Roberto Hornero

• PhD. Prof.
• Professor (Full) at University of Valladolid

Obstructive sleep apnea (OSA) and insomnia are the two most prevalent sleep disorders, often co-occurring in a condition termed comorbid insomnia and sleep apnea (COMISA). While autonomic nervous system (ANS) dysfunction resulting from each of these disorders has been separately established through heart rate variability (HRV) analysis, the specifi...

Diabetic retinopathy (DR) is one of the leading causes of blindness globally. Several studies indicate that 90% of cases are preventable through early detection and appropriate treatment. Due to the increasing number of diabetic patients, the number of images that ophthalmologists have to manually analyze is becoming unaffordable. In this study, we...

Sleep irregularity has been linked to multiple deleterious consequences in clinical populations or community adults and adolescents, but little is known about young adults. In this study, we explored the relationships between two measures of sleep regularity and a wide range of factors (lifestyle behaviors, subjective sleep, clinical outcomes, and...

Introduction Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental condition that affects cognitive, academic, behavioral, emotional, and social functioning, primarily in children. Despite its high prevalence, current pharmacological treatments are not effective in 30% of cases and show poor long-term adherence. Non-pharmacologica...

The growing interest in electroencephalography (EEG) research has highlighted the need for low-cost, wearable EEG acquisition systems. The high cost of commercially available EEG equipment poses a significant challenge to the widespread adoption of these systems and, consequently, to the advancement of potential real-world applications. This paper...

Obstructive sleep apnea (OSA) in children is a prevalent and serious respiratory condition linked to cardiovascular morbidity. Polysomnography, the standard diagnostic approach, faces challenges in accessibility and complexity, leading to underdiagnosis. To simplify OSA diagnosis, deep learning (DL) algorithms have been developed using cardiac sign...

El deterioro cognitivo leve (DCL) y la demencia debidos a la enfermedad de Alzheimer (EA) afectan a la actividad cerebral, provocando alteraciones tanto en regiones cerebrales específicas como en sus dependencias estadísticas. La magnetoencefalografía (MEG) y la electroencefalografía (EEG) permiten registrar la actividad cerebral y extraer diferent...

La electroencefalografía (EEG) es una técnica que permite medir la actividad eléctrica generada en el cerebro. Para ello es necesaria la utilización de algún paradigma de registro como el EEG en estado de reposo (resting-state, RS), en el que se pretende inducir un estado de divagación mental (mind-wandering, MW). Sin embargo, la consistencia de lo...

La demencia debida a la enfermedad de Alzheimer (EA) es una patología neurológica caracterizada por déficits cognitivos, conductuales y funcionales. Por otro lado, el deterioro cognitivo leve (DCL) puede considerarse un estado prodrómico de la EA. El objetivo de este estudio es realizar una clasificación multiclase de estas dos patologías integrand...

Background and Objective: Alzheimer's disease (AD) is a neurological disorder that impairs brain functions associated with cognition, memory, and behavior. Noninvasive neurophysiological techniques like magnetoen-cephalography (MEG) and electroencephalography (EEG) have shown promise in reflecting brain changes related to AD. These techniques are u...

Introduction: Visual attention is a cognitive skill related to visual perception and neural activity, and also moderated by expertise, in time-constrained professional domains (e.g., aviation, driving, sport, surgery). However, the contribution of both perceptual and neural processes on performance has been studied separately in the literature. De...

Deep-learning algorithms have been proposed to analyze overnight airflow (AF) and oximetry (SpO 2) signals to simplify the diagnosis of pediatric obstructive sleep apnea (OSA), but current algorithms are hardly interpretable. Explainable artificial intelligence (XAI) algorithms can clarify the models-derived predictions on these signals, enhancing...

La migraña es un trastorno neurológico que se divide en dos subtipos dependiendo de la frecuencia de los ataques al mes: migraña crónica (MC) y episódica (ME). No existen biomarcadores que permitan realizar un diagnóstico preciso. Por ello, el objetivo de este estudio es cuantificar las posibles alteraciones producidas por los subtipos de migraña e...

La actividad electroencefalográfica (EEG) espontánea es generada por el cerebro de forma natural en ausencia de estímulos específicos. El registro de la actividad EEG en estado de reposo (RS, resting-state) suele realizarse tratando de “no pensar en nada”, con lo cual se induce un estado de divagación mental (MW, mind-wandering). Sin embargo, exist...

Las hiperintesidades de materia blanca (white matter hyperintensities, WMHs) son indicios de lesiones en el tejido cerebral observables mediante resonancia magnética. Las WMHs son útiles para caracterizar cuadros patológicos tempranos y están asociadas a un incremento del riesgo de diversas dolencias. Sin embargo, el impacto que producen dichas ano...

La degeneración macular asociada a la edad (DMAE) es un trastorno que afecta a la mácula, una zona de la retina clave para la agudeza visual. La DMAE es una de las causas más frecuentes de ceguera en personas mayores de 60 años en los países desarrollados. Aunque se han propuesto tratamientos que frenan su desarrollo, su eficacia disminuye signific...

La degeneración macular asociada a la edad (DMAE) es la principal causa de pérdida irreversible de visión en la población anciana. Los algoritmos de deep learning y, en particular, las redes neuronales convolucionales (CNN), han demostrado ser útiles en el diagnóstico precoz de la enfermedad. En este trabajo se compararon 12 modelos CNN preentrenad...

Code-modulated visual evoked potentials (c-VEPs) are an innovative control signal utilized in brain-computer interfaces (BCIs) with promising performance. Prior studies on steady-state visual evoked potentials (SSVEPs) have indicated that the spatial frequency of checkerboard-like stimuli influences both performance and user experience. Spatial fre...

Background Obstructive sleep apnea (OSA) is a risk factor for metabolic syndrome (MetS) in adults, but its association in prepubertal children is still questionable due to the relatively limited cardiometabolic data available and the phenotypic heterogeneity. Objective To identify the role of OSA as a potential mediator of MetS in prepubertal chil...

The high prevalence of sleep apnea and the limitations of polysomnography have prompted the investigation of strategies aimed at automated diagnosis using a restricted number of physiological measures. This study aimed to demonstrate that thoracic (THO) and abdominal (ABD) movement signals are useful for accurately estimating the severity of sleep...

Code-modulated visual evoked potentials (c-VEPs) have potential as a reliable and non-invasive control signal for brain-computer interfaces (BCIs). However, these systems need to become more user-friendly. Non-binary codes have been proposed to reduce visual fatigue, but there is still a lack of adaptive methods to shorten trial durations. To addre...

Brain-computer interfaces (BCI) based on code-modulated visual evoked potentials (c-VEP) have shown great potential for communication and device control. These systems encode each command using different sequences of visual stimuli. Normally, the stimulation pattern is binary (i.e., black and white), but non-binary stimuli sequences with different...

Introduction and objective Video games are crucial to the entertainment industry, nonetheless they can be challenging to access for those with severe motor disabilities. Brain-computer interfaces (BCI) systems have the potential to help these individuals by allowing them to control video games using their brain signals. Furthermore, multiplayer BCI...

The majority of electroencephalographic (EEG) and magnetoencephalographic (MEG) studies filter and analyse neural signals in specific frequency ranges, known as "canonical" frequency bands. However, this segmentation, is not exempt from limitations, mainly due to the lack of adaptation to the neural idiosyncrasies of each individual. In this study,...

Introduction Logically valid deductive arguments are clear examples of abstract recursive computational procedures on propositions or on probabilities. However, it is not known if the cortical time-consuming inferential processes in which logical arguments are eventually realized in the brain are in fact physically different from other kinds of inf...

Objective. Brain connectivity networks are usually characterized in terms of properties coming from the complex network theory. Using new measures to summarize the attributes of functional connectivity networks can be an important step for their better understanding and characterization, as well as to comprehend the alterations associated with neur...

Background and objective. Neurofeedback (NF) is a paradigm that allows users to self-modulate patterns of brain activity. It is implemented with a closed-loop brain-computer interface (BCI) system that analyzes the user’s brain activity in real-time and provides continuous feedback. This paradigm is of great interest due to its potential as a non-p...

Identifying potentially life-threatening diseases is a key challenge for emergency medical services. This study aims at examining the role of different prehospital biomarkers from point-of-care testing to derive and validate a score to detect 2-day in-hospital mortality. We conducted a prospective, observational, prehospital, ongoing, and derivatio...

The majority of electroencephalographic (EEG) and magnetoencephalographic (MEG) studies filter and analyse neural signals in specific frequency ranges, known as "canonical" frequency bands. However, this segmentation, is not exempt from limitations, mainly due to the lack of adaptation to the neural idiosyncrasies of each individual. In this study,...

Background and objective: Neurotechnologies have great potential to transform our society in ways that are yet to be uncovered. The rate of development in this field has increased significantly in recent years, but there are still barriers that need to be overcome before bringing neurotechnologies to the general public. One of these barriers is th...

- Heart rate variability (HRV) is modulated by sleep stages and apneic events. Previous studies in children compared classical HRV parameters during sleep stages between obstructive sleep apnea (OSA) and controls. However, HRV-based characterization incorporating both sleep stages and apneic events has not been conducted. Furthermore, recently prop...

Objective. Previous studies have reported neurophysiological differences between chronic migraine (CM) and healthy controls (HC). The aim of the current study is to evaluate how the CM condition affects the brain activity in women using spectral measures. Methods. We have included 62 female subjects: 32 CM patients (age 34.50 (27.50, 39.00)) and 30...

Background The diagnosis of migraine is mainly clinical and self-reported, which makes additional examinations unnecessary in most cases. Migraine can be subtyped into chronic (CM) and episodic (EM). Despite the very high prevalence of migraine, there are no evidence-based guidelines for differentiating between these subtypes other than the number...

La migraña puede ser clasificada en dos subtipos: migraña crónica (MC) y episódica (ME), en función de los días que se sufre dolor de cabeza al mes (más, o menos de 15 días). Estos dos subtipos de migraña requieren un tratamiento diferente, lo cual sugiere que el desarrollo de cada una también es distinta. El objetivo de este estudio es analizar la...

Detecting obstructive sleep apnea (OSA) is important to both prevent significant comorbidities in people with Down syndrome (DS) and untangle contributions to other behavioral and mental health diagnoses. However, laboratory‐based polysomnograms are often poorly tolerated, unavailable, or not covered by health insurance for this population. In prev...

El Neurofeedback (NF) es una de las principales aplicaciones de los sistemas Brain-Computer Interfaces (BCI). Esta técnica busca inducir cambios en la actividad cerebral del usuario a través del aprendizaje de la modulación voluntaria de los ritmos neuronales. En este trabajo se presenta un análisis exploratorio de los efectos del NF desde una pers...

La evaluación de la calidad de las retinografías es una etapa fundamental en los sistemas automáticos de cribado de distintas patologías oculares, como son la retinopatía diabética, el glaucoma, las cataratas o la degeneración macular asociada a la edad. El objetivo de este trabajo fue desarrollar un método basado en deep learning y un mecanismo de...

A growing number of studies have shown the strong relationship between sleep and different cognitive processes, especially those that involve memory consolidation. Traditionally, these processes were attributed to mechanisms related to the macroarchitecture of sleep, as sleep cycles or the duration of specific stages, such as the REM stage. More re...

The overnight polysomnography shows a range of drawbacks to diagnose obstructive sleep apnea (OSA) that have led to the search for artificial intelligence-based alternatives. Many classic machine learning methods have been already evaluated for this purpose. In this chapter, we show the main approaches found in the scientific literature along with...

Automated analysis of the blood oxygen saturation (SpO 2) signal from nocturnal oximetry has shown usefulness to simplify the diagnosis of obstructive sleep apnea (OSA), including the detection of respiratory events. However, the few preceding studies using SpO 2 recordings have focused on the automated detection of respiratory events versus normal...

Obstructive sleep apnea (OSA) is a multidi-mensional disease often underdiagnosed due to the complexity and unavailability of its standard diagnostic method: the polysomnography. Among the alternative abbreviated tests searching for a compromise between simplicity and accurateness, oximetry is probably the most popular. The blood oxygen saturation...

The airflow (AF) is a physiological signal involved in the overnight polysomnography (PSG) that reflects the respiratory activity. This signal is able to show the particularities of sleep apnea and is therefore used to define apneic events. In this regard, a growing number of studies have shown the usefulness of employing the overnight airflow as t...

Background Orthokeratology (ortho-k) is an overnight clinical contact lens wear technique to correct myopia and to reduce myopia progression wearing reverse-geometry rigid gas-permeable lenses. The lens fitting procedure in clinical practice usually requires subjective assessment of fluorescein pattern (fluorescein “bull’s eye” pattern). The aim of...

Complex properties of functional connectivity networks built using source-level neural electromagnetic signals are useful to characterize the alterations of mild cognitive impairment (MCI). Source-level signals were obtained from 20 electroencephalographic and 20 magnetoencephalographic longitudinal recordings of MCI patients using a finite element...

Background Machine‐learning approaches have enabled promising results in efforts to simplify the diagnosis of pediatric obstructive sleep apnea (OSA). A comprehensive review and analysis of such studies increase the confidence level of practitioners and healthcare providers in the implementation of these methodologies in clinical practice. Objecti...

Introduction. Logically valid deductive arguments are clear examples of abstract recursive computational procedures on propositions or on probabilities. However, it is not known if the cortical time-consuming inferential processes in which logical arguments are eventually realized in the brain are in fact physically different from other kinds of in...

Previous studies have suggested that the typical slow oscillations (SO) characteristics during sleep could be modified in the presence of pediatric obstructive sleep apnea (OSA). Here, we evaluate whether these modifications are significant and if they may reflect cognitive deficits. We recorded the overnight electroencephalogram (EEG) of 294 pedia...

The gold standard approach to diagnose obstructive sleep apnea (OSA) in children is overnight in-lab polysomnography (PSG), which is labor-intensive for clinicians and onerous to healthcare systems and families. Simplification of PSG should enhance availability and comfort, and reduce complexity and waitlists. Airflow (AF) and oximetry (SpO2) signa...

In this study, we present a new Deep Learning (DL) architecture for Motor Imagery (MI) based Brain Computer Interfaces (BCIs) called EEGSym . Our implementation aims to improve previous state-of-the-art performances on MI classification by overcoming inter-subject variability and reducing BCI inefficiency, which has been estimated to affect 10-50...

Despite significant and meritorious research efforts over the last decades, the functions and evolutionary determinants of sleep remain one of the mysterious and relatively unexplored dimensions of physiology (Krueger et al, 2016). The recipe for deciphering such an attractive challenge in biology and medicine most probably includes ingredients suc...

Hallucinations are considered characteristic symptoms of psychosis and part of the ‘psychosis superspectrum’ of the Hierarchical Taxonomy Of Psychopathology (HiTOP) initiative. To gain insight into their psychopathological relevance, we studied their dimensional placement within a single dense transdiagnostic network constituting of basic symptoms...

Objective. Schizophrenia is a psychiatric disorder that has been shown to disturb the dynamic top-down processing of sensory information. Various imaging techniques have revealed abnormalities in brain activity associated with this disorder, both locally and between cerebral regions. However, there is increasing interest in investigating dynamic ne...

Background and objective: Brain-computer interfaces (BCI) based on event-related potentials (ERP) are a promising technology for alternative and augmented communication in an assistive context. However, most approaches to date are synchronous, requiring the intervention of a supervisor when the user wishes to turn his attention away from the BCI s...

Motor and cognitive disabilities may lead to communication difficulties, exacerbated by the intelligibility of speech and gesture. In this context, brain–computer interfaces (BCIs) can be viewed as novel augmentative and alternative communication technologies to assist these people. Despite the extensive research in BCIs during the last decades, po...

Neurofeedback training (NFT) allows to self-regulate neural activity, having application on a wide range of disorders to improve cognitive functions. This work was aimed at designing, developing and testing a novel NFT platform to prevent cognitive decline due to normal ageing in elderly population. A closed-loop brain-computer interface based on e...

Resumen La enfermedad de Alzheimer (EA) es una enfermedad de-generativa con alta prevalencia en la sociedad actual. El diagnóstico de la misma es complejo y costoso. Por ello, se investiga en nuevas formas de caracterización de las altera-ciones que esta enfermedad provoca en la red neuronal. En el presente trabajo se pretende evaluar la robustez d...

Many brain–computer interface (BCI) studies overlook the channel optimization due to its inherent complexity. However, a careful channel selection increases the performance and users’ comfort while reducing the cost of the system. Evolutionary meta-heuristics, which have demonstrated their usefulness in solving complex problems, have not been fully...

Objective. Code-modulated visual evoked potentials (c-VEP) have been consolidated in recent years as robust control signals capable of providing non-invasive brain–computer interfaces (BCIs) for reliable, high-speed communication. Their usefulness for communication and control purposes has been reflected in an exponential increase of related articl...

La enfermedad de Alzheimer (EA) constituye la principal causa de demencia en los países occidentales. Para su estudio se pueden utilizar diversas técnicas neurofisiológicas y de neuroimagen, entre las que destaca la electroencefalografía (EEG) por su bajo coste, portabilidad y ser no invasivo. La EEG ha revelado diferentes alteraciones que provoca...

Neurofeedback training (NFT) has shown promising results in recent years as a tool to address the effects of age-related cognitive decline in the elderly. Since previous studies have linked reduced complexity of electroencephalography (EEG) signal to the process of cognitive decline, we propose the use of non-linear methods to characterise changes...

Pediatric obstructive sleep apnea (OSA) is a prevalent disorder that disrupts sleep and is associated with neurocognitive and behavioral negative consequences, potentially hampering the development of children for years. However, its relationships with sleep electroencephalogram (EEG) have been scarcely investigated. Here, our main objective was to...

Overnight pulse oximetry has shown usefulness to simplify obstructive sleep apnea (OSA) diagnosis when combined with machine-learning approaches. However, the development and evaluation of a single model with ability to reach high diagnostic performance in both community-based non-referral and clinical referral cohorts are still pending. Since ense...

Sleep staging is of paramount importance in children with suspicion of pediatric obstructive sleep apnea (OSA). Complexity, cost, and intrusiveness of overnight polysomnography (PSG), the gold standard, have led to the search for alternative tests. In this sense, the photoplethysmography signal (PPG) carries useful information about the autonomous...

The main objective of this study was to examine the influence that recording length, sampling frequency, and imaging modality have on the estimation and characterization of spontaneous brain meta-states during rest. To this end, a recently developed method of meta-state extraction and characterization was applied to a subset of 16 healthy elderly s...

Connectivity analyses are widely used to assess the interaction brain networks. This type of analyses is usually conducted considering the well-known classical frequency bands: delta, theta, alpha, beta, and gamma. However, this parcellation of the frequency content can bias the analyses, since it does not consider the between-subject variability o...

The author wishes to make the following correction to this paper [...]