Introduction

According to the biopsychosocial model, Anorexia Nervosa (AN) results from the interaction of different factors, including biological, psychological and environmental ones [1]. The ever-increasing prevalence of the disease prompts more investigations to search for innovative and more effective therapeutic strategies [2, 3]. Electroencephalography (EEG) and neurofunctional neuroimaging (fMRI) have been applied for gaining a better understanding of the psychopathology of these disorders [4,5,6]. EEG studies in other psychiatric conditions have shown some specific hallmarks of neuronal activity, such as increased presence of delta (1–3 Hz) and theta activity (3.125–8 Hz) in participants with AN [6, 7] and with Schizophrenia [8] compared to the unaffected controls. Moreover, participants with AN suffering from Major Depression showed a significant correlation between symptoms of motor slowdown and the presence of slow EEG activity, specifically alpha1 and theta 2 [9].

These abnormalities can provide support for the therapeutic use of neuromodulatory approaches such as transcranial magnetic stimulation (TMS) or transcranial direct current stimulation (TDCS) [10]. Actually, neuromodulatory approaches, such as transcranial magnetic stimulation (TMS) or transcranial direct current stimulation (TDCS), have been already successfully applied to the treatment of several neurological and psychiatric conditions [11, 12].

In recent years, the use of EEG methods has also been associated with experimental therapeutic protocols investigating the rationale for the use of music-therapy in AN, schizophrenia, and major depression [13]. Specifically, musical administration might have a therapeutic effect on the synchronization of encephalic rhythms and on the prefrontal-hippocampal plasticity involved in psychoticism and anxiety [14].

Concerning AN, research applying EEG to music-therapy is still limited. Some preliminary EEG studies in AN revealed theta waves patterns in frontal hemispheres of these individuals, suggesting a cortical slow-wave pattern in AN [15]. This alteration could be consequent to malnutrition as suggested by previous EEG studies [16]. However, other authors have hypothesized that the detection of lower frequencies in parieto-occipital delta waves and fronto-median alpha activity in AN compared to healthy controls may represent a specific neurobiological characteristic of this disorder and not exclusively a consequence of malnutrition [17]. This pattern could be connected to a slight frontal dysfunction or to a state of increased attention-vigilance [18]. Studies using Event-Related Potentials (ERPs) recording techniques showed second rate amplitudes and latency alterations in early and late ERPs evoked components in AN [19], suggesting deficits in environmental stimuli processing and selective attention shifting [20].

On the other hand, the evidence of a therapeutic effect of music therapy in AN is still limited, even though there have been encouraging preliminary reports. For instance, music therapy may represent a useful adjunctive treatment to overcome resistances to treatment, as suggested by a reduction in post-meal anxiety and distress with music therapy as compared to standard support therapy [21].

The aim of this preliminary study is to explore the EEG characteristics in a sample of female participants with AN as compared healthy participants (HP). The second aim was to explore the effect of music stimulation on EEG activity in AN and HP, and to examine the possible association between EEG and psychopathology characteristics. According to a comprehensive theoretical model of the AN psychopathology including many psychological dysfunctions [1, 2] the authors focused on emotional dysregulation and impulsivity, general psychopathology symptoms, and alexithymic traits, which are relevant elements involved in sustaining the clinical manifestations of the disorder and could influence the response to musical stimuli.

Methods

Participants

Thirty female participants (20 with AN and 10 HP) were enrolled in this study. Participants with AN were recruited from the Outpatient Service of the Regional Expert Centre for the Eating Disorder of the University of Torino, AOU Città della Salute e della Scienza di Torino, between December 2016 and June 2017. All participants received a psychiatric examination to determine the presence of AN using the Structured Clinical Interview for Diagnosis (SCID) for DSM-IV-TR, a tool that has fair to excellent inter-rater reliability on axis I and excellent on axis II diagnoses [22, 23]. To make the sample as homogeneous as possible and increase study specificity, we adopted restrictive inclusion and exclusion criteria. In particular, participants were: (1) female only, to avoid gender-related differences on EEG; (2) with BMI ≥ 14, to avoid severe malnutrion, which has been shown to affect brain functioning; (3) with age between 16 and 25 years, to avoid possible effects of brain maturation/involution; and (4) with less than 1.5 years of duration of illness, to avoid a chronic history of illness with possible effects on brain functioning.

We excluded patients with (1) intellectual disability; (2) developmental or learning disorders; (3) psychotic disorders; (4) neurological disorder (e.g., multiple sclerosis, stroke, etc.); (5) history of dementia or severe head trauma; (6) current acute psychotic condition; (7) substance abuse; or (8) history of hearing problems, to avoid possible effects on the basal EEG and the musical stimulation unrelated to the AN.

From an initial group of 20 participants with AN, 10 were excluded (4 for lowering of the BMI below 14, 3 for refusing to undergo EEG recording, 2 for failure to complete the tests, and 1 for excessive motion artefacts at the EEG recording). The final group consisted of 10 participants with AN (Table 1).

Table 1 Sociodemographic, clinical and psychopathological Mann Withney U comparison
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A sample of 10 healthy participants matched for sex, social status, ethnicity, language, country of origin (Italy), age, and education, was recruited as a control group from local high schools and university students. Inclusion and exclusion criteria for healthy participants were the same as the AN participants. Participants were personally contacted by research staff during/after cultural events involving such students (e.g. concerts, seminaries, lectures). No count of excluded subjects was performed.

Ethics

All participants provided written informed consent to this study. All the procedures were conducted according to the 1995 Declaration of Helsinki as revised in Edinburgh in 2000. Study was approved by the Ethics Committee of AOU City of Science and Health, Turin (protocol number: 0089968).

Measures

According to our routine clinical assessment [1, 2], all participants completed a battery of self-administered psychometric tests including:

The Toronto Alexithymia Scale-20 (TAS-20) [24], a 20-item questionnaire used to assess the level of alexithymia. This scale had a strong support for its reliability and factorial validity [25]. The total score of the scale is the sum of the scores of three TAS-20 subscales (Difficulty Describing Feelings, Difficulty Identifying Feelings, and Externally Oriented Thinking).

The Barratt Impulsiveness Scale (BIS) [26], used as a measure of the degree of subject’s impulsivity. It includes 30 items that are scored to yield six first-order factors (attention, motor, self-control, cognitive complexity, perseverance, and cognitive instability impulsiveness) and three second-order factors (attentional, motor, and non-planning impulsiveness). The BIS is the most widely used self-report measure of impulsive personality traits. It showed good validity and reliability.

The Beck Depression Inventory–II (BDI—II) [27], a questionnaire that scores depressive symptoms and measures the contribution of somatic and cognitive-affective symptoms, with a total cutoff for clinical significance of 16.

The Symptom Checklist-90 (SCL-90) [28], which is composed of 90 items that assess the presence and the severity of mental distress symptoms during the last week (including the day of evaluation), in different domains. It differs from other self-administered questionnaires, because it measures both internalizing and externalizing symptoms, thus capturing the entire psychopathological spectrum. According to the literature, its psychometric characteristics are appropriate for assessing the psychopathological profile [29].

The nine symptom dimensions are the following:

Somatization (SOM): ailments that arise from the perception of bodily dysfunction. Obsession-Compulsion (O-C): thoughts, impulses and actions experienced as incoercible and unwanted by the subject. Interpersonal sensitivity (INT): feelings of inadequacy and inferiority towards other people. Depression (DEP): a broad spectrum of symptoms of the depressive syndrome. Anxiety (ANX): a set of symptoms and behaviors related to high manifest anxiety. Hostility (HOS): thoughts, feelings and actions characteristic of a state of anger or irritability. Phobic anxiety (PHOB): persistent irrational and non-proportionate fear response against specific people, places and occasions that leads to avoidance/flight behaviors. Paranoid Ideation (PAR): thought disorder characterized by suspicion, fear of loss of autonomy mixed with hostility and reference ideas. Psychoticism (PSY): although it includes some of the main symptoms of schizophrenia (hallucinations, thought insertion), it is to be understood as a continuous dimension of human experience characterized by withdrawal, isolation and schizoid lifestyle.

A global index is calculated as the sum of all the item scores of the checklist.

The Temperament and Character Inventory (TCI) [30], a questionnaire that provides an estimate of the personality structure, according to the neurobiological model proposed by Cloninger and coworkers in 1994. There are four scales for temperament: Novelty Seeking (NS), Harm Avoidance (HA), Reward Dependence (RD, Persistence (P) and three scales for character: Self Directedness (SD; Cooperativeness (C) and Self-Transcendence (ST). Its psychometric properties support clinical usefulness in assessing personality psychopathology.

The Emotion Regulation Questionnaire (ERQ) [31], a 10-item questionnaire that evaluates the emotion regulation modalities implemented by the subject. It is designed to measure the respondent's tendency to regulate emotions in two ways, with Cognitive Reappraisal and Expressive Suppression. Respondents answer each item on a 7-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly agree). It has shown acceptable validity and reliability.

The Difficulty in the Emotion Regulation Scale (DERS) [32], a 36-item questionnaire measuring individual patterns of emotional regulation. DERS items were chosen to simultaneously evaluate difficulties in four domains of emotion regulation: (1) awareness and understanding of emotion, (2) acceptance of emotion, (4) impulsiveness, (3) ability to adopt goal-directed behaviors, and (4) ability to access efficient regulation strategies. A key feature of this scale is that it groups a variety of elements known to be involved in emotion regulation into a single instrument. It has shown excellent internal consistency and good test–retest reliability and construct validity.

EEG data acquisition

With the participant comfortably seated in a semi-recumbent position in a quiet room with attenuated light, 40-min eyes-closed EEG recordings were obtained using a 19-channel EEG Analysis Station according to the Jasper International 10–20 System (JIS) (33). According to JIS, electrodes were placed at Fp2, F8, T8/T4, P8/T6, O2, F4, C4, P4, Fp1, F7, T7/T3, P7/T5, O1, F3, C3, P3, Fz, Cz, and Pz through a self-adhesive conductive paste.

First, a quantitative electroencephalographic (qEEG) recording was performed. Quantitative EEG (qEEG) is a method of analyzing the electrical activity of the brain to derive quantitative patterns that may correspond to diagnostic information and/or cognitive deficits [33]. The peculiarity of qEEG is that it takes into account frequency and amplitude in a simultaneous and independent way. The qEEG allows 6 main frequency bands to be obtained, one for each electrode used, according to a Fourier spectral analysis. The electrodes record and transmit the surface potentials to a computer, which converts them (using an analog digital method) into graphic values and quantifies them (with spectral analysis on successive epochs of 2 s) [34]. The qEEG recording was obtained in three different situations:

  • at rest, with no musical stimuli;

  • while listening to a standardized music, the same one for participants with AN and HP [35];

  • while listening to an individually selected track.

Prior to data analysis, artifact detection was performed to exclude eye-movements, head-movements, muscle-movements, and segments of decreased alertness. EEG recordings were then exported using ELMIKO’s EEG DigiTrak Analysis Software to the ASCII format for later processing.

N100 and P300 analysis

The visual N1 (N100) is a visual evoked potential. Visual evoked potentials are a series of voltage deflections observed in response to visual stimulation, including onset, offset, and changes in stimulus. Its amplitude is influenced by selective attention and has been used to study a variety of attentional processes. The visual N1 has also been interpreted to reflect a discrimination process that takes place within the locus of attention. As compared with conditions that simply require a response, the N1 component is enhanced in conditions that require a differentiation between classes of stimuli [36]. This effect is similar for color- and form-based discriminations, regardless of the level of difficulty of the discrimination.

The P300 wave is an event-related potential (ERP) component elicited in the process of decision making. It is considered a possible index of attention and processing capacity. According to the literature, Odball Paradigm Method has been used to elicit ERP [36]. According to this method, low-probability target items are mixed with high-probability non-target (or “standard”) items: a P300 wave manifests itself in response to rare stimuli, called targets, dispensed in a random sequence that sees them alternated with more frequent stimuli, called non-targets. The detection of P300 evoked potentials was performed first in basal conditions, then after listening to the standard musical stimulus, and finally after the individualized musical stimulus, according to the Oddball Paradigm Method.

Statistical analysis

A nonparametric comparison of the sociodemographic (age, education), clinical (BMI), personality and psychopathological characteristics of the AN and HP groups was carried out with Mann–Whitney U test.

The qEEG variables were analyzed with the Mann–Whitney U test, assuming as a null hypothesis the non-variation within the distribution between the absolute amplitude averages in AN and HP. A global measurement survey was initially carried out, including the set of measurements taken at baseline, during the standard musical stimulus and during the individual musical stimulus. With regard to the event-related evoked potentials (N100 and P300), we conducted a Mann–Whitney U test between participants with AN and HP in three different conditions: (1) at baseline; (2) after a common musical stimulus; and (3) after the preferred individual musical stimulus. The intra-group variability was verified separately for participants with AN and controls using the Wilcoxon test for paired samples to compare the three different conditions to verify a variation that should confirm or refute the normalization observed in the intergroup comparisons.

Finally, we performed a Spearman ranks bivariate correlation between psychometric, clinical and EEG variables to detect possible relationships between EEG parameters and descriptive variables.

We considered the significance threshold of p < 0.001 for the psychometric measures to avoid the Type I statistical error due to the high number of applied tests, and p < 0.05 for EEG analysis in consideration to the explorative nature of the study.

Results

Sociodemographic, clinical and psychopathological variables

All participants were Caucasian, Italian, of Italian mother-language, and of middle-income social status. Table 1 shows significant differences between participants with AN and controls in clinical and psychopathological indices.

Quantitative EEG (qEEG) analysis and comparison between participants with AN and healthy participants

Significant differences in qEEG were found between AN and HS with higher values reported in AN regarding the following electrodes and waves: T3 (wave theta: p < 0.02), T5 (wave alpha: p < 0.02 and beta: p < 0.02), P3 (wave theta: p < 0.05), T6 (wave beta: p < 0.04) e O1 (wave theta: p < 0.03 and wave beta 1: p < 0.02) (see Table 2).

Table 2 Quantitative EEG comparison between patients and healthy participants using Mann–Whitney U test
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ERPs comparison between participants with AN and HP in different conditions

Table 3 summarizes the significant differences evidenced between AN and HP in both N100 and P300 latency and at baseline, after the standard musical stimulus and after individual musical stimulus in frontal, central and parietal zones. AN participants displayed higher N100 latency in all zones at baseline and after each stimulation. AN participants also displayed higher P300 latency after the standard musical stimulus in the frontal zone, at baseline in the central zone and in all conditions in the parietal zone.

Table 3 ERPs comparison between AN and healthy participants using Mann–Whitney U test
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ERP intragroup comparison after musical stimulus

ERP intragroup comparison of different conditions showed significant differences between baseline condition and individual stimuli condition in the HP group, specifically in latency of P300 in the frontal zone (p < 0.037), central zone (p < 0.017) and parietal zone (p < 0.011), while no significant difference was found in the AN group (see Table 4).

Table 4 ERPs intragroup comparison of different conditions (baseline and after individualized stimulus) using Wilcoxon test
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Correlation between ERPs and psychopathological characteristics of the AN group

Correlation analysis between personality and psychopathology characteristics, and EPRs (Table 5).

Discussion

As expected, participants affected by AN evidenced consistent differences with respect to healthy controls regarding personality traits, general psychopathology, and emotional processing [19]. Since music therapy is supposed to influence emotional elaboration [13, 14], the differences in alexithymia and emotional dysregulation in AN participants represent possible therapeutic targets for an adjunctive music-therapeutic approach [21].

Table 5 Correlation between ERPs and psychopathological characteristics of the AN group using Spearman ranks correlation test
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Participants with AN evidenced some electrophysiological signs of brain suffering possibly due to reduced blood perfusion of the temporal-parietal areas with respect to controls [37]. According to previous studies, this may be due to low BMI [38]. In particular, it has been evidenced how BMI significantly reduces the perfusion of temporal cortical areas causing deficits in executive functions such as the performance in visual-spatial executive tasks [39]. Neuroimaging studies in participants with AN also highlighted functional alteration of temporal-parietal regions such as the left parahippocampal gyrus and the left fusiform gyrus [40]. Moreover, recent studies suggested a role of the parietal lobe in the development and maintenance of body image [41, 42]. Thus, as proposed by Smeets and Kosslyn [43], the temporal-parietal asymmetry observed in our AN participants may be relevant to their distortion of body image perception. Further research should explore if such alteration precedes or is consequent to the BMI reduction.

The greater N100 baseline latency of AN participants may suggest a deficit in selective attention [44, 45] or an increased state of arousal [46]. The latter interpretation would be consistent with the reported association of a higher N100 latency to a dysfunction in the catecholamine production [47]. The fact that the basal inter-group difference remains evident throughout the experiment, and it is not significantly affected by the two musical stimulations, supports the conclusion that the higher N100 latency is a stable characteristic of this population and may influence the perception of the external environment in AN. This neurophysiologic trait could be related to the high harm avoidance in the AN participants, which is a typical marker of trait-hyperarousal related to stable temperament features [48, 49].

Moreover, the concomitant differences in time distribution and in the left asymmetry index evidenced in participants with AN suggest a difference in the processing of emotional information related to the musical stimulus. This would be consistent with possible alterations in the functional limbic circuits involved in the processing of emotional information in AN [50]. A previous report suggests that, in healthy people, musical stimuli produce an intense activation of the reward system at the limbic level [51]. Recent evidence ascribes this action to the recruitment of the accumbens nuclei [52], an area involved in the pathogenesis of affective manifestations in AN [6, 53]. The fact that in our participants with AN such activation was not effective in re-approaching the latency of N100 by reducing their arousal level supports the notion of a functional deficit of the accumbens nuclei in AN [6, 53]. However, the lack of pre- and post-stimulus differences within the control group is suggestive of poor sensitivity of the N100 latency to the musical stimulus per se, and reduces its relevance as a distinctive marker of AN.

In contrast with the N100 latency, the latency of the P300 was significantly reduced in AN participants. Multiple reports have linked this finding with hyper-arousal and increased obsessiveness [54], both traits associated with AN. Indeed, some researchers have suggested that high obsessiveness and increased vigilance constitute true and proper endophenotypes of the anorexic psychopathology that are present early at the subclinical level [55]. This is generally interpreted as that, while healthy individuals in baseline conditions display low levels of vigilance and pay attention to different stimuli in a different manner, proportionate to their relevance [56], individuals with AN, and possibly also at-risk but not yet affected youngsters, tend to process stimuli with faster categorizations due to an increased state of vigilance. It is thus possible that their high alert levels bring their vigilance functioning closer to that of subjects with Obsessive Compulsive Disorder and Panic Attack Disorder [54, 57]. AN individuals, therefore, would be quicker in the categorization of external stimuli, but, in the long term, this increased level of activation could lead to a reduction in their ability to discriminate stimuli [58]. This is consistent with the neuropsychological theories that correlate a deficit in shifting selective attention to prolonged hyperstimulation conditions [5]. This discriminative deficit may be present in individuals with both AN and attention-deficit/hyperactivity disorder (ADHD) [59].

The musical stimulus, therefore, seems not to act on participants with AN who maintain the left hemispheric filter as general operation [60]. The absence of any specific response to individualized musical stimuli is further evidence of poor capacity for discrimination in AN [58]. This may represent a marker of abnormal self-related functioning and has been correlated to an altered resting-state activity in schizophrenia. In particular, the lack of sensibility to a stimulus related to the self supports the hypothesis of impaired self-development in these individuals [61,62,63].

The strong positive correlation between both the frontal and the parietal components of the latency of the N100 after the standard stimulus, and the level of awareness among the participants with AN supports the hypothesis that in this disorder there is an altered control of the selective attention related with difficulty in the management of emotional states [61]. In particular, this finding is consistent with the hypothesis that an emotional interference could impair the recognition of a musical stimulus not related to the subject. This mechanism may impair the response to the musical stimulus also in healthy controls who do not display levels of awareness significantly higher than those of AN participants. Individuals with AN display a lack of confidence in managing and modulating negative emotions because of their deficit mechanisms of regulation and containment of negative affects [64]. It seems that individuals with AN suppress the awareness of their emotions displaying a dysfunctional emotional regulation strategy. This is also consistent with the findings concerning the left asymmetry in the quantitative analysis and the typical characteristics of neurocognitive rigidity [65].

On the other hand, the positive correlation of the latency of P300 in the central zone with the Hostility scores, and the negative one with Harm Avoidance scores may suggest that in AN the impairment of decision making and the attentional process could be impaired by their higher levels of relational psychopathology and to their temperament traits related to the hyperarousal towards the environment, and not specifically with malnutrition. The “song of the anorexia nervosa” could be related to an hyperarousal caused by an hostile perception of the relationships with others which would impair the attachment and consequently the development of the self [1, 2, 61]. Being these data preliminary, this association needs to be further investigated for replication in a larger number of participants.

Conclusions

Our study reveals differences in the functioning of the left hemisphere of AN participants compared to healthy controls confirming the presence of some type of asymmetry in this disorder [60]. In parallel, the observed differences in N100 and P300 latency of the event-related evoked acoustic potentials in AN indicate similarities with other psychiatric disorders, such as OCD, where there are abnormalities in shifting selective attention to external stimuli [2]. Such a procedural dysfunction may represent an endophenotype of AN that evoked potentials can precociously detect even before the full disorder becomes evident and that can track during treatment [55]. The generalized hyperarousal and hypersensitivity, which we called “the song of anorexia nervosa”, may constitute a barrier to treatment by impairing the responsiveness to positive interactions, including those with family, peers, and therapists, that are meant to increase self-esteem and favor the development of their self [61].

The combination of a higher latency of N100 with a low latency in P300 in response to the musical stimulus may represent a specific endophenotype feature of AN. If confirmed and replicated by further studies, it may have applications to both prevention, by identifying individuals are a risk for AN, and clinical management, by identifying signs of treatment resistance and risk for relapse [2].

Finally, while the present results provide some neurophysiologic evidence in support of music therapy to enhance traditional therapies in AN, it also points to some objective obstacles to its efficacy. Recent data suggest that music therapy can have a therapeutic anxiolytic effect in AN [20]. In fact, music therapy stimulates the frontal and limbic areas, activates the emotional and cognitive functions related to the reward system, and may increase inter-hemispheric connectivity [37]. However, hyperarousal and difficulty in selective attention may be barriers and lead to resistance to music therapy [6, 54]. Thus, it might be necessary to use a specific frequency stimulation to overcome these obstacles.

Limitations

Our study is exploratory and preliminary. The results are promising, but a number of limitations must be taken into account, including the small sample size and uncertainty of localization and interpretation, which are typical of surface methods. Moreover, the lack of previous similar EEG studies in psychiatry, and in AN in particular, adds to the challenges of the data interpretation. The study does not investigate the therapeutic effects of music therapy in AN or the possible beneficial implications of adding music therapy to conventional psychotherapeutic or psychopharmacological interventions. Controlled studies are needed to test the efficacy of this adjuvant therapy. By exploring the effects of the music stimulation from a neurophysiologic point of view and correlating cognitive evoked potentials to psychopathology this study contributes to a better understanding of the potential role of music therapy in AN.

“What is already known on this subject?”

Music-therapy helps synchronization of encephalic rhythms and prefrontal-hippocampal plasticity involved in psychoticism and anxiety. Few studies in AN, it was evidenced anxiolytic after-meal effect.

What does this study add?”

It explores EEG the effect of music stimulation on AN. AN display hyperarousal and abnormal reactivity. AN may impair response to environment, this may be an hallmark useful for clinical follow-up.