Psychophysiological evaluation of the Smartick method in children with reading and mathematical difficulties.

Introduction: Assistive technologies for learning are aimed at promoting academic skills, such as reading and mathematics. These technologies mainly embrace mobile and web apps addressed to children with learning difficulties. Nevertheless, most applications lack pedagogical foundation. Additionally, the task of selecting suitable technology for educational purposes becomes challenging. Hence, this protocol posits the psychophysiological assessment of an online method for learning (OML) named Smartick. This platform comprises reading and math activities for learning training. In this protocol, individual monitoring of each child is proposed to determine the progress in learning caused by Smartick. Methods and analysis: One hundred and twelve children aged between 8 and 12 who present reading or math difficulty after a rigorous psychometric evaluation will be recruited. The study comprises four sessions. In sessions 1 and 2, collective and individual psychometric evaluations will be performed, respectively. Reading and mathematical proficiency will be assessed, as well as attentional levels and intellectual quotient. Subsequently, each child will be semi-randomly assigned to either the experimental or control groups. Afterward, a first EEG will be collected for all children in session 3. Then, experimental groups will use Smartick for 3 months, in addition to their traditional learning method. In contrast, control groups will only continue with their traditional learning method. Finally, session 4 will consist of performing a second psychometric evaluation and another EEG, so that psychophysiological parameters can be encountered that indicate learning improvements due to the OML, regardless of the traditional learning method at hand. Discussion: Currently, few studies have validated learning improvement due to assistive technologies for learning. However, this proposal presents a psychophysiological evaluation addressed to children with reading or math difficulties who will be trained with an OML.

Improved emotion differentiation under reduced acoustic variability of speech in autism.

BACKGROUND: Socio-emotional impairments are among the diagnostic criteria for autism spectrum disorder (ASD), but the actual knowledge has substantiated both altered and intact emotional prosodies recognition. Here, a Bayesian framework of perception is considered suggesting that the oversampling of sensory evidence would impair perception within highly variable environments. However, reliable hierarchical structures for spectral and temporal cues would foster emotion discrimination by autistics. METHODS: Event-related spectral perturbations (ERSP) extracted from electroencephalographic (EEG) data indexed the perception of anger, disgust, fear, happiness, neutral, and sadness prosodies while listening to speech uttered by (a) human or (b) synthesized voices characterized by reduced volatility and variability of acoustic environments. The assessment of mechanisms for perception was extended to the visual domain by analyzing the behavioral accuracy within a non-social task in which dynamics of precision weighting between bottom-up evidence and top-down inferences were emphasized. Eighty children (mean 9.7 years old; standard deviation 1.8) volunteered including 40 autistics. The symptomatology was assessed at the time of the study via the Autism Diagnostic Observation Schedule, Second Edition, and parents' responses on the Autism Spectrum Rating Scales. A mixed within-between analysis of variance was conducted to assess the effects of group (autism versus typical development), voice, emotions, and interaction between factors. A Bayesian analysis was implemented to quantify the evidence in favor of the null hypothesis in case of non-significance. Post hoc comparisons were corrected for multiple testing. RESULTS: Autistic children presented impaired emotion differentiation while listening to speech uttered by human voices, which was improved when the acoustic volatility and variability of voices were reduced. Divergent neural patterns were observed from neurotypicals to autistics, emphasizing different mechanisms for perception. Accordingly, behavioral measurements on the visual task were consistent with the over-precision ascribed to the environmental variability (sensory processing) that weakened performance. Unlike autistic children, neurotypicals could differentiate emotions induced by all voices. CONCLUSIONS: This study outlines behavioral and neurophysiological mechanisms that underpin responses to sensory variability. Neurobiological insights into the processing of emotional prosodies emphasized the potential of acoustically modified emotional prosodies to improve emotion differentiation by autistics. TRIAL REGISTRATION: BioMed Central ISRCTN Registry, ISRCTN18117434. Registered on September 20, 2020.

EEG signals from tinnitus sufferers at identifying their sound tinnitus.

The present database contains brain activity of subjective tinnitus sufferers at identifying their sound tinnitus. The main objective of this database is to provide spontaneous Electroencephalographic (EEG) activity at rest, and evoked EEG activity when tinnitus sufferers attempt to identify their sound tinnitus among 54 tinnitus sound examples. For the database, 37 volunteers were recruited: 15 ones without tinnitus (Control Group - CG), and 22 ones with tinnitus (Tinnitus Group - TG). For EEG recording, 30 channels were used to record two conditions: 1) basal condition, where the volunteer remained in a state of rest with the open eyes for two minutes; and 2) active condition, where the volunteer must have identified his/her sound stimulus by pressing a key. For the active condition, a sound-tinnitus library was generated in accordance with the most typical acoustic properties of tinnitus. The library consisted in ten pure tones (250 Hz, 500 Hz, 1 kHz, 2 kHz, 3 kHz, 3.5 kHz, 4 kHz, 6 kHz, 8 kHz, 10 kHz), a White Noise (WN), a Narrow Band noise-High frequencies (NBH, 4 kHz-10 kHz), a Narrow Band noise-Medium frequencies (NBM,1 kHz-4 kHz), a Narrow-Band noise Low frequencies (NBL, 250 Hz-1 kHz), ten pure tones combined with WN, ten pure tones superimposed with NBH, ten tones with NBM and ten pure tones combined with NBL. In total, 54 sound-tinnitus were applied for both groups. In the case of CG, volunteers must have identified a sound at 3.5 kHz. In addition to EEG information, a csv-file with audiometric and psychoacoustic information of volunteers is provided. For TG, this information refers to: 1) hearing level, 2) type of tinnitus, 3) tinnitus frequency, 4) tinnitus perception, 5) Hospital Anxiety and Depression Scale (HADS) and 6) Tinnitus Functional Index (TFI). For CG, the information refers to: 1) hearing level, and 2) HADS.

Neuromarkers based on EEG Statistics in Time and Frequency Domains to Detect Tinnitus / Neuromarcadores basados en Estadística de EEG en el Dominio Temporal y Frecuencial para Detectar Acufeno

Abstract: Tinnitus detection and characterization requires a carefully elaborated diagnosis mainly owing to its heterogeneity nature. The present investigation aims to find features in Electroencephalographic (EEG) signals from time and frequency domain analysis that could distinguish between healthy and tinnitus sufferers with different levels of hearing loss. For this purpose, 24 volunteers were recruited and equally divided into four groups: 1) controls, 2) slow tinnitus, 3) middle tinnitus and 4) high tinnitus. EEG signals were registered in two states, with eyes closed and opened for 60 seconds. EEG analysis was focused on two bandwidths: delta and alpha band. For time domain, the EEG features estimated were mean, standard deviation, kurtosis, maximum peak, skewness and shape. For frequency domain, the EEG features obtained were mean, skewness, power spectral density. Normality of EEG data was evaluated by the Lilliefors test, and as a result, the nonparametric technique Kruskal-Wallis H statistic to test significance was applied. Results show that EEG features are more differentiable between tinnitus sufferers and controls in frequency domain than in time domain. EEG features from tinnitus patients with high HL are significantly different from the rest of the groups in alpha frequency band activity when shape and skewness are computed.

Resumen: La detección y caracterización del acúfeno requiere un diagnóstico cuidadosamente elaborado debido principalmente a su naturaleza heterogénea. La presente investigación tiene como objetivo encontrar características en las señales electroencefalográficas (EEG) a partir del análisis del dominio del tiempo y frecuencia que podrían distinguir entre pacientes sanos y con acúfeno con diferentes niveles de pérdida auditiva. Para ello, se reclutaron 24 voluntarios y se dividieron por igual en cuatro grupos: 1) controles, 2) acúfeno bajo, 3) acúfeno medio y 4) acufeno alto. La actividad EEG se registró en reposo en dos condiciones: ojos cerrados y abiertos durante un minuto. El análisis de EEG se centró en anchos de banda delta y alfa. Para el dominio del tiempo, las características del EEG estimadas fueron la media, la desviación estándar, la curtosis, el pico máximo, la asimetría y la forma. Para el dominio de la frecuencia, las características de EEG obtenidas fueron media, asimetría, densidad espectral de potencia. La normalidad de los datos del EEG se evaluó mediante la prueba de Lilliefors y, como resultado, se aplicó la técnica no paramétrica del estadístico H de Kruskal-Wallis para probar la significación. Los resultados muestran que las características del EEG son más diferenciables entre los pacientes con acúfeno y los controles en el dominio de la frecuencia que en el dominio del tiempo. Las características del EEG de los pacientes con acúfeno con alta pérdida de audición son significativamente diferentes del resto de los grupos en la actividad de la banda de alfa cuando se calculan la forma y la asimetría.

Acoustic Characterization of Edzna: A Measurement Dataset.

Acoustic characterizations of different locations are necessary to obtain relevant information on their behavior, particularly in the case of places that have not been fully understood or which purpose is still unknown since they are from cultures that no longer exist. Acoustic measurements were conducted in the archaeological zone of Edzna to obtain useful information to better understand the customs and practices of its past inhabitants. The information obtained from these acoustic measurements is presented in a dataset, which includes measurements taken at 32 points around the entire archaeological zone, with special attention given to the Main Plaza, the Great Acropolis, and the Little Acropolis. Two recording systems were used for this purpose: a microphone and a binaural head. As a result, a measurement database with the following characteristics was obtained: it comprises a total of 32 measurement points with 4 different sound source positions. In total, there are 297 files divided into separate folders. The sampling frequency used was 96 kHz, and the files are in mat format.

Binaural Beat Effects on Attention: A Study Based on the Oddball Paradigm.

The impact of binaural beats (BBs) on human cognition and behavior remains and various methods have been used to measure their effect, including neurophysiological, psychometric, and human performance evaluations. The few approaches where the level of neural synchronicity and connectivity were measured by neuroimaging techniques have only been undertaken in spontaneous mode. The present research proposes an approach based on the oddball paradigm to study BB effect by estimating the level of attention induced by BBs. Evoked activity of 25 young adults between 19 and 24 years old with no hearing impairments nor clinical neurological history were analyzed. The experiment was conducted in two different sessions of 24.5 min. The first part consisted of 20-min BB stimulation in either theta (BBθ) or beta (BBß). After the BB stimulation, an oddball paradigm was applied in each BB condition to assess the attentional effect induced by BBs. Attention enhancement is expected for BBß with respect to BBθ. Target event related potentials (ERPs) were mainly analyzed in the time and time-frequency domains. The frequency analysis was based on continuous wavelet transform (CWT), event-related spectral perturbation (ERSP), and inter-trial phase coherence (ITPC). The study revealed that the P300 component was not significantly different between conditions (BBθ vs. BBß). However, the target grand average ERP in BBθ condition was mainly composed of 8 Hz-frequency components, appearing before 400 ms post-stimulus, and mainly on the centro-parietal regions. In contrast, the target grand average ERP in BBß condition was mainly composed of frequency components below 6 Hz, mainly appearing at 400 ms post-stimulus on the parieto-occipital regions. Furthermore, ERPs in the BBθ condition were more phase locked than the BBß condition.

Autistic traits shape neuronal oscillations during emotion perception under attentional load modulation.

Emotional content is particularly salient, but situational factors such as cognitive load may disturb the attentional prioritization towards affective stimuli and interfere with their processing. In this study, 31 autistic and 31 typically developed children volunteered to assess their perception of affective prosodies via event-related spectral perturbations of neuronal oscillations recorded by electroencephalography under attentional load modulations induced by Multiple Object Tracking or neutral images. Although intermediate load optimized emotion processing by typically developed children, load and emotion did not interplay in children with autism. Results also outlined impaired emotional integration emphasized in theta, alpha and beta oscillations at early and late stages, and lower attentional ability indexed by the tracking capacity. Furthermore, both tracking capacity and neuronal patterns of emotion perception during task were predicted by daily-life autistic behaviors. These findings highlight that intermediate load may encourage emotion processing in typically developed children. However, autism aligns with impaired affective processing and selective attention, both insensitive to load modulations. Results were discussed within a Bayesian perspective that suggests atypical updating in precision between sensations and hidden states, towards poor contextual evaluations. For the first time, implicit emotion perception assessed by neuronal markers was integrated with environmental demands to characterize autism.

Perception of task-irrelevant affective prosody by typically developed and diagnosed children with Autism Spectrum Disorder under attentional loads: electroencephalographic and behavioural data.

The relevance of affective information triggers cognitive prioritisation, dictated by both the attentional load of the relevant task, and socio-emotional abilities. This dataset provides electroencephalographic (EEG) signals related to implicit emotional speech perception under low, intermediate, and high attentional demands. Demographic and behavioural data are also provided. Specific social-emotional reciprocity and verbal communication characterise Autism Spectrum Disorder (ASD) and may influence the processing of affective prosodies. Therefore, 62 children and their parents or legal guardians participated in data collection, including 31 children with high autistic traits (x̄age=9.6-year-old, σage=1.5) who previously received a diagnosis of ASD by a medical specialist, and 31 typically developed children (x̄age=10.2-year-old, σage=1.2). Assessments of the scope of autistic behaviours using the Autism Spectrum Rating Scales (ASRS, parent report) are provided for every child. During the experiment, children listened to task-irrelevant affective prosodies (anger, disgust, fear, happiness, neutral and sadness) while answering three visual tasks: neutral image viewing (low attentional load), one-target 4-disc Multiple Object Tracking (MOT; intermediate), one-target 8-disc MOT (high). The EEG data recorded during all three tasks and the tracking capacity (behavioural data) from MOT conditions are included in the dataset. Particularly, the tracking capacity was computed as a standardised index of attentional abilities during MOT, corrected for guessing. Beforehand, children answered the Edinburgh Handedness Inventory, and resting-state EEG activity of children was recorded for 2 minutes with eyes open. Those data are also provided. The present dataset can be used to investigate the electrophysiological correlates of implicit emotion and speech perceptions and their interaction with attentional load and autistic traits. Besides, resting-state EEG data may be used to characterise inter-individual heterogeneity at rest and, in turn, associate it with attentional capacities during MOT and with autistic behavioural patterns. Finally, tracking capacity may be useful to explore dynamic and selective attentional mechanisms under emotional constraints.

Chronic neuropathic pain: EEG data in eyes open and eyes closed with painDETECT and brief pain inventory reports.

Thirty-six chronic neuropathic pain patients (8 men and 28 women) of Mexican nationality with a mean age of 44±13.98 were recruited for EEG signal recording in eyes open and eyes closed resting state condition. Each condition was recorded for 5 min, with a total recording session time of 10 min. An ID number was given to each patient after signing up for the study, with which they answered the painDETECT questionnaire as a screening process for neuropathic pain alongside their clinical history. The day of the recording, the patients answered the Brief Pain Inventory, as an evaluation questionnaire for the interference of the pain with their daily life. Twenty-two EEG channels positioned in accordance with the 10/20 international system were registered with Smarting mBrain device. EEG signals were sampled at 250 Hz with a bandwidth between 0.1 and 100 Hz. The article provides two types of data: (1) raw EEG data in resting state and (2) the report of patients for two validated pain questionnaires. The data described in this article can be used for classifier algorithms considering stratifying chronic neuropathic pain patients with EEG data alongside their pain scores. In sum, this data is of extreme relevance for the pain field, where researchers have been seeking to integrate the pain experience with objective physiological data, such as the EEG.

Comparative analysis of acoustic therapies for tinnitus treatment based on auditory event-related potentials.

Introduction: So far, Auditory Event-Related Potential (AERP) features have been used to characterize neural activity of patients with tinnitus. However, these EEG patterns could be used to evaluate tinnitus evolution as well. The aim of the present study is to propose a methodology based on AERPs to evaluate the effectiveness of four acoustic therapies for tinnitus treatment. Methods: The acoustic therapies were: (1) Tinnitus Retraining Therapy (TRT), (2) Auditory Discrimination Therapy (ADT), (3) Therapy for Enriched Acoustic Environment (TEAE), and (4) Binaural Beats Therapy (BBT). In addition, relaxing music was included as a placebo for both: tinnitus sufferers and healthy individuals. To meet this aim, 103 participants were recruited, 53% were females and 47% were males. All the participants were treated for 8 weeks with one of these five sounds, which were moreover tuned in accordance with the acoustic features of their tinnitus (if applied) and hearing loss. They were electroencephalographically monitored before and after their acoustic therapy, and wherefrom AERPs were estimated. The sound effect of acoustic therapies was evaluated by examining the area under the curve of those AERPs. Two parameters were obtained: (1) amplitude and (2) topographical distribution. Results: The findings of the investigation showed that after an 8-week treatment, TRT and ADT, respectively achieved significant neurophysiological changes over somatosensory and occipital regions. On one hand, TRT increased the tinnitus perception. On the other hand, ADT redirected the tinnitus attention, what in turn diminished the tinnitus perception. Tinnitus handicapped inventory outcomes verified these neurophysiological findings, revealing that 31% of patients in each group reported that TRT increased tinnitus perception, but ADT diminished it. Discussion: Tinnitus has been identified as a multifactorial condition highly associated with hearing loss, age, sex, marital status, education, and even, employment. However, no conclusive evidence has been found yet. In this study, a significant (but low) correlation was found between tinnitus intensity and right ear hearing loss, left ear hearing loss, heart rate, area under the curve of AERPs, and acoustic therapy. This study raises the possibility to assign acoustic therapies by neurophysiological response of patient.

EEG frequency band analysis in chronic neuropathic pain: A linear and nonlinear approach to classify pain severity.

BACKGROUND AND OBJECTIVE: Chronic neuropathic pain (NP) is a chronic pain condition that severely impacts a patient's life. Pain management has proved to be inefficient due to a lack of a simple clinical tool that may identify and monitor NP. A low-cost, noninvasive tool that provides relevant information on NP is the electroencephalogram (EEG). However, the commonly used linear EEG features have proved to be limited in characterizing NP pathophysiology. This study sought to determine whether nonlinear EEG features such as approximate entropy (ApEn) would better differentiate pain severity than absolute band power. METHODS: A non-parametric statistical approach based on the Brief Pain Inventory (BPI), along with linear and nonlinear EEG features, is proposed in this study. For this purpose, thirty-six chronic NP patients were recruited, and 22 channels were registered. Additionally, a control database of 13 participants with no NP was used as a reference, where 19 channels were registered. For both groups, EEG was recorded for 10 min in a resting state: 5 min with eyes open (EO) and 5 min with eyes closed (EC). Absolute band power and ApEn EEG features in the five clinical frequency bands (delta, theta, alpha, beta, and gamma) were estimated for all channels in both groups. As a result, 220-dimensional and 190-dimensional feature vectors were obtained for experimental and control classes respectively. For the experimental class, NP patients were grouped according to their BPI evaluation in three groups: low, moderate, and high pain. Finally, feature vectors were compared between groups using Kruskal Wallis and post-hoc Dunn's tests. RESULTS: ApEn revealed significant statistical difference (p <=0.0001) in most frequency bands and conditions among the groups. In contrast, power had less significant differences between groups, particularly with EO. Furthermore, NP groups were notably clustered using only ApEn in theta, alpha, and beta bands. CONCLUSIONS: The results indicate that ApEn effectively characterizes the different severities of chronic NP rather than the commonly used linear features. ApEn and other nonlinear techniques (e.g., spectral entropy, Shannon entropy) might be a more suitable methodology to monitor chronic NP experience.

Mexican validation of the International Affective Digitized Sounds second edition (IADS-2) and additional sounds.

Affective stimuli have been extensively used in emotion research for a better understanding of emotion regulation. Sound ratings, specifically non-verbal sounds, are biased by demographic indicators such as sex and nationality. Therefore, it is crucial to characterize sounds prior to their use in emotion research. This study aims to validate the IADS-2 database and additional sounds in a sample from the Mexican population. Three hundred twenty-nine participants born and raised in Mexico remotely listened to 174 sounds in monophonic format. They rated sounds according to the valence-arousal-dominance model using the Self-Assessment Manikin test. Results positively correlated to those of previous studies. Sex differences were observed only in dominance between female and male groups, contrary to the results from Portuguese, American and Japanese validations. Geographic region analysis demonstrated differences in arousal, indicating the need for additional research on occident and south regions. Furthermore, when conducting affective research, headphones and audio quality should be considered, primarily to reduce variability due to audio-related aspects, and to avoid changes in emotional experience. Finally, this study supports the feasibility of remote affective sound experiments over the internet as reported in previous research.

Neuronal and behavioral affective perceptions of human and naturalness-reduced emotional prosodies.

Artificial voices are nowadays embedded into our daily lives with latest neural voices approaching human voice consistency (naturalness). Nevertheless, behavioral, and neuronal correlates of the perception of less naturalistic emotional prosodies are still misunderstood. In this study, we explored the acoustic tendencies that define naturalness from human to synthesized voices. Then, we created naturalness-reduced emotional utterances by acoustic editions of human voices. Finally, we used Event-Related Potentials (ERP) to assess the time dynamics of emotional integration when listening to both human and synthesized voices in a healthy adult sample. Additionally, listeners rated their perceptions for valence, arousal, discrete emotions, naturalness, and intelligibility. Synthesized voices were characterized by less lexical stress (i.e., reduced difference between stressed and unstressed syllables within words) as regards duration and median pitch modulations. Besides, spectral content was attenuated toward lower F2 and F3 frequencies and lower intensities for harmonics 1 and 4. Both psychometric and neuronal correlates were sensitive to naturalness reduction. (1) Naturalness and intelligibility ratings dropped with emotional utterances synthetization, (2) Discrete emotion recognition was impaired as naturalness declined, consistent with P200 and Late Positive Potentials (LPP) being less sensitive to emotional differentiation at lower naturalness, and (3) Relative P200 and LPP amplitudes between prosodies were modulated by synthetization. Nevertheless, (4) Valence and arousal perceptions were preserved at lower naturalness, (5) Valence (arousal) ratings correlated negatively (positively) with Higuchi's fractal dimension extracted on neuronal data under all naturalness perturbations, (6) Inter-Trial Phase Coherence (ITPC) and standard deviation measurements revealed high inter-individual heterogeneity for emotion perception that is still preserved as naturalness reduces. Notably, partial between-participant synchrony (low ITPC), along with high amplitude dispersion on ERPs at both early and late stages emphasized miscellaneous emotional responses among subjects. In this study, we highlighted for the first time both behavioral and neuronal basis of emotional perception under acoustic naturalness alterations. Partial dependencies between ecological relevance and emotion understanding outlined the modulation but not the annihilation of emotional integration by synthetization.

Chronic neuropathic pain is more than a perception: Systems and methods for an integral characterization.

The management of chronic neuropathic pain remains a challenge, because pain is subjective, and measuring it objectively is usually out of question. However, neuropathic pain is also a signal provided by maladaptive neuronal activity. Thus, the integral management of chronic neuropathic pain should not only rely on the subjective perception of the patient, but also on objective data that measures the evolution of neuronal activity. We will discuss different objective and subjective methods for the characterization of neuropathic pain. Additionally, the gaps and proposals for an integral management of chronic neuropathic pain will also be discussed. The current management that relies mostly on subjective measures has not been sufficient, therefore, this has hindered advances in pain management and clinical trials. If an integral characterization is achieved, clinical management and stratification for clinical trials could be based on both questionnaires and neuronal activity. Appropriate characterization may lead to an increased effectiveness for new therapies, and a better quality of life for neuropathic pain sufferers.

Effect of Auditory Discrimination Therapy on Attentional Processes of Tinnitus Patients.

Tinnitus is an auditory condition that causes humans to hear a sound anytime, anywhere. Chronic and refractory tinnitus is caused by an over synchronization of neurons. Sound has been applied as an alternative treatment to resynchronize neuronal activity. To date, various acoustic therapies have been proposed to treat tinnitus. However, the effect is not yet well understood. Therefore, the objective of this study is to establish an objective methodology using electroencephalography (EEG) signals to measure changes in attentional processes in patients with tinnitus treated with auditory discrimination therapy (ADT). To this aim, first, event-related (de-) synchronization (ERD/ERS) responses were mapped to extract the levels of synchronization related to the auditory recognition event. Second, the deep representations of the scalograms were extracted using a previously trained Convolutional Neural Network (CNN) architecture (MobileNet v2). Third, the deep spectrum features corresponding to the study datasets were analyzed to investigate performance in terms of attention and memory changes. The results proved strong evidence of the feasibility of ADT to treat tinnitus, which is possibly due to attentional redirection.

Binaural sound therapy for tinnitus treatment: A psychometric and neurophysiological evaluation.

INTRODUCTION: Tinnitus is an annoying buzz that manifests itself in many ways. In addition, it can provoke anxiety, stress, depression, and fatigue. The acoustic therapies have become the most commonly applied treatment for tinnitus, either self-administered or clinically prescribed. Binaural Sound Therapy (BST) and Music Therapy (MT) aim to reverse the neuroplasticity phenomenon related to tinnitus by adequately stimulating the auditory path-way. The goal of this research is to evaluate the feasibility of applying BST for tinnitus treatment by comparing its effect with MT effect. MATERIALS AND METHODS: 34 patients with tinnitus from 29 to 60 years were informed about the experimental procedure and consented their participation. Patients were divided into two groups: 1) MT and 2) BST. They applied their sound-based treatment for one hour every day along eight weeks. Each treatment was adjusted to Hearing Loss (HL) and tinnitus characteristics of each participant. To record EEG data, a bio-signal amplifier with sixteen EEG channels was used. The system recorded data at a sampling frequency of 256 Hz within a bandwidth between 0.1 and 100 Hz. RESULTS: The questionnaire-monitoring reported that MT increased tinnitus perception in 30% of the patients, and increased anxiety and stress in 8% of them. Regarding EEG-monitoring, major neural synchronicity over the frontal lobe was found after the treatment. In the case of BST reduced stress in 23% of patients. Additionally, BST reduced tinnitus perception similar to MT (15% of patients). With respect to EEG-monitoring, slightly major neural synchronicity over the right frontal lobe was found after the treatment. CONCLUSIONS: MT should be applied with caution since it could be worsening the tinnitus sufferer condition. On the other hand, BST is recommended for tinnitus sufferers who have side effects concerning stress but no anxiety.

Personalized Theta and Beta Binaural Beats for Brain Entrainment: An Electroencephalographic Analysis.

Binaural beats (BB) consist of two slightly distinct auditory frequencies (one in each ear), which are differentiated with clinical electroencephalographic (EEG) bandwidths, namely, delta, theta, alpha, beta, or gamma. This auditory stimulation has been widely used to module brain rhythms and thus inducing the mental condition associated with the EEG bandwidth in use. The aim of this research was to investigate whether personalized BB (specifically those within theta and beta EEG bands) improve brain entrainment. Personalized BB consisted of pure tones with a carrier tone of 500 Hz in the left ear together with an adjustable frequency in the right ear that was defined for theta BB (since f c for theta EEG band was 4.60 Hz ± 0.70 SD) and beta BB (since f c for beta EEG band was 18.42 Hz ± 2.82 SD). The adjustable frequencies were estimated for each participant in accordance with their heart rate by applying the Brain-Body Coupling Theorem postulated by Klimesch. To achieve this aim, 20 healthy volunteers were stimulated with their personalized theta and beta BB for 20 min and their EEG signals were collected with 22 channels. EEG analysis was based on the comparison of power spectral density among three mental conditions: (1) theta BB stimulation, (2) beta BB stimulation, and (3) resting state. Results showed larger absolute power differences for both BB stimulation sessions than resting state on bilateral temporal and parietal regions. This power change seems to be related to auditory perception and sound location. However, no significant differences were found between theta and beta BB sessions when it was expected to achieve different brain entrainments, since theta and beta BB induce relaxation and readiness, respectively. In addition, relative power analysis (theta BB/resting state) revealed alpha band desynchronization in the parieto-occipital region when volunteers listened to theta BB, suggesting that participants felt uncomfortable. In conclusion, neural resynchronization was met with both personalized theta and beta BB, but no different mental conditions seemed to be achieved.

Different Headphone Models Modulate Differently Alpha and Theta Brain Oscillations When Listening to the Same Sound.

The frequency content of a sound changes the perception of acoustic features, but can headphones also change auditory information interpretation? Audio devices such as headphones are factors that have not been taken into consideration at studying sound perception, specifically in acoustic therapies. In particular, alternative treatments based on psychoacoustic effects could be more effective if the frequency response of headphones is found as a determining factor.This investigation, therefore, aims to study the brain response (in terms of electroencephalographic activity) produced by listening to pink noise in three different headphone models. Furthermore, not only the immediate response is studied, but the sound habituation (after daily exposure to pink noise for 30 days) is also investigated. The investigation findings reveal that headphones with a flatter frequency response provide more accurate acoustic information to the brain, what in turn, demands a larger number and a wider variety of mental resources, even after a habituation process.Clinical Relevance-This investigation establishes that audio devices are a determining factor to achieve specific psychoacoustic effects since they change the auditory information decoding at a cortical level.

Identification of Neuropathic Pain Severity based on Linear and Non-Linear EEG Features.

The lack of an integral characterization of chronic neuropathic pain (NP) has led to pharmacotherapy mismanagement and has hindered advances in clinical trials. In this study, we attempted to identify chronic NP by fusing psychometric (based on the Brief Inventory of Pain - BIP), and both linear and non-linear electroencephalographic (EEG) features. For this purpose, 35 chronic NP patients were recruited voluntarily. All the volunteers answered the BIP; and additionally, 22 EEG channels positioned in accordance with the 10/20 international system were registered for 10 minutes at resting state: 5 minutes with eyes open and 5 minutes with eyes closed. EEG Signals were sampled at 250 Hz within a bandwidth between 0.1 and 100 Hz. As linear features, absolute band power was obtained per clinical frequency band: delta (0.1~4 Hz), theta (4~8 Hz), alpha (8~12 Hz), beta (12~30 Hz) and gamma (30~100 Hz); considering five regions: prefrontal, frontal, central, parietal and occipital. As non-linear features, approximate entropy was calculated per channel and per clinical frequency band with addition of the broadband (0.1~100 Hz). Resulting feature vectors were grouped in line with the BIP outcome. Three groups were considered: low, moderate, and high pain. Finally, BIP-EEG patterns were classified in those three classes, achieving 96% accuracy. This result improves a previous work of a SVM classifier that used exclusively linear EEG features and showed an accuracy between 87% and 90% per class to predict central NP after spinal cord injury.

The Mexican Emotional Speech Database (MESD): elaboration and assessment based on machine learning.

The Mexican Emotional Speech Database is presented along with the evaluation of its reliability based on machine learning analysis. The database contains 864 voice recordings with six different prosodies: anger, disgust, fear, happiness, neutral, and sadness. Furthermore, three voice categories are included: female adult, male adult, and child. The following emotion recognition was reached for each category: 89.4%, 93.9% and 83.3% accuracy on female, male and child voices, respectively.Clinical Relevance - Mexican Emotional Speech Database is a contribution to healthcare emotional speech data and can be used to help objective diagnosis and disease characterization.