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Journal of Affective Disorders ∎ (∎∎∎∎) ∎∎∎–∎∎∎ Contents lists available at SciVerse ScienceDirect Journal of Affective Disorders journal homepage: www.elsevier.com/locate/jad Research report Alpha absolute power measurement in panic disorder with agoraphobia patients Marcele Regine de Carvalho a,b,c,n, Bruna Brandão Velasques c,d,g, Rafael C. Freire a,b, Maurício Cagy c,e, Juliana Bittencourt Marques c, Silmar Teixeira c,h,i, Bernard P. Rangé j, Roberto Piedade c, Pedro Ribeiro c,d,f, Antonio Egidio Nardi a,b, Hagop Souren Akiskal k a Laboratory of Panic and Respiration, Institute of Psychiatry of Federal University of Rio de Janeiro (IPUB/UFRJ), Rio de Janeiro, Brazil National Institute of Translational Medicine (INCT-TM), Rio de Janeiro, Brazil c Brain Mapping and Sensory Motor Integration, Institute of Psychiatry of Federal University of Rio de Janeiro (IPUB/UFRJ), Rio de Janeiro, Brazil d Institute of Applied Neuroscience (INA), Rio de Janeiro, Brazil e Division of Epidemiology and Biostatistics, Institute of Community Health, Federal, Fluminense University (UFF), Rio de Janeiro, Brazil f Bioscience Department (EEFD/ UFRJ), School of Physical Education, Rio de Janeiro, Brazil g Neuromuscular Research Laboratory, National Institute of Traumatology and Orthopaedics (NITO), Rio de Janeiro, Brazil h Physiotherapy Department – Piquet Carneiro Policlinic – State University of Rio de Janeiro, Brazil. i Laboratory of Physical Therapy, Veiga de Almeida University, Rio de Janeiro, Brazil. j Institute of Psychology of Federal University of Rio de Janeiro (IP/UFRJ), Rio de Janeiro, Brazil. k International Mood Center, University of California, San Diego, La Jolla, USA b art ic l e i nf o a b s t r a c t Article history: Received 12 March 2013 Received in revised form 5 June 2013 Accepted 5 June 2013 Background: Panic attacks are thought to be a result from a dysfunctional coordination of cortical and brainstem sensory information leading to heightened amygdala activity with subsequent neuroendocrine, autonomic and behavioral activation. Prefrontal areas may be responsible for inhibitory top-down control processes and alpha synchronization seems to reflect this modulation. The objective of this study was to measure frontal absolute alpha-power with qEEG in 24 subjects with panic disorder and agoraphobia (PDA) compared to 21 healthy controls. Methods: qEEG data were acquired while participants watched a computer simulation, consisting of moments classified as “high anxiety”(HAM) and “low anxiety” (LAM). qEEG data were also acquired during two rest conditions, before and after the computer simulation display. Results: We observed a higher absolute alpha-power in controls when compared to the PDA patients while watching the computer simulation. The main finding was an interaction between the moment and group factors on frontal cortex. Our findings suggest that the decreased alpha-power in the frontal cortex for the PDA group may reflect a state of high excitability. Conclusions: Our results suggest a possible deficiency in top-down control processes of anxiety reflected by a low absolute alpha-power in the PDA group while watching the computer simulation and they highlight that prefrontal regions and frontal region nearby the temporal area are recruited during the exposure to anxiogenic stimuli. & 2013 Elsevier B.V. All rights reserved. Keywords: Absolute alpha-power Panic disorder qEEG Frontal cortex Neurobiology Brain mapping 1. Introduction Panic attacks (PA) are defined as sudden periods of intense fear or discomfort, where various somatic and cognitive symptoms are experienced, such as accelerated heart rate, sweating, trembling, smothering, chest pain, nausea, dizziness, fear of losing control, and fear of dying. Panic disorder (PD) patients experience recurrent PA and fear their future repetition and consequences (APA, 2000). The PA also n Corresponding author at: Rua Desembargador Izidro, 40/504, 20521-160 Rio de Janeiro, Brazil. Tel.: +55 21 2436 8202; cell: +55 21 9658 7080; fax: +55 21 2523 6839. E-mail address: [email protected] (M.R. de Carvalho). produces behavioral changes and decrease the quality of life of those with PD (APA, 2000). PD subjects have elevated prevalence of comorbid mental disorders (Goodwin and Gotlib, 2004). Agoraphobia (AG) is associated with substantial clinical severity and impairment relative to those with PD uncomplicated by agoraphobia (Pollack and Smoller, 1995; White and Barlow, 2002; Kessler et al., 2006). PD affects 3–4% of the general population and the lifetime prevalence estimates are 22.7% for PA, 3.7% for PD without AG and 1.1% for Panic Disorder with Agoraphobia (PDA) (Kessler et al., 2006). Gorman et al. (2000) developed one of the most influential hypotheses of the PD neurocircuitry. They suggest that PA result from a dysfunctional coordination of cortical and brainstem sensory information leading to a heightened amygdala activity 0165-0327/$ - see front matter & 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jad.2013.06.002 Please cite this article as: de Carvalho, M.R., et al., Alpha absolute power measurement in panic disorder with agoraphobia patients. Journal of Affective Disorders (2013), http://dx.doi.org/10.1016/j.jad.2013.06.002i M.R. de Carvalho et al. / Journal of Affective Disorders ∎ (∎∎∎∎) ∎∎∎–∎∎∎ 2 with subsequent neuroendocrine, autonomic and behavioral activation. Gorman et al. (2000) states that the medial prefrontal cortex (PFC), along with other cortical sites that process higher order sensory information is important in modulating anxiety responses and inhibiting amygdala firing. The PFC's activity is associated with attempts to regulate the outcome of attentional, interpretive and associative processes triggered by the occurrence of potentially threat related cues. Amygdala activity (directly activated by the thalamus or activated by the lack of PFC inhibition), in turn, may trigger activity of some subcortical sites, typical of PA symptoms (Dresler et al., 2013; Martin et al., 2009; De Carvalho et al., 2010; Stein, 2005). Lateral PFC and orbitofrontal cortex have been associated with cognitive strategies to regulate emotion, such as reappraisal; dorsolateral prefrontal activity has been related to the use of proactive metacognitive strategies aimed at self-regulating the fear and anxiety evoked by the anxiogenic stimuli (Aupperle et al., 2009). More generally, the PFC is believed to govern executive functioning, which refers to a heterogeneous and wide-ranging set of cognitive operations, including attention allocation, inhibitory control, hypothesis generation, and self-monitoring, as well as other skills (Mohlman, 2005). The alpha band (8–13 Hz) reflects top-down, inhibitory control processes (Klimesch et al., 2007). Moreover, a decrease in absolute alpha-power is related to neural excitation, such as cognitive processing (Klimesch et al., 2007). The major findings about alpha band showed a low alpha rhythm in anxiety (Siciliani et al., 1975; Enoch et al., 1995; Kalashnikova and Sorokina, 1995; Wiedemann et al., 1998; Gordeev, 2008; Wise et al., 2011). Thus, an absolute alpha-power decrease in the frontal cortex observed in PD may reflect a dysfunction in thalamic–cortical circuits that is associated with incapacity to inhibit irrelevant information, role played especially by the PFC (Klimesch et al., 2007). In this context, the aim of this study is to observe absolute alpha-power in the scalp frontal region as a whole (F3, F7, Fz, F4, F8, Fp1, Fp2 electrodes) in PDA patients compared to healthy controls while watching an anxiogenic computer simulation (Freire et al., 2010) comprised of high anxiety moments (HAM) and low anxiety moments (LAM). We were expecting a low absolute alpha-power in PDA patients on all electrodes when compared to healthy controls. Moreover, we formulated the hypothesis that, in high anxiogenic moments, absolute alphapower may be different than in low anxiety moments. 2. Methods 2.1. Participants We selected a sample by convenience of 24 PDA patients (8 male and 16 female; ages varying between 25 and 61 years old, mean: 38.75, SD: 710.09), who were in psychopharmacological treatment at the Laboratory of Panic and Respiration at the Institute of Psychiatry and were evaluated in the Department of Applied Psychology at the Institute of Psychology before treatment; these are both institutes of the Federal University of Rio de Janeiro (UFRJ). The recruitment of subjects was done through posters with information about the research in the outpatient institute of psychiatry and psychology at UFRJ. All patients that met the study inclusion criteria were invited to participate. The patients were interviewed with the M.I.N.I. 5.0 (Sheehan et al., 1998; Amorim, 2000) and fulfilled DSM-IV [1] criteria for PDA. Another inclusion criterion was the occurrence of at least two panic attacks in a 30-day period before the visit. Patients with comorbid dysthymia (n¼1), generalized anxiety disorder (n¼2), social phobia (n¼1) or depression (n¼ 3) were included only when PDA was judged to be the primary diagnosis. Some of them began the treatment unmedicated (n¼7), while others were already taking antidepressants (n¼3), benzodiazepines (n¼ 5) or both antidepressants and benzodiazepines (n¼9). The patients performed three selfevaluation questionnaires to measure the severity of anxiety, depression and PDA symptoms: Beck Anxiety Inventory (BAI) (Beck et al., 1988) (mean score: 22.68 and SD: 714,17; which means moderate anxiety); Beck Depression Inventory (BDI) (Beck et al., 1961) (mean score: 16.37 and SD: 710,99; which means mild depression). Seven of the 24 subjects had BDI scores above the relevant clinical threshold for depression and Panic and Agoraphobia Scale (PAS) (Bandelow, 1995) (mean score: 23.82 and SD:79.96; which means moderate PDA symptoms). There was also a control group with 21 healthy participants (4 male and 17 female; ages from 23 to 61 years old, mean: 40.52, SD: 7 12.47) who were screened with the M.I.N.I. 5.0 (Sheehan et al., 1998; Amorim, 2000) and did not fulfill criteria for any psychiatric disorder. Subjects with other psychiatric disorders, neurological, cardiologic or respiratory diseases were not included in this study, neither in the patient nor in the control group. Patient and control group did not differ from each other in age (p ¼0.848).Our local Ethics Committee (Comitê de Ética em Pesquisa do Instituto de Psiquiatria da Universidade Federal do Rio de Janeiro—CEP-IPUB/UFRJ) approved the protocol, which complied with the principles of the Declaration of Helsinki. After the experiment was fully explained, the subjects signed a voluntary written consent. 2.2. Computer simulation The simulation consisted of a 4-min three-dimensional computer animation developed by Triptyque LAB (www.triptyquelab.com). Two 30-s periods in which a gray screen was displayed, one before and the other after the animation per se, were included in this animation. This was in a first person perspective (a graphical perspective rendered from the viewpoint of observer of the computer simulation) and there was a camera movement as if the subject was walking inside/outside a bus and looking at different directions during a bus ride. The animation starts at a bus stop: the bus arrives, the subject gets on the bus and sits down, the bus moves through city streets, it stops again and is filled by many people, it moves through the streets, goes in a tunnel, stops inside the tunnel because of traffic, it starts moving again, gets out the tunnel, stops at a bus stop, and the subject gets off the bus and watches the bus leave. The simulation included sound, which consisted of ordinary street noises associated with the images (Freire et al., 2010). In a previous study, this computer simulation demonstrated to be a useful method to induce anxiety and somatic symptoms in PDA patients. Compared to health controls, they had higher scores in anxiety self-evaluation scales and had higher skin conductance level, electrodermal response magnitude, respiratory rate, tidal volume, and respiratory rate irregularities. Two of 10 patients had PA. The heart rate means were higher for PDA patients who had PA (Freire et al., 2010). The computer simulation consisted of situations classified as “high anxiety” and “low anxiety”. They were classified as being “high” or “low anxiety” by patients that participated in the cited previous study (Freire et al., 2010). The high anxiety situations were when the bus gets filled with people, when the bus gets in a tunnel and when it stops inside the tunnel because of traffic. And the low anxiety situations were those when the camera just moves around and the subject sees the bus, when the bus moves through the streets but is not filled with people, when the bus leaves the tunnel and there is no traffic and when the subject gets off the bus and watches the bus go away. These low anxiety situations refer to the situations where the difficulty of exposure to anxiogenic events tends to be smaller (but it still exists), that is, moments when the patient is about to leave the situations of greater discomfort and for this reason may experiment Please cite this article as: de Carvalho, M.R., et al., Alpha absolute power measurement in panic disorder with agoraphobia patients. Journal of Affective Disorders (2013), http://dx.doi.org/10.1016/j.jad.2013.06.002i M.R. de Carvalho et al. / Journal of Affective Disorders ∎ (∎∎∎∎) ∎∎∎–∎∎∎ less anxiety. All these situations were connected with EEG recordings through a computer software designed by the Brain Mapping and Sensory Motor Integration Laboratory of the Psychiatry Institute of the Federal University of Rio de Janeiro. 2.3. Experimental procedures The experiment was fully explained to the subjects and they signed a voluntary written consent. Patients with PDA filled out the BAI, BDI and PAS scales. Subjects were seated on a comfortable chair in a darkened and sound-protected room in order to minimize sensory interference. The subjects were positioned in front of a 32-inch monitor and the distance between the participants and the monitor was 30 cm. Speakers were positioned around the room and the experiment was divided into three stages: (1) rest condition 1 (RC1): 4 min of open eyes rest qEEG recording; (2) computer simulation (low anxiety and high anxiety situations)—the participants watched the movie, and concomitant signal qEEG was recorded; and (3) rest condition 2 (RC2): 4 min of open eyes rest qEEG recording. All qEEG recordings, for both patients and healthy controls, were made in the afternoon, from 1 PM to 4 PM. Subjects were oriented to have at least 8 h of sleep before recordings. 2.4. EEG data acquisition recording The International 10/20 EEG electrode system (Jasper, 1958) was used with a 20-channel EEG system (Braintech-3000, EMSA Medical Instruments, Brazil). The 20 electrodes were arranged on a nylon cap (ElectroCap Inc., Fairfax, VA, USA) yielding monopolar derivation using the earlobes reference. Impedance of EEG and EOG electrodes was kept between 5 and 10 kΩ. The data recorded had total amplitude of less than 70 mV. The EEG signal was amplified with a gain of 22,000, analogically filtered between 0.01 Hz (high-pass) and 80 Hz (low-pass), and sampled at 200 Hz. The software Data Acquisition (Delphi 5.0) from the Brain Mapping and Sensory Motor Integration Lab was employed with the digital filter notch (60 Hz). 2.5. Data processing and analysis We applied a visual inspection and independent component analysis (ICA) to remove possible sources of artifacts produced by the task (i.e., blinking and muscle -related artifacts) (Onton et al., 2006). The data were collected using the bi-auricular reference and they were transformed (re-referenced) using the average reference after we conducted the artifact elimination using ICA. Through visual inspection, we removed all the trials which clearly showed blinking and a muscle-related artifacts “influence”, and through ICA we removed the components that showed blinking and muscle-related artifacts “contamination”. A classic estimator was applied for the power spectral density (PSD) performed by MATLAB 5.3 (Matworks, Inc.). Eight hundred (4 s 200 Hz) samples with rectangular windowing were analyzed. For the computer simulation, we extracted qEEG parameters within a time frame of 1 s before and 2 s after each situation. As the anxiogenic events do not have an instantaneous beginning, rather, they are gradual, the gap of 1 s prior to labeling served as a guarantee that we did not lose snippets of information signal due to a failure in marking the exact start of events. Therefore, the situations were classified according to their characteristics and they were grouped into two different moments: low anxiety moments (LAM) and high anxiety moments (HAM). LAM and HAM moments were 3 s length periods spread along the computerized simulation. Six moments were marked during the computer simulation (a total of 9 s of LAM and 9 s of HAM). The Fourier 3 Transform resolution was 1/4 s–0.25 Hz (FFT). The “Run-test” and “Reverse-Arrangement test” were applied to examine a stationary process, which was accepted for every 1 s (epoch's duration). In this manner, based on artifact-free EEG epochs, the threshold was defined by the mean plus three standard deviations; epochs which showed a total power higher than this threshold were not included into the analysis. 2.6. Statistical analysis Statistical analysis was performed using SPSS for Windows— version 17.0 (SPSS Inc., Chicago, USA) and absolute alpha-power (8–13 Hz) was the dependent variable of interest. Absolute alphapower values during the computer simulation presentation were assessed in 24 PDA patients and were compared with 21 healthy controls. An ANOVA three-way was performed among the independent variables: group (2 levels: patients and control group), moment (4 levels: RC1, LAM, HAM, and R2) and electrode (7 levels: F7, F3, Fz, F8, F4, Fp1 and Fp2). Scheffé post hoc test was used. In cases where we found interaction, we examined the interaction with a t-test or with an ANOVA one-way in order to understand further results. We also reported the effect size using Eta Partial Squared (ηp²). Additional analysis was performed excluding four subjects that presented PDA with comorbid Major Depressive Disorder (MDD) and Generalized Anxiety Disorder (GAD). The same statistical analysis procedure was performed with the remaining 20 PDA patients and the 21 healthy controls. 3. Results We analyzed absolute alpha-power on the frontal cortex. An ANOVA three-way was performed between the independent variables: group, moment and electrode. We did not find an interaction among the three factors (F¼ 0.739; p ¼ 0.774; ηp² ¼ 0.001), but we found an interaction between group vs. moment (F¼23.572; p ¼0.001; ηp² ¼ 0.003) (Fig. 1), moment vs. electrode (F¼3.512; p ¼0.001; ηp² ¼ 0.003) (Fig. 2) and group vs. electrode (F¼3.284; p ¼0.003; ηp²¼ 0.001) (Fig. 3). As the interaction between group and moment on the frontal cortex was the main finding according to our objectives, between groups t-tests were performed to examine this interaction. We detected a difference between RC1 (p ¼0.001), LAM (p¼ 0.001) and RC2 (p¼ 0.001), but no difference was detected on HAM (p ¼0.363). We found the greater absolute alpha power for RC2 and the lowest for LAM. From RC1 to LAM the absolute alpha power diminished and it rose from LAM to RC2. We performed an ANOVA one-way for each moment to examine the interaction between moment and electrode. We Fig. 1. Mean and standard deviation of absolute alpha power on the frontal cortex. The statistical analysis revealed an interaction between group and moment (p ¼ 0.001). Please cite this article as: de Carvalho, M.R., et al., Alpha absolute power measurement in panic disorder with agoraphobia patients. Journal of Affective Disorders (2013), http://dx.doi.org/10.1016/j.jad.2013.06.002i 4 M.R. de Carvalho et al. / Journal of Affective Disorders ∎ (∎∎∎∎) ∎∎∎–∎∎∎ MDD and GAD, as it could bias the finding results. We found that these comorbid conditions could not account for the findings, and, for this reason, these analyses were not reported here. 4. Discussion Fig. 2. Mean and standard deviation of absolute alpha power on the frontal cortex. The statistical analysis revealed an interaction between moment and electrode (p¼ 0.001). Fig. 3. Mean and standard deviation of absolute alpha power on the frontal cortex. The statistical analysis revealed an interaction between group and electrode (p¼ 0.003). detected a difference among electrodes for each moment: RC1 (F¼ 9.993; p ¼0.000; ηp² ¼0.006), LAM (F¼ 15.420; p ¼0.000; ηp²¼ 0.047), HAM (F¼ 13.164; p ¼0.000; ηp²¼ 0.035) and RC2 (F¼ 11.726; p ¼0.000; ηp²¼ 0.007). For RC1, according to Scheffé post hoc test, the differences were found between the following pair of electrodes: F3–Fz (p¼ 0.000), F3–Fp2 (p ¼0.045), Fz–F4 (p ¼0.000), Fz–F8 (p¼ 0.000) and Fz–Fp1 (p¼ 0.003). For LAM: F7–F3 (p ¼0.000), F7–Fz (p ¼0.001), F7–F4 (p ¼0.000), F3–F8 (p ¼0.044), F3–Fp1 (p ¼0.000), F3–Fp2 (p ¼0.000), Fz–Fp1 (p ¼0.001), Fz–Fp2 (p ¼ 0.037), F4–Fp1(p ¼0.000) and F4–Fp2 (p ¼ 0.000). For HAM: F7–F3 (p ¼0.015), F7–F4 (p ¼0.012), F3–Fp1 (p ¼0.000), F3–Fp2 (p ¼0.000), Fz–Fp1 (p ¼ 0.011), Fz–Fp2 (p ¼0.000), F4–Fp1 (p¼ 0.000) and F4–Fp2 (p ¼0.000). For RC2: F7–Fz (p ¼0.000), F3–Fz (p ¼ 0.000), F3–Fp2 (p ¼0.007), Fz–F4 (p ¼0.000), Fz–F8 (p ¼0.000) and Fz–Fp1 (p ¼0.001). We observed that absolute alpha power for Fp1 and Fp2 were constantly higher for all moments. We performed an ANOVA one-way for each group to examine the interaction between group and electrode. We detected a difference among electrodes for each group: Healthy Controls (F¼ 13.118; p ¼0.000; ηp² ¼0.006) and PDA (F¼15.694; p ¼0.000; ηp²¼ 0.008). For controls, according to Scheffé post hoc test, the differences were found between the following pair of electrodes: F7–F3 (p¼ 0.010), F3–Fz (p¼ 0.000), F3–Fp2 (p ¼0.023), Fz–F4 (p ¼0.000), Fz–F8 (p ¼0.000), Fz–Fp1 (p¼ 0.000) and F4–Fp2 (p ¼ 0.021). For PDA: F7–F3 (p ¼0.010), F3–Fz (p¼ 0.000), F3–Fp1 (p ¼0.000), F3–Fp2 (p ¼0.000), Fz–F4 (p ¼0.023), Fz–F8 (p ¼ 0.002), F4–Fp1 (p ¼0.034), F4–Fp2 (p ¼0.002), F8–Fp1 (p ¼0.003) and F8–Fp2 (0.000). In both groups, absolute alpha power for Fz, Fp1 and Fp2 were constantly higher. We did additional analyses, following the same procedures described above, that excluded the individuals with comorbid This study aimed to shed light on the relationship between electrocortical activity on frontal cortex in PDA patients and a healthy control group. Specifically, we investigated the absolute alpha-power difference between the PDA and the control group on the frontal cortex while watching a computer simulation (Freire et al., 2010) with HAM and LAM. Based on previous electrophysiological findings in PDA patients, we hypothesized that these would present a low absolute alpha-power for all frontal electrodes. We expected that frontal region would react differently between the HAM and LAM. Moreover, we anticipated the frontal region would participate more actively in the modulation of high anxiogenic emotional stimuli processing. The interactions between moment and group in frontal cortex demonstrate that absolute alpha power fluctuation depends on the relationship between both factors: moment and group. A greater absolute alpha-power for healthy subjects when compared to the PDA patients was found in the frontal area. We can highlight that in moment and group interaction RC1, LAM and RC2 differed from each other, with a greater absolute alpha power for RC2 and a lower absolute alpha power for LAM. It was interesting to find out that LAM was more significant than HAM for both groups. We can hypothesize that it might have happened because PDA patients tend to be hypersensitive even for lower anxiety stimulus, exhibiting hyperousal responses, as they are hypervigilant to danger cues (Beck et al., 1992). Hoehn-Saric et al. (1991) reported that PD patients with frequent PA exhibited heightened cardiovascular arousal and decreased electrodermal flexibility, even in nonthreatening situations, when compared to controls. Besides, we cannot ignore that in HAM there was an increase in the mean of absolute alpha power plus a large variability in PDA patients in relation to controls, which did not happen in LAM. Our results are in agreement with previous studies that report a low absolute alpha-power in PD patients (Siciliani et al., 1975; Enoch et al., 1995; Kalashnikova and Sorokina, 1995; Wiedemann et al., 1998; Gordeev, 2008; Wise et al., 2011). The decrease of alpha activity has been associated with a state of high excitability and lower inhibitory control (Gordeev, 2008; Pavlenko et al., 2009), while an increase of alpha power represents a low excitability state, related to a relaxed condition (Cahn and Polich, 2006; Gordeev, 2008; Pavlenko et al., 2009). Thus, our results of greater absolute alpha-power for healthy subjects when compared to the PDA patients in the frontal area can be interpreted as a greater frontal activation and this may be related to an impaired frontal attempt to regulate downstream excitability (although we cannot direct test this hypothesis) or to the reflection of the excitation originated from deeper subcortical regions. Alpha is elicited in situations where subjects withhold or control the execution of a response and it is obtained over sites that probably are under or exert top-down control. Thus, it is assumed that alpha is related to top-down and inhibitory control processes (Siciliani et al., 1975). Alpha may also be considered an index for measuring emotional stability; as previous studies have shown the appearance of alpha during meditation, which indicates a state of low brain excitability with a reduction of stress and anxiety (Cho et al., 2011). Further, the lateral frontal region is located nearby the temporal cortex, an important region that is correlated with the limbic system activity, especially with amygdala activity (LeDoux, 1992). The medial temporal lobe consists of the amygdala and the hippocampus (including the entorhinal, Please cite this article as: de Carvalho, M.R., et al., Alpha absolute power measurement in panic disorder with agoraphobia patients. Journal of Affective Disorders (2013), http://dx.doi.org/10.1016/j.jad.2013.06.002i M.R. de Carvalho et al. / Journal of Affective Disorders ∎ (∎∎∎∎) ∎∎∎–∎∎∎ perirhinal and parahippocampal cortices); these structures are known to be involved in memory and emotional learning (LeDoux, 1992). The role of such structures in emotional learning and memory is particularly well characterized in classical fear conditioning (Liu et al., 2010). The amygdala plays a special central role in fear learning processes. It is known that the amygdala is a center where different impulses converge, and it conducts excitatory efferent outputs to the hypothalamus, midbrain and brainstem areas, which subsequently select suitable behavioral and autonomic programs (Globish et al., 1999). The amygdala also participates in fear extinction along with the medial PFC and hippocampus. The medial PFC is thought to regulate extinction of long-term memory. It has been seen that with constant presentation of the conditioned stimuli, the lateral amygdala is responsible for decreased firing, and the medial PFC inhibits firing of amygdala neurons, under the modulation of the hippocampus (Garakani et al., 2006). If the PFC top-down modulation is not working properly, anxiety symptoms are likely to be more prominent. Besides, there is some evidence that support that the lateral PFC controls anxiety related limbic activity through connections with ventromedial prefrontal cortex (Klumpers et al., 2010). Anatomical studies demonstrated that the medial PFC and the 1ateral PFC have direct connections with limbic structures, such as the amygdala, the hypothalamus and the hippocampus (Groenewegen et al., 1990; McDonald et al., 1996). Areas of the dorsolateral PFC are likely to be recruited during deliberate emotional regulation through cognitive appraisal paradigms' studies (Ochsner et al., 2002; Eippert et al., 2007). There is also evidence that healthy subjects downregulate their defensive states while recruiting ventromedial and right lateral prefrontal areas (Klumpers et al., 2010). Thus, the lateral PFC must be one site that contributes to the modulation of the activation of the amygdala, exerting inhibitory effects on the amygdaloid complex and being critical for the inhibition of conditioned fear (Lacroix et al., 2000). The constantly high absolute alpha power for prefrontal region found on both interactions: moment vs. electrode and group vs. electrode is also in line with the presented hypothesis of an impaired top-down regulation. The findings for frontal area demonstrated that both patients and healthy controls presented higher alpha values at RC1 and RC2 when compared to LAM and HAM. These findings suggest that the computer simulation was effective in inducing anxiety, as also demonstrated in a previous study that measured peripheral physiological alterations in PDA patients, where they demonstrated significant anxiety, electrodermal and respiratory alterations related to control subjects (Freire et al., 2010). Another possible explanation to be considered is that alpha was reduced during the increased information processing associated with the computer simulation. Our results confirm our hypothesis that the PDA patients present a lower absolute alpha power in the frontal cortex when compared to healthy controls. Our additional analyses that excluded subjects with MDD and GAD showed that MDD and GAD were conditions that did not bias the findings. Panic disorder is almost never clinically manifested without comorbidity, most of which is also characterized by over-arousal. Research conducted in collaboration between International Mood Center in San Diego and University of Pisa, Italy, has indeed reported high levels of arousal in panic disorder and its comorbid boundaries, especially bipolar II (Akiskal et al., 2006). In other words, the specific findings of this paper have broader implications for anxious-bipolar patients and probably beyond. The limitations of this study were the small sample, the wide age range of participants, the gender of participants was not balanced in the samples and the use of psychotropic medications by most of the PDA patients. About only 29% of the patients (seven) were drug-free during the experiment. Some of the patients also have psychiatric comorbidities, and they represented 5 about 29% of the patients' sample. As Freire et al. (2010) also pointed out in their study, the lack of interactivity between the computer simulation and the participants may have been another limitation, since interaction, like the one provided by virtual reality environments, would probably contribute to the enhancement of the computer simulation anxiogenic properties. Role of funding source Purchase and maintenance of research equipment was supported by the Brazilian Council for Scientific and Technological Development (CNPq) and INCT Translational Medicine (CNPq). Conflict of interest None to declare. 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