Search Results (208)

Background/Objective: Timely and successful treatments for Alzheimer’s disease (AD) depend on early detection. The Multimer Detection System (MDS-OAβ) for quantifying plasma oligomeric amyloid-β (OAβ) has shown promise as a biomarker of amyloid disease. The theta-to-alpha ratio (TAR) and theta-to-beta ratio (TBR) are two examples of spectral power metrics that can be used in resting-state quantitative EEG (qEEG) to evaluate brain function non-invasively. This study used resting-state EEG (rEEG) recordings obtained while the subjects were both eyes-open (EO) and eyes-closed (EC) to investigate the relationship between regional qEEG power ratios and plasma MDS-OAβ levels in older adults. Methods: The analysis comprised 174 patients between the ages of 60 and 85, with 2 in the low-MDS-OAβ group and 82 in the high-MDS-OAβ group. The clinical plasma cutoff was 0.78 ng/mL. All participants underwent rEEG recordings and plasma OAβ quantification. EEG pre-processing included bandpass filtering (0.5–100 Hz), average re-referencing, artifact rejection using independent component analysis (ICA), and spectral power estimation using Welch’s method. The TAR and TBR were calculated across five lobar regions (frontal, central, parietal, occipital, and temporal) during both EO and EC conditions. To normalize data distributions, EEG ratio variables were log-transformed prior to statistical analysis. Group comparisons and linear regression analyses were conducted to evaluate the associations between EEG power ratios and MDS-OAβ levels. Adjusted regression models included age, years of education, and neuropsychological test scores as covariates. Statistical significance was set at p < 0.05. Results: No significant associations were found between TAR and plasma MDS-OAβ levels across any lobar regions under either EO or EC conditions. In contrast, TBR exhibited consistent and significant negative associations with MDS-OAβ levels, particularly under EC conditions. Adjusted regression models revealed that higher MDS-OAβ levels were associated with lower TBR values in the central (β = −0.059, p = 0.015), parietal (β = −0.072, p = 0.006), occipital (β = −0.067, p = 0.040), and temporal (β = −0.053, p = 0.018) lobes, with the strongest inverse relationship observed in the parietal lobe. A similar, though slightly weaker, pattern was observed during EO conditions, with significant inverse associations in the frontal, central, and temporal lobes. Conclusions: Our findings indicate that, after adjusting for covariates, increased plasma MDS-OAβ levels are significantly associated with a reduced TBR, particularly in the parietal and central lobes, under both EO and EC resting-state conditions. In contrast, no significant associations were observed with TAR. These results suggest that a lower TBR may reflect an increased peripheral amyloid burden and highlight its potential as a sensitive qEEG biomarker for early amyloid-related brain changes in older adults. Full article

Gerstmann syndrome (GS) is characterised by the tetrad of agraphia, acalculia, finger agnosia, and right-left disorientation, which was first described by Josef Gerstmann in 1924 and is conventionally linked to lesions of the dominant angular gyrus. Contemporary neuroimaging and lesion mapping research indicates that a more dispersed parietal and occipito-temporal network may be involved. Bilateral parietal lobe infarcts are uncommon and usually arise from embolic events or small artery pathology, frequently resulting in multifocal cognitive and perceptual impairments. A 52-year-old male presented with acute confusion, perseverative speech, and an inability to follow commands. The neurological examination indicated the presence of the complete Gerstmann tetrad. The Magnetic Resonance Imaging (MRI brain) revealed bilateral parieto-occipital infarcts, with greater severity on the left, indicative of ischaemia in the territory of the posterior cerebral artery (PCA). The medical team provided supportive care and implemented secondary stroke prevention, leading to partial neurocognitive recovery over a period of three weeks. This case highlights a rare presentation of Gerstmann syndrome due to bilateral parieto-occipital infarcts and emphasises that the syndrome can arise from bilateral or widespread parietal injury rather than lesions limited to the angular gyrus. The prompt identification of the Gerstmann constellation helps localise the lesion, enhances diagnostic accuracy, and aids in rehabilitation planning. Full article

Traumatic brain injury (TBI) is a significant public health concern and its rising prevalence in road traffic accidents underscores the need for deeper understanding and tailored investigation. This study explores the feasibility of employing the female finite element head model (FeFEHM) to analyse biomechanical responses in two distinct road traffic accident scenarios, focusing on strain and stress distribution in critical brain structures. Two collision scenarios from the German In-Depth Accident Study (GIDAS) were reconstructed using validated Total Human Model for Safety (THUMS) simulations. The extracted skull kinematics were applied to the FeFEHM in ABAQUS to compute maximum principal strain, von Mises stress, and intracranial pressure across key brain regions, including the corpus callosum and pituitary gland. Simulations revealed strain concentrations in the parietal and temporal lobes, while the mid-body region was the most affected in the corpus callosum. Pituitary gland deformation was minimal under both loading conditions. Our findings align qualitatively with reported injury sites and injury risk was consistent with those observed in the real-world crashes. The findings highlight the potential of integrating sex-specific biomechanical models into crash biomechanics workflows. Future work should extend this approach across larger datasets and impact scenarios to support its implementation in regulatory and engineering contexts, since the actual sample size prevents conclusions regarding sex-specific biomechanics. Full article

Humans show neural specificity in processing animal-related information, especially regarding companion animals. However, the underlying cognitive mechanisms remain poorly understood. This study’s main objective is to investigate human neural specificity in processing companion animal-related information, compared to other animal types and inanimate objects. Forty participants viewed four image types (companion animals, neutral animals, positive objects, neutral objects) during functional magnetic resonance imaging (fMRI) scans and judged image categories. T-test results showed: 1. Processing companion animal-related information elicited specific brain activation in the right Inferior Parietal Lobe (right IPL), right Middle Occipital Gyrus (right MOG), left Superior Frontal Gyrus (left SFG), and left Precuneus (left PCu) (<0.05). 2. Generalized Psychophysiological Interaction (gPPI) analysis revealed specific functional connectivity changes between relevant brain regions during companion animal info processing (<0.05). 3. Dynamic Causal Modelling (DCM) analysis showed significant intrinsic connectivity differences between pet owners and non-pet owners: specifically, left IPL to left PCu and right ACC to right MOG (posterior probability, Pp > 0.95). The results of this study demonstrate that humans exhibit distinct neural specificity when processing information related to companion animals compared with livestock and inanimate objects. This neural specificity involves brain regions linked to higher-order cognitive functions (e.g., visual processing, emotion, and attachment), all of which are integral components of the human attachment network. These regions are part of the human attachment network, and their functional role likely relates to attachment mechanisms. These findings help clarify companion animals’ impact on human neural activity during human–animal interactions and guide applications like animal-assisted therapy. Full article

Background/Objectives: Age-related structural changes in the human brain provide essential insights into cognitive aging and the onset of neurodegenerative diseases. This study aimed to comprehensively characterize age-related volumetric changes across multiple brain regions in a large, diverse, cognitively healthy cohort spanning adulthood (ages 21–90), integrating Korean, Information eXtraction from Images (IXI), and Alzheimer’s Disease Neuroimaging Initiative (ADNI) MRI datasets of cognitively healthy participants to characterize normative volumetric changes across adulthood using demographically diverse datasets. Methods: High resolution 3T T1-weighted MRI images from three distinct cohorts (totaling 1833 subjects) were processed through an optimized neuroimaging pipeline, combining advanced preprocessing with neural network-based segmentation. Volumetric data for 95 brain structures were segmented and analyzed across seven age bins (21–30 through 81–90). Pipeline reliability was validated against FreeSurfer using intraclass correlation coefficients (ICC) and coefficients of variation (CoV). Regression-based correction was used to correct for sex and cohort effects on brain region volume. Then, percentage change in each mean bilateral volumes of regions across the lifespan were computed to describe volumetric changes across life spans. Results: The segmentation pipeline demonstrated excellent agreement with FreeSurfer (mean ICC: 0.9965). Drastic volumetric expansions were observed in white matter hypointensities (122.6%), lateral ventricles (115.9%), and inferior lateral ventricles (116.8%). Moderate-to-notable shrinkage was found predominantly in the frontal lobe (pars triangularis: 21.5%), parietal lobe (inferior parietal: 20.4%), temporal lobe (transverse temporal: 21.6%), and cingulate cortex (caudal anterior cingulate: 16.1%). Minimal volume changes occurred in regions such as the insula (3.7%) and pallidum (2.6%). Conclusions: This study presents a comprehensive reference of normative regional brain volume changes across adulthood, highlighting substantial inter-regional variability. The findings can provide an essential foundation for differentiating normal aging patterns from early pathological alterations. Full article

Cognitive deficiencies are significant factors affecting aviation piloting capabilities. However, due to the limited stability resulting from the insufficient appeal of traditional attention or memory cognitive training, multi-task gamified cognitive training (MTGCT) may be more beneficial in generating far transfer effects in task performance. This study explores the enhancement effects of simulated flight operation capabilities based on visuo-spatial attention and working memory MTGCT. Additionally, we explore the neurophysiological impacts through changes in EEG power spectral density (PSD) characteristics and brain asymmetry, and whether these impacts exhibit a certain retention effect. This study designed a 28-day simulated flight operation capability enhancement experiment. In addition, the behavioral performance and EEG signal changes in 28 college students (divided into control and training groups) were analyzed. The results indicated that MTGCT significantly enhanced simulated flight operational capabilities, and the neural framework formed by physiological changes remains effective for at least two weeks. The physiological changes included a decrease in the $\theta$ band PSD and an increase in the $\alpha$ band PSD in the frontal and parietal lobes due to optimized cognitive resource allocation, as well as the frontal $\theta$ band leftward asymmetry and the frontoparietal $\alpha$ band rightward asymmetry due to the formation of neural activity patterns. These findings support, to some extent, the feasibility and effectiveness of using MTGCT as a periodic training method to enhance the operational and cognitive abilities of aviation personnel. Full article

Background/Objectives: There is scarce evidence on the neural underpinnings of balance in people with chronic acquired brain injury (ABI). Thus, the objective was to measure this in adults with ABI during four balance tasks and to examine the relationship between neural activity and balance performance. Methods: Twenty-seven adults with chronic ABI (Age (M ± SD): 51.30 ± 18.67 years, 18 females) were included in this study. Functional near-infrared spectroscopy (fNIRS) was used to measure task-dependent neural activity, which was quantified using oxygenated hemoglobin (HbO) beta values. A force plate was used to measure balance performance, quantified as the amount of sway. One-sample t-tests were used to test for significant task-dependent neural activity during each balance task (HbO > 0) at each fNIRS channel. Pearson’s correlations were used to test for relationships between fNIRS channels with significant task-dependent activity and balance performance. Results: Significant task-dependent neural activity was observed in an fNIRS channel situated over the right superior parietal lobe, p = 0.039, along with 4 channels over the right inferior parietal lobe (IPL), p range = 0.013–0.043 and 3 channels over left IPL, p range = 0.019–0.030. There were moderate negative relationships between IPL activity and balance, r range = −0.441–0.419, p range = 0.031–0.046. Conclusions: We observed significant task-dependent neural activity in superior and inferior parietal lobes. Additionally, greater neural recruitment of the inferior parietal lobes was associated with less sway during balance performance, which provides evidence of the neural underpinnings of balance in ABI. Full article

Spatial representation is a core element of spatial cognition in orienteering, but the visual-spatial neural modulation mechanisms underlying spatial representations with differently oriented maps have not yet been systematically elucidated. This study recruited 67 orienteering athletes as participants and employed a single-factor (map orientation: normal vs. rotated) between-subjects experimental design. Eye-tracking and functional near-infrared spectroscopy (fNIRS) techniques were used simultaneously to collect behavioral, eye movement, and brain activity data, investigating the effects of map orientation on visual attention and brain activity characteristics during terrain symbol representation processing in orienteering athletes. The results revealed that compared to the normal orientation, the rotated orientation led to significantly decreased task accuracy, significantly prolonged reaction times, and significantly increased saccade amplitude and pupil diameter. Brain activation analysis showed that the rotated orientation elicited significantly higher activation levels in the right dorsolateral prefrontal cortex (R-DLPFC), bilateral parietal lobe cortex (L-PL, R-PL), right temporal lobe (R-TL), and visual cortex (VC) compared to the normal orientation, along with enhanced functional connectivity. Correlation analysis revealed that under normal map orientation, accuracy was positively correlated with both saccade amplitude and pupil diameter; accuracy was positively correlated with activation in the R-DLPFC; saccade amplitude was positively correlated with activation in the R-DLPFC and R-PL; and pupil diameter was positively correlated with activation in the R-DLPFC. Under rotated map orientation, accuracy was positively correlated with saccade amplitude and pupil diameter, and pupil diameter was positively correlated with activation in both the L-PL and R-PL. The results indicate that map orientation significantly influences the visual search patterns and neural activity characteristics of orienteering athletes, impacting task performance through the coupling mode of visual-neural activity. Full article

Contrast-induced encephalopathy (CIE) is a rare complication after percutaneous coronary intervention (PCI) that mimics intracranial hemorrhage (ICH). Its computed tomography (CT) findings (cortical contrast enhancement, sulci effacement) overlap with cerebrovascular conditions (e.g., cerebral infarction, subarachnoid hemorrhage). Dual-energy CT (DECT) differentiates blood/calcification from iodinated contrast medium (CM) extravasation via material decomposition, contributing to the accurate diagnosis of CIE. We report a CIE case highlighting DECT’s value. A 74-year-old woman underwent PCI. 50 min post-PCI, she had moderate headache (Numeric Rating Scale 4), dizziness, non-projectile vomiting (no seizures); vital signs were stable, no focal deficits, mannitol ineffective. Non-contrast CT demonstrated a left parietal 75 Hounsfield unit (HU) high-attenuation lesion, indistinguishable from acute intracerebral hemorrhage. Conventional non-contrast CT revealed a high-attenuation lesion (75 HU) in the left parietal lobe—indistinguishable from ICH. DECT clarified the diagnosis: virtual non-contrast maps showed CM extravasation, iodine concentration maps confirmed focal CM accumulation, and effective atomic number maps improved lesion visualization. The patient’s headache resolved within 5 h; follow-up non-contrast CT at 24 h showed complete disappearance of the lesion. She resumed clopidogrel, discharged day 3 without sequelae. This case underscores DECT’s role in distinguishing CIE (transient CM, normal neuro exam) from ICH (persistent hemorrhage), guiding safe post-PCI antiplatelet therapy. Full article

Major depressive disorder is a mental health condition characterized by ongoing feelings of sadness, trouble focusing or making decisions, and a frequent sense of fatigue or hopelessness that lasts for a prolonged period. If left undiagnosed, it can have serious consequences, including suicide. This study proposes a 3D convolutional neural network model to detect major depressive disorder using 3D grey matter images from magnetic resonance imaging. The proposed 3D convolutional architecture comprises multiple hierarchical convolutional and pooling layers, designed to automatically learn spatial patterns from magnetic resonance imaging data. The model was optimized via Bayesian hyperparameter tuning, achieving an accuracy of 72.26%, an area under the receiver operating characteristic curve of 0.80, and an area under the precision–recall curve of 0.81 on a large multisite dataset comprising 1276 patients and 1104 healthy controls. Gradient-weighted class activation mapping is utilized to find brain regions associated with major depressive disorder. From this study, six regions were identified, namely, the frontal lobe, parietal lobe, temporal lobe, thalamus, insular cortex and corpus callosum which may be affected by major depressive disorder. Full article

Background: Dilated cardiomyopathy (DCM) is a major cause of heart failure and arrhythmic mortality; yet, its association with cerebrovascular events, particularly in the absence of atrial fibrillation (AF), remains insufficiently explored. Purpose: This study aimed to determine the prevalence, mechanisms, and anatomical distribution of stroke in patients with DCM and to assess the role of AF and structural remodeling in stroke risk. Methods: We retrospectively analyzed 471 patients who died with DCM at the Emergency County Clinical Hospital of Bihor between 1 January 2022 and 31 December 2024. Clinical records, neuroimaging, autopsy reports, and histopathological data were reviewed. Stroke subtypes were classified according to TOAST criteria (large artery atherosclerosis, cardioembolic, small vessel disease, other determined, undetermined) and hemorrhagic categories (intracerebral, subarachnoid). Demographic, echocardiographic, and comorbidity data were compared between patients with and without cerebrovascular events. Results: Of 471 patients with DCM, 45 (9.6%) had concomitant stroke: pure ischemic in 32 (71.1%), 7 (15.6%) showed ischemic with hemorrhagic transformation, and primary hemorrhagic in 6 (13.3%). The parietal lobe was most frequently affected. AF was present in 26 patients (57.8%) and was significantly associated with ischemic stroke (p = 0.004), though embolic strokes also occurred in sinus rhythm. Patients with stroke had significantly lower left ventricular ejection fraction (28.0 ± 13.7% vs. 34.0 ± 11.2%, p = 0.007) and larger atrial dimensions. Histopathological findings confirmed acute and chronic ischemic injury patterns, including “red neurons,” white matter vacuolization, and gliotic scarring. Conclusions: Stroke is a frequent and often underdiagnosed complication in DCM, predominantly ischemic and embolic in nature. Importantly, embolic events were observed even in patients without AF, suggesting that atrial remodeling in DCM may independently predispose to cerebrovascular risk. These results underscore the need for refined preventive strategies, including careful atrial assessment and exploration of whether anticoagulation may benefit selected high-risk DCM patients without AF, a question that requires confirmation in prospective trials. Potential embolic sources in DCM include atrial cardiopathy and left ventricular thrombus in the setting of severe systolic dysfunction; therefore, careful ventricular as well as atrial assessment is warranted in high-risk DCM. Full article

Objectives: The aim of this study is to investigate the changes in quantitative indices of brain volume and cortex development in preterm infants with enlarged subarachnoid space (ESS). Methods: A single-center retrospective cohort study was performed in Hong Kong University–Shenzhen Hospital from November 2014 to November 2023, involving 200 preterm infants whose brain MRI images were available. Parameters including the volume of cerebrospinal fluid (CSF), brain tissues, total intracranial cavity (ICC), and key indices of cortex maturation (surface area, cortical thickness, cortical volume, mean curvature) were compared between the groups with ESS and without ESS. The retrospective nature of this study may introduce selection bias in the process of enrolling preterm infants with ESS. Results: The groups with severe and mild ESS had a significantly greater ICC volume than the group without ESS (severe: 384.66 ± 30.33 [p < 0.001]; mild: 374.25 ± 26.45 [p < 0.001] vs. no ESS: 356.78 ± 26.03), and the difference was mostly due to the gap in extra-CSF volume among the three groups (severe: 74.20 ± 5.1 and mild: 55.36 ± 3.8 vs. no ESS: 40.54 ± 4.3, p ≤ 0.001). Only the volume of parenchyma of the severe-ESS group was significantly different (severe: 302.35 ± 26.43 vs. no ESS: 312.27 ± 20.75, p = 0.003). Regarding indices of cortex maturation, only the mean curvature showed a significant difference between the three groups, and most of the significant clusters were located around the parietal and temporal lobes. Conclusions: ESS may be associated with impaired early brain maturation in preterm infants after birth. A further neurodevelopmental follow-up study is needed. Full article

Cerebral perfusion single-photon emission computed tomography (SPECT) is a nuclear medicine imaging technique that uses radiopharmaceuticals that selectively accumulate in the brain. However, cerebral perfusion SPECT is typically interpreted through visual assessment, making the results susceptible to observer subjectivity and varying levels of experience. The easy Z-score Imaging System (eZIS) is a software that quantitatively analyzes cerebral perfusion SPECT images obtained using 99mTc-ECD by comparing them with a normal database and applying Z-scores for quantification. The eZIS received regulatory approval in January 2015 and is currently used as an auxiliary tool for clinical diagnosis. The eZIS aids in diagnosing Alzheimer’s disease by quantifying the degree of cerebral blood flow reduction in the posterior cingulate gyrus, precuneus, and parietal lobe, which are characteristic regions affected by the disease. Additionally, it can assist in diagnosing Lewy body dementia by evaluating the “cingulate island sign,” a characteristic finding in which cerebral blood flow in the posterior cingulate gyrus and precuneus is relatively preserved compared with that in the occipital lobe. eZIS is thus extremely useful for dementia diagnosis. Full article

Background/Objectives: Electroencephalography (EEG)-based emotion recognition plays an important role in affective computing and brain–computer interface applications. However, existing methods often face the challenge of achieving high classification accuracy while maintaining physiological interpretability. Methods: In this study, we propose a convolutional neural network (CNN) model with a simple architecture for EEG-based emotion classification. The model achieves classification accuracies of 95.21% for low/high arousal, 94.59% for low/high valence, and 93.01% for quaternary classification tasks on the DEAP dataset. To further improve model interpretability and support practical applications, Gradient-weighted Class Activation Mapping (Grad-CAM) is employed to identify the EEG electrode regions that contribute most to the classification results. Results: The visualization reveals that electrodes located in the right prefrontal cortex and left parietal lobe are the most influential, which is consistent with findings from emotional lateralization theory. Conclusions: This provides a physiological basis for optimizing electrode placement in wearable EEG-based emotion recognition systems. The proposed method combines high classification performance with interpretability and provides guidance for the design of efficient and portable affective computing systems. Full article

Background: Developmental dyslexia (DD) is the most common form of specific learning disorders (SLDs). From a neurocognitive point of view, dyslexic reading is associated with atypical neurofunctional patterns in the left hemisphere, mainly in the posterior areas linked to lexical access and phonological processing. Nowadays, rehabilitation treatments do not aim to fix the disorder but rather improve adaptive skills. On the other hand, the transcranial direct current stimulation (tDCS) has recently gained popularity in this field. In fact, a few studies have documented enhanced accuracy and speed after the tDCS over the parietal cortex, although the results were mainly limited to non-word reading. Methods: We conducted a single-case study employing an innovative multifocal eight-channel tDCS aimed at increasing the reading network activity in the left hemisphere and inhibiting the contralateral areas. The participant was a 9-year-old boy with a diagnosis of severe mixed-type specific learning disorder. The high-definition multifocal tDCS was administered over key areas of the frontal, temporal, parietal, and occipital lobes (four 3.14 cm² electrodes per hemisphere) in conjunction with tachistoscope training over a span of 10 weeks, with three sessions per week for a total of thirty sessions. Standardized assessments of reading were carried out at the beginning, at the end of the treatment, and at one- and six-month follow-up. Results: The treatment led to a 77% improvement in the accuracy of passage reading and an 83% improvement in the reading of high-frequency short words, with stable results at the 1- and 6-month follow-up. By contrast, in line with the severity of the disorder, there were only slight improvements in the speed parameter. Conclusions: This is the first study to document such remarkable improvements in reading in a case of severe SLD: if confirmed, these promising findings could pave the way for an effective, non-invasive rehabilitation for SLDs using multifocal tDCS. However, future studies are needed to overcome the limitations of single-case studies, such as the lack of control conditions and quantifiable analysis. Full article