Cortical sources of resting-state EEG rhythms in “experienced” HIV subjects under antiretroviral...

Clinical Neurophysiology xxx (2014) xxx–xxx

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Clinical Neurophysiology

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Cortical sources of resting-state EEG rhythms in ‘‘experienced’’ HIVsubjects under antiretroviral therapy

http://dx.doi.org/10.1016/j.clinph.2014.01.0241388-2457/� 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

⇑ Corresponding author at: Department of Physiology and Pharmacology, University of Rome ‘‘La Sapienza’’, P.le Aldo Moro, 5, 00185 Rome, Italy. Tel.: +39 0649fax: +39 0649910917.

E-mail address: [email protected] (C. Babiloni).

Please cite this article in press as: Babiloni C et al. Cortical sources of resting-state EEG rhythms in ‘‘experienced’’ HIV subjects under antiretroviral tClin Neurophysiol (2014), http://dx.doi.org/10.1016/j.clinph.2014.01.024

Claudio Babiloni a,b,⇑, Paola Buffo c, Fabrizio Vecchio b, Paolo Onorati a,b, Chiara Muratori b,Stefano Ferracuti d, Paolo Roma d, Michele Battuello d, Nicole Donato d, Giuseppe Noce c,Francesco Di Campli e,f, Laura Gianserra e, Elisabetta Teti e, Antonio Aceti e, Andrea Soricelli c,g,Magdalena Viscione h, Massimo Andreoni h, Paolo M. Rossini b,i, Alfredo Pennica e

a Department of Physiology and Pharmacology, University of Rome ‘‘La Sapienza’’, Rome, Italyb IRCCS S. Raffaele Pisana, Rome, Italyc IRCCS SDN Foundation, Naples, Italyd Psychiatry, Faculty of Medicine and Psychology, University of Rome ‘‘La Sapienza’’, Rome, Italye Infectious Diseases, Faculty of Medicine and Psychology, University of Rome ‘‘La Sapienza’’, Rome, Italyf ViiV Healthcare, Italyg Department of Studies of Institutions and Territorial Systems, University of Naples ‘‘Parthenope’’, Naples, Italyh Clinical Infectious Diseases, ‘‘Tor Vergata’’ University, Rome, Italyi Department of Geriatrics, Neuroscience & Orthopedics, Catholic University ‘‘Sacro Cuore’’, Rome, Italy

a r t i c l e i n f o

Article history:Accepted 20 January 2014Available online xxxx

Keywords:Human immunodeficiency virus (HIV)CD4 lymphocyteResting-state electroencephalography (EEG)Low-resolution brain electromagneticsource tomography (LORETA)Brain rhythmsAlpha

h i g h l i g h t s

� Treatment-naïve patients with human immunodeficiency virus (HIV) are characterized by diffuseabnormalities of resting-state cortical electroencephalographic (EEG) rhythms.

� Here, we tested the hypothesis that these EEG rhythms vary as a function of the systemic immuneactivity in HIV patients treated with antiretroviral therapy (ART).

� The present results suggest that in ART-HIV subjects, cortical sources of resting-state alpha rhythmsare related to systemic immune activity and cognitive performance.

a b s t r a c t

Objective: Treatment-naïve patients with human immunodeficiency virus (HIV) are characterized bydiffuse abnormalities of resting-state cortical electroencephalographic (EEG) rhythms (Babiloni et al.,2012a). Here, we tested the hypothesis that these EEG rhythms vary as a function of the systemicimmune activity and antiretroviral therapy (ART) in HIV patients.Methods: Resting-state eyes-closed EEG data were recorded in 68 ART-HIV patients (mini mental stateevaluation (MMSE) of 27.5 ± 0.3 SEM), in 60 treatment-naïve HIV subjects (MMSE of 27.5 ± 0.4 SEM)and in 75 age-matched cognitively normal subjects (MMSE of 29.3 ± 0.1 SEM). Based on the CD4 lympho-cytes’ count, we divided ART-HIV subjects into two subgroups: those with CD4 > 500 cells/ll (ART-HIV+)and those with CD4 < 500 cells/ll (ART-HIV�). EEG rhythms of interest were delta (2–4 Hz), theta(4–8 Hz), alpha 1 (8–10.5 Hz), alpha 2 (10.5–12 Hz), beta 1 (13–20 Hz), and beta 2 (20–30 Hz). CorticalEEG sources were estimated by LORETA software.Results: Widespread theta, alpha, and beta sources were lower in ART-HIV subjects than in controlsubjects. Furthermore, occipital and temporal alpha 1 sources were lower in treatment-naïve HIV thanin ART-HIV subjects. Moreover, the opposite was true for widespread pathological delta sources.Finally, parietal, occipital, and temporal alpha 1 sources were lower in ART-HIV� than in ART-HIV+subjects.

910989;

herapy.

http://dx.doi.org/10.1016/j.clinph.2014.01.024

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2 C. Babiloni et al. / Clinical Neurophysiology xxx (2014) xxx–xxx

Please cite this article in press as: Babiloni C et aClin Neurophysiol (2014), http://dx.doi.org/10.1

Conclusions: In ART-HIV subjects, cortical sources of resting-state alpha rhythms are related to sys-temic immune activity and cART.Significance: This EEG procedure may produce biomarkers of treatment response in patients’ braincompartments for longitudinal clinical studies.� 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights

reserved.

1. Introduction

Human immunodeficiency virus (HIV) penetrates into the cen-tral nervous system (CNS) within 2 weeks of infection, probablythrough a transmigration of infected monocytes across the brain–blood barrier (Williams et al., 2012; Chalmers et al., 1990; Robertset al., 2010). Autopsy studies reported that the HIV infectionundergoes neuropathological changes in 80–90% of the subjects(McArthur, 1987; Fauci and Lane, 1998; Williams et al., 2002,2012. As a consequence, the infection of the brain is typically asso-ciated with neurologic symptoms and/or cognitive impairment todementia (Anthony and Bell, 2008; Antinori et al., 2007). Subclini-cal neuropathy was reported in 10–40% and 53–100% of asymp-tomatic HIV and AIDS subjects, respectively (Chavanet et al.,1988; Gastaut et al., 1989). Furthermore, about 50–70% of theHIV subjects suffer from neurologic symptoms during the courseof the illness (Selnes, 2005).

Neurological and neuropsychological symptoms are mitigatedin HIV subjects receiving a combination of antiretroviral therapies(cART; Clifford, 2008), possibly due to the reduction of the viralload (VL) and to the maintenance of CD4 cell counts (Grahamet al., 1992; Hammer et al., 1997; Hunt et al., 2003; Williamset al., 2012). As HIV subjects treated with cART (ART-HIV sub-jects) live longer, the prevalence of patients with neurologicaland neuropsychological symptoms is increasing and representsa burden for the health services in the near future (Cysiqueet al., 2009; Sevigny et al., 2004). This has motivated the researchof ‘‘biomarkers’’ for the assessment of the effects of HIV on thebrain structure and function. Furthermore, these biomarkers as‘‘surrogate’’ markers would clearly be useful in interventional tri-als, perhaps reducing the number of subjects or duration of thefollow-up.

Concerning the functional biomarkers, functional MRI (fMRI)unveiled abnormalities of cortical blood-oxygen-level dependence(BOLD) in HIV subjects (Ances et al., 2008). Arterial spin labelingMRI showed an inverse correlation between the measurement ofresting-state cerebral blood flow (rCBF) and the degree of neuro-cognitive impairment soon after seroconversion (Ances et al.,2009). Fluorodeoxyglucose positron emission tomography (FDG-PET) unveiled a relationship of the resting-state mesial-frontalmetabolic rate with some relevant variables, such as the diseaseprogression, the therapy duration, and the plasma levels of neur-oinflammatory markers (Andersen et al., 2010). However, itshould be remarked that FDG-PET biomarkers are invasive, whilestructural MRI biomarkers are relatively expensive for serialscreening measurements in large populations of HIV subjects atrisk of HIV-associated neurocognitive disorders (HAND). For thesereasons, other fully noninvasive and cost-effective procedureshave been investigated in the past years as integrativemethodologies.

A promising approach for the assessment of global brainfunction in HIV subjects is the recording of scalp electroencephalo-graphic (EEG) rhythms during wakeful resting-state eyes-closedcondition. This approach is based on low cost and very popularequipment, it is fully noninvasive, is back translational to research

l. Cortical sources of resting-sta016/j.clinph.2014.01.024

in animal models, and can be applied in serial measurements with-out the misleading effects due to the repetition of the procedure inhumans (Rossini et al., 2007). This EEG recording essentially mea-sures voltages at the scalp level, which are directly associated withneural currents in the extracellular space of brain neurons (Nunez,1995). These currents are associated to ion flow because of excit-atory and inhibitory postsynaptic potentials. The temporal resolu-tion of scalp EEG potentials is very high (e.g., up to fractions ofmilliseconds), whereas the spatial resolution is quite lower (e.g.,centimeters) than that of fMRI (e.g., millimeters) and PET (e.g.,1 cm). Previous studies have successfully investigated the eyes-closed resting-state scalp EEG rhythms in HIV subjects. Comparedto healthy subjects (control), HIV subjects showed a decrement ofposterior alpha (8–12 Hz) rhythms (Gruzelier et al., 1996; Bald-eweg and Gruzelier, 1997; Baldeweg et al., 1997). Abnormalitiesof the alpha rhythms preceded cognitive and neurological impair-ment at the symptomatic stage of HIV infection; these abnormali-ties were associated with changes in psychiatric status and werenormalized by cART (Baldeweg and Gruzelier, 1997; Baldeweget al., 1997). Furthermore, abnormalities of theta (4–7 Hz) and al-pha rhythms were related to mood ratings and immune status(i.e., CD4 counts) in asymptomatic HIV subjects (Gruzelier et al.,1996). Finally, abnormalities of resting-state EEG rhythms in HIVsubjects were related to atrophy of brain gray matter and to whitematter lesions as revealed by MRI (Harrison et al., 1998).

A step forward for the study of the relationship between rest-ing-state scalp EEG rhythms and cognitive impairment is themathematical estimation of the cortical sources of these rhythmsby the popular freeware called low-resolution brain electromag-netic tomography (LORETA; Pascual-Marqui and Michel, 1994;Pascual-Marqui et al., 1999, 2002). For example, LORETA sourceestimation unveiled useful candidate EEG biomarkers in subjectswith mild cognitive impairment (MCI), Alzheimer’s disease (AD),cerebrovascular dementia, and Parkinson’s disease with dementia(Caso et al., 2012; Nishida et al., 2011; Zappasodi et al., 2008; Gian-otti et al., 2008; Saletu et al., 2005; Babiloni et al., 2004,2006a,b,c,d,e, 2007a,b,c, 2008, 2009a,b, 2010, 2011a,b,c). Recently,our research group has used such a methodological approach intreatment-naïve HIV subjects showing abnormalities of centraland parietal sources of delta rhythms (<4 Hz) as well as topograph-ically diffuse changes of the sources of low- and high-frequency al-pha rhythms (Babiloni et al., 2012a). Those findings led support tothe notion that the cortical sources of resting-state scalp EEGrhythms reflect the abnormal functioning of the brain synchroniza-tion mechanisms generating scalp EEG oscillatory activity in HIVsubjects. Those findings also raised the issue whether the corticalsources of delta and alpha rhythms show some normalization inthe HIV subjects who receive a successful cART. To preliminarilytest this hypothesis by a cross-sectional design study, cortical(LORETA) sources of eyes-closed resting-state EEG rhythms werecompared in HIV patients treated with ART, treatment-naïve HIVpatients, and healthy subjects. The ART-HIV group was also dividedinto two subgroups as a function of the immune activity, and cor-tical sources of EEG rhythms were compared among the two ART-HIV subgroups and the group of healthy subjects.

te EEG rhythms in ‘‘experienced’’ HIV subjects under antiretroviral therapy.


C. Babiloni et al. / Clinical Neurophysiology xxx (2014) xxx–xxx 3

2. Methods

2.1. Subjects

This study evaluated 68 consecutive Italian HIV patients treatedwith cART (58 males; mean age 45.99 years ± 1.4 standard error ofmean, SEM) recruited by the clinical unit of S. Andrea Hospital ofRome. The mean duration of the therapy was 45 months (±3SEM). A second group of patients comprised 60 consecutive Italiantreatment-naïve HIV subjects (treatment-naïve group; 51 males;40.83 years ± 1 SEM), obtained by selecting individuals from whomwe recorded eyes-closed resting-state EEG data from the clinicalunits of S. Andrea Hospital of the University of Rome ‘‘La Sapienza’’and of ‘‘Tor Vergata’’ University of Rome (18 of them were used inthe previous reference study quoted by Babiloni et al., 2012a). Fur-thermore, a control group of 75 cognitively normal subjects (con-trol group; 53 males; 46.6 years ± 1.6 SEM) was obtainedselecting individuals from whom we recorded eyes-closed rest-ing-state EEG data in previous studies (Babiloni et al., 2004,2006a,b,c,d,e). The subjects’ selection ensured the best matchingof age, gender, and education between the control groups and thatof ART-HIV subjects.

All experiments were performed with the informed and overtconsent of each participant, in line with the Code of Ethics of theWorld Medical Association (Declaration of Helsinki) and the stan-dards established by the Author’s Institutional Review Board. Writ-ten informed consent was obtained prior to the experiment,following the approval by the local ethical committee for researchon human beings. Noteworthy, the study was approved by all theclinical institutions involved in the data collection.

2.2. Diagnostic criteria

All participants were asked to provide a blood sample for theconfirmation of HIV serostatus. The clinical laboratory evaluationalso included complete blood count (CBC), HIV RNA VL, CD4 lym-phocyte count and percent, treponema screening, HBV-HCVscreening, toxoplasmosis and cytomegalovirus antibody titers, re-nal and liver function, serum protein, and albumin. Toxicologicalanalyses for cocaine, opiates, amphetamine, and marijuana wereperformed on urine samples. It is noted that none of the HIV sub-jects showed CD4 counts compatible with a diagnosis of full-blownAIDS. All HIV subjects belonged to the sexual transmission riskgroup (about 50% homosexually active individuals).

Based on the values of CD4 count, we divided ART-HIV subjectsinto two subgroups paired for demographic and clinical features onthe basis of the threshold of CD4 > 500 cells/ll, namely those withCD4 > 500 cells/ll (ART-HIV+; N = 37; CD4 = 700.68 ± 37.6 SEM;mean age 45.1 years ± 1.6 SEM) and those with CD4 < 500 cells/ll(ART-HIV�; N = 31; CD4 = 337.84 ± 22.7 SEM; mean age47.7 years ± 2.3 SEM). The rationale of this methodological optionis that a reference EEG study of the present workgroup has showna correlation between resting-state EEG variables of interest andCD4 count in treatment-naïve HIV subjects, suggesting that thesynchronization of cortical neurons generating EEG is influencedby the effect of HIV on the immune system (Babiloni et al.,2012a). Furthermore, the value of CD4 count at 500 cells/ll refersto the threshold to start the therapy in treatment-naïve HIV sub-jects according to the new guidelines of the World Health Organi-zation (July 2013). Table 1 summarizes the relevant demographicand clinical data of the control, ART-HIV, and treatment-naïveparticipants. Table 2 summarizes the relevant demographic andclinical data of the ART-HIV+, and ART-HIV� participants. Asexpected, the CD4 count differed among the ART-HIV+ and ART-HIV� (F(1,52) = 56.43; p < 0.00001). Of note, the ART-HIV-group

Please cite this article in press as: Babiloni C et al. Cortical sources of resting-staClin Neurophysiol (2014), http://dx.doi.org/10.1016/j.clinph.2014.01.024

presented seven patients with a VL higher than 20 copies/ml,whereas the ART-HIV+ group presented five patients with a VLhigher than 20 copies/ml. The results of the present exploratorystudy motivate future EEG investigations measuring the patients’adherence to the therapy by blood sample analysis.

A structured psychiatric interview (i.e. CDIS-IV) was used fordetecting DSM-IV Axis I and II disorders. A subgroup of 55 ART-HIV participants completed questionnaires or brief interviewsassessing medical history, medication use, parental psychopathol-ogy, demographics, psychiatric symptoms, alcohol and drug use,and cognitive status. A battery of neuropsychological tests wasperformed to assess cognitive performance in several domains,including memory, language, executive function/attention, and vi-suo-construction abilities. The tests assessing memory were theimmediate and delayed recall measure of the Rey Auditory VerbalLearning Test and the delayed recall (Rey, 1958; Carlesimo et al.,1996). The test to assess memory was the Prose Memory Test de-layed recall of a story (Spinnler and Tognoni, 1987). The tests to as-sess language were the 1-min verbal fluency for letters (Novelliet al., 1986), and the 1-min verbal fluency for fruits, animals, orcar trades (Novelli et al., 1986). The tests to assess executive func-tion and attention were the Trail Making Test part A and B (Reitan,1958). Finally, Mini-Mental State Exam (MMSE) was performed toglobally test basic cognitive functions (Folstein et al., 1975). TheMMSE score was lower in ART-HIV (27.7 ± 0.3 SEM) than in control(29.3 ± 0.1 SEM) subjects (p < 0.0001). Table 3 reports in detail thescore to the neuropsychological tests in the ART-HIV+ and ART-HIV�.

Exclusion criteria included pregnancy, seizures, mental retarda-tion, and neurosurgery. Furthermore, excluding criteria includedhistory of head injury with loss of consciousness for > 10 min tofollow the procedures by Bauer and colleague (2006); no subjecthas any loss of consciousness in the present study). In addition,participants were required to have no acute illness, an IQscore > 70, and no major neurological, psychiatric (i.e., DSM-IV-de-fined schizophrenia or bipolar disorder) or medical (i.e., hyperten-sion, chronic obstructive pulmonary disease, type 1 diabetes,cirrhosis, hepatic encephalopathy, ocular disorders, etc.) disordersunrelated to HIV/AIDS. Positive urine toxicology or breathalyzertests or recent (past year) dependence upon alcohol, cocaine, oropiates was also exclusionary.

EEG datasets of the control subjects belonged to an availabledatabase of the research group. All control subjects underwentphysical and neurological examinations as well as cognitivescreening. Subjects affected by chronic systemic illnesses, thosereceiving psychoactive drugs, or with a history of neurological orpsychiatric disease were excluded. All control subjects had a GDSscore < 14 (no depression).

2.3. EEG recordings

Eyes-closed resting-state EEG data were recorded with the fol-lowing features: 0.3–70 Hz bandpass; cephalic reference; and spa-tial sampling from 19 electrodes positioned according to theInternational 10–20 System (i.e., Fp1, Fp2, F7, F3, Fz, F4, F8, T3,C3, Cz, C4, T4, T5, P3, Pz, P4, T6, O1, O2). To monitor eye move-ments, the horizontal and vertical electrooculograms (EOG, 0.3–70 Hz bandpass) were also collected. All data were digitized in acontinuous recording mode (5 min of EEG; 256 Hz sampling rate).The experiments were performed in the late morning in all sub-jects. In order to keep the level of vigilance constant, an experi-menter controlled on-line the subject and EEG–EOG traces. Heverbally alerted the subject any time there were signs of behavioraland/or EEG drowsiness. Specifically, the experimenter monitoredeventual appearance of ‘‘tonic’’ theta rhythms, K complexes, andsleep spindles (behavior in the control subjects). Of note, a low



Table 1Demographic and neuropsychological data of matched control healthy subjects and of patients with human immunodeficiency virus (HIV) subjects under antiretroviral therapy(ART) and treatment-naïve.

Control (mean ± SEM) Treatment-naïve (mean ± SEM) ART-HIV (mean ± SEM)

N 75 60 68Age (years) 46.61 ± 1.57 40.83 ± 1.00 45.99 ± 1.39Education (years) 12.1 ± 0.5 12.57 ± 0.51 12.21 ± 0.51MMSE 29.35 ± 0.13 27.53 ± 0.41 27.50 ± 0.33IAF (Hz) 9.68 ± 0.13 9.34 ± 0.18 9.64 ± 0.16CD4 count (cells/ll) – 470.07 ± 38.88 535.26 ± 29.58Viral Load (copies/ml) – 28,9870.85 ± 1,02,648.18 455.79 ± 315.35

Table 2Demographic and neuropsychological data of patients with human immunodeficiency virus (HIV) subjects under antiretroviral therapy (ART). Of note, the ART-HIV group wasdivided in two subgroups: the HIV subjects with CD4 count > 500 cells/ll (ART-HIV+) and the HIV subjects with CD4 count < 500 cells/ll (ART-HIV�).

ART-HIV+ (mean ± SEM) ART-HIV� (mean ± SEM) Statistical comparison between HIV groups

N 37 31Age (years) 44.84 ± 1.74 47.35 ± 2.62 n.s.Education (years) 12.5 ± 0.7 11.8 ± 0.8 n.s.MMSE 27.5 ± 0.4 27.48 ± 0.5 n.s.IAF (Hz) 9.87 ± 0.23 9.46 ± 0.22 n.s.CD4 count (cells/ll) 700.68 ± 37.6 337.84 ± 22.7 p = 0.00001Viral load (copies/ml) 975.77 ± 685.94 23.81 ± 11.99 n.s.Treatment duration (months) 39.84 ± 5.21 56.97 ± 5.13 P = 0.0149Disease duration (months) 74.08 ± 17.07 76.97 ± 9.60 n.s.

Table 3Neuropsychological data of the ART-HIV+ and ART-HIV� groups together with the p value of the statistical ANOVA analysis ART-HIV� versus ART-HIV+.

ART-HIV+ (mean ± SEM) ART-HIV– (mean ± SEM) Statistical comparison between HIV groups

Rey list immediate recall 33.5 ± 1.1 34.2 ± 0.6 p = 0.61Rey list delayed recall 12.1 ± 1.0 12.0 ± 1.1 p = 0.96Delayed recall of a story (Prose Memory Test) 8.6 ± 0.7 9.7 ± 0.9 p = 0.31Verbal fluency for letter 33.1 ± 11.4 29.6 ± 12.0 p = 0.28Verbal fluency for category 40.2 ± 7.6 37.9 ± 11.4 p = 0.64Trail Making Test part A 36.3 ± 2.4 39.6 ± 3.1 p = 0.39Trail Making Test part B 100.5 ± 6.5 103.3 ± 12.2 p = 0.82


percentage of subjects (<10%) required such verbal prompt. TheEEG segments affected by this artifact were discarded from furtheranalyses.

The duration of the EEG recording (5 min) allowed the compar-ison of the present results with several previous AD studies usingeither EEG recording periods 65 min (Babiloni et al., 2004,2006a,b,c,d; Buchan et al., 1997; Pucci et al., 1999; Rodriguezet al., 2002; Szelies et al., 1999) or about 1 min (Dierks et al.,1993, 2000); longer epochs would have reduced data variabilitybut increased risks for dropping vigilance and arousal.

The recorded EEG data were analyzed and fragmented off-linein consecutive epochs of 2 s. The EEG epochs with ocular, muscular,and other types of artifact s (including verbal prompts) were pre-liminarily identified by a computerized automatic procedure. EEGepochs with sporadic blinking artifacts (<10% of the total) werecorrected by an autoregressive method (Moretti et al., 2003).Two independent experimenters, blind to the diagnosis, manuallyconfirmed the EEG segments accepted for further analysis. All indi-vidual EEG datasets were considered for the subsequent EEG spec-tral analysis, as they showed >2.5 min of artifact-free EEGsegments with respect to the whole EEG recording of about 5 min.

2.4. Spectral analysis of the EEG data

A digital FFT-based power spectrum analysis (Welch technique,Hanning windowing function, no phase shift) computed powerdensity of EEG rhythms with 0.5 Hz frequency resolution. The fol-lowing standard frequency bands of interest were delta (2–4 Hz),


theta (4–8 Hz), alpha 1 (8–10.5 Hz), alpha 2 (10.5–13 Hz), beta 1(13–20 Hz), and beta 2 (20–30 Hz), in continuity with a bulk of pre-vious studies on the cortical sources of resting EEG rhythms inpathological aging (Babiloni et al., 2004, 2006a,b,c,d,e) and withother previous EEG studies on dementia (Holschneider et al.,1999; Besthorn et al., 1997; Cook and Leuchter, 1996; Jelic et al.,1996; Kolev et al., 2002; Leuchter et al., 1993; Nobili et al., 1997).

Choice of the fixed EEG bands did not account for individual al-pha frequency (IAF) peak, defined as the frequency associated tothe strongest EEG power at the extended alpha range when thepower spectra of all electrodes of the montage are averaged (IAFtypically peaks around 10 Hz in adults, Klimesch, 1999). However,this should not affect the results, because >90% of the control andthe HIV subjects had the IAF peaks within the alpha 1 band (8–10.5 Hz).

2.5. Cortical source of EEG rhythms as computed by LORETA

LORETA software as provided at http://www.unizh.ch/keyinst/NewLORETA/LORETA01.htm was used for the estimation of corticalsources of EEG rhythms (Pascual-Marqui and Michel, 1994; Pasc-ual-Marqui et al., 1999, 2002). LORETA is a functional imagingtechnique belonging to a family of linear inverse solution proce-dures (Valdès et al., 1998) modeling 3D distributions of EEGsources (Pascual-Marqui et al., 2002). LORETA has been success-fully used in recent EEG studies on pathological brain aging usingthe same experimental setup (electrode montage, sample




frequency, etc.) of the present study (Dierks et al., 2000; Babiloniet al., 2004, 2006a,b,c,d,e).

LORETA computes 3D linear solutions (LORETA solutions) forthe EEG inverse problem within a three-shell spherical head modelincluding scalp, skull, and brain compartments.

LORETA solutions consist of voxel current density values able topredict EEG spectral power density at scalp electrodes. Further-more, it is a reference-free method of EEG analysis, in that one ob-tains the same LORETA source distribution for EEG data referencedto any reference electrode including common average. Estimatedcortical sources of scalp EEG voltages are expected to reflect thesynchronous synaptic neural currents of the pyramidal corticalneurons, which are associated to local field potentials. A normali-zation of the data was obtained by normalizing the LORETA currentdensity at each voxel with the power density averaged across allfrequencies (0.5–45 Hz) and across all 2394 voxels of the brain vol-ume. The general procedure fitted the LORETA solutions in a Gauss-ian distribution and reduced intersubject variability (Leuchteret al., 1993; Nuwer, 1988).

In line with the low spatial resolution of the adopted technique,we collapsed the voxels of LORETA solutions at frontal, central,parietal, occipital, and temporal regions of the brain model codedinto Talairach space. The Brodmann areas listed in Table 4 formedeach of these regions of interest (ROIs).

2.6. Statistical analysis of the LORETA solutions

Main statistical comparisons were performed by ANOVAs usingnormalized regional LORETA solutions as a dependent variable(p < 0.05). The MMSE score served as a covariate as it differed be-tween the HIV and control groups (p < 0.05). For the lack of differ-ence between the groups (p > 0.05), subjects’ age, education,gender, and IAF were not used as covariates. Furthermore, treat-ment duration, disease duration, and VL were used as covariatesin the main statistical analyses. Mauchley’s test evaluated thesphericity assumption (p < 0.05). In case the Mauchley test con-firmed such an assumption, the Greenhouse–Geisser procedurecorrected the degrees of freedom. Duncan test was used for aplanned post hoc testing limited to the statistically significantmain effect group and the statistical interactions including the fac-tor group (p < 0.05). More details are reported in the followingparagraphs.

The first ANOVA aimed at evaluating the working hypothesisthat the regional normalized LORETA solutions were different inamplitude among the ART-HIV, the naïve, and the control groups.The ANOVA design used the factors group (ART-HIV, naïve, andcontrol; independent variable), band (delta, theta, alpha 1, alpha2, beta 1, beta 2), and ROI (central, frontal, parietal, occipital, tem-poral). The planned post hoc testing evaluated the prediction of anormalization of the LORETA delta and alpha 1 sources in theART-HIV subjects.

The second ANOVA aimed at evaluating the working hypothesisthat the regional normalized LORETA solutions differed inamplitude among the ART-HIV+, ART-HIV�, and control subjects.

Table 4Brodmann areas included in the cortical regions of interest (ROIs) of the presentstudy. LORETA solutions were collapsed in frontal, central, parietal, occipital, andtemporal ROIs.

LORETA Brodmann areas into the regions of interest (ROIs)

Frontal 8, 9, 10, 11, 44, 45, 46, 47Central 1, 2, 3, 4, 6Parietal 5, 7, 30, 39, 40, 43Temporal 20, 21, 22, 37, 38, 41, 42Occipital 17, 18, 19


Specifically, the ANOVA design of the LORETA solutions used thesame factor of the first one with the exception of the factor groupthat included ART-HIV+, ART-HIV� and control as independentvariable. The planned post hoc testing evaluated the prediction ofdifferences in amplitude of the LORETA solutions following the pat-tern control = ART-HIV+ – ART-HIV�. According to the previousreference, LORETA study in the treatment-naïve HIV subjects(Babiloni et al., 2012a), we expected the delta sources to be higherin amplitude in the ART-HIV� than in the ART-HIV+ group, and thealpha sources to be lower in amplitude in the ART-HIV� than in theART-HIV+ group.

To test the hypothesis of a relationship between cognitive dys-functions and the regional normalized LORETA solutions showingstatistically significant differences according to the pattern con-trol = ART-HIV+ – ART-HIV�, we computed a statistical correlationbetween an EEG variable of interest and the score of the neuropsy-chological tests used for the assessment of the cognitive functionsin the ART-HIV subjects. This correlation analysis was performedby non-parametric Spearman test with Bonferroni correction(p < 0.05).

3. Results

3.1. Topography of the EEG cortical sources as estimated by LORETA

For illustrative purposes, Fig. 1 maps the grand average of theLORETA solutions (i.e., relative power current density at corticalvoxels) modeling the distributed EEG cortical sources for delta,theta, alpha 1, alpha 2, beta 1, and beta 2 bands in the three groupsof subjects. The control group presented alpha 1 sources with themaximal values of amplitude distributed in parieto-occipital re-gions. Delta, theta, and alpha 2 sources had moderate amplitudevalues when compared to alpha 1 sources. Finally, beta 1 and beta2 sources were characterized by lowest amplitude values.

Compared to the control group, the ART-HIV group showed awidespread decrease in amplitude of theta, alpha 1, alpha 2, andbeta 1 sources. The decrease of alpha power was also more evidentin the treatment-naïve group.

3.2. Statistical comparisons of LORETA EEG sources

Fig. 2 shows mean regional normalized LORETA solutions(distributed EEG sources) relative to a statistical ANOVA interac-tion (F(40,4000) = 2.63; p < 0.00001) among the factors group(control, naïve, and ART-HIV, independent variable), band (delta,theta, alpha 1, alpha 2, beta 1, beta 2), and ROI (frontal, central,parietal, occipital, temporal). In this figure, the LORETA solutionshave the shape of EEG relative power spectra. Notably, profileand magnitude of these spectra in the three groups differed acrossvarious cortical macro-regions. Main results of the planned posthoc testing showed that cortical sources of resting-state theta(frontal, parietal, occipital), alpha 1 (central, occipital, temporal),alpha 2 (frontal, central, parietal, occipital, temporal), beta 1(parietal, occipital, temporal), and beta 2 (temporal) rhythms werelower in amplitude in the ART-HIV than in the control group(p < 0.04–0.00001). Furthermore, cortical sources of resting-stateoccipital and temporal alpha 1 were higher in amplitude in theART-HIV than in the treatment-naïve group (p < 0.001–0.00001),while the opposite was true in the cortical sources of frontal,parietal, occipital, and temporal delta rhythms (p < 0.02–0.0002).

Fig. 3 shows mean regional normalized LORETA solutions (dis-tributed EEG sources) relative to a statistical ANOVA interaction(F(40,2800) = 1.98; p < 0.0003) among the factors group (controlART-HIV+, ART-HIV�), band and ROI. Noteworthy, profile and mag-nitude of these spectra in the two ART-HIV groups differed across



Fig. 1. Grand average of low-resolution brain electromagnetic tomography (LORETA) solutions modeling the distributed electroencephalographic (EEG) cortical sources. Theleft side of the maps (top view) corresponds to the left hemisphere. Legend: LORETA, low-resolution brain electromagnetic tomography. Color scale: all power densityestimates were scaled based on the averaged maximum value (i.e., alpha 1 power value of occipital region in Control). (For interpretation of the references to colour in thisfigure legend, the reader is referred to the web version of this article.)

Fig. 2. Regional normalized LORETA solutions (mean across subjects) relative to a statistical ANOVA among the factors group, band, and ROI. Legend: the rectangles refer tothe cortical regions and frequency bands in which LORETA solutions presented statistically significant comparisons.


Please cite this article in press as: Babiloni C et al. Cortical sources of resting-state EEG rhythms in ‘‘experienced’’ HIV subjects under antiretroviral therapy.Clin Neurophysiol (2014), http://dx.doi.org/10.1016/j.clinph.2014.01.024



various cortical macro-regions. In the control group, the delta andtheta sources were preponderant in the frontal regions, whereasthe alpha sources were preponderant in the parietal and occipitalregions. Furthermore, there was a difference between the controlgroup and the ART-HIV groups. The planned post hoc testingshowed that the parietal, temporal, and occipital sources of rest-ing-state alpha 1 and alpha 2 rhythms were lower in amplitudein the ART-HIV� than in the ART-HIV+ group (p < 0.05–0.00001).Furthermore, these EEG sources were lower in amplitude in bothART-HIV groups than in the control group (p < 0.05–0.00001).

To test the hypothesis that the amplitude of the parietal, occip-ital, and temporal alpha 1 sources is related to relevant cognitivefunctions in the ART-HIV subjects as a whole group, we computeda statistical correlation between an EEG variable of interest and thescore of the seven neuropsychological tests mentioned in the‘‘Methods’’ section. To reduce the repetitions of the univariate test-ing, we averaged the amplitude of the parietal, occipital, and tem-poral alpha 1 sources to produce such EEG variables to be used asan input for the correlation analysis by Spearman test (p < 0.05). Ofnote, the temporal, parietal, and occipital cortical regions are ofspecial interest as they showed dominant alpha 1 rhythms in theresting-state condition. Furthermore, they were characterized bythe maximum statistical difference of the alpha 1 power betweenthe ART-HIV+ and the ART-HIV� group. Bonferroni correction forseven repetitions of the analysis gave a threshold of p < 0.007 tohave p < 0.05 corrected. Results showed only a positive statisticalcorrelation between the amplitude of the averaged alpha sourcesand the score of Rey list delayed recall (r = 0.39, p = 0.003). Thescatter plot of this correlation is illustrated in Fig. 4.

3.3. Control results

As a first control analysis, we performed an ANOVA for each fre-quency band of interest. The results confirmed those obtained bythe single ANOVA including the factor band. Specifically, the ANO-VAs showed a significant interaction between the factors groupand ROI for the following bands: theta (p < 0.05), alpha 1(p < 0.05), alpha 2 (p < 0.01), and beta (p < 0.05).

Fig. 3. Regional normalized LORETA solutions (mean across subjects) relative to a statirectangles refer to the cortical regions and frequency bands in which LORETA solutions(p < 0.05). (For interpretation of the references to colour in this figure legend, the reade


In order to investigate the relationship among the mentionedeffects on theta, alpha, and beta bands, we made a control correla-tion analysis between the sources of the alpha rhythms and thoseof the theta and beta rhythms in the ART-HIV subjects (Pearson’stest, p < 0.05). Results showed a statistically significant correlationbetween the alpha sources and those of the theta and beta bands(p < 0.05). Table 5 reports the r and p values of such a control cor-relation analysis.

Main results of the present study showed that the effects of thecART on immune activity (i.e., CD4 counts) were related to the cor-tical sources of EEG rhythms in the HIV subjects. In the same vein,a control analysis was performed to confirm the relationship be-tween the effects of the cART and EEG variables using anotherprobe of the therapy such as the VL. In the present database, 12out of 70 ART-HIV subjects showed VL > 20. For the purpose of thiscontrol analysis, we selected two subgroups of ART-HIV subjectspaired for demographic and level of immune activity (i.e., CD4count): those with VL > 20 copies (VL + group, N = 12;VL = 2554.41; range: 24–18,530; MMSE = 27.8, mean age = 48.6,CD4 = 524) and those with VL < 20 copies (VL� group, N = 35,MMSE = 27.5, mean age = 49.2, CD4 = 521). The ANOVA designused the normalized regional LORETA solutions as a dependentvariable and included the factors group (VL+, VL�; independentvariable), band (delta, theta, alpha 1, alpha 2, beta 1, beta 2), andROI (frontal, central, parietal, occipital, temporal). Main resultsshowed a statistical interaction (F(20,900) = 2.34; p < 0.001) amongthe three factors, while the planned post hoc testing indicated thatwidespread cortical sources of resting-state parietal, occipital andtemporal alpha 1 rhythms were lower in amplitude in the VL�than in the VL+ group (p < 0.05–0.00001). These results corrobo-rated those of the main analysis showing that these alpha sourceswere lower in amplitude in the ART-HIV� (<500 CD4) than in theART-HIV+ (>500 CD4) subgroups.

4. Discussion

In a previous study of our group, treatment-naïve HIV subjectswere characterized by diffuse abnormalities of the cortical sources

stical ANOVA interaction among the factors group, band, and ROI. Legend: the redpresented statistically significant LORETA patterns Control > ART-HIV+ > ART-HIV�r is referred to the web version of this article.)



Fig. 4. Scatter plot relative to the results of a correlation analysis between episodic memory performance as expressed by Rey list delayed recall (Reydiff) and the amplitudeof EEG variable of interest of alpha 1 sources in ART-HIV subjects as a whole group. Reydiff positively correlated with the magnitude of alpha 1 sources(r = 0.39, p = 0.003).

Table 5Correlation analysis between the sources of the alpha rhythms and those of the thetaand beta rhythms in the ART-HIV subjects.

Alpha 1 Theta Central Parietal Temporal

Central P = 0.003r = 0.3585

Parietal P = 0.001r = 0.3866

Temporal p = 0.0001r = 0.5185

Alpha 1 Beta 1 Parietal Occipital Temporal

Temporal p = 0.046r = 0.2424

Occipital p = 0.001r = 0.3847

Temporal p = 0.002r = 0.3717


of resting-state EEG rhythms associated with cognitive deficits(Babiloni et al., 2012a). Here, the same methodological approachwas used to investigate the candidate EEG biomarkers of ART-HIV subjects. The present cross-sectional design study tested thehypothesis that in ART-HIV subjects, cortical sources of resting-state EEG rhythms are related to biological variables possiblyreflecting the therapy success. Based on the CD4 count, the ART-HIV subjects were divided into two subgroups and the corticalsources of resting-state EEG rhythms were compared to those ofa group of age-matched control subjects. Results showed no differ-ence in amplitude of the delta sources between the ART-HIV andthe control group as a possible beneficial effect of the therapyand features of the infection. By contrast, widespread corticalsources of theta, alpha, and beta rhythms were lower in amplitudein the ART-HIV than in the control group. These sources alsoshowed a remarkable cross-correlation in the ART-HIV group as apossible unselective desynchronizing effect of the infection onthe physiological mechanisms generating the EEG oscillations indifferent frequency bands. Furthermore, the parietal, occipital,and temporal low-frequency alpha sources were positively corre-lated to memory function as probed by Rey list delayed recall.


Moreover, they were lower in amplitude in the ART-HIV subjectswith poor immune activity (ART-HIV�) than in those with higherimmune activity (ART-HIV+), the effect not being explained bythe disease duration. In the same vein, a control analysis showedthat when the level of immune activity was paired, the parietal,occipital, and temporal sources of low-frequency alpha rhythmswere lower in amplitude in the ART-HIV subjects with higher VL(>20 copies) than in those with lower VL (<20 copies). Finally,the occipital and temporal sources of low-frequency alpha rhythmswere lower in amplitude in the treatment-naïve HIV than in the‘‘experienced’’ ART-HIV group. Moreover, the opposite was truefor widespread pathological delta sources, namely, they were high-er in amplitude in the treatment-naïve HIV than in the ‘‘experi-enced’’ ART-HIV group.

The present results can be interpreted in light of previous stud-ies using the same methodological approach in amnestic MCI andAD subjects. It has been shown that higher delta and lower alphasources were related to cognitive deficits (Babiloni et al., 2006d,2011a,b, 2012b). Furthermore, the amplitude of the frontal deltasources correlated with the atrophy of frontal white matter(Babiloni et al., 2006d). Finally, the amplitude of the delta and al-pha sources correlated with the global atrophy of cortical graymatter volume (Babiloni et al., 2012b).

The present results also extend previous evidence showing thatposterior alpha (8–12 Hz) rhythms and cognitive abilities werelower in HIV patients than in control subjects, with a partial nor-malization by cART (Gruzelier et al., 1996; Harrison et al., 1998;Baldeweg and Gruzelier, 1997; Baldeweg et al., 1997). In a previousreference study, treatment-naïve HIV subjects were characterizedby a higher amplitude of central-parietal sources of delta rhythms(<4 Hz) and a lower amplitude of widespread sources of low- andhigh-frequency alpha rhythms (Babiloni et al., 2012a).

In the present study, cART could not avoid a general impairmentof the brain synchronization mechanisms generating theta, alpha,and beta sources in the ART-HIV group. When especially effectiveon the immune system (i.e., in the ART-HIV+ subjects), the therapyjust limited the derangement of parietal, temporal, and occipital al-pha sources. What is the physiological meaning of these effects?An overview of the reference neurophysiologic model is reported




in the following section. In the physiological condition of awakeeyes-closed resting state, cortical delta and theta rhythms are typ-ically negligible; cortical beta rhythms are prominent in motorareas, while cortical alpha rhythms are the most important oscilla-tory activity and are dominant in visual, somato-motor and audi-tory areas (Rossini et al., 1991; Klimesch, 1996, 1997, 1998;Pfurtscheller and Lopez da Silva, 1999). The cortical alpha rhythmsmight reflect cycles of excitation and inhibition, gating the flow ofthe sensory and motor information from thalamus to the cerebralcortex during the eyes-closed condition (Pfurtscheller and Lopezda Silva, 1999), whereas they might frame perceptual events in dis-crete snapshots of around 70–100 ms during active sensory andmotor information processing (Fingelkurts and Fingelkurts, 2006;Mathewson et al., 2009). In this theoretical framework, the low-frequency (8–10.5 Hz) alpha rhythms would reflect the fluctuationof the global cortical arousal and attention during the resting-statecondition (Klimesch, 1996; Klimesch et al., 1997; Klimesch et al.,1998; Rossini et al., 1991). The higher the amplitude of the occip-ital alpha rhythms, the lower the local cortical arousal as demon-strated by the co-registration of resting-state EEG rhythms andfMRI (Laufs et al., 2003; Gonçalves et al., 2006; Mantini et al.,2007). Previous EEG-fMRI evidence also emphasized the importantrole of the thalamus in the generation of the cortical alpharhythms, namely the higher the cortical alpha power, the higherthe thalamic activation (Gonçalves et al., 2006). Keeping in mindthe above findings and theoretical overview, it can be speculatedthat, when successful, cART restores the functional connectivitybetween thalamus and cerebral cortex that inhibits corticofugalslow oscillations (<1 Hz) and related thalamic-generated deltarhythms (1–4 Hz) in the condition of awake resting-state (Steriade,2003).

4.1. Conclusions

The present cross-sectional design study tested the hypothesisthat the cortical sources of resting-state EEG rhythms change asa function of HIV-relevant biological variables and ART in HIV pa-tients. Results showed that widespread theta, alpha, and betasources were lower in amplitude in the ART-HIV than in the con-trol group. Furthermore, parietal, occipital, and temporal alpha 1sources were lower in amplitude in the ART-HIV subjects with lessimmune activity (<500 CD4) than in the ART-HIV subjects withmore immune activity (>500 CD4) subjects. Moreover, the ART-HIV subjects showed normal delta sources, in contrast to the EEGabnormalities observed in a group of treatment-naïve HIV subjectswith high values of VL. These results suggest that in ‘‘experienced’’ART-HIV subjects compared to treatment-naïve HIV patients andcontrol subjects, cortical sources of the resting-state alpha rhythmsare related to systemic immune activity and might be sensitive tothe interaction between the therapy and features of the infection.

When considering the present results, it should be remarkedthat this is just an exploratory study aimed at evaluating the rela-tionship between new markers of resting-state EEG sources andrelevant dimensions of HIV infections and ART. We manipulatedbasic variables such as CD4 count with an arbitrary threshold of500 cells typically used as a threshold for the beginning of ARTin treatment-naïve HIV patients, virus copies (VL > 20), and admin-istration of a chronic therapy. It can be argued that the significanceof the CD4 count before the start of the therapy and along ART maybe different, so this threshold is quite arbitrary (as any other CD4count threshold). Furthermore, there is no clear evidence that acount of CD4 < 500 can be regarded as a marker of a lack of therapyresponse, and it is probable that a complex interaction betweenHIV infection and immune system prevents the definition of sucha threshold. HIV infection might impair immune system and capa-bility to generate CD4 before the start of the ART therapy, while


such therapy might indeed reduce copies of the HIV virus. Finally,both CD4 count and HIV VL in plasma might not be directly relatedto virus activity in the brain. Despite its intrinsic limitations, thepreliminary results of the present study provide first evidence thatcortical sources of resting-state EEG rhythms are promising bio-markers of the effects of ART on HIV patients’ brain compartmentfor future longitudinal studies. In particular, cortical sources ofresting-state alpha rhythms directly may capture an abnormalmechanism of inhibitory cortical neural synchronization in HIV pa-tients during wakeful and non-goal-oriented mental activity(Pfurtscheller and Lopez da Silva, 1999). Future studies should clar-ify if such abnormal alpha rhythms in HIV patients are the conse-quence of a (compartmentalized) viral infection of brain tissue orrather a question of immune status. They will have also to elabo-rate on the relation of brain infection and EEG alteration in moredetail for future application to drug discovery and monitoring.

Acknowledgments

This work is dedicated to the memory of Dr. Elisabetta Vernetti.This research was developed thanks to the financial support of Fat-ebenefratelli Association for Biomedical Research (AFaR), TosinvestSanità (Pisana), and to the unrestricted financial contribution ofViiV Healthcare Italy.

References

Ances BM, Roc AC, Korczykowski M, Wolf RL, Kolson DL. Combination antiretroviraltherapy modulates the blood oxygen level-dependent amplitude in humanimmunodeficiency virus-seropositive patients. J Neurovirol 2008;14:418–24.

Ances BM, Sisti D, Vaida F, Liang CL, Leontiev O, Perthen JE, et al. Resting cerebralblood flow: a potential biomarker of the effects of HIV in the brain. Neurology2009;73:702–7028.

Andersen AB, Law I, Krabbe KS, Bruunsgaard H, Ostrowski SR, Ullum H, et al.Cerebral FDG-PET scanning abnormalities in optimally treated HIV patients. JNeuroinflammation 2010;7:13.

Anthony IC, Bell JE. The Neuropathology of HIV/AIDS. Int Rev Psychiat2008;20:15–24.

Antinori A, Trotta MP, Lorenzini P, Torti C, Gianotti N, Maggiolo F, et al. Virologicalresponse to salvage therapy in HIV-infected persons carrying the reversetranscriptase K65R mutation. Antivir Ther 2007;12:1175–83.

Babiloni C, Binetti G, Cassetta E, Cerboneschi D, Dal Forno G, Del Percio C, et al.Mapping distributed sources of cortical rhythms in mild Alzheimers disease: amulti-centric EEG study. NeuroImage 2004;22:57–67.

Babiloni C, Binetti G, Cassarino A, Dal Forno G, Del Percio C, Ferreri F, et al. Sources ofcortical rhythms in adults during physiological aging: a multi-centric EEGstudy. Hum Brain Mapp 2006a;27:162–72.

Babiloni C, Binetti G, Cassetta E, Dal Forno G, Del Percio C, Ferreri F. Sources ofcortical rhythms change as a function of cognitive impairment in pathologicalaging: a multi-centric study. Clin Neurophysiol 2006b;117:252–68.

Babiloni C, Benussi L, Binetti G, Bosco P, Busonero G, Cesaretti S, et al. Genotype(cystatin C) and EEG phenotype in Alzheimer disease and mild cognitiveimpairment: a multicentric study. NeuroImage 2006c;29:948–64.

Babiloni C, Frisoni G, Steriade M, Bresciani L, Binetti G, Del Percio C, et al. Frontalwhite matter volume and delta EEG sources negatively correlate in awakesubjects with mild cognitive impairment and Alzheimer’s disease. ClinNeurophysiol 2006d;117:1113–29.

Babiloni C, Cassetta E, Dal Forno G, Del Percio C, Ferreri F, Ferri R. Donepezil effectson sources of cortical rhythms in mild Alzheimer’s disease: responders vs. non-responders. NeuroImage 2006e;31:1650–65.

Babiloni C, Cassetta E, Binetti G, Tombini M, Del Percio C, Ferreri F, et al. Resting EEGsources correlate with attentional span in mild cognitive impairment andAlzheimer’s disease. Eur J Neurosci 2007a;25:3742–57.

Babiloni C, Squitti R, Del Percio C, Cassetta E, Ventriglia MC, Ferreri F, et al. Freecopper and resting temporal EEG rhythms correlate across healthy, mildcognitive impairment, and Alzheimer’s disease subjects. Clin Neurophysiol2007b;118:1244–60.

Babiloni C, Bosco P, Ghidoni R, Del Percio C, Squitti R, Binetti G, et al. Homocysteineand electroencephalographic rhythms in Alzheimer disease: a multicentricstudy. Neuroscience 2007c;145:942–54.

Babiloni C, Frisoni GB, Pievani M, Toscano L, Del Percio C, Geroldi C, et al. White-matter vascular lesions correlate with alpha EEG sources in mild cognitiveimpairment. Neuropsychologia 2008;46:1707–20.

Babiloni C, Frisoni GB, Pievani M, Vecchio F, Lizio R, Buttiglione M, et al.Hippocampal volume and cortical sources of EEG alpha rhythms in mildcognitive impairment and Alzheimer disease. NeuroImage 2009a;44:123–35.


http://refhub.elsevier.com/S1388-2457(14)00063-7/h0005



















































Babiloni C, Frisoni GB, Del Percio C, Zanetti O, Bonomini C, Cassetta E, et al.Ibuprofen treatment modifies cortical sources of EEG rhythms in mildAlzheimer’s disease. Clin Neurophysiol 2009b;120:709–18.

Babiloni C, Lizio R, Vecchio F, Frisoni GB, Pievani M, Geroldi C, et al. Reactivity ofcortical alpha rhythms to eye opening in mild cognitive impairment andAlzheimer’s disease: an EEG study. J Alzheimers Dis 2010;22:1047–64.

Babiloni C, Frisoni GB, Vecchio F, Lizio R, Pievani M, Cristina G, et al. Stability ofclinical condition in mild cognitive impairment is related to cortical sources ofalpha rhythms: an electroencephalographic study. Hum Brain Mapp2011a;32:1916–31.

Babiloni C, De Pandis MF, Vecchio F, Buffo P, Sorpresi F, Frisoni GB, et al. Corticalsources of resting state electroencephalographic rhythms in Parkinson’s diseaserelated dementia and Alzheimer’s disease. Clin Neurophysiol2011b;122:2355–64.

Babiloni C, Lizio R, Carducci F, Vecchio F, Redolfi A, Marino S, et al. Resting statecortical electroencephalographic rhythms and white matter vascular lesions insubjects with Alzheimer’s disease: an Italian multicenter study. J AlzheimersDis 2011c;26:331–46.

Babiloni C, Vecchio F, Buffo P, Onorati P, Muratori C, Ferracuti S, et al. Corticalsources of resting-state EEG rhythms are abnormal in naïve HIV subjects. ClinNeurophysiol 2012a;123:2163–71.

Babiloni C, Carducci F, Lizio R, Vecchio F, Baglieri A, Bernardini S, et al. Resting statecortical electroencephalographic rhythms are related to gray matter volume insubjects with mild cognitive impairment and Alzheimer’s disease. Hum BrainMapp 2012. http://dx.doi.org/10.1002/hbm.22005.

Baldeweg T, Gruzelier JH. Alpha EEG activity and subcortical pathology in HIVinfection. Int J Psychophysiol 1997;26:431–42.

Baldeweg T, Catalan J, Pugh K, Gruzelier J, Lovett E, Scurlock H, et al.Neurophysiological changes associated with psychiatric symptoms in HIV-infected individuals without AIDS. Biol Psychiatry 1997;41:474–87.

Bauer LO, Shanley JD. ASPD blunts the effects of HIV and antiretroviral treatment onevent-related brain potentials. Neuropsychobiology 2006;53:17–25.

Besthorn C, Zerfass R, Geiger-Kabisch C, Sattel H, Daniel S, Schreiter-Gasser U, et al.Discrimination of Alzheimer’s disease and normal aging by EEG data.Electroencephalogr Clin Neurophysiol 1997;103:241–8.

Buchan RJ, Nagata K, Yokoyama E, Langman P, Yuya H, Hirata Y, et al. Regionalcorrelations between the EEG and oxygen metabolism in dementia ofAlzheimer’s type. Electroencephalogr Clin Neurophysiol 1997;103:409–17.

Carlesimo GA, Caltagirone C, Gainotti G. The group for the standardization of themental deterioration battery. The mental deterioration battery: normative data,diagnostic reliability and qualitative analyses of cognitive impairment. EurNeurol 1996;36:378–84.

Caso F, Cursi M, Magnani G, Fanelli G, Falautano M, Comi G, Leocani L, Minicucci F.Quantitative EEG and LORETA: valuable tools in discerning FTD from AD?Neurobiol Aging 2012;33:2343–56.

Chalmers AC, Aprill BS, Shepherd H. CSF and HIV. Arch Neurol 1990;150:1538–40.Chavanet PU, Giroud BS, Lancon JP, Borsotti JP, Waldner-Combernoux AC, Pillon D,

et al. Altered peripheral nerve conduction in HIV patients. Cancer Detect Prev1988;12:249–57.

Clifford DB. HIV-associated neurocognitive disease continues in the antiretroviralera. Top HIV Med 2008;16:94–8.

Cook IA, Leuchter AF. Synaptic dysfunction in Alzheimer’s disease: clinicalassessment using quantitative EEG. Behav Brain Res 1996;78:15–23.

Cysique LA, Vaida F, Letendre S, Gibson S, Cherner M, Woods SP, et al. Dynamics ofcognitive change in impaired HIV-positive patients initiating antiretroviraltherapy. Neurology 2009;73:342–8.

Dierks T, Ihl R, Frolich L, Maurer K. Dementia of the Alzheimer type: effects on thespontaneous EEG described by dipole sources. Psychiatry Res 1993;50:51–162.

Dierks T, Jelic V, Pascual-Marqui RD, Wahlund LO, Julin P, Linden DEJ, et al. Spatialpattern of cerebral glucose metabolism (PET) correlates with localization ofintracerebral EEG-generators in Alzheimer’s disease. Clin Neurophysiol2000;111:1817–24.

Fauci SAS, Lane HC. HIV disease – AIDS and related disorders. In: Fauci SAS,Braunwald E, Esselbacher RT, et al., editors. Harrison’s principle of internalmedicine. 14th ed. USA: McGraw Hill Co.; 1998. p. 1791–855.

Fingelkurts AA, Fingelkurts AA. Timing in cognition and EEG brain dynamics:discreteness versus continuity. Cogn Process 2006;7:135–62.

Folstein MF, Folstein SE, McHugh PR. ‘‘Mini-mental state’’. A practical method forgrading the cognitive state of patients for the clinician. J Psychiatr Res1975;12:189–98.

Gastaut JL, Gastaut JA, Pellissier JF, Tapco JB, Weill O. Peripheral neuropathies in HIVinfections – a prospective study of 56 cases. Rev Neurol 1989;145:451–9.

Gianotti LR, Künig G, Faber PL, Lehmann D, Pascual-Marqui RD, Kochi K, et al.Rivastigmine effects on EEG spectra and three-dimensional LORETA functionalimaging in Alzheimer’s disease. Psychopharmacology 2008;198:323–32.

Gonçalves SI, de Munck JC, Pouwels PJ, Schoonhoven R, Kuijer JP, Maurits NM, et al.Correlating the alpha rhythm to BOLD using simultaneous EEG/fMRI: inter-subject variability. NeuroImage 2006;30:203–13.

Graham BS, Belshe RB, Clements ML, Dolin R, Corey L, Wright PF, et al. Vaccinationof vaccinia-naïve adults with human immunodeficiency virus type 1 gp160recombinant vaccinia virus in a blinded, controlled, randomized clinical trial.The AIDS vaccine clinical trials network. J Infect Dis 1992;166:244–52.

Gruzelier J, Burgess A, Baldeweg T, Riccio M, Hawkins D, Stygall J, et al. Prospectiveassociations between lateralised brain function and immune status in HIVinfection: analysis of EEG, cognition and mood over 30 months. Int JPsychophysiol 1996;23:215–24.


Hammer SM, Squires KE, Hughes MD, Grimes JM, Demeter LM, Currier JS, et al. Acontrolled trial of two nucleoside analogues plus indinavir in persons withhuman immunodeficiency virus infection and CD4 cell counts of 200 per cubicmillimeter or less. AIDS Clinical Trials Group 320 Study Team. N Engl J Med1997;337:725–33.

Harrison MJ, Newman SP, Hall-Craggs MA, Fowler CJ, Miller R, Kendall BE, et al.Evidence of CNS impairment in HIV infection: clinical, neuropsychological, EEG,and MRI/MRS study. J Neurol Neurosurg Psychiatry 1998;65:301–7.

Holschneider DP, Waite JJ, Leuchter AF, Walton NY, Scremin OU. Changes inelectrocortical power and coherence in response to the selective cholinergicimmunotoxin 192 IgG-saporin. Exp Brain Res 1999;126:270–80.

Hunt PW, Deeks SG, Rodriguez B, Valdez H, Shade SB, Abrams DI. Continued CD4 cellcount increases in HIV-infected adults experiencing 4 years of viral suppressionon antiretroviral therapy. AIDS 2003;17:1907–15.

Jelic V, Shigeta M, Julin P, Almkvist O, Winblad B, Wahlund LO. Quantitativeelectroencephalography power and coherence in Alzheimer’s disease and mildcognitive impairment. Dementia 1996;7:314–23.

Klimesch W. Memory processes, brain oscillations and EEG synchronization. Int JPsychophysiol 1996;24:61–100.

Klimesch W. EEG alpha and theta oscillations reflect cognitive and memoryperformance: a review and analysis. Brain Res Brain Res Rev 1999;29:169–95.

Klimesch W, Doppelmayr M, Pachinger T, Russegger H. Event-relateddesynchronization in the alpha band and the processing of semanticinformation. Brain Res Cogn Brain Res 1997;6:83–94.

Klimesch W, Doppelmayr M, Russegger H, Pachinger T, Schwaiger J. Induced alphaband power changes in the human EEG and attention. Neurosci Lett1998;244:73–6.

Kolev V, Yordanova J, Basar-Eroglu C, Basar E. Age effects on visual EEG responsesreveal distinct frontal alpha networks. Clin Neurophysiol 2002;113:901–10.

Laufs H, Kleinschmidt A, Beyerle A, Eger E, Salek-Haddadi A, Preibisch C. EEG-correlated fMRI of human alpha activity. NeuroImage 2003;19:1463–76.

Leuchter AF, Cook IA, Newton TF, Dunkin J, Walter DO, et al. Regional differences inbrain electrical activity in dementia: use of spectral power and spectral ratiomeasures. Electroenceph Clin Neurophysiol 1993;87:385–93.

Mantini D, Perrucci MG, Cugini S, Ferretti A, Romani GL, Del Gratta C. Completeartifact removal for EEG recorded during continuous fMRI using independentcomponent analysis. NeuroImage 2007;34:598–607.

Mathewson KE, Gratton G, Fabiani M, Beck DM, Ro T. To see or not to see:prestimulus alpha phase predicts visual awareness. J Neurosci2009;29:2725–32.

McArthur JC. Neurological manifestations of AIDS. Medicine 1987;26:601–11.Moretti DV, Babiloni F, Carducci F, Cincotti F, Remondini E, Rossini PM, et al.

Computerized processing of EEG-EOG-EMG artifacts for multicentirc studies inEEG oscillations and event-related potentials. Int J Pshycophysiol2003;47:199–216.

Nishida K, Yoshimura M, Isotani T, Yoshida T, Kitaura Y, Saito A, et al. Differences inquantitative EEG between frontotemporal dementia and Alzheimer’s disease asrevealed by LORETA. Clin Neurophysiol 2011;122:1718–25.

Nobili F, Cutolo M, Sulli A, Castaldi A, Sardanelli F, Accardo S, et al. Impairedquantitative cerebral blood flow in scleroderma patients. J Neurol Sci1997;152:63–71.

Novelli G, Papagno C, Capitani E, Laiacona N, Vallar G, Cappa SF. Tre test clinici diricerca e produzione lessicale. Taratura su soggetti normali. Arch. PsicologiaNeurol. Psichiatria 1986;47:477–506.

Nunez P. Neocortical dynamics and human EEG rhythms. New York: OxfordUniversity Press; 1995.

Nuwer MR. Quantitative EEG. I: techniques and problems of frequency analysis andtopographic mapping. J Clin Neurophysiol 1988;5:1–43.

Pascual-Marqui RD, Michel CM. LORETA (low resolution brain electromagnetictomography): new authentic 3D functional images of the brain. ISBETNewsletter ISSN 1994;5:4–8.

Pascual-Marqui RD, Lehmann D, Koenig T, Kochi K, Merlo MC, Hell D, et al. Lowresolution brain electromagnetic tomography (LORETA) functional imaging inacute, neuroleptic-naïve, first-episode, productive schizophrenia. PsychiatryRes 1999;90:169–79.

Pascual-Marqui RD, Esslen M, Kochi K, Lehmann D. Functional imaging with lowresolution brain electromagnetic tomography (LORETA): a review. MethodsFind Exp Clin Pharmacol 2002;24:91–5.

Pfurtscheller G. Lopez da Silva F. Event-related EEG/MEG synchronization anddesynchronization: basic principles. Clin Neurophysiol 1999;110:1842–57.

Pucci E, Belardinelli N, Cacchio G, Signorino M, Angeleri F. EEG power spectrumdifferences in early and late onset forms of Alzheimer’s disease. ClinNeurophysiol 1999;110:621–31.

Reitan R. Validity of the Trail Making Test as an indication of organic brain damage.Percept Mot Skills 1958;8:271–6.

Rey (Hrsg.) A. Memorisation d‘une serie de 15 mots en 5 repetitions. In: Rey A,editor. L‘examen clinique en psychologie. Paris: L‘examen clinique enpsychologie. Presses Universitaires de France; 1958.

Roberts TK, Buckner CM, Berman JW. Leukocyte transmigration across the blood–brain barrier: perspectives on neuroAIDS. Front Biosci 2010;15:478–536.

Rodriguez G, Vitali P, De Leo C, De Carli F, Girtler N, Nobili F. Quantitative EEGchanges in Alzheimer patients during long-term donepezil therapy.Neuropsychobiology 2002;46:49–56.

Rossini PM, Desiato MT, Lavaroni F, Caramia MD. Brain excitability andelectroencephalographic activation: non-invasive evaluation in healthyhumans via transcranial magnetic stimulation. Brain Res 1991;567:111–9.























http://dx.doi.org/10.1002/hbm.22005
























































































































































Rossini PM, Rossi S, Babiloni C, Polich J. Clinical neurophysiology of aging brain:from normal aging to neurodegeneration. Prog Neurobiol 2007;83:375–400.

Saletu B, Anderer P, Saletu-Zyhlarz GM, Pascual-Marqui RD. EEG mapping and low-resolution brain electromagnetic tomography (LORETA) in diagnosis andtherapy of psychiatric disorders: evidence for a key–lock principle. Clin EEGNeurosci 2005;36:108–15.

Selnes OA. Memory loss in persons with HIV/AIDS: assessment and strategies forcoping. AIDS Read 2005;15(289–292):294.

Sevigny JJ, Albert SM, McDermott MP, McArthur JC, Sacktor N, Conant K, et al.Evaluation of HIV RNA and markers of immune activation as predictors of HIV-associated dementia. Neurology 2004;63:2084–90.

Spinnler H, Tognoni G. Standardizzazione e taratura italiana di testneuropsicologici. Ital J Neurol Sci 1987;8:1–120.

Steriade M. The corticothalamic system in sleep. Front Biosci 2003;8:878–99.Szelies B, Mielke R, Kessler J, Heiss WD. EEG power changes are related to regional

cerebral glucose metabolism in vascular dementia. Clin Neurophysiol1999;110:615–20.


Valdès P, Picton TW, Trujillo N, Bosch J, Aubert E, Riera J. ConstrainingEEG-MEG source imaging with statistical neuroanatomy. NeuroImage1998;4:635.

Williams MA, Trout R, Spector SA. HIV-1 gp120 modulates the immunologicalfunction and expression of accessory and co-stimulatory molecules ofmonocyte-derived dendritic cells. J Hematother Stem Cell Res 2002;11:829–47.

Williams DW, Eugenin EA, Calderon TM, Berman JW. Monocyte maturation, HIVsusceptibility, and transmigration across the blood brain barrier are critical inHIV neuropathogenesis. J Leukoc Biol 2012;91:401–15.

Zappasodi F, Salustri C, Babiloni C, Cassetta E, Del Percio C, Ercolani M, et al. Anobservational study on the influence of the APOE-epsilon4 allele on thecorrelation between ‘free’ copper toxicosis and EEG activity in Alzheimerdisease. Brain Res 2008;1215:183–9.

































Cortical sources of resting-state EEG rhythms in “experienced” HIV subjects under antiretroviral...

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