] compared PFC activity in younger adults and in low-/high-performing older adults during memory tasks using PET and fMRI. The results suggest that low-performing older adults recruited a similar network as young adults but used it inefficiently, whereas high-performing older adults counteracted age-related neural decline through a plastic reorganization of neurocognitive networks.

Such cognitive deficits, even mild, cause great distress to the elderly with MCI, who feel that their autonomy, independence, and ability to lead high-quality lives are negatively affected. These impairments are often considered the most debilitating aspect of aging [22].

Transcranial magnetic stimulation (TMS) emerges as a therapeutic tool with clinical benefits in neurological and psychiatric diseases. The method is based on generating a rapidly variable magnetic field over the scalp in awake subjects, which induces a transitory electric current in the cortical surface and modulating neuronal function directly underneath the coil, and in connected brain regions [2325]. Repetitive TMS (rTMS) at low frequencies (<1 Hz) reduce cortical excitability, whereas high-frequency rTMS (>1 Hz) facilitates neuronal excitability [26, 27].

Thereby, TMS fulfills an important contribution for studying mechanisms of cognitive function and behavioral plasticity in the human brain [28]. As rTMS can interfere transiently with cortical processing [29], change in behavioral and cognitive performances occurs conversely. Repetitive TMS (rTMS) promote modulation of cortical circuits by inducing changes in synaptic plasticity and reorganization of the cortex, modulating neuronal activity beyond the stimulation period [3032]. The after-effects of repeated sessions may outlast for days and even weeks [4, 33]. Evidence suggests that off-line rTMS might outlast the stimulation period by synaptic LTP and LTD mechanisms [3436], even at brain sites distant from those stimulated [18, 37].

HF rTMS induces upregulation of N-methyl-D-aspartate (NMDA) receptor activity and increases gamma-aminobutyric acid (GABA) mediated inhibition [38, 39]. rTMS might reach other neuronal processes, such as genetic and protein regulation, and circuit-level patterns, such as network oscillations [40] and changes in neural signaling by triggering the activation of neuromodulators, such as acetylcholine, dopamine, norepinephrine, and serotonin [41]. Moreover, rTMS also leads to nonneuronal processes, such as changes in blood flow [40, 42]. Brain derived neurotrophic factor (BDNF) is part of the neural signals for synaptic plasticity [34, 43]. It is, however, unclear by which mechanism rTMS induces lasting effects on the brain. Nevertheless, such effects are often described as LTD- or LTP-like, respectively, long-term depression and potentiation [30].

With regard to TMS and memory studies, Turriziani et al. [18] reported improvement in recognition memory (verbal and nonverbal) performance after online LF rTMS over right DLPFC of healthy and MCI individuals. Manenti et al. [19] studied the effect of online HF rTMS (20 Hz, 90% MT) during encoding or retrieval of associated and nonassociated word pairs. A predominance of left DLPFC over right DLPFC was observed in the low-performing elderly. The same research group [44] conducted a trial with young subjects, using online HF rTMS (10 Hz, 90% MT) during retrieval phase of a face-naming task (episodic memory retrieval). The results suggest a recruitment of left DLPFC during retrieval without using retrieval strategies, whereas there is a shift to the right DLPFC if retrieval strategies were needed. Solé-Padullés et al. [45] combined functional magnetic resonance imaging (MRI) and off-line HF rTMS (5 Hz, 80% MT) of the left and right DLPFC before memory tasks, improving learning of face-name associations in the elderly with memory dysfunction, with increased metabolic activation of the right DLPFC. However, an angled active coil was used in the sham condition [46, 47], and a double-cone coil was used. Rossi et al. [48] compared the effect of online HF rTMS to the right and left DLPFC (20 Hz, 90% MT) on visuospatial recognition memory of subjects <45 and >50 years old. They reported a greater interference of rTMS to the right DLPFC compared to to the left DLPFC, in younger subjects. This asymmetry is progressively vanished as the age increases. The bilateral interference effects found in the older group corroborates this reasoning and HAROLD model, which the neural retrieval correlates modify along aging as a compensatory functioning of the DLPFC in elders for episodic memory performance.

A recent article [34] reviewed studies on TMS as diagnostic and as therapeutic tool in patients with MCI and AD, suggesting that rTMS can improve or restore several impaired cognitive functions in AD and MCI.

Manenti et al. [49] conducted a systematic review on studies of TMS and episodic memory addressing young and elderly adults and subjects with memory dysfunction. They report that, despite numerous studies on the role of the DLPFC in episodic memory, there are many studies also demonstrating the involvement of a more distributed neural network, sustaining this function involving the temporal lobes and parietal cortices. For example, Cotelli et al. [3], in a single-case report, applied sessions of HF rTMS (20 Hz, 100% MT) to the left parietal cortex of one male patient with a-MCI, in 10 consecutive days. The observed improvement on association memory tasks persisted significantly for 24 weeks after stimulation.

Finally, [50] conducted a systematic review on cognitive effects of HF rTMS studies and its potential long-term effects. The authors included only off-line rTMS studies using more than a single rTMS session. Baseline subjects diagnoses addressed young and older subjects, clinical (neurologic/psychiatric) or not. They verified that HF rTMS (10–20 Hz) is most likely to cause significant cognitive improvement when applied over the left DLPFC, within a range of 10–15 successive sessions and an individual 80–110% MT.

In the present study, we used several neuropsychological measures, including a very sensitive measure of everyday memory (RBMT). We firstly aimed to investigate whether HF rTMS over the left DLPFC improve everyday memory of elderly patients with MCI and, secondly, to evaluate the effects of rTMS in executive functions. We have chosen the left DLPFC as the target area based on previous rTMS and functional neuroimaging studies of memory in healthy and in MCI patients. To date, there has been no randomized controlled double-blind study in this population.

2. Materials and Methods

2.1. Inclusion Criteria

Thirty-four elderly subjects, both sexes, age ranging between 60 and 74 years, with education level ≥ 4 years, meeting clinical/neuropsychological criteria for MCI for at least one year, were recruited from the community, through media advertisements, between October 2010 and June 2011.

The study protocol was approved by the Local Ethics Committee and all subjects signed informed-consent forms before enrolling in the trial and registering at NCT01292382.

2.1.1. Screening Tests: Part I

In the first step of the screening (part I), we used the Montreal Cognitive Assessment test (MoCA test) [51], the Clinical Dementia Rating (CDR) Scale [28], the 15-item Geriatric Dementia Scale (GDS-15) [52], the 17-item Hamilton Depression (HAMD-17) Scale [53], and the14-item Hamilton Anxiety (HAMA-14) Scale [54]. GDS-15 is a diagnostic assessment and evaluates depressive symptoms in the elderly. The HAMD-17 scale is not a diagnostic instrument but quantifies the severity of depression, comprising somatic and psychological parameters, and allows a follow-up of the patient. We use the two scales for screening due to their different approaches of the depressive disorder, often underestimated in a geriatric clinical evaluation. The respective cut-off points for the tests and scales are in Table 1.

Screening batteryCut-off scores

MoCA Test1≤24

MoCA test: Montreal Cognitive Assessment test; 2CDR: Clinical Dementia Rating; 3GDS-15: 15-Item Geriatric Dementia Scale; 4HAMD-17: 17-Item Hamilton Depression Scale; 5HAMA-14: 14-Item Hamilton Anxiety Scale.

2.1.2. Screening Tests: Part II

The second step of the screening (part II) included lab tests, cerebral MRI scan, and neuropsychological evaluation.

(1) Lab Tests. Lab tests were performed for clinical screening in order to detect and exclude clinical secondary causes of dementia or cognitive deficits, such as hypothyroidism, SIDA, vitamin B12 and folate deficiency, excessive alcohol consumption, syphilis, and risk factors for cardiovascular disease, such as atherosclerosis and diabetes. The results were required to be normal: complete blood count (CBC), thyroid-stimulating hormone (TSH), T3, T4, folic acid, vitamin B12, albumin, total cholesterol, HDL/LDL, triglycerides, alanine transaminase (ALT), aspartate transaminase (AST), gamma-glutamyl transferase (GGT), sodium, potassium, urea, creatinine, fasting glucose, VDRL, and ELISA anti-HIV test.

(2) Brain MRI Scan. All the patients were examined through brain MRI scans, analyzed by two experts MD. MRI based exclusion criteria were evidence of focal or lacunar ischemia, expansive brain tumors, and hydrocephalus. Changes related to normal aging, such as foci of rare nonspecific gliosis, were accepted. All participants had ischemic score Hachinski <7 (original) and <5 (modified by Loeb).

(3) Neuropsychological Examination. Next, a neuropsychological and functional activity battery was applied as inclusion and outcome criteria: IQCODE, Informant Questionnaire on Cognitive Decline in the Elderly [55]; B-ADL, Bayer Activities of Daily Living Scale [56].

Memory Tests. (1) MMSE, Minimental State Examination [57], an effective 11-question test used as a screening instrument to separate patients with cognitive impairment from those without it and (2) RBMT, the Rivermead Behavioural Memory Test [58], a brief test battery to assess everyday memory, with high level of ecological validity and good correlation with traditional episodic memory, were carried out [59, 60]. The RBMT consists of 12 subtests each of which addresses an important aspect of everyday memory function, mimicking daily life situations, recalling the first and last names; immediate and delayed recalling of a route, of a short story, and of a message (remembering to pick up an envelope and place it in a specific place); remembering to retrieve a personal belonging at the end of the examination and to ask for an appointment when an alarm sounds; immediate and delayed recalling of photographs of people, and nine questions about time and spatial orientation. (3) Logical memory (LM) I and II subtests of Wechsler Memory Scale [61], to measure encoding, retrieval, and logical memory ability were carried out. In LM I subtest, two short stories are presented and the examinee is asked to retell each one from memory immediately after hearing it. On the other hand, in LM II the delayed condition assesses long-term narrative memory with free recall and recognition tasks; (4) RAVLT, Rey Auditory-Verbal Learning Test [6264], to evaluate short-term auditory-verbal memory, rate of learning, learning, and retrieval was carried out. Subjects repeat lists of 15 unrelated words over five different trials and then again after 30 minutes. From Wechsler Adult Intelligence Scale III [65], we applied two working memory subtests [66]: (1) letter-number sequencing test, where the participant is presented with a series of numbers and letters in random order and is instructed to repeat back letters and numbers combinations, first numbers in ascending order and then letters in alphabetical order [66] and (2) digit span, where the examinee repeats in direct and reverse order two series of three and two digits, respectively, read by the examiner. Executive function tests (frontal lobe tasks) were carried out. (1) Trail Making Test (TMT) A/B [6770], to evaluate psychomotor speed, focus, visual search, mental flexibility, and sequencing, was carried out. In TMT-A, participants are asked to draw lines sequentially connecting 25 encircled numbers; task requirements are similar for TMT-B except for the fact that the person must differentiate between numbers and letters. The score represents the amount of time required, in seconds, to complete each task. (2) Verbal fluency tests, FAS and animal naming [71], to assess, respectively, the measure of total number of words generated in one minute for the letters F, A, and S (phonemic fluency) and of animal names (semantic fluency) were carried out; (3) Victoria Stroop Test [72] involves three trials. Three cards are presented in the same sequence and the examinee is instructed to read or call out the color name as quickly as possible. First, in the “word trial,” the subject reads words of color names (e.g., red and blue) printed in black ink; secondly, in the “color trial,” they identify colors (e.g., rectangles printed in red or blue). Finally, in the “color-word” response inhibition trial, they must name the color in which a word is presented, while ignoring the printed word.

All the scores were adjusted according to age, gender, and education level, and the tests were administered in accordance with the standard procedures.

2.2. Exclusion Criteria

The exclusion criteria are listed as follows: psychiatric disorders (except remitted depression ≥ 12 months) and alcohol and/or drug abuse, according to SCID-P [73], neurological conditions, severe uncontrolled organic disease, use of pacemaker, history of seizures, history of major head trauma, history of neurosurgery, and cerebral metallic artifacts.

2.3. TMS Procedures

Participants were randomly assigned in a double-blind condition to receive either active or sham rTMS. Randomization was performed through a random number generator ( by a third-party investigator. Patients and rater were blinded to patients’ treatment.

We used a high-speed magnetic stimulator (MagPro X100, MagVenture A/S, Farum, Denmark) with a figure-of-eight coil.

We used for the sham group a placebo coil, with a mechanical outline and sound level (click) identical to the active one. The placebo coil’s magnetic shield provides a field reduction of approximately 90% [46, 74]. The motor threshold (MT) for each patient was determined by contraction of the right abductor of pollicis brevis muscle of the thumb, following the method described by Wassermann et al. [75].

rTMS was applied over the left DLPFC at the point located approximately 5 cm in a parasagittal plane parallel to the point of maximum stimulation of the short abductor of the thumb, with the lowest possible intensity in five of ten stimuli.

Subjects assigned to the active group received 10 Hz rTMS at 110% of MT, each train lasting 5 seconds, with 25-second intervals (2,000 pulses/day) for 10 consecutive weekdays. The sham group received the same protocol using a placebo coil.

At the end of the study period, after blinding was removed, the sham patients were given the option of receiving active rTMS treatment.

Security and side effects scales were assessed through a questionnaire as well as clinical evaluation, based on the most frequent adverse effects of TMS by The Safety of TMS Consensus Group [33].

2.4. Blind Condition

Patients and team raters were blinded to the assignment condition; however, for technical reasons, the clinicians who administered the rTMS were not. The rater was an experienced neuropsychologist, blinded to the treatment status and with no contact with the treatment team.

After completing the sessions, patients were asked what treatment they thought they received and why.

A lab researcher (C. G. M.) generated and concealed the random allocation sequence, and a secretary (S. L. F.) enrolled and assigned participants to interventions. The effectiveness of the blinding was assessed after the follow-up period.

2.5. Efficacy Variables

The primary outcome variable was the RBMT, for assessing everyday memory.

The secondary efficacy outcome variables were other neuropsychological domains assessments.

2.6. Statistical Analysis

Statistical analysis was performed by the SPSS v. 14 (Statistical Package for the Social Sciences, Chicago, IL, 2005). The Kolmogorov-Smirnov test was conducted to assess whether continuous variables followed a normal distribution. Statistical significance for all analyses was set to .

Descriptive statistical analysis was performed for demographics: contingency tables for categorical variables (gender, comorbidity, marital status, and education level) and descriptive measures (mean and standard deviation) for continuous variables (age). The Fisher’s exact test was used to verify the association of categorical variables. A Student’s -test was used to compare the mean of continuous normally distributed variables of both groups; the Mann-Whitney-Wilcoxon test was used when the variables did not follow a normal distribution. Two-way analysis of variance (ANOVA) for repeated measures compared group and time effect, as compared to the normal distribution of the data or residues. The blind control was evaluated by Cohen’s kappa coefficient of agreement to assess patients’ views of whether or not they belonged to a given group.

2.7. Flow Chart

Table 2 shows the overall structure of this study.

(T-2) = screening part I
     Clinical and demographic data
     MoCA test1, CDR2, and GDS-153
     HAMD-174 and HAMA-145
     Signed informed-consent forms

(T-1) = screening part II
   IQCODE6 and B-ADL7
   Lab blood sample analysis
   Brain MRI/Hachinsky Ischemic Score

(T0) = 1st cognitive assessment battery (baseline)
   1st rTMS session
   Collateral effects scale

(T1) = 10th rTMS session
  2nd cognitive assessment batery
  Collateral effects scale

(T2) = one month after T1
       3rd cognitive assessment battery
       IQCODE and B-ADL

MoCA test: Montreal Cognitive Assessment test; 2CDR: Clinical Dementia Rating; 3GDS-15: 15-Item Geriatric Dementia Scale; 4HAMD-17: 17-Item Hamilton Depression Scale; 5HAMA-14: 14-item Hamilton Anxiety Scale; 6IQCODE: Informant Questionnaire on Cognitive Decline in the Elderly; 7B-ADL: Bayer Activities of Daily Living Scale; 8SCID-DSM-IV: Structured Clinical Interview for DSM-IV Axis I Disorders-Diagnostic and Statistical Manual of Mental Disorders, fourth edition. Cognitive assessment battery: MMSE: Minimental State Examination; RBMT: Rivermead Behavioral Memory Test; WMS: Wechsler Memory Scale; WAIS: Wechsler Adult Intelligence Scale; RAVLT: Rey Auditory-Verbal Learning Test; Stroop: Stroop Color-Word Interference Test; Trail Making Test A/B.

3. Results

3.1. Subjects

Out of 109 screened subjects, 73 did not fulfill the enrollment criteria. Among the 36 subjects left, 17 were randomly assigned to the active group and 19 to the sham group. In the active group, two drop-out subjects, after the first session, were excluded due to inability to follow the protocol. Therefore, 34 subjects entered the treatment phase (Figure 1). Among them, 31 were classified as a-MCI and three as nonamnesic-MCI (two in the sham group and one in the active group).

Causes of exclusion are listed in Table 3.


MoCA1 > 2679.59%
Education level <4 years22.74%
Depressive symptoms (GDS-152 > 5)2534.25%
Effective bipolar disorder (SCID-DSM IV3)79.59%
Chronic benzodiazepine use11.37%
Sleep disorders45.48%
History of traumatic brain injury22.74%
Cerebral MRI4 disorders1520.55%
 Normal pressure hydrocephalus22.74%
 Lacunar infarct/ischemic stroke810.96%
 Frontoparietal meningioma11.37%
 Cerebellar cyst11.37%
 Frontal granuloma11.37%
 Hemorrhagic lesion11.37%
 Frontal lobe atrophy11.37%
Mild AD534.11%
Parkinson disease34.11%
Frontotemporal dementia11.37%

MoCA: Montreal Cognitive Assessment; 2GDS-15: 15-items Geriatric Depression Scale; 3SCID: Structured Clinical Interview for Axis I Disorders-Diagnostic and Statistical Manual of Mental Disorders, fourth edition; 4MRI: magnetic resonance imaging; 5AD: Alzheimer’s disease.

In the first step of the screening phase, no statistically significant difference was observed among the selected subjects (Table 4). There were no diagnostic cases of late life depression, nor present depression, excluded by various validated tests in preliminary evaluation, such as GDS, HAMD-17, and SCID DSM-IV.

Test/scaleActive rTMS
n = 15
(mean ± SD)
n = 19
(mean ± SD)

MoCA124.5 ± 1.824.2 ± 2.30.605
GDS-1521.7 ± 1.71.4 ± 1.30.559
HAMD-1731.7 ± 2.11.5 ± 2.10.781
HAMA-1441.7 ± 1.11.4 ± 1.50.532

SD: standard deviation; Student’s t-test. 1MoCA: Montreal Cognitive Assessment; 2GDS-15: 15-item Geriatric Depression Scale; 3HAMD–17, 17-item Hamilton Depression Scale; 4HAMA–14, 14-item Hamilton Anxiety Scale.

Clinical and demographic characteristics were also similar in both groups, as seen in Table 5. At baseline, groups were homogeneous in terms of neuropsychological examination, except for digit span ().

Features Active rTMS
(n = 15)
(n = 19)

Age, years (mean ± SD)65.1 ± 3.565.2 ± 4.10.9541
Gender, n (%)0.7242
 Male6 (40.0)6 (31.6)
 Female9 (60.0)13 (68.4)
Education level, years
(mean ± SD)
15.1 ± 4.412.4 ± 4.70.0941
Marital status, n (%)0.9092
 Married8 (53.3)8 (42.1)
 Single2 (13.3)4 (21.1)
 Widow3 (20.0)4 (21.1)
 Divorced2 (13.3)3 (15.8)
 Living alone, n (%)1 (67)7 (36.8)
 Living with family, n (%)14 (93.3)12 (63.2)
Professional activities, n (%)0.2882
 Not retired7 (46.7)5 (26.3)
 Retired8 (53.3)14 (73.7)
Physical activity, n (%)
(≥twice a week, ≥1 year)
9 (60.0)12 (63.2)>0.9992
Comorbidities, n (%)
 Hypertension9 (60.0)5 (26.3)0.0802
 Diabetes mellitus2 (10.5)2 (13.3)>0.9992
 Dyslipidemia9 (60.0)9 (47.4)0.5102
 Thyroid disease7 (46.7)4 (21.1)0.1512
 Osteoporosis3 (20.0)5 (26.3)>0.9992
 Tobacco consumption1 (6.7)1 (5.3)>0.9992
 Neoplasia1 (6.7)2 (1.5)>0.9992

SD: standard deviation; 1Student’s t-test; 2Fisher’s test.
3.2. Blind Integrity

An assessment of the effectiveness of the blinding revealed that most patients did not guess correctly, when asked to which group they believed they were assigned. The Kappa coefficient was equal to 0.190, which indicates a low correlation and blind integrity.

3.3. Tolerability and Safety

rTMS at 10 Hz with 110% of the MT was safe and well tolerated. A zero value presented in almost all cells of the side effects precludes any statistical analysis beyond a descriptive one. Side effects were mild and transient prevailing in the active group. However, a gradual reduction in side effects was observed throughout the sessions (see Table 6).

# Sessions1510
Side effectsGroup (%) (%) (%)

HeadacheActive rTMS5 (33.3)4 (26.7)1 (5.3)
Sham5 (33.3)0 (0)0 (0)

Cervical painActive rTMS0 (0)0 (0)0 (0)
Sham1 (5.3)0 (0)0 (0)

Scalp pain Active rTMS5 (33.3)2 (13.3)2 (13.3)
Sham1 (5.3)1 (5.3)0 (0)

Burning scalp Active rTMS0 (0)0 (0)0 (0)
Sham1 (5.3)0 (0)0 (0)

Concentration difficulties Active rTMS0 (0)0 (0)0 (0)
Sham0 (0)0 (0)0 (0)

Symptoms related to rTMS application; side effects after the 1st, 5th, and 10th rTMS sessions, respectively.
3.4. Outcome Variables

Four neuropsychological tests showed heterogeneous statistical improvement along time (Table 7).

MeanSDMeanSDMeanSDT0 × T1T1 × T2T0 × T2

RBMTActive rTMS20.872.1022.601.6822.871.36
Group effect0.0420.5930.029

Logical memory II (delayed)Active rTMS21.876.4021.676.7925.476.56
Group effect0.0330.8210.002

Letter-number sequencing testActive rTMS10.202.089.801.7410.872.36
Group effect0.1300.0390.489

Trail making test BActive rTMS99.1329.26107.1347.8795.4031.58
Group effect0.0360.0230.988

Verbal fluency/animal namingActive rTMS18.474.4918.005.6618.805.65
Group effect0.0950.6130.029

Analysis performed with two-way ANOVA for repeated measures (p > 0.05); statistically significant group effect; SD: standard deviation; timing of procedures: T0: baseline cognitive assessment before 1st rTMS; T1: 2nd cognitive assessment (after 10th rTMS session); T2: 3rd cognitive assessment (30 days after T1).

The primary outcome variable RBMT was statistically higher in the active group after the 10th session and after one-month follow-up (Figure 2).

Although final scores of the logical memory II were similar, initial values for the sham group indicate a significance favoring them (Figure 3).

Figure 4 shows initial improvement in letter-number sequencing test for the sham group (T0-T1). Nevertheless, the gain for the active group at T2 did not show a significant difference at the end of follow-up (T2).

In TMT-B, an initial improvement in the sham group was showed as well as, conversely, a later improvement in the active rTMS group (T1-T2). No definitive effect was shown in either group from basal to last evaluation (Figure 5).

Transient improvement was observed in the sham group in verbal fluency/animal naming, at T2. However, the final scores were similar in both groups and quite heterogeneous in T0 (Figure 6).

4. Discussion

We report improvement in everyday memory after 10 sessions of HF rTMS, in a double-blind, randomized sham-controlled study. The duration of the improvement persisted at least for 30 days after the last rTMS session, assessed by the RBMT. This is the first randomized, controlled, double-blind study on early and late after-effects of rTMS on everyday memory of the elderly with MCI. This result suggests a sustained gain in episodic memory. The RBMT aids to identify compensatory strategies and to design specific neuropsychological rehabilitation programs. As the tasks mimic daily life situations, RMBT analyses individuals’ tasks performances and how memory impairment affects everyday activities [76].

Nevertheless, others memory tests, logical memory (LM) II and letter-number sequencing (LNS) exhibited different outcomes. Sham group improvement in LM II is probably due a tendency to different baseline scores between both groups. A gain in the score of the active group in T2 is noted and can suggest a lag practice effect compared to that which may occur in sham group. In LNS test, we have an improvement of sham group at T1 and impairment at T2. Conversely, active group performance suggested a temporary deterioration soon after rTMS protocol (T1), followed by lag amelioration at T2.

Concerning the two frontal tasks, TMT-B and the verbal fluency test animal naming, the results showed some discrepancies. In TMT-B, there was an initial impairment in the active TMS group, followed by a great improvement after a month. Conversely, in animal naming test, the sham group had a gain and then impairment at the last evaluation, but the improvement of sham group may be due a tendency to statistical difference between baseline scores, which should require a larger sample to better define the result.

Anyway, this raises the possibility that the rTMS could have, at least in a short term, some negative effect on some performances. Even if most of the TMS findings show considerable variability, genetic factors can be argued. The presence of BDNF-Val66Met polymorphism could influence the protein synthesis, affecting cortical reactivity with decreased experience-dependent plasticity induced by rTMS. Thereby, this genetic variation in the normal population can produce significant differences in the after-effects of rTMS protocols [34, 43]. Koch et al. investigated the correlation between motor cortical plasticity (with TMS) and the levels of Ab, total tau (t-Tau), and phosphorylated tau detected in cerebrospinal fluid (CSF) of patients with AD. They identified that higher CSF t-Tau levels were associated with a stronger inhibition of the MEPs, suggesting that also CSF t-Tau modulates excitatory activity and may alter mechanisms of cortical plasticity. In one study of HF rTMS to bilateral PFC of patients with depression, Loo et al. [77] found an individual temporary deterioration in executive function/planning in the HF rTMS; two years later, the same group manifested a selective deterioration in the retention of verbal material [78].

One of the strengths of our study is its ecological validity. The patients recruited actively sought healthcare for memory disturbance in the community, through the media (radio and newspapers) and ads in the subway and buses, even by referral of fellow physicians or participants themselves.

Some peculiarities about rTMS efficacy in elderly populations are consistent with our data. It is well described that there is a better response to higher frequencies and intensity pulses rTMS, which should be explained by the greater prefrontal atrophy in the elderly. Due to cerebral atrophy, the distance from the skull to the PFC increases with age in greater proportion than the motor cortex [34, 7982]. So, also, longer treatment protocols may be more effective [42, 83]. Moreover, patients tend to reach a greater improvement than healthy participants [50].

The duration of off-line rTMS after-effects in cognitive performance seems to indicate that longer trains induce longer-lasting and more robust effects, and rTMS parameters used in this study were consistent with those recommended on the induction of long-term cognitive effects (off-line paradigm) after more than one session of HF rTMS [30, 84].

Besides distant activations via neural pathways projections from the target of stimulation, the length of action of rTMS also depends on the rTMS “dose,” that is, the intensity of stimulation [37], which is directly related to the interindividual resting motor threshold.

Specific particularities influencing the interpretation of the results should be considered. First, due to the presence of a continuum of memory impairment from normal aging to MCI [85], the problem of high heterogeneity within our sample might be an important issue. Second, the “5 cm rule,” presents many limitations [8688]. Third, we did not use different versions of RBMT, possibly introducing a bias although the practice effect is also present in all neuropsychological batteries. Finally, a selection bias may have occurred, due a diagnostic revision in a consensus meeting with the neuropsychology team. The initial goal was a sample of patients with a-MCI, that is, MCI subtype which is most susceptible to conversion to AD [1]. However, to keep the randomization, we maintained the three patients (9%) with nonamnesic MCI.

Interventional therapies studies for improving cognitive skills are of paramount importance and are likely to have a great impact on public health. The growing proportion of older people and the length of life increase through the world rapidly. Such issue requires the development of interventions to improve well-being, social engagement, and independence for ageing people [89].

There is a great interest in neuromodulation by rTMS due the persistence of after-effects induced by LTP mechanism [27, 30, 34, 37, 9092]. LTP is an increase in the synaptic strength that could last for days or even weeks and months. Once induced and expressed, LTP is divided in two forms: early-LTP (E-LTP) and late-LTP (L- LTP). E-LTP is an increase in synaptic strength that persists for 30–60 minutes after induction, depending on modifications of existing proteins, for example, protein phosphorylation. L-LTP could last for hours, days, or even weeks and includes other mechanisms like changes in gene expression and the synthesis of proteins [30]. The duration of rTMS after-effect is proportional to the length of stimulation [84].

Most studies on healthy aging are focused on prevention. rTMS can be viewed as a tool for cognitive enhancement of the elderly with MCI, reversing or compensating cognitive deficits [4, 93] and improving quality of life. rTMS may interact synergistically with cognitive training to lead to even greater neurocognitive enhancement [9395]. The elderly might benefit from cognitive rehabilitation with rTMS as an add-on instrument in cognitive training programs of a variety of neurological and cognitive disorders [96].

5. Conclusion

In conclusion, this study suggests that 10 consecutive sessions or HF rTMS to the left DLPFC at 10 Hz in the elderly with MCI selectively improve everyday memory. The improvement was sustained for at least a month. rTMS may be a promising useful tool for interventional single (or combined) therapy for individuals with MCI or with memory decline. Further research is necessary to replicate these findings with larger sample size and also to investigate rTMS combined with other cognitive training therapies.

Conflict of Interests

All authors reported no financial conflict of interests.


The authors thank Mrs. Julia Tizue Fukushima for precious paper suggestions, Mr. Bernardo dos Santos for statistical analysis, and Mrs. Sandra de Lima Falcon for the carefully working on recruitment of volunteers.


  1. R. C. Petersen and S. Negash, “Mild cognitive impairment: an overview,” CNS Spectrums, vol. 13, no. 1, pp. 45–53, 2008. View at: Google Scholar
  2. R. C. Petersen, G. E. Smith, S. C. Waring, R. J. Ivnik, E. G. Tangalos, and E. Kokmen, “Mild cognitive impairment: clinical characterization and outcome,” Archives of Neurology, vol. 56, no. 3, pp. 303–308, 1999. View at: Publisher Site | Google Scholar
  3. M. Cotelli, M. Calabria, R. Manenti et al., “Brain stimulation improves associative memory in an individual with amnestic mild cognitive impairment,” Neurocase, vol. 18, no. 3, pp. 217–223, 2012. View at: Publisher Site | Google Scholar
  4. M. Cotelli, R. Manenti, O. Zanetti, and C. Miniussi, “Non-pharmacological intervention for memory decline,” Frontiers in Human Neuroscience, vol. 6, article 46, 2012. View at: Publisher Site | Google Scholar
  5. M. Irish, B. A. Lawlor, R. F. Coen, and S. M. O'Mara, “Everyday episodic memory in amnestic mild cognitive impairment: a preliminary investigation,” BMC Neuroscience, vol. 12, article 80, 2011. View at: Publisher Site | Google Scholar
  6. B. J. Kelley and R. C. Petersen, “Alzheimer’s disease and mild cognitive impairment,” Neurologic Clinics, vol. 25, no. 3, pp. 577–609, 2007. View at: Publisher Site | Google Scholar
  7. G. A. Jicha, J. E. Parisi, D. W. Dickson et al., “Neuropathologic outcome of mild cognitive impairment following progression to clinical dementia,” Archives of Neurology, vol. 63, no. 5, pp. 674–681, 2006. View at: Publisher Site | Google Scholar
  8. R. A. Sperling, P. S. Aisen, L. A. Beckett et al., “Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease,” Alzheimer's and Dementia, vol. 7, no. 3, pp. 280–292, 2011. View at: Publisher Site | Google Scholar
  9. M. J. Summers and N. L. J. Saunders, “Neuropsychological measures predict decline to alzheimer's dementia from mild cognitive impairment,” Neuropsychology, vol. 26, no. 4, pp. 498–508, 2012. View at: Publisher Site | Google Scholar
  10. G. W. Small, S. Y. Bookheimer, P. M. Thompson et al., “Current and future uses of neuroimaging for cognitively impaired patients,” The Lancet Neurology, vol. 7, no. 2, pp. 161–172, 2008. View at: Publisher Site | Google Scholar
  11. R. M. Chapman, M. Mapstone, J. W. McCrary et al., “Predicting conversion from mild cognitive impairment to Alzheimer's disease using neuropsychological tests and multivariate methods,” Journal of Clinical and Experimental Neuropsychology, vol. 33, no. 2, pp. 187–199, 2011. View at: Publisher Site | Google Scholar
  12. H. Kazui, A. Matsuda, N. Hirono et al., “Everyday memory impairment of patients with mild cognitive impairment,” Dementia and Geriatric Cognitive Disorders, vol. 19, no. 5-6, pp. 331–337, 2005. View at: Publisher Site | Google Scholar
  13. M. Sandrini, M. Brambilla, R. Manenti, S. Rosini, L. G. Cohen, and M. Cotelli, “Noninvasive stimulation of prefrontal cortex strengthens existing episodic memories and reduces forgetting in the elderly,” Frontiers in Aging Neuroscience, vol. 6, article 289, 2014. View at: Publisher Site | Google Scholar
  14. M. S. Yassuda, M. K. Flaks, L. F. Viola et al., “Psychometric characteristics of the Rivermead Behavioural Memory Test (RBMT) as an early detection instrument for dementia and mild cognitive impairment in Brazil,” International Psychogeriatrics, vol. 22, no. 6, pp. 1003–1011, 2010. View at: Publisher Site | Google Scholar
  15. R. Cabeza, N. D. Anderson, J. K. Locantore, and A. R. McIntosh, “Aging gracefully: compensatory brain activity in high-performing older adults,” NeuroImage, vol. 17, no. 3, pp. 1394–1402, 2002. View at: Publisher Site | Google Scholar
  16. J. S. Simons and H. J. Spiers, “Prefrontal and medial temporal lobe interactions in long-term memory,” Nature Reviews Neuroscience, vol. 4, no. 8, pp. 637–648, 2003. View at: Publisher Site | Google Scholar
  17. R. Cabeza, E. Ciaramelli, I. R. Olson, and M. Moscovitch, “The parietal cortex and episodic memory: an attentional account,” Nature Reviews Neuroscience, vol. 9, no. 8, pp. 613–625, 2008. View at: Publisher Site | Google Scholar
  18. P. Turriziani, D. Smirni, G. Zappalà, G. R. Mangano, M. Oliveri, and L. Cipolotti, “Enhancing memory performance with rTMS in healthy subjects and individuals with Mild Cognitive Impairment: the role of the right dorsolateral prefrontal cortex,” Frontiers in Human Neuroscience, vol. 6, article 62, 2012. View at: Publisher Site | Google Scholar
  19. R. Manenti, M. Cotelli, and C. Miniussi, “Successful physiological aging and episodic memory: a brain stimulation study,” Behavioural Brain Research, vol. 216, no. 1, pp. 153–158, 2011. View at: Publisher Site | Google Scholar
  20. R. Cabeza, C. L. Grady, L. Nyberg et al., “Age-related differences in neural activity during memory encoding and retrieval: a positron emission tomography study,” Journal of Neuroscience, vol. 17, no. 1, pp. 391–400, 1997. View at: Google Scholar
  21. E. Tulving, S. Kapur, F. I. M. Craik, M. Moscovitch, and S. Houle, “Hemispheric encoding/retrieval asymmetry in episodic memory: positron emission tomography findings,” Proceedings of the National Academy of Sciences of the United States of America, vol. 91, no. 6, pp. 2016–2020, 1994. View at: Publisher Site | Google Scholar
  22. B. Voytek and A. Gazzaley, “Stimulating the aging brain,” Annals of Neurology, vol. 73, no. 1, pp. 1–3, 2013. View at: Publisher Site | Google Scholar
  23. M. S. George, F. Padberg, T. E. Schlaepfer et al., “Controversy: repetitive transcranial magnetic stimulation or transcranial direct current stimulation shows efficacy in treating psychiatric diseases (depression, mania, schizophrenia, obsessive-complusive disorder, panic, posttraumatic stress disorder),” Brain Stimulation, vol. 2, no. 1, pp. 14–21, 2009. View at: Publisher Site | Google Scholar
  24. E. M. Wassermann, C. Epstein, U. Ziemann, V. Walsh, T. Paus, and S. Lisanby, Handbook of Tanscranial Stimulation, Oxford University Press, Oxford, UK, 2008.
  25. M. Jahanshahi and J. Rothwell, “Transcranial magnetic stimulation studies of cognition: an emerging field,” Experimental Brain Research, vol. 131, no. 1, pp. 1–9, 2000. View at: Publisher Site | Google Scholar
  26. A. Pascual-Leone, J. Valls-Solé, E. M. Wassermann, and M. Hallett, “Responses to rapid-rate transcranial magnetic stimulation of the human motor cortex,” Brain, vol. 117, no. 4, pp. 847–858, 1994. View at: Publisher Site | Google Scholar
  27. F. Maeda, J. P. Keenan, J. M. Tormos, H. Topka, and A. Pascual-Leone, “Modulation of corticospinal excitability by repetitive transcranial magnetic stimulation,” Clinical Neurophysiology, vol. 111, no. 5, pp. 800–805, 2000. View at: Publisher Site | Google Scholar
  28. J. C. Morris, “The Clinical Dementia Rating (CDR): current version and scoring rules,” Neurology, vol. 43, no. 11, pp. 2412–2414, 1993. View at: Google Scholar
  29. H. R. Siebner, G. Hartwigsen, T. Kassuba, and J. C. Rothwell, “How does transcranial magnetic stimulation modify neuronal activity in the brain? Implications for studies of cognition,” Cortex, vol. 45, no. 9, pp. 1035–1042, 2009. View at: Publisher Site | Google Scholar
  30. J. M. Hoogendam, G. M. J. Ramakers, and V. Di Lazzaro, “Physiology of repetitive transcranial magnetic stimulation of the human brain,” Brain Stimulation, vol. 3, no. 2, pp. 95–118, 2010. View at: Publisher Site | Google Scholar
  31. H. R. Siebner and J. Rothwell, “Transcranial magnetic stimulation: new insights into representational cortical plasticity,” Experimental Brain Research, vol. 148, no. 1, pp. 1–16, 2003. View at: Publisher Site | Google Scholar
  32. B. Luber, S. M. McClintock, and S. H. Lisanby, “Applications of transcranial magnetic stimulation and magnetic seizure therapy in the study and treatment of disorders related to cerebral aging,” Dialogues in Clinical Neuroscience, vol. 15, no. 1, pp. 87–98, 2013. View at: Google Scholar
  33. S. Rossi, M. Hallett, P. M. Rossini et al., “Safety, ethical considerations, and application guidelines for the use of transcranial magnetic stimulation in clinical practice and research,” Clinical Neurophysiology, vol. 120, no. 12, pp. 2008–2039, 2009. View at: Publisher Site | Google Scholar
  34. R. Nardone, F. Tezzon, Y. Höller, S. Golaszewski, E. Trinka, and F. Brigo, “Transcranial magnetic stimulation (TMS)/repetitive TMS in mild cognitive impairment and Alzheimer's disease,” Acta Neurologica Scandinavica, vol. 129, no. 6, pp. 351–366, 2014. View at: Publisher Site | Google Scholar
  35. U. Ziemann, W. Paulus, M. A. Nitsche et al., “Consensus: motor cortex plasticity protocols,” Brain Stimulation, vol. 1, no. 3, pp. 164–182, 2008. View at: Publisher Site | Google Scholar
  36. G. W. Thickbroom, “Transcranial magnetic stimulation and synaptic plasticity: experimental framework and human models,” Experimental Brain Research, vol. 180, no. 4, pp. 583–593, 2007. View at: Publisher Site | Google Scholar
  37. J. P. Lefaucheur, N. André-Obadia, A. Antal et al., “Evidence-based guidelines on the therapeutic use of repetitive transcranial magnetic stimulation (rTMS),” Clinical Neurophysiology, vol. 125, no. 11, pp. 2150–2206, 2014. View at: Publisher Site | Google Scholar
  38. S. H. Lisanby, B. Luber, T. Perera, and H. A. Sackeim, “Transcranial magnetic stimulation: applications in basic neuroscience and neuropsychopharmacology,” International Journal of Neuropsychopharmacology, vol. 3, no. 3, pp. 259–273, 2000. View at: Publisher Site | Google Scholar
  39. A. Demirtas-Tatlidede, A. M. Vahabzadeh-Hagh, and A. Pascual-Leone, “Can noninvasive brain stimulation enhance cognition in neuropsychiatric disorders?” Neuropharmacology, vol. 64, pp. 566–578, 2013. View at: Publisher Site | Google Scholar
  40. P. T. Huerta and B. T. Volpe, “Transcranial magnetic stimulation, synaptic plasticity and network oscillations,” Journal of NeuroEngineering and Rehabilitation, vol. 6, no. 1, article 7, 2009. View at: Publisher Site | Google Scholar
  41. A. Gazzaley and M. D'Esposito, “Top-down modulation and normal aging,” Annals of the New York Academy of Sciences, vol. 1097, pp. 67–83, 2007. View at: Publisher Site | Google Scholar
  42. A. A. Gershon, P. N. Dannon, and L. Grunhaus, “Transcranial magnetic stimulation in the treatment of depression,” American Journal of Psychiatry, vol. 160, no. 5, pp. 835–845, 2003. View at: Publisher Site | Google Scholar
  43. B. Cheeran, P. Talelli, F. Mori et al., “A common polymorphism in the brain-derived neurotrophic factor gene (BDNF) modulates human cortical plasticity and the response to rTMS,” Journal of Physiology, vol. 586, no. 23, pp. 5717–5725, 2008. View at: Publisher Site | Google Scholar
  44. R. Manenti, M. Cotelli, M. Calabria, C. Maioli, and C. Miniussi, “The role of the dorsolateral prefrontal cortex in retrieval from long-term memory depends on strategies: a repetitive transcranial magnetic stimulation study,” Neuroscience, vol. 166, no. 2, pp. 501–507, 2010. View at: Publisher Site | Google Scholar
  45. C. Solé-Padullés, D. Bartrés-Faz, C. Junqué et al., “Repetitive transcranial magnetic stimulation effects on brain function and cognition among elders with memory dysfunction. A randomized sham-controlled study,” Cerebral Cortex, vol. 16, no. 10, pp. 1487–1493, 2006. View at: Publisher Site | Google Scholar
  46. S. H. Lisanby, D. Gutman, B. Luber, C. Schroeder, and H. A. Sackeim, “Sham TMS: intracerebral measurement of the induced electrical field and the induction of motor-evoked potentials,” Biological Psychiatry, vol. 49, no. 5, pp. 460–463, 2001. View at: Publisher Site | Google Scholar
  47. K. R. Mills, S. J. Boniface, and M. Schubert, “Magnetic brain stimulation with a double coil: the importance of coil orientation,” Electroencephalography and Clinical Neurophysiology/Evoked Potentials Section, vol. 85, no. 1, pp. 17–21, 1992. View at: Publisher Site | Google Scholar
  48. S. Rossi, C. Miniussi, P. Pasqualetti, C. Babiloni, P. M. Rossini, and S. F. Cappa, “Age-related functional changes of prefrontal cortex in long-term memory: a repetitive transcranial magnetic stimulation study,” The Journal of Neuroscience, vol. 24, no. 36, pp. 7939–7944, 2004. View at: Publisher Site | Google Scholar
  49. R. Manenti, M. Cotelli, I. H. Robertson, and C. Miniussi, “Transcranial brain stimulation studies of episodic memory in young adults, elderly adults and individuals with memory dysfunction: a review,” Brain Stimulation, vol. 5, no. 2, pp. 103–109, 2012. View at: Publisher Site | Google Scholar
  50. B. Guse, P. Falkai, and T. Wobrock, “Cognitive effects of high-frequency repetitive transcranial magnetic stimulation: a systematic review,” Journal of Neural Transmission, vol. 117, no. 1, pp. 105–122, 2010. View at: Publisher Site | Google Scholar
  51. Z. S. Nasreddine, N. A. Phillips, V. Bédirian et al., “The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment,” Journal of the American Geriatrics Society, vol. 53, no. 4, pp. 695–699, 2005. View at: Publisher Site | Google Scholar
  52. J. I. Sheikh and J. A. Yesavage, “Geriatric depression scale (GDS): recent evidence and development of a shorter version,” Clinical Gerontologist, vol. 5, no. 1-2, pp. 165–173, 1986. View at: Publisher Site | Google Scholar
  53. M. Hamilton, “A rating scale for depression,” Journal of Neurology, Neurosurgery, and Psychiatry, vol. 23, pp. 56–62, 1960. View at: Publisher Site | Google Scholar
  54. M. Hamilton, “The assessment of anxiety states by rating,” The British Journal of Medical Psychology, vol. 32, no. 1, pp. 50–55, 1959. View at: Publisher Site | Google Scholar
  55. A. F. Jorm and A. E. Korten, “Assessment of cognitive decline in the elderly by informant interview,” British Journal of Psychiatry, vol. 152, pp. 209–213, 1988. View at: Publisher Site | Google Scholar
  56. I. Hindmarch, H. Lehfeld, P. De Jongh, and H. Erzigkeit, “The Bayer: activities of daily living scale (B-ADL),” Dementia and Geriatric Cognitive Disorders, vol. 9, no. 2, pp. 20–26, 1998. View at: Google Scholar
  57. M. F. Folstein, S. E. Folstein, and P. R. Mchugh, “‘Mini-mental state’. A practical method for grading the cognitive state of patients for the clinician,” Journal of Psychiatric Research, vol. 12, no. 3, pp. 189–198, 1975. View at: Google Scholar
  58. B. Wilson, J. Cockburn, A. Baddeley, and R. Hiorns, “The development and validation of a test battery for detecting and monitoring everyday memory problems,” Journal of Clinical and Experimental Neuropsychology, vol. 11, no. 6, pp. 855–870, 1989. View at: Publisher Site | Google Scholar
  59. H. Adachi, S. Shinagawa, K. Komori et al., “Comparison of the utility of everyday memory test and the Alzheimer's Disease Assessment Scale-Cognitive part for evaluation of mild cognitive impairment and very mild Alzheimer's disease,” Psychiatry and Clinical Neurosciences, vol. 67, no. 3, pp. 148–153, 2013. View at: Publisher Site | Google Scholar
  60. H. G. G. Van Balen, P. S. H. Westzaan, and T. Mulder, “Stratified norms for the rivermead behavioural memory test,” Neuropsychological Rehabilitation, vol. 6, no. 3, pp. 203–217, 1996. View at: Publisher Site | Google Scholar
  61. D. I. Wechsler, Examiner's Manual: Wechsler Adult Intelligence Scale—Revised, The Psychological Corporation, New York, NY, USA, 1981.
  62. L. F. M. Malloy-Diniz, M. F. Cruz, V. M. Torres, and R. M. Cosenza, “O teste de aprendizagem auditivo-verbal de Rey: normas para uma população brasileira,” Revista Brasileira de Neurologia, vol. 36, pp. 79–83, 2000. View at: Google Scholar
  63. L. F. Malloy-Diniz, V. A. P. Lasmar, L. D. S. R. Gazinelli, D. Fuentes, and J. V. Salgado, “The Rey Auditory-Verbal Learning Test: applicability for the brazilian elderly population,” Revista Brasileira de Psiquiatria, vol. 29, no. 4, pp. 324–329, 2007. View at: Publisher Site | Google Scholar
  64. R. M. Savage and W. D. Gouvier, “Rey auditory-verbal learning test: the effects of age and gender, and norms for delayed recall and story recognition trials,” Archives of Clinical Neuropsychology, vol. 7, no. 5, pp. 407–414, 1992. View at: Publisher Site | Google Scholar
  65. D. Wechsler, WAIS-III: Administration and Scoring Manual, The Psychological Corporation, San Antonio, Tex, USA, 1997.
  66. B. D. Hill, E. M. Elliott, J. T. Shelton, R. D. Pella, J. R. O'Jile, and W. D. Gouvier, “Can we improve the clinical assessment of working memory? An evaluation of the WAIS-III using a working memory criterion construct,” Journal of Clinical and Experimental Neuropsychology, vol. 32, no. 3, pp. 315–323, 2010. View at: Publisher Site | Google Scholar
  67. T. N. Tombaugh, “Trail Making test A and B: normative data stratified by age and education,” Archives of Clinical Neuropsychology, vol. 19, no. 2, pp. 203–214, 2004. View at: Publisher Site | Google Scholar
  68. C. R. Reynolds, Comprehensive Trail Making Test: Examiner's Manual, Pro-Ed, Austin, Tex, USA, 2002.
  69. J. E. Mezzich and J. A. Moses Jr., “Efficient screening for brain dysfunction,” Biological Psychiatry, vol. 15, no. 2, pp. 333–337, 1980. View at: Google Scholar
  70. R. M. Reitan, “Validity of the Trail Making test as an indicator of organic brain damage,” Perceptual and Motor Skills, vol. 8, no. 3, pp. 271–276, 1958. View at: Publisher Site | Google Scholar
  71. T. N. Tombaugh, J. Kozak, and L. Rees, “Normative data stratified by age and education for two measures of verbal fluency: FAS and animal naming,” Archives of Clinical Neuropsychology, vol. 14, no. 2, pp. 167–177, 1999. View at: Publisher Site | Google Scholar
  72. M. R. Trenerry, B. Crosson, J. DeBoe, and W. R. Leber, The Stroop Neuropsychological Screening Test, Psychological Assessment Resources, Odessa, Ukraine, 1989.
  73. M. B. First, R. L. Spitzer, M. Gibbon, and J. B. W. Willian, Structured Clinical Interview for DSM IV Axis I disorders—Research version—Non-Patient Edition (SCID-I/NP), Biometrics Research Department, New York, NY, USA, 2002.
  74. C. K. Loo, J. L. Taylor, S. C. Gandevia, B. N. McDarmont, P. B. Mitchell, and P. S. Sachdev, “Transcranial magnetic stimulation (TMS) in controlled treatment studies: are some ‘sham’ forms active?” Biological Psychiatry, vol. 47, no. 4, pp. 325–331, 2000. View at: Publisher Site | Google Scholar
  75. E. M. Wassermann, A. Pascual-Leone, J. Valls-Solé, C. Toro, L. G. Cohen, and M. Hallett, “Topography of the inhibitory and excitatory responses to transcranial magnetic stimulation in a hand muscle,” Electroencephalography and Clinical Neurophysiology, vol. 89, no. 6, pp. 424–433, 1993. View at: Google Scholar
  76. S. Bolló-Gasol, G. Piñol-Ripoll, J. C. Cejudo-Bolivar, A. Llorente-Vizcaino, and H. Peraita-Adrados, “Ecological assessment of mild cognitive impairment and Alzheimer disease using the Rivermead Behavioural Memory Test,” Neurología, vol. 29, no. 6, pp. 339–345, 2013. View at: Publisher Site | Google Scholar
  77. C. K. Loo, P. Sachdev, H. Elsayed et al., “Effects of a 2- to 4-week course of repetitive Transcranial Magnetic Stimulation (rTMS) on neuropsychologic functioning, electroencephalogram, and auditory threshold in depressed patients,” Biological Psychiatry, vol. 49, no. 7, pp. 615–623, 2001. View at: Publisher Site | Google Scholar
  78. C. K. Loo, P. B. Mitchell, V. M. Croker et al., “Double-blind controlled investigation of bilateral prefrontal transcranial magnetic stimulation for the treatment of resistant major depression,” Psychological Medicine, vol. 33, no. 1, pp. 33–40, 2003. View at: Publisher Site | Google Scholar
  79. Z. Nahas, X. Li, F. A. Kozel et al., “Safety and benefits of distance-adjusted prefrontal transcranial magnetic stimulation in depressed patients 55–75 years of age: a pilot study,” Depression and Anxiety, vol. 19, no. 4, pp. 249–256, 2004, Erratum in: F. R. Daro, B. B. Bellini, Z. H. Nahas, D. E. Bohning, M. S. George, M. A. Marcolin, Depression and Anxiety, vol. 27, no. 1, p. 90, 2010. View at: Google Scholar
  80. M. G. Stokes, C. D. Chambers, I. C. Gould et al., “Distance-adjusted motor threshold for transcranial magnetic stimulation,” Clinical Neurophysiology, vol. 118, no. 7, pp. 1617–1625, 2007. View at: Publisher Site | Google Scholar
  81. F. R. Daro, B. B. Bellini, Z. H. Nahas, D. E. Bohning, M. S. George, and M. A. Marcolin, “Safety and benefits of distance-adjusted prefrontal transcranial magnetic stimulation in depressed patients 55–75 years of age: a pilot study,” Depression and Anxiety, vol. 27, no. 1, p. 90, 2010, Erratum. View at: Publisher Site | Google Scholar
  82. Z. Nahas, X. Li, F. A. Kozel et al., “Safety and benefits of distance-adjusted prefrontal transcranial magnetic stimulation in depressed patients 55–75 years of age: a pilot study,” Depression and Anxiety, vol. 19, no. 4, pp. 249–256, 2004, Erratum to Depression and Anxiety, vol. 27, no. 1, p. 90, 2010. View at: Publisher Site | Google Scholar
  83. P. G. Janicak, S. M. Dowd, B. Martis et al., “Repetitive transcranial magnetic stimulation versus electroconvulsive therapy for major depression: preliminary results of a randomized trial,” Biological Psychiatry, vol. 51, no. 8, pp. 659–667, 2002. View at: Publisher Site | Google Scholar
  84. E. M. Robertson, H. Théoret, and A. Pascual-Leone, “Studies in cognition: the problems solved and created by transcranial magnetic stimulation,” Journal of Cognitive Neuroscience, vol. 15, no. 7, pp. 948–960, 2003. View at: Publisher Site | Google Scholar
  85. R. C. Petersen, R. Doody, A. Kurz et al., “Current concepts in mild cognitive impairment,” Archives of Neurology, vol. 58, no. 12, pp. 1985–1992, 2001. View at: Publisher Site | Google Scholar
  86. C. Schönfeldt-Lecuona, J.-P. Lefaucheur, L. Cardenas-Morales, R. C. Wolf, T. Kammer, and U. Herwig, “The value of neuronavigated rTMS for the treatment of depression,” Neurophysiologie Clinique/Clinical Neurophysiology, vol. 40, no. 1, pp. 37–43, 2010. View at: Publisher Site | Google Scholar
  87. R. Ahdab, S. S. Ayache, P. Brugières, C. Goujon, and J. P. Lefaucheur, “Comparison of ‘standard’ and ‘navigated’ procedures of TMS coil positioning over motor, premotor and prefrontal targets in patients with chronic pain and depression,” Neurophysiologie Clinique, vol. 40, no. 1, pp. 27–36, 2010. View at: Publisher Site | Google Scholar
  88. W. Beam, J. J. Borckardt, S. T. Reeves, and M. S. George, “An efficient and accurate new method for locating the F3 position for prefrontal TMS applications,” Brain Stimulation, vol. 2, no. 1, pp. 50–54, 2009. View at: Publisher Site | Google Scholar
  89. A.-M. Vallence and M. R. Goldsworthy, “Can noninvasive brain stimulation enhance function in the ageing brain?” Journal of Neurophysiology, vol. 111, no. 1, pp. 1–3, 2014. View at: Publisher Site | Google Scholar
  90. M. Gangitano, A. Valero-Cabré, J. M. Tormos, F. M. Mottaghy, J. R. Romero, and Á. Pascual-Leone, “Modulation of input-output curves by low and high frequency repetitive transcranial magnetic stimulation of the motor cortex,” Clinical Neurophysiology, vol. 113, no. 8, pp. 1249–1257, 2002. View at: Publisher Site | Google Scholar
  91. T. Touge, W. Gerschlager, P. Brown, and J. C. Rothwell, “Are the after-effects of low-frequency rTMS on motor cortex excitability due to changes in the efficacy of cortical synapses?” Clinical Neurophysiology, vol. 112, no. 11, pp. 2138–2145, 2001. View at: Publisher Site | Google Scholar
  92. R. Chen, J. Classen, C. Gerloff et al., “Depression of motor cortex excitability by low-frequency transcranial magnetic stimulation,” Neurology, vol. 48, no. 5, pp. 1398–1403, 1997. View at: Publisher Site | Google Scholar
  93. V. P. Clark and R. Parasuraman, “Neuroenhancement: enhancing brain and mind in health and in disease,” NeuroImage, vol. 85, pp. 889–894, 2014. View at: Publisher Site | Google Scholar
  94. R. McKendrick, H. Ayaz, R. Olmstead, and R. Parasuraman, “Enhancing dual-task performance with verbal and spatial working memory training: continuous monitoring of cerebral hemodynamics with NIRS,” NeuroImage, vol. 85, pp. 1014–1026, 2014. View at: Publisher Site | Google Scholar
  95. J. Bentwich, E. Dobronevsky, S. Aichenbaum et al., “Beneficial effect of repetitive transcranial magnetic stimulation combined with cognitive training for the treatment of Alzheimer's disease: a proof of concept study,” Journal of Neural Transmission, vol. 118, no. 3, pp. 463–471, 2011. View at: Publisher Site | Google Scholar
  96. G. Vallar and N. Bolognini, “Behavioural facilitation following brain stimulation: implications for neurorehabilitation,” Neuropsychological Rehabilitation, vol. 21, no. 5, pp. 618–649, 2011. View at: Publisher Site | Google Scholar

Copyright © 2015 Hellen Livia Drumond Marra et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

More related articles

 PDF Download Citation Citation
 Download other formatsMore
 Order printed copiesOrder

Related articles