Projects

Mental or brain disorders are characterized by a significant disturbance in a person’s cognition, emotional regulation or behavior, that can be occasional or chronic. Usually, mental disorders are connected to distress or impairment in important areas of functioning. In fact, 1 in every 8 people was living with a mental disorder in 2019; being anxiety and depressive disorders the most common. Despite the availability of effective prevention and treatment options, a large majority of those with mental disorders lack access to adequate care. Additionally, individuals with mental health issues often face stigma, discrimination, and human rights violations.

Notwithstanding the evident genetic substrate and the many cerebral alterations identified during the last decades, there is still little knowledge about the causes of severe psychiatric disorders, such as schizophrenia and bipolar disorder; which leads to a non-targeted treatment that is only partially efficacious. On top of that, there exists a large heterogeneity within each diagnosis, being the patients too different among themselves, suggesting that each diagnostic label includes different biologically substrates. Thus, segregating valid clusters of cases may help in identifying causal mechanisms that may be very useful in both diagnosis and in defining targets for new more tolerable and efficacious treatments. In the last decade, we have reported the possibility of identifying the aforementioned clusters based on the cerebral structure, the cognitive performance and the pattern of bioelectrical activity of patients. Concretely, we have reported a subgroup across schizophrenia and bipolar disorder characterized by a very poor cognitive performance, anatomical deficits and a hyperactive brain that cannot modulate adequately its activity during cognitive tasks.

A deficit in the inhibitory systems of the brain, which are based on the GABA neurotransmitter, is thought to contribute significantly to this group. Therefore, we propose examining its function using transcranial magnetic stimulation (TMS), since it is thought to modulate them. Moreover, we have been using it during the last years. We have already collected a sample of more than 200 cases and 200 controls studied with magnetic resonance, electroencephalography (EEG), clinical and cognitive assessments and, in part, transcranial magnetic stimulation. We need to increase this sample to approximately 500 subjects per group to be able to identify subgroups of patients based on the causal mechanisms contributing to their illness. Finally, we also expect that the patients with a significant cerebral inhibitory deficit would respond to a particular treatment (clozapine) selectively, since this drug improves GABA function in the cortex.

The main objectives are:

• To identify a group of patients with psychotic disorders (possibly including a majority of patients with schizophrenia, but also cases of bipolar disorders) characterized primarily by a significant cognitive deficit, which will be accompanied by abnormal ego experiences, functional cortical hyperactivation, decreased regional cortical thickness and decreased mean fractional anisotropy.
• To assess cortical GABA hypofunction of GABA-A or/and GABA-B type with TMS in patients and controls and its relation to cognition.
• To assess the relation between inhibitory deficits and cognitive task-induced variation (modulation) of bioelectrical activity, assessed with EEG.
• To compare treatment resistance between patients with or without inhibitory activity deficits, and the degree of response to clozapine
• To compare treatment resistance between patients with or without inhibitory activity deficits, and the degree of response to clozapine

In order to achieve the aforementioned objectives, different procedures are going to be implemented. First, we will use TMS-EEG data to assess the cortical inhibitory systems of the brain of both pathological and non-pathological populations. To assess this function, two different paired-pulses paradigms will be employed: the long-interval intracortical inhibition (LICI) protocol, that is thought to be mediated by GABA-B receptor and the short-interval intracortical inhibition (SICI), mediated by GABA-A receptor. For the evaluation of the cognitive performance, an auditory oddball task will be used. Three different tones (a distractor, a target and a standard tones) will be presented to the participant, who will have to press a button each time they hear the target one. The cortical activity during the task will be recorded with EEG. Both, TMS-EEG and EEG data will be analyzed to characterize the cortical activity of the participants and to extract the features needed to perform the clustering and the assessing of the cortical GABA hypofunction and the relation between the inhibitory deficits and the cognitive performance.

Publications
Fernández-Linsenbarth I, Mijancos-Martínez G, Bachiller A, Núñez P, Rodríguez-González V, Beño-Ruiz-de-la-Sierra RM, Roig-Herrero A, Arjona-Valladares A, Poza J, Mañanas MÁ, Molina V. Relation between task-related activity modulation and cortical inhibitory function in schizophrenia and healthy controls: a TMS-EEG study. Eur Arch Psychiatry Clin Neurosci. 2024 Jan 19. doi: /10.1007/s00406-023-01745-0 . Epub ahead of print. PMID: 38243018.

In this pilot study the authors aim to explore the association between EEG modulation during a cognitive task (using and auditory task) and the inhibitory system function (employing TMS-EEG) in vivo in a sample including healthy controls and patients with schizophrenia. Results replicated the task-related cortical activity modulation deficit in schizophrenia patients. Moreover, they showed higher cortical reactivity compared to healthy controls. Cortical reactivity was inversely associated with EEG modulation, supporting the idea that a hypofunction of the inhibitory system could hamper the task-related modulation of EEG activity.

Díez Á, Gomez-Pilar J, Poza J, Beño-Ruiz-de-la-Sierra R, Fernández-Linsenbarth I, Recio-Barbero M, Núñez P, Holgado-Madera P, Molina V. Functional network properties in schizophrenia and bipolar disorder assessed with high-density electroencephalography. Prog Neuropsychopharmacol Biol Psychiatry. 2024 Feb 8;129:110902. doi: 10.1016/j.pnpbp.2023.110902. Epub 2023 Nov 29. PMID: 38036032.

This study investigates cortical functional networks in schizophrenia (SCZ) using graph theory parameters applied to high-density EEG. Connectivity Strength (CS) measures global network synchrony, and Shannon Graph Complexity (SGC) assesses network distribution of link weights, allowing to distinguish between primary and secondary pathways. Brain activity of the participants (healthy controls -HC-, SCZ patients and bipolar disorder -BD- patietns) during a P300 oddball task was recorded using EEG. SCZ patients had higher pre-stimulus CS values and lower theta-band CS modulation compared to HC. Both SCZ and BD patients showed reduced theta-band CS modulation. Chronic SCZ patients also exhibited reduced SGC modulation. Relationships were found between theta-band SGC modulation and CS measures, which correlated with cognitive outcomes and negative symptoms. The study concluded that SCZ and BD patients have hyperactive, hypomodulatory networks, particularly in secondary pathways, independent of antipsychotic effects.

Beño-Ruiz-de-la-Sierra RM, Arjona-Valladares A, Hernández-García M, Fernández-Linsenbarth I, Díez Á, Fondevila Estevez S, Castaño C, Muñoz F, Sanz-Fuentenebro J, Roig-Herrero A, Molina V. Corollary Discharge Dysfunction as a Possible Substrate of Anomalous Self-experiences in Schizophrenia. Schizophr Bull. 2023 Nov 10:sbad157. doi: 10.1093/schbul/sbad157 . Epub ahead of print. PMID: 37951230.

The study explores the dysfunction of the corollary discharge mechanism in schizophrenia (SCZ), which suppresses the perception of self-generated speech and reduces the auditory N1 event-related potential during EEG recordings. A dysfunction in this mechanism may be linked to anomalous self-experiences (AEs) in SCZ.ERP were recorded with EEG from SCZ patients and healthy control; both during concurrent listening to self-produced vowels (talk condition) and and non-concurrent listening to the same vowels (listen condition). AEs and symptomatology were scored with IPASE, PANSS and BNSS. N1 amplitude was lower during talk conditions compared to listen condition in both populations. However, the difference in N1 amplitude between both conditions was significantly higher in controls than in schizophrenia patients. These differences in patients correlated significantly and negatively with the IPASE, PANSS, and BNSS scores. The findings suggest that corollary discharge dysfunction may underlie ASEs in schizophrenia.

Beño-Ruiz-de-la-Sierra RM, Arjona-Valladares A, Fondevila Estevez S, Fernández-Linsenbarth I, Díez Á, Molina V. Corollary discharge function in healthy controls: Evidence about self-speech and external speech processing. Eur J Neurosci. 2023 Oct;58(7):3705-3713. doi: 10.1111/ejn.16125. Epub 2023 Aug 27. PMID: 37635264.

The study examines corollary discharge in healthy individuals, which reduces perception of self-generated speech and attenuates the auditory N1 component. Event-related potentials were recorded in a healthy population in three conditions: self-spoken vowels (talk condition), played-back vowels of their own voice (listen-self condition), and played-back vowels of an external voice (listen-other condition). The N1 amplitude was smaller for self-spoken vowels compared to both played-back conditions, with no differences between the two listen conditions. The P2 component and peak latencies showed no differences across conditions. These results confirm that corollary discharge dampens sensory responses to self-generated speech and provide new neurophysiological evidence about the similarities in the processing of played-back vowels with our own voice (ownership experience) and with an external voice.

Congresses proceedings

2024 SIRS Congress (Schizophrenia International Research Society), 3-7 April, Florence, Italy.
Fernández-Linsenbarth, I; Mijancos-Martínez, G; Bachiller, A; Beño-Ruis-de-la-Sierra, R; Arjona-Valladares, A; Roig-Herrero, A; Mañanas, A; Molina, V. Cortical reactivity and task-related activity modulation in schizophrenia and healthy controls: A TMS-EEG study.

Beño-Ruiz-de-la-Sierra, Arjona-Valladares, A; R; G; Fondevila-Estévez, S; Fernández-Linsenbarth, I; Roig-Herrero, A; Díez, A; Molina, V. Corollary discharge dysfunction as a potential underlying mechanism for Abnormal Self-Experiences and its association with clinical symptoms in schizophrenia.

2023 EMBC Congress (45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society), 24-27 July, Sydney, Australia
Mijancos-Martinez G, Bachiller A, Fernandez-Linsenbarth I, Romero S, Alonso JF, Molina V, Mañanas MA. Cortical inhibition on TMS-EEG: interstimulus interval effect on short-interval paired-pulse. Annu Int Conf IEEE Eng Med Biol Soc. 2023 Jul;2023:1-4. doi: 10.1109/EMBC40787.2023.10340654 . PMID: 38083290.

Strength training, functional exercises, and movement imbalance assessment are the major pillars of the typical motor rehabilitation process and evaluation. Surprisingly, therapists just have the patient's perspective regarding muscular weariness or pain; they do not evaluate neuromuscular activity, even if it is the cause of the disorder. Since there is currently no commercial tool that can accurately assess muscular status, patients and therapists are generally unaware of it, despite the fact that it is essential to defining the rehabilitation program and tracking its progress.

The available systems to evaluate muscle function for diagnosis consist of intramuscular electromyography (EMG) delivered using needles, which is highly accurate but causes discomfort to patients. The alternative is surface EMG, a non‑invasive option that relies primarily on two electrodes, showing a limitation when it comes to measuring muscle activity and, consequently, muscular functionality.

BIOART team improved the surface EMG muscle activity system by advancing innovative technology, developing electrode arrays on a highly adaptable technical fabric. The multiple EMG channels displayed on an array can be recorded over a significant muscle area. Through wireless transmission to a computer or tablet, this project enabled us to finish the pre‑industrial prototype, create user‑friendly interfaces that let patients direct the exercises and give clinicians indexes and reports to track their progress, and apply machine learning algorithms for automated patient evaluation.

During this project, we conducted a comprehensive market analysis, examining different potential customer segments and regions, including market size, go‑to‑market strategy, and reimbursement models. We integrated all available information to develop a preliminary business plan outlining the spin‑off creation model and the commercialization of MyoArm as a product for rehabilitation centers, either directly or through insurance companies. The preliminary business plan has been continuously refined and expanded into an investor‑ready plan with a 5‑year forecast.

The project helped us to mature the technology to create a commercially available product to fit a need in the market. During the product development, we explored other areas that helped us design a roadmap for technology transfer and prepare us as a team for future spin‑off creation and product commercialization.

The main objectives are:

• Objective 1: Technical Development. Integration of 2D dry electrode arrays into fabric for obtaining a sensor for the upper arm; completion of the pre‑industrial prototype by transmitting wirelessly to a computer/tablet; development of user‑friendly interfaces for patients to guide the exercises and for clinicians with indexes and reports to monitor the patient’s progress; and implementation of machine‑learning algorithms for automatic patient evaluation.
• Objective 2: Clinical Valorisation. System validation in control subjects and patients.
• Objective 3: Preliminary Business Development. Business development and technology transfer initiatives including market analysis studies, financial roadmap, business plan development, intellectual property initiatives, regulatory roadmap and exploitation activities.
• Objective 4: Team integration. Integrating the interdisciplinary team to have a less expensive MVP to obtain the most important clinical outcome on time.

The methodology includes three main areas: Management, Technical Solution and Clinical Evaluation.

MANAGEMENT

The project is organized into three working areas associated with the acceleration of the technology transfer: technical, clinical and business. In all areas, the participation of physicians and engineers is very important:

• To design and develop a medical device according to the needs and usability of therapists and patients.
• Its validation with the support of engineers to show its management and functionalities to the physicians during the RCT and the later upgrade.
• To define business strategies for market access of private and public health system and CE mark regulation.

An interdisciplinary team is crucial for the success of all issues and its integration has been considered with a specific Work Package and specific objectives. The project team is composed of experts in biomedical engineering, medical doctors experts in rehabilitation, and one engineer expert on entrepreneurship and business. Separated meetings will be necessary to discuss specific technical or clinical issues, but periodic joint ones will also be programmed, particularly semester one‑day workshops to share the project progress, discuss issues and next steps, and prepare deliverables and milestones.

TECHNICAL SOLUTION

Regarding the design and development of both hardware and software of MyoArm, the common guidelines for medical devices will be followed: limited manufacturing costs, scalable design, low battery consumption, maximum usability and comfort for patients (textile sensor easy to put on, smaller dimensions and weight of the device, motivating serious games) and therapists (automatic and simple reports of patients’ progress, selection of more useful information about muscle function, prognosis indexes based on machine learning), regulatory requirements, low risk level of hazards and maintenance avoiding short‑term obsolete electronic components or software platforms, etc.

CLINICAL EVALUATION

Participants will be asked to answer questionnaires evaluating the impact of experienced motor‑impairment fatigue on daily life activities (Modified Fatigue Impact Scale), the Spanish version of the Disabilities of the Arm, Shoulder and Hand (DASH) questionnaire for functional impact assessment, and the perceived quality of life (WHOQOL‑BREF questionnaire). Motor function of all participants will be evaluated by a physician to assess motor impairment and to evaluate motor strength and fatigue using clinical tests (Medical Research Council scale).

Then, an estimation of muscle mass and body composition will be conducted using ultrasound and bio‑impedance, respectively. Instrumental evaluation of motor strength and fatigue will be conducted on upper limbs. Hand grip strength will be measured using dynamometry and isokinetic dynamometry. Muscle strength is considered the maximal isometric torque during 5 s in three consecutive trials. Muscle fatigue is evaluated using the JAMAR grip test during 12 repeated contractions of 30 s, and a fatigue index is calculated as the ratio between the average of the last and the first three recordings. Changes in muscle mass and body composition will be assessed via ultrasound and bio‑impedance. All patients will perform isometric and non‑isometric tasks according to the specific motor impairment.

Publications

Shirzadi, M., Rojas-Martínez, M., Alonso, J. F., Serna, L. Y., Chaler, J., Mañanas, M. A., & Marateb, H. R. (2024). AML-DECODER: Advanced Machine Learning for HD-sEMG Signal Classification—Decoding Lateral Epicondylitis in Forearm Muscles. Diagnostics, 14(20), 2255. doi: 10.3390/diagnostics14202255 .

In this study, the authors used innovative algorithms for wearable devices and garments that are critical for diagnosing and monitoring disease progression, such as lateral epicondylitis (LE). They analyzed signals from the forearm muscles of 14 healthy controls and 14 LE patients using high‑density surface electromyography and employed advanced signal features and neural networks for classification.

Shirzadi, M., Marateb, H. R., Rojas-Martínez, M., Mansourian, M., Botter, A., Vieira dos Anjos, F., Vieira, M. V., & Mañanas, M. A. (2023). A real-time and convex model for the estimation of muscle force from surface electromyographic signals in the upper and lower limbs. Frontiers in Physiology, 14, 1098225. doi: 10.3389/fphys.2023.1098225 .

The authors proposed a new real‑time convex and interpretable model for estimating muscle force from sEMG signals in upper and lower limbs. They validated it in isometric tasks in upper and lower limbs and compared its performance with multiple state‑of‑the‑art models, reporting high accuracy and low computation time.

Shirzadi, M., Marateb, H. R., McGill, K. C., Muceli, S., Mañanas, M. A., & Farina, D. (2023). An accurate and real-time method for resolving superimposed action potentials in multiunit recordings. IEEE Transactions on Biomedical Engineering, 70(1), 378–389. doi: 10.1109/TBME.2022.3192119 .

The study presents algorithms to resolve superimposed action potentials in intramuscular EMG and neural recordings, enabling accurate spike sorting in real time. The proposed methods showed high accuracy and efficiency across large simulated and experimental datasets.

Marateb, H. R., Rojas-Martínez, M., Zamani, S., Shirzadi, M., Koochekian, A., & Mañanas, M. A. (2023). The application of Industry 4.0 technologies for automated health monitoring and surveillance during pandemics and post-pandemic life. In Advanced Signal Processing for Industry 4.0, Volume 1. IOP Publishing. doi: 10.1088/978-0-7503-5247-5ch6 .

This chapter discusses how Industry 4.0 technologies such as IoT, AI, big data and cloud computing can support automated health monitoring and surveillance during pandemics. It reviews recent literature and outlines use cases including smart healthcare, contact tracing, and risk assessment.