Brain Sciences

2 pages, 165 KiB

Open AccessCorrection

Correction: Macchini et al. Intra-Arrest Therapeutic Hypothermia and Neurologic Outcome in Patients Admitted After Out-of-Hospital Cardiac Arrest: A Post Hoc Analysis of the Princess Trial. Brain Sci. 2022, 12, 1374

by Elisabetta MACCHINI, Emelie DILLENBECK, Martin JONSSON, Filippo ANNONI, Sune FORSBERG, Jacob HOLLENBERG, Anatolij TRUHLAR, Leif SVENSSON, Per NORDBERG and Fabio Silvio TACCONE

Brain Sci. 2025, 15(7), 748; https://doi.org/10.3390/brainsci15070748 (registering DOI) - 14 Jul 2025

Abstract

In the original publication [...] Full article

3 pages, 141 KiB

Open AccessComment

Redefining Clinical Perspectives on MCS: Toward an Evidence-Based, Multisystem Model. Comment on Jacques, L. Multiple Chemical Sensitivity: A Clinical Perspective. Brain Sci. 2024, 14, 1261

by Elaine Psaradellis

Brain Sci. 2025, 15(7), 747; https://doi.org/10.3390/brainsci15070747 (registering DOI) - 14 Jul 2025

Abstract

The article “Multiple Chemical Sensitivity: A Clinical Perspective”, published in Brain Sciences, suggests that multiple chemical sensitivity (MCS) is primarily a psychogenic disorder, rooted in unresolved emotional trauma and stress responses [...] Full article

18 pages, 823 KiB

Open AccessReview

GABAergic Influences on Medulloblastoma

by Viviane Aline Buffon, Jurandir M. Ribas Filho, Osvaldo Malafaia, Isadora D. Tassinari, Rafael Roesler and Gustavo R. Isolan

Brain Sci. 2025, 15(7), 746; https://doi.org/10.3390/brainsci15070746 (registering DOI) - 11 Jul 2025

Abstract

Medulloblastoma (MB) is the most common malignant brain tumor in children and typically arises in the cerebellum, likely due to disruptions in neuronal precursor development. The primary inhibitory neurotransmitter in the central nervous system (CNS), γ-aminobutyric acid (GABA), exerts its effects through GABA [...] Read more.

Medulloblastoma (MB) is the most common malignant brain tumor in children and typically arises in the cerebellum, likely due to disruptions in neuronal precursor development. The primary inhibitory neurotransmitter in the central nervous system (CNS), γ-aminobutyric acid (GABA), exerts its effects through GABA_A, GABA_B, and GABA_C receptors. GABA receptor activity regulates the development and function of cerebellar neurons, including glutamatergic cerebellar granule cells (CGCs). Beyond the nervous system, GABA is also a common metabolite in non-neuronal cell types. An increasing body of evidence indicates that GABA can influence cell proliferation, differentiation, and migration in several types of adult solid tumors, including brain cancers. GABA and GABA_A receptor agonists can impair the viability and survival of MB cells, primarily acting on GABA_A receptors containing the α5 subunit. A marked expression of the gene encoding the α5 subunit is found across all MB tumor molecular subgroups, particularly Group 3 MB, which has a poor prognosis. Importantly, high levels of the γ-aminobutyric acid type A receptor subunit α5 (GABRA5) gene are associated with shorter patient overall survival in Group 3 and Group 4 MB. In contrast, high γ-aminobutyric acid type A receptor subunit β1 (GABRB1) gene expression is related to longer survival in all MB subgroups. The GABAergic system may, therefore, regulate MB cell function and tumor progression and influence patient prognosis, and is worthy of further investigation as a biomarker and therapeutic target in MB. Full article

(This article belongs to the Special Issue Editorial Board Collection Series: Advances in Neuro-Oncology)

► Show Figures

Figure 1

12 pages, 674 KiB

Open AccessArticle

Quality of Life in Multiple Sclerosis Compared to Amyotrophic Lateral Sclerosis: Fatigue and Fast Disease Progression Interferes with the Ability to Psychosocially Adjust

by Luisa T. Balz, Ingo Uttner, Jochen Weishaupt, Albert C. Ludolph, Daniela Taranu, Ioannis Vardakas, Stefanie Jung, Tanja Fangerau, Deborah K. Erhart, Makbule Senel, Hayrettin Tumani and Dorothée E. Lulé

Brain Sci. 2025, 15(7), 745; https://doi.org/10.3390/brainsci15070745 - 11 Jul 2025

Abstract

Background/Objectives: Multiple sclerosis (MS) is a complex neurological disease that is associated with a broad spectrum of physical and psychological symptoms. Psychosocial adjustment (PSA) refers to the ability to cope with these challenges, which influence quality of life (QoL) and depressiveness in [...] Read more.

Background/Objectives: Multiple sclerosis (MS) is a complex neurological disease that is associated with a broad spectrum of physical and psychological symptoms. Psychosocial adjustment (PSA) refers to the ability to cope with these challenges, which influence quality of life (QoL) and depressiveness in ways not yet fully understood. This study explores the relationship of PSA and disease-specific symptoms in MS, including fatigue, a prominent MS symptom. Additionally, PSA was compared to Amyotrophic Lateral Sclerosis (ALS) to disentangle the impact of disease trajectory on PSA. Methods: We interviewed 77 MS patients using patient-reported outcome measures on QoL and depression and compared them to 30 ALS patients. Confirmatory factor analysis and regression analysis were used to identify PSA indicators and predictors in MS, while t-tests assessed PSA differences across diseases. Results: Key PSA indicators in MS included physical (PQoL), mental (MQoL), and subjective (SQoL) quality of life, as well as depressiveness, with cognitive and motor fatigue emerging as significant predictors. MS patients had higher PQoL and SQoL and lower levels of depression compared to ALS patients, while both groups were comparable with regard to MQoL. Conclusions: PSA in MS is supported by high QoL and low depression levels, with fatigue being a significant predictor. Despite different disease trajectories, patients with MS and ALS showed comparable MQoL, indicating that both diseases similarly impact mental QoL, reflecting a partial overlap in psychosocial adjustment. Overall, psychosocial adjustment was more favorable in MS, likely due to its slower disease progression compared to ALS. Full article

(This article belongs to the Special Issue Neuropsychological Impact and Quality of Life in Chronic Illness)

► Show Figures

Figure 1

18 pages, 1399 KiB

Open AccessArticle

Single-Stage Endovascular Management of Concurrent Intracranial Aneurysms and Arterial Stenoses: Clinical Outcomes, Procedural Strategies, and Predictive Factors

by Marat Sarshayev, Shayakhmet Makhanbetkhan, Aiman Maidan, Roger Barranco Pons, Dimash Davletov, Abzal Zhumabekov and Mynzhylky Berdikhojayev

Brain Sci. 2025, 15(7), 744; https://doi.org/10.3390/brainsci15070744 (registering DOI) - 11 Jul 2025

Abstract

Background: The coexistence of extracranial arterial stenoses and intracranial aneurysms presents a unique clinical dilemma. While staged interventions are traditionally preferred to reduce procedural risks, recent advances have enabled single-stage endovascular treatment. This study evaluates the clinical outcomes, procedural strategies, and predictive factors [...] Read more.

Background: The coexistence of extracranial arterial stenoses and intracranial aneurysms presents a unique clinical dilemma. While staged interventions are traditionally preferred to reduce procedural risks, recent advances have enabled single-stage endovascular treatment. This study evaluates the clinical outcomes, procedural strategies, and predictive factors associated with such combined interventions. Methods: This retrospective study included 47 patients treated with single-stage endovascular procedures for concurrent extracranial stenosis and intracranial aneurysm between 2016 and 2024. Clinical, angiographic, and procedural data were collected. Outcomes were assessed using the mmodified Rankin Scale (mRS), and statistical analyses were performed to identify associations between clinical variables and functional outcomes. Results: Of the 47 patients, 85.1% achieved favorable outcomes (mRS 0–2) at ≥6-month follow-up. The most commonly treated arteries were the internal carotid artery (70.2%) and the middle cerebral artery (34%). Stent-assisted coiling or flow diversion was performed in 93.6% of aneurysm cases, while 91.5% underwent carotid or vertebral stenting. Lesion laterality (left-sided aneurysms, p = 0.019) and stenosis length (p = 0.0469) were significantly associated with outcomes. Smoking was linked to multiple stenoses (p = 0.0191). Two patients experienced major complications: one aneurysmal rebleed after stenting, and one intraoperative rupture. Conclusions: Single-stage endovascular treatment for patients with concurrent extracranial stenosis and intracranial aneurysm is technically feasible and clinically effective in selected cases. Lesion configuration, anatomical considerations, and individualized planning are critical in optimizing outcomes. Full article

(This article belongs to the Special Issue The Latest Exploration of Cerebrovascular Diseases: From Preclinical Research to Treatment)

► Show Figures

Figure 1

9 pages, 199 KiB

Open AccessReview

Glial Diversity and Evolution: Insights from Teleost Fish

by Carla Lucini and Claudia Gatta

Brain Sci. 2025, 15(7), 743; https://doi.org/10.3390/brainsci15070743 - 11 Jul 2025

Abstract

Glial cells, once considered mere support for neurons, have emerged as key players in brain function across vertebrates. The historical study of glia dates to the 19th century with the identification of ependymal cells and astrocytes, followed by the discovery of oligodendrocytes and [...] Read more.

Glial cells, once considered mere support for neurons, have emerged as key players in brain function across vertebrates. The historical study of glia dates to the 19th century with the identification of ependymal cells and astrocytes, followed by the discovery of oligodendrocytes and microglia. While neurocentric perspectives overlooked glial functions, recent research highlights their essential roles in neurodevelopment, synapse regulation, brain homeostasis, and neuroimmune responses. In teleost fish, a group comprising over 32,000 species, glial cells exhibit unique properties compared to their mammalian counterparts. Thus, the aim of this review is synthesizing the current literature on fish glial cells, emphasizing their evolutionary significance, diversity, and potential as models for understanding vertebrate neurobiology. Microglia originate from both yolk sac cells and hematopoietic stem cells, forming distinct populations with specialized functions in the adult brain. Neural stem cells, including radial glial cells (RGCs) and neuroepithelial cells, remain active throughout life, supporting continuous neuro- and gliogenesis, a phenomenon far more extensive than in mammals. Ependymocytes line brain ventricles and show structural variability, with some resembling quiescent progenitor cells. Astrocytes are largely absent in most fish species. However, zebrafish exhibit astrocyte-like glial cells which show some structural and functional features in common with mammalian astrocytes. Oligodendrocytes share conserved mechanisms with mammals in myelination and axon insulation. Full article

(This article belongs to the Section Neuroglia)

18 pages, 638 KiB

Open AccessCase Report

Feasibility of Home-Based Transcranial Direct Current Stimulation with Telerehabilitation in Primary Progressive Aphasia—A Case Series

by Anna Uta Rysop, Tanja Grewe, Caterina Breitenstein, Ferdinand Binkofski, Mandy Roheger, Nina Unger, Agnes Flöel and Marcus Meinzer

Brain Sci. 2025, 15(7), 742; https://doi.org/10.3390/brainsci15070742 - 10 Jul 2025

Abstract

Background: Primary progressive aphasia (PPA) is a neurodegenerative disease characterised by progressive impairment of speech and language abilities. Intensive speech and language teletherapy combined with remotely supervised, self-administered transcranial direct current stimulation (tDCS) may be suited to remove barriers to accessing potentially effective [...] Read more.

Background: Primary progressive aphasia (PPA) is a neurodegenerative disease characterised by progressive impairment of speech and language abilities. Intensive speech and language teletherapy combined with remotely supervised, self-administered transcranial direct current stimulation (tDCS) may be suited to remove barriers to accessing potentially effective treatments, but there is only limited evidence on the feasibility of this combined approach. Methods: This pilot case series investigated the feasibility, tolerability and preliminary efficacy of a novel telerehabilitation programme combined with home-based, self-administered tDCS for people with primary progressive aphasia (pwPPA). The intervention programme was co-developed with pwPPA and their caregivers, to reflect their priorities regarding treatment content and outcomes (i.e., naming, functional communication). Results: Two pwPPA successfully completed the telerehabilitation intervention with daily naming training and communicative-pragmatic therapy paired with tDCS, over 10 consecutive workdays. Caregivers assisted in the setup of equipment required for teletherapy and home-based tDCS. Participants successfully completed the programme with a 95% completion rate. Home-based tDCS was well tolerated. Both participants showed improvements in naming and communication, suggesting preliminary efficacy of the intervention. Conclusions: Overall, this study demonstrates the feasibility and potential benefit of a novel, easily accessible and patient-relevant telerehabilitation intervention for pwPPA, which requires confirmation in a future larger-scale exploratory trial. Full article

(This article belongs to the Special Issue Primary Progressive Aphasia: What Happens to Speech and Language? What Can We Do to Help?)

► Show Figures

Figure 1

27 pages, 344 KiB

Open AccessArticle

Biopsychosocial Profile of Chronic Alcohol Users: Insights from a Cross-Sectional Study

by Luciana Angela Ignat, Raluca Oana Tipa, Alina Roxana Cehan and Vladimir Constantin Bacârea

Brain Sci. 2025, 15(7), 741; https://doi.org/10.3390/brainsci15070741 - 10 Jul 2025

Abstract

Introduction: Chronic alcohol use is a complex condition influenced by psychological, behavioral, and socio-demographic factors. This study aimed to develop a comprehensive psychosocial profile of individuals with alcohol use disorder (AUD) by examining associations between psychometric variables and relapse risk including repeated psychiatric [...] Read more.

Introduction: Chronic alcohol use is a complex condition influenced by psychological, behavioral, and socio-demographic factors. This study aimed to develop a comprehensive psychosocial profile of individuals with alcohol use disorder (AUD) by examining associations between psychometric variables and relapse risk including repeated psychiatric hospitalizations. Methodology: A cross-sectional observational analytical study was conducted on a sample of 104 patients admitted for alcohol withdrawal management at the “Prof. Dr. Al. Obregia” Psychiatric Clinical Hospital in Bucharest between March 2023 and September 2024. Participants completed a set of validated psychometric tools: the Drinker Inventory of Consequences—Lifetime Version (DrInC), Readiness to Change Questionnaire—Treatment Version (RTCQ), Drinking Expectancy Questionnaire (DEQ), and Drinking Refusal Self-Efficacy Questionnaire (DRSEQ). Additional data were collected on the socio-demographic (education level, socio-professional category), genetic (family history of alcohol use), and behavioral factors (length of abstinence, tobacco use, co-occurring substance use disorders). Results: Higher alcohol-related consequence scores (DrInC) were significantly associated with lower education (p < 0.001, η² = 0.483), disadvantaged socio-professional status (p < 0.001, η² = 0.514), and family history of alcohol use (p < 0.001, η² = 0.226). Self-efficacy (DRSEQ) was significantly lower among individuals with co-occurring substance use (p < 0.001) and nicotine dependence (p < 0.001). Logistic regression showed that the DrInC scores significantly predicted readmission within three months (OR = 1.09, p = 0.001). Conclusions: Psychometric tools are effective in identifying individuals at high risk. Personalized, evidence-based interventions tailored to both psychological and socio-professional profiles, combined with structured post-discharge support, are essential for improving long-term recovery and reducing the readmission rates. Full article

(This article belongs to the Section Neuropathology)

12 pages, 211 KiB

Open AccessCase Report

Acute Medical Events in Adults with Profound Autism: A Review and Illustrative Case Series

by Heli Patel, Anamika L. Shrimali, Christopher J. McDougle and Hannah M. Carroll

Brain Sci. 2025, 15(7), 740; https://doi.org/10.3390/brainsci15070740 - 10 Jul 2025

Abstract

Background: Autism spectrum disorder (ASD) is associated with social-communication challenges that can hinder timely diagnosis and treatment during acute medical events (AMEs). The purpose of this report is to review the literature on medical comorbidities and AMEs in adults with profound ASD [...] Read more.

Background: Autism spectrum disorder (ASD) is associated with social-communication challenges that can hinder timely diagnosis and treatment during acute medical events (AMEs). The purpose of this report is to review the literature on medical comorbidities and AMEs in adults with profound ASD and highlight how healthcare teams can better understand atypical presentations of acute pain and discomfort in adults with profound ASD to reduce delayed diagnoses, delays in treatment, and ultimately improve health outcomes. Methods: The literature on medical comorbidities and AMEs in adults with profound ASD was reviewed using the following databases: PubMed, PsycINFO, and Google Scholar. The histories of three adults with profound ASD who experienced AMEs—specifically, appendicitis, nephrolithiasis, and eosinophilic esophagitis (EoE)—are described. The clinical cases were selected to illustrate the challenges inherent in diagnosing and treating AMEs in adults with profound ASD in the context of the review. Results: In Case 1, a 31-year-old male with autism was diagnosed with perforated appendicitis after his family noticed behavioral changes. In Case 2, a 36-year-old male with autism experienced intermittent pain from nephrolithiasis and communicated his discomfort through irritability and pointing. In Case 3, a 34-year-old male with autism exhibited atypical behavior due to pain from undiagnosed EoE, identified after years of untreated pain and multiple unsuccessful clinical procedures. Conclusions: This review and the illustrative cases demonstrate the significant role that communication barriers play in delayed medical diagnoses for adults with profound ASD during AMEs. Integrating caregiver insights and recognizing atypical pain expressions are essential for improving the accuracy and timeliness of diagnosis and treatment in this population. Full article

(This article belongs to the Special Issue Unraveling Autism: Neurobiological Mechanisms and Emerging Therapeutic Advances)

19 pages, 1039 KiB

Open AccessArticle

Prediction of Parkinson Disease Using Long-Term, Short-Term Acoustic Features Based on Machine Learning

by Mehdi Rashidi, Serena Arima, Andrea Claudio Stetco, Chiara Coppola, Debora Musarò, Marco Greco, Marina Damato, Filomena My, Angela Lupo, Marta Lorenzo, Antonio Danieli, Giuseppe Maruccio, Alberto Argentiero, Andrea Buccoliero, Marcello Dorian Donzella and Michele Maffia

Brain Sci. 2025, 15(7), 739; https://doi.org/10.3390/brainsci15070739 - 10 Jul 2025

Abstract

Background: Parkinson’s disease (PD) is the second most common neurodegenerative disorder after Alzheimer’s disease, affecting countless individuals worldwide. PD is characterized by the onset of a marked motor symptomatology in association with several non-motor manifestations. The clinical phase of the disease is usually [...] Read more.

Background: Parkinson’s disease (PD) is the second most common neurodegenerative disorder after Alzheimer’s disease, affecting countless individuals worldwide. PD is characterized by the onset of a marked motor symptomatology in association with several non-motor manifestations. The clinical phase of the disease is usually preceded by a long prodromal phase, devoid of overt motor symptomatology but often showing some conditions such as sleep disturbance, constipation, anosmia, and phonatory changes. To date, speech analysis appears to be a promising digital biomarker to anticipate even 10 years before the onset of clinical PD, as well serving as a useful prognostic tool for patient follow-up. That is why, the voice can be nominated as the non-invasive method to detect PD from healthy subjects (HS). Methods: Our study was based on cross-sectional study to analysis voice impairment. A dataset comprising 81 voice samples (41 from healthy individuals and 40 from PD patients) was utilized to train and evaluate common machine learning (ML) models using various types of features, including long-term (jitter, shimmer, and cepstral peak prominence (CPP)), short-term features (Mel-frequency cepstral coefficient (MFCC)), and non-standard measurements (pitch period entropy (PPE) and recurrence period density entropy (RPDE)). The study adopted multiple machine learning (ML) algorithms, including random forest (RF), K-nearest neighbors (KNN), decision tree (DT), naïve Bayes (NB), support vector machines (SVM), and logistic regression (LR). Cross-validation technique was applied to ensure the reliability of performance metrics on train and test subsets. These metrics (accuracy, recall, and precision), help determine the most effective models for distinguishing PD from healthy subjects. Result: Among all the algorithms used in this research, random forest (RF) was the best-performing model, achieving an accuracy of 82.72% with a ROC-AUC score of 89.65%. Although other models, such as support vector machine (SVM), could be considered with an accuracy of 75.29% and a ROC-AUC score of 82.63%, RF was by far the best one when evaluated across all metrics. The K-nearest neighbor (KNN) and decision tree (DT) performed the worst. Notably, by combining a comprehensive set of long-term, short-term, and non-standard acoustic features, unlike previous studies that typically focused on only a subset, our study achieved higher predictive performance, offering a more robust model for early PD detection. Conclusions: This study highlights the potential of combining advanced acoustic analysis with ML algorithms to develop non-invasive and reliable tools for early PD detection, offering substantial benefits for the healthcare sector. Full article

(This article belongs to the Section Neurodegenerative Diseases)

► Show Figures

Figure 1

6 pages, 352 KiB

Open AccessArticle

A Single-Incision Method for the Removal of Vagus Nerve Stimulators: A Single-Institution Retrospective Review

by Michael Baumgartner, Matthew Diehl and James E. Baumgartner

Brain Sci. 2025, 15(7), 738; https://doi.org/10.3390/brainsci15070738 - 10 Jul 2025

Abstract

Vagal nerve stimulators (VNSs) improve seizure control in up to half of the patients who have them implanted. In non-responding patients, VNS removal may be necessary. Removal is traditionally accomplished through two incisions. We present our experience removing VNSs through a single incision. [...] Read more.

Vagal nerve stimulators (VNSs) improve seizure control in up to half of the patients who have them implanted. In non-responding patients, VNS removal may be necessary. Removal is traditionally accomplished through two incisions. We present our experience removing VNSs through a single incision. Background/Objectives: To determine if VNS removal can be safely performed through a single incision. Methods: The medical records of 73 consecutive patients who underwent VNS removal at our institution from 2012 to 2024 were reviewed. Patients were divided into single-incision and two-incision treatment groups. Operative time and surgical complications were compared between groups. Results: A total of 73 patients underwent VNS removal during the study timeframe. Forty-eight VNS removals were accomplished via a single incision, while 25 required both incisions. Time in the operating room was roughly half as long for single-incision removal vs. two-incision removal (29.4 min, range 11–84 vs. 74.2 min, range 33–203); however, single incision was initially attempted in all cases. In two of the incision cases, the neck dissection resulted in an injury to the internal jugular (IJ) vein. In one case, the IJ was repaired and the lead wire removed. In a second case, the IJ could not be repaired, and a segment of lead wire was retained. In a third case, a short length of lead wire was discovered after a single-incision removal and a second procedure was necessary for removal. There were no significant differences in the rates of transient vocal cord weakness, cough, and/or dysphagia between both treatment groups (p = 0.7368), and there were no cases of permanent nerve palsy. Conclusions: VNS removal can be safely accomplished via a single incision in most cases. Successful single-incision procedures may be shorter than the two-incision approach. Attempted VNS removal via a single incision may result in increased incidence of transient hoarseness, dysphagia, and/or cough, but may result in reduced rates of permanent injury or IJ injury. Full article

(This article belongs to the Section Neurosurgery and Neuroanatomy)

► Show Figures

Figure 1

15 pages, 295 KiB

Open AccessArticle

Validity Evidence of the TRIACOG-Online Administered In-Person to Adults Post Stroke

by Luana Comito Muner, Guilherme Domingos Martins, Ana Beatriz Santos Honda, Natália Becker and Jaqueline de Carvalho Rodrigues

Brain Sci. 2025, 15(7), 737; https://doi.org/10.3390/brainsci15070737 - 10 Jul 2025

Abstract

Background/Objectives: Neuropsychological assessment tools adapted for digital formats are crucial to expanding access and improving cognitive evaluation in post-stroke patients. This study aimed to examine the reliability, convergent validity, and criterion-related validity (concurrent and known-groups) of TRIACOG-Online, a computerized cognitive screening tool [...] Read more.

Background/Objectives: Neuropsychological assessment tools adapted for digital formats are crucial to expanding access and improving cognitive evaluation in post-stroke patients. This study aimed to examine the reliability, convergent validity, and criterion-related validity (concurrent and known-groups) of TRIACOG-Online, a computerized cognitive screening tool designed to assess multiple domains in post-stroke adults in person or remotely. Methods: 98 participants (47 neurologically healthy adults and 51 post-stroke patients) completed a sociodemographic questionnaire, the Mini-Mental State Examination—MMSE, G-38—Nonverbal Intelligence Test, and the TRIACOG-Online assessment. Evaluations were conducted in person, computer mediated. Results: TRIACOG-Online demonstrated high internal consistency (Cronbach’s α = 0.872; McDonald’s ω = 0.923). Statistically significant differences were found between groups in episodic memory, attention, executive functions, and numerical processing, with healthy individuals outperforming post-stroke participants. Effect sizes were medium to large in several domains, especially for visual memory. Validity evidence based on the relationship with external variables was supported by negative correlations with age and positive correlations with education and reading and writing habits, particularly in the clinical group. Educational level showed stronger associations with verbal memory and language, suggesting a protective role in post-stroke cognitive performance. TRIACOG-Online scores demonstrated evidence of convergent validity with MMSE and G-38. Conclusions: TRIACOG-Online shows strong psychometric properties for the cognitive assessment of post-stroke adults. Its computerized format represents a promising tool for clinical and research use in neuropsychology, especially for bedside applications. Full article

(This article belongs to the Special Issue Advances in Cognitive and Psychometric Evaluation)

14 pages, 1117 KiB

Open AccessArticle

Factors Influencing Virtual Art Therapy in Patients with Stroke

by Marco Iosa, Roberto De Giorgi, Federico Gentili, Alberto Ciotti, Cristiano Rubeca, Silvia Casolani, Claudia Salera and Gaetano Tieri

Brain Sci. 2025, 15(7), 736; https://doi.org/10.3390/brainsci15070736 - 9 Jul 2025

Abstract

Background: Art therapy was recently administered to stroke patients using immersive virtual reality technology, chosen to provide the illusion of being able to replicate an artistic masterpiece. This approach was effective in improving rehabilitative outcomes due to the so-called Michelangelo effect: patients’ [...] Read more.

Background: Art therapy was recently administered to stroke patients using immersive virtual reality technology, chosen to provide the illusion of being able to replicate an artistic masterpiece. This approach was effective in improving rehabilitative outcomes due to the so-called Michelangelo effect: patients’ interaction with artistic stimuli reduced perceived fatigue and improved performance. The aim of the present study was to investigate which factors may influence those outcomes (e.g., type of artwork, esthetic valence, perceived fatigue, clinical conditions). Methods: An observational study was conducted on 25 patients with stroke who performed the protocol of virtual art therapy (VAT). In each trial, patients were asked to rate the esthetic valence of the artworks and their perceived fatigue, whereas therapists assessed patients’ participation in the therapy (Pittsburgh Rehabilitation Participation Scale, PRPS). Moreover, before and after treatment, patients’ independence in daily living activities (Barthel Index, BI), and their upper limb functioning (Manual Muscle Test, MMT) and spasticity (Ashworth Scale, AS) were measured. Results: The after-treatment BI scores depended on the before-treatment BI score (p < 0.001) and on the PRPS score (p = 0.006), which, in turn, was increased by the subjective esthetic valence (p = 0.044). Perceived fatigue is a complex factor that may have influenced the outcomes (p = 0.049). Conclusions: There was a general effect of art in reducing fatigue and improving participation of patients during therapy. The variability observed among patients mainly depended on their clinical conditions, but also on the esthetic valence given to each artwork, that could also be intertwined with the difficulty of the task. Art therapy has a high potential to improve rehabilitation outcomes, especially if combined with new technologies, but psychometric investigation of the effects of each factor is needed to design the most effective protocols. Full article

(This article belongs to the Special Issue Advancements in Diagnosis and Treatment of Stroke and Cerebral Aneurysms: A Call for Innovative Research Submissions)

► Show Figures

Figure 1

21 pages, 1842 KiB

Open AccessArticle

Acute Stroke Severity Assessment: The Impact of Lesion Size and Functional Connectivity

by Karolin Weigel, Christian Gaser, Stefan Brodoehl, Franziska Wagner, Elisabeth Jochmann, Daniel Güllmar, Thomas E. Mayer and Carsten M. Klingner

Brain Sci. 2025, 15(7), 735; https://doi.org/10.3390/brainsci15070735 - 9 Jul 2025

Abstract

Background/Objectives: Early and accurate prediction of stroke severity is crucial for optimizing guided therapeutic decisions and improving outcomes. This study investigates the predictive value of lesion size and functional connectivity for neurological deficits, assessed by the National Institutes of Health Stroke Scale (NIHSS [...] Read more.

Background/Objectives: Early and accurate prediction of stroke severity is crucial for optimizing guided therapeutic decisions and improving outcomes. This study investigates the predictive value of lesion size and functional connectivity for neurological deficits, assessed by the National Institutes of Health Stroke Scale (NIHSS score), in patients with acute or subacute subcortical ischemic stroke. Methods: Forty-four patients (mean age: 68.11 years, 23 male, and admission NIHSS score 4.30 points) underwent high-resolution anatomical and resting-state functional Magnetic Resonance Imaging (rs-fMRI) within seven days of stroke onset. Lesion size was volumetrically quantified, while functional connectivity within the motor, default mode, and frontoparietal networks was analyzed using seed-based correlation methods. Multiple linear regression and cross-validation were applied to develop predictive models for stroke severity. Results: Our results showed that lesion size explained 48% of the variance in NIHSS scores (R² = 0.48, cross-validated R² = 0.49). Functional connectivity metrics alone were less predictive but enhanced model performance when combined with lesion size (achieving an R² = 0.71, cross-validated R² = 0.73). Additionally, left hemisphere connectivity features were particularly informative, as models based on left-hemispheric connectivity outperformed those using right-hemispheric or bilateral predictors. This suggests that the inclusion of contralateral hemisphere data did not enhance, and in some configurations, slightly reduced, model performance—potentially due to lateralized functional organization and lesion distribution in our cohort. Conclusions: The findings highlight lesion size as a reliable early marker of stroke severity and underscore the complementary value of functional connectivity analysis. Integrating rs-fMRI into clinical stroke imaging protocols offers a potential approach for refining prognostic models. Future research efforts should prioritize establishing this approach in larger cohorts and analyzing additional biomarkers to improve predictive models, advancing personalized therapeutic strategies for stroke management. Full article

► Show Figures

Graphical abstract

45 pages, 6622 KiB

Open AccessReview

Evolutionary Trajectories of Consciousness: From Biological Foundations to Technological Horizons

by Evgenii Gusev, Alexey Sarapultsev and Maria Komelkova

Brain Sci. 2025, 15(7), 734; https://doi.org/10.3390/brainsci15070734 - 9 Jul 2025

Abstract

Consciousness remains one of the most critical yet least understood functions of the brain, not only in humans but also in certain highly organized animal species. In this review, we propose treating consciousness as an emergent, goal-directed informational system organized by the subjective [...] Read more.

Consciousness remains one of the most critical yet least understood functions of the brain, not only in humans but also in certain highly organized animal species. In this review, we propose treating consciousness as an emergent, goal-directed informational system organized by the subjective “self” as an active system-forming factor. We present an integrative theoretical–systems framework in which subjectivity functions as system-forming factor of consciousness (SFF) throughout biological evolution. Beginning with proto-conscious invertebrates, we trace progressive elaborations of working and long-term memory, the refinement of behavioral programs, and the emergence of an internal arbiter capable of resolving competing drives. In endothermic vertebrates, subjectivity acquires distinct functional features—sensory filtering, causal reasoning, and adaptive arbitration—underpinned by increasingly complex neural architectures. This evolutionary trajectory culminates in humans, where subjectivity attains its highest level of organization through culturally mediated networks. Although the framework does not assume any specific neural substrate, it provides a testable roadmap linking evolutionary biology, information theory, and quantitative modeling. By clarifying why consciousness arose and how subjectivity shapes complex networks, this perspective also lays the groundwork for exploring possible nonbiological extensions of subjectivity. Full article

(This article belongs to the Special Issue Understanding the Functioning of Brain Networks in Health and Disease)

► Show Figures

Figure 1

16 pages, 283 KiB

Open AccessReview

The Brain in the Age of Smartphones and the Internet: The Possible Protective Role of Sport

by Laura Coco, Jonida Balla, Leonardo Noto, Valentina Perciavalle, Andrea Buscemi, Donatella Di Corrado and Marinella Coco

Brain Sci. 2025, 15(7), 733; https://doi.org/10.3390/brainsci15070733 - 9 Jul 2025

Abstract

Background: The widespread use of smartphones and the internet has transformed communication, but excessive use has raised concerns about smartphone and internet addiction, which can lead to psychological, physical, and social issues. The objective of this literature review is to explore the relationship [...] Read more.

Background: The widespread use of smartphones and the internet has transformed communication, but excessive use has raised concerns about smartphone and internet addiction, which can lead to psychological, physical, and social issues. The objective of this literature review is to explore the relationship between smartphone and internet addiction and physical activity, particularly focusing on whether physical exercise, especially sports, can serve as a protective factor against addiction. The review aims to examine how physical activity can reduce the negative impacts of addiction and improve overall mental health. Methods: This review synthesizes empirical research on smartphone and internet addiction and its connection to physical activity. It examines studies exploring how addiction leads to physical inactivity and how participation in physical activities, especially sports, can counteract this effect. The review also evaluates research on psychological mechanisms, such as self-esteem, self-control, and emotional resilience, that mediate the relationship between physical activity and addiction. Additionally, it discusses how sociodemographic and contextual factors influence this relationship. Conclusions: The findings consistently show an inverse relationship between smartphone and internet use and physical activity, with physical activity acting as a protective factor against addiction. Sports and other physical activities have been linked to reduced addictive behaviors, enhanced psychological well-being, and improved emotional resilience. Promoting physical activity, particularly sports, along with psychological interventions, appears to be an effective strategy for preventing and treating smartphone and internet addiction. Future research should focus on developing tailored interventions and studying diverse populations to optimize addiction prevention. Full article

15 pages, 559 KiB

Open AccessArticle

Exploring Fixation Times During Emotional Decoding in Intimate Partner Violence Perpetrators: An Eye-Tracking Pilot Study

by Carolina Sarrate-Costa, Marisol Lila, Luis Moya-Albiol and Ángel Romero-Martínez

Brain Sci. 2025, 15(7), 732; https://doi.org/10.3390/brainsci15070732 - 8 Jul 2025

Abstract

Background/Objectives: Deficits in emotion recognition abilities have been described as risk factors for intimate partner violence (IPV) perpetration. However, much of this research is based on self-reports or instruments that present limited psychometric properties. While current scientific literature supports the use of eye [...] Read more.

Background/Objectives: Deficits in emotion recognition abilities have been described as risk factors for intimate partner violence (IPV) perpetration. However, much of this research is based on self-reports or instruments that present limited psychometric properties. While current scientific literature supports the use of eye tracking to assess cognitive and emotional processes, including emotional decoding abilities, there is a gap in the scientific literature when it comes to measuring these processes in IPV perpetrators using eye tracking in an emotional decoding task. Hence, the aim of this study was to examine the association between fixation times via eye tracking and emotional decoding abilities in IPV perpetrators, controlling for potential confounding variables. Methods: To this end, an emotion recognition task was created using an eye tracker in a group of 52 IPV perpetrators. This task consisted of 20 images with people expressing different emotions. For each picture, the facial region was selected as an area of interest (AOI). The fixation times were added to obtain a total gaze fixation time score. Additionally, an ad hoc emotional decoding multiple-choice test about each picture was developed. These instruments were complemented with other self-reports previously designed to measure emotion decoding abilities. Results: The results showed that the longer the total fixation times on the AOI, the better the emotional decoding abilities in IPV perpetrators. Specifically, fixation times explained 20% of the variance in emotional decoding test scores. Additionally, our ad hoc emotional decoding test was significantly correlated with previously designed emotion recognition tools and showed similar reliability to the eyes test. Conclusions: Overall, this pilot study highlights the importance of including eye movement signals to explore attentional processes involved in emotion recognition abilities in IPV perpetrators. This would allow us to adequately specify the therapeutic needs of IPV perpetrators to improve current interventions. Full article

(This article belongs to the Special Issue Emotional Recognition and Behavioral Regulation: An Integral Perspective)

► Show Figures

Figure 1

17 pages, 1326 KiB

Open AccessReview

State-Dependent Transcranial Magnetic Stimulation Synchronized with Electroencephalography: Mechanisms, Applications, and Future Directions

by He Chen, Tao Liu, Yinglu Song, Zhaohuan Ding and Xiaoli Li

Brain Sci. 2025, 15(7), 731; https://doi.org/10.3390/brainsci15070731 - 8 Jul 2025

Abstract

Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) has emerged as a transformative tool for probing cortical dynamics with millisecond precision. This review examines the state-dependent nature of TMS-EEG, a critical yet underexplored dimension influencing measurement reliability and clinical applicability. By integrating TMS’s neuromodulatory [...] Read more.

Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) has emerged as a transformative tool for probing cortical dynamics with millisecond precision. This review examines the state-dependent nature of TMS-EEG, a critical yet underexplored dimension influencing measurement reliability and clinical applicability. By integrating TMS’s neuromodulatory capacity with EEG’s temporal resolution, this synergy enables real-time analysis of brain network dynamics under varying neural states. We delineate foundational mechanisms of TMS-evoked potentials (TEPs), discuss challenges posed by temporal and inter-individual variability, and evaluate advanced paradigms such as closed-loop and task-embedded TMS-EEG. The former leverages real-time EEG feedback to synchronize stimulation with oscillatory phases, while the latter aligns TMS pulses with task-specific cognitive phases to map transient network activations. Current limitations—including hardware constraints, signal artifacts, and inconsistent preprocessing pipelines—are critically analyzed. Future directions emphasize adaptive algorithms for neural state prediction, phase-specific stimulation protocols, and standardized methodologies to enhance reproducibility. By bridging mechanistic insights with personalized neuromodulation strategies, state-dependent TMS-EEG holds promise for advancing both basic neuroscience and precision medicine, particularly in psychiatric and neurological disorders characterized by dynamic neural dysregulation. Full article

(This article belongs to the Section Neurotechnology and Neuroimaging)

► Show Figures

Figure 1

28 pages, 2586 KiB

Open AccessReview

Diagnostic, Therapeutic, and Prognostic Applications of Artificial Intelligence (AI) in the Clinical Management of Brain Metastases (BMs)

by Kyriacos Evangelou, Panagiotis Zemperligkos, Anastasios Politis, Evgenia Lani, Enrique Gutierrez-Valencia, Ioannis Kotsantis, Georgios Velonakis, Efstathios Boviatsis, Lampis C. Stavrinou and Aristotelis Kalyvas

Brain Sci. 2025, 15(7), 730; https://doi.org/10.3390/brainsci15070730 - 8 Jul 2025

Abstract

Brain metastases (BMs) are the most common intracranial tumors in adults. Their heterogeneity, potential multifocality, and complex biomolecular behavior pose significant diagnostic and therapeutic challenges. Artificial intelligence (AI) has the potential to revolutionize BM diagnosis by facilitating early lesion detection, precise imaging segmentation, [...] Read more.

Brain metastases (BMs) are the most common intracranial tumors in adults. Their heterogeneity, potential multifocality, and complex biomolecular behavior pose significant diagnostic and therapeutic challenges. Artificial intelligence (AI) has the potential to revolutionize BM diagnosis by facilitating early lesion detection, precise imaging segmentation, and non-invasive molecular characterization. Machine learning (ML) and deep learning (DL) models have shown promising results in differentiating BMs from other intracranial tumors with similar imaging characteristics—such as gliomas and primary central nervous system lymphomas (PCNSLs)—and predicting tumor features (e.g., genetic mutations) that can guide individualized and targeted therapies. Intraoperatively, AI-driven systems can enable optimal tumor resection by integrating functional brain maps into preoperative imaging, thus facilitating the identification and safeguarding of eloquent brain regions through augmented reality (AR)-assisted neuronavigation. Even postoperatively, AI can be instrumental for radiotherapy planning personalization through the optimization of dose distribution, maximizing disease control while minimizing adjacent healthy tissue damage. Applications in systemic chemo- and immunotherapy include predictive insights into treatment responses; AI can analyze genomic and radiomic features to facilitate the selection of the most suitable, patient-specific treatment regimen, especially for those whose disease demonstrates specific genetic profiles such as epidermal growth factor receptor mutations (e.g., EGFR, HER2). Moreover, AI-based prognostic models can significantly ameliorate survival and recurrence risk prediction, further contributing to follow-up strategy personalization. Despite these advancements and the promising landscape, multiple challenges—including data availability and variability, decision-making interpretability, and ethical, legal, and regulatory concerns—limit the broader implementation of AI into the everyday clinical management of BMs. Future endeavors should thus prioritize the development of generalized AI models, the combination of large and diverse datasets, and the integration of clinical and molecular data into imaging, in an effort to maximally enhance the clinical application of AI in BM care and optimize patient outcomes. Full article

(This article belongs to the Section Neuro-oncology)

► Show Figures

Figure 1

Journal Description

Brain Sciences

Latest Articles

Journal Menu

Journal Browser

Highly Accessed Articles

Latest Books

E-Mail Alert

News

Topics

Conferences

Special Issues

Topical Collections

Further Information

Guidelines

MDPI Initiatives

Follow MDPI