Brain Sciences最新文献

Background/objectives: Ventriculoperitoneal shunting is a validated procedure for the treatment of idiopathic normal-pressure hydrocephalus. To select shunt-responsive patients, infusion and tap tests can be used. Only gait is evaluated after the procedure to establish a potential improvement. In this study, we present our Hydro-Real-Time Neuropsychological Testing protocol to assess the feasibility of performing an ultra-fast assessment of patients during the infusion and tap test.

Methods: We tested 57 patients during the infusion and tap test to obtain real-time feedback on their cognitive status. Data were obtained immediately before the infusion phase (T0), when the pressure plateau was reached (T1), and immediately after cerebrospinal fluid subtraction (T2). Based on cerebrospinal fluid dynamics, 63.15% of the patients presented a resistance to outflow > 12 mmHg/mL/min, while 88% had a positive tap test response.

Results: Compared to T0, cerebrospinal fluid removal significantly improved performance on tasks exploring executive functions (counting backward, p < 0.001; verbal fluency, p < 0.001). Patients were significantly faster at counting backward at T2 vs. T1 (p < 0.05) and at T2 vs. T0 (p < 0.001) and were significantly faster at counting forward at T2 vs. T1 (p < 0.005), suggesting an improvement in speed at T2. There was a significantly smaller index at T1 vs. T0 (p = 0.005) and at T2 vs. T0 (p < 0.001), suggesting a more marked improvement in patients' executive abilities at T2 and a smaller improvement at T1. Regarding verbal fluency, patients were worse at T1 vs. T0 (p < 0.001) and at T2 vs. T0 (p < 0.001).

Conclusions: Patients' performance can be monitored during the infusion and tap test as significant changes in executive functions are observable. In future, this protocol might help improve patients' selection for surgery.

Background: Elastic image fusion (EIF) using an intraoperative CT (iCT) scan may enhance neuronavigation accuracy and compensate for brain shift. Objective: To evaluate the safety and reliability of the EIF algorithm (Virtual iMRI Cranial 4.5, Brainlab AG, Munich Germany, for the identification of residual tumour in glioblastoma surgery. Moreover, the impact of brain shift on software reliability is assessed. Methods: This ambispective study included 80 patients with a diagnosis of glioblastoma. Pre-operative MRI was elastically fused with an intraoperative CT scan (BodyTom; Samsung-Neurologica, Danvers, MA, USA) acquired at the end of the resection. Diagnostic specificity and the sensitivity of each tool was determined. The impact of brain shift on residual tumour was statistically analysed. An analysis of accuracy was performed through Target Registration Error (TRE) measurement after rigid image fusion (RIF) and EIF. A qualitative evaluation of each Virtual MRI image (VMRI) was performed. Results: VMRI identified residual tumour in 26/80 patients (32.5%), confirmed by post-operative MRI (true positive). Of these, 5 cases were left intentionally due to DES-positive responses, 8 cases underwent near maximal or subtotal resection, and 13 cases were not detected by iCT. However, in the other 27/80 cases (33.8%), VMRI reported residual tumour that was present neither on iCT nor on post-operative MRI (false positive). i-CT showed a sensitivity of 56% and specificity of 100%; VMRI demonstrated a sensitivity of 100% and specificity of 50%. Spearman correlation analysis showed a moderate correlation between pre-operative volume and VMRI tumour residual. Moreover, tumour involving insula or infiltrating more than one lobe displayed higher median values (p = 0.023) of virtual residual tumour. A statistically significant reduction towards lower TRE values after EIF was observed for test structures. Conclusions: Virtual iMRI was proven to be a feasible option to detect residual tumour. Its integration within a multimodal imaging protocol may provide neurosurgeons with intraoperatively updated imaging.

Background/objectives: High-intensity interval training (HIIT) alternates short periods of intense exercise with recovery, effectively enhancing cardiorespiratory fitness, endurance, and strength in various populations. Concurrently, brain-derived neurotrophic factor (BDNF) supports neuronal resilience and activity-dependent plasticity, which are vital for learning and memory. This study aims to systematically review changes in BDNF levels in response to HIIT, with three primary objectives: evaluating the benefits of HIIT for BDNF modulation, assessing methodological quality and the risk of bias in reviewed studies, and identifying patterns in BDNF response based on HIIT protocols and population characteristics.

Methods: Comprehensive database searches were conducted in PubMed and SPORTDiscus to identify relevant studies published up to April 2024. Given the diversity in study designs and outcomes, a narrative synthesis was performed rather than a meta-analysis. Bias was evaluated using visualization tools such as RobVis, and the review was conducted by a single researcher, which may limit its comprehensiveness.

Results: Twelve studies met the inclusion criteria, with most indicating significant increases in BDNF levels post-HIIT, suggesting HIIT's potential to enhance neuroplasticity and cognitive functions. However, variations in BDNF responses were observed across different HIIT protocols and study populations. Some studies reported decreases or no change in BDNF levels, reflecting the complex regulation of BDNF influenced by factors such as exercise intensity, duration, and individual variability.

Conclusions: HIIT shows promise as an intervention for increasing BDNF levels, with potential benefits for brain health and cognitive function. These findings underscore the need for further research to confirm the optimal conditions under which HIIT can effectively enhance neurological outcomes. Future studies should explore standardized HIIT protocols and the long-term impact of HIIT on BDNF and neuroplasticity.

Background/objectives: Stressors occurring across the life course are considered to have a cumulative impact on health, but there is no instrument for assessing lifetime stressor exposure in Korea. Therefore, we validated the Stress and Adversity Inventory (Adult STRAIN) in Korean.

Methods: We translated the Adult STRAIN into Korean and examined its concurrent, predictive, and comparative predictive validity in 218 Korean adults (79 men, 139 women; M_age = 29.5; 19-50 years old) recruited from a psychiatric setting. We assessed concurrent validity using Pearson's correlations, predictive validity using multiple regression models, and comparative predictive validity using multivariate logistic regression to identify participants with lifetime psychiatric diagnoses.

Results: The Korean STRAIN exhibited sufficient usability and acceptability; good concurrent validity with other measures of early adversity, life events, and perceived stress (rs = 0.48-0.61); and strong predictive validity in relation to anxiety and depressive symptoms (β = 0.08-0.47; ΔR2 = 0.11-0.21). Each domain of Korean-style stress, based on the timing, type, life domain, and sociopsychological characteristics of stress exposure, showed a different distribution of lifetime psychiatric diagnosis probabilities (odds ratios = 1.20-4.85). Finally, the test-retest reliability for total lifetime stressor count and severity over four weeks was high.

Conclusions: The Korean STRAIN is a practical, valid, and reliable instrument for researchers and clinicians to efficiently assess lifetime stressor exposure.

Speech is a highly skilled motor activity that shares a core problem with other motor skills: how to reduce the massive degrees of freedom (DOF) to the extent that the central nervous control and learning of complex motor movements become possible. It is hypothesized in this paper that a key solution to the DOF problem is to eliminate most of the temporal degrees of freedom by synchronizing concurrent movements, and that this is performed in speech through the syllable-a mechanism that synchronizes consonantal, vocalic, and laryngeal gestures. Under this hypothesis, syllable articulation is enabled by three basic mechanisms: target approximation, edge-synchronization, and tactile anchoring. This synchronization theory of the syllable also offers a coherent account of coarticulation, as it explicates how various coarticulation-related phenomena, including coarticulation resistance, locus, locus equation, diphone, etc., are byproducts of syllable formation. It also provides a theoretical basis for understanding how suprasegmental events such as tone, intonation, phonation, etc., are aligned to segmental events in speech. It may also have implications for understanding vocal learning, speech disorders, and motor control in general.

Objective: The objective of this study was to examine the effect of observing actions at different speeds on the speed of motor task performance in subsequent actions.

Methods: Sixty individuals, divided equally between those with non-specific chronic low back pain (NSCLBP) and asymptomatic subjects, were enrolled. Participants were further split into subgroups to observe lumbar flexion and Timed Up and Go (TUG) test actions at either a slow or fast pace, following a randomized assignment. For post-video observation, participants replicated the observed actions three times without specific performance instructions, allowing for the assessment of their execution speed.

Results: The analysis revealed that individuals observing actions at a faster pace executed the subsequent motor tasks significantly quicker than their counterparts who viewed the same actions at a slower speed. This was consistent across both NSCLBP sufferers and asymptomatic subjects, indicating that the action observation (AO) speed directly influenced the execution speeds of lumbar flexion and TUG test movements.

Conclusions: The findings demonstrate that AO speed significantly affects the pace of motor execution, irrespective of NSCLBP presence. This underscores the potential of utilizing varied AO speeds as a strategic component in clinical practice, particularly for enhancing motor planning and execution in physical therapy settings. The study highlights the importance of incorporating AO speed variations into therapeutic interventions for improving patient outcomes in motor task performance.

Background/objectives: 22q11.2 microdeletion syndrome (22q11DS) is a genetic disease caused by aberration of chromosome 22 that results in some phenotypic features and developmental disorders. This paper presents a cross-sectional study on speech and communication of Polish children with 22q11DS.

Methods: Individuals affected with 22q11DS may show difficulties in functioning, including speech and hearing. Therefore, we prepared a speech development questionnaire and employed it to obtain data from parents (or legal guardians) of 54 children with 22q11DS. The questionnaire covered the following speech and communication development stages: babbling, using first words, first sentences, verbal and non-verbal communication, speech disfluencies, hearing loss, speech intelligibility, difficulties in interpersonal contact, and participation in speech therapy. The obtained answers underwent statistical analysis to verify relationships between the stages of personal development and selected dysfunctions and disorders.

Results: In the study group we observed delays in achieving subsequent speech developmental stages and that hearing loss was associated with delays in producing first words. Hearing loss was reported in about a quarter of cases, but a significant proportion of children (55.56%) reported speech disfluencies, which had not been emphasized in previous works, where hearing loss is considered a common co-occurring disorder.

Conclusions: Our findings suggest that this may represent a phenomenon associated with 22q11DS that warrants further investigation using standardized tests for assessing disfluencies. Additionally, we observed that speech therapists and caregivers were perceived as not fully aware of the speech development impairments caused by 22q11DS. These preliminary observations point to the need for future studies and increased awareness efforts in this area.

Objectives: Computer-aided schizophrenia (SZ) detection methods mainly depend on electroencephalogram and brain magnetic resonance images, which both capture physical signals from patients' brains. These inspection techniques take too much time and affect patients' compliance and cooperation, while difficult for clinicians to comprehend the principle of detection decisions. This study proposes a novel method using face diagnosis images based on traditional Chinese medicine principles, providing a non-invasive, efficient, and interpretable alternative for SZ detection.

Methods: An innovative face diagnosis image analysis method for SZ detection, which learns feature representations based on Vision Transformer (ViT) directly from face diagnosis images. It provides a face features distribution visualization and quantitative importance of each facial region and is proposed to supplement interpretation and to increase efficiency in SZ detection while keeping a high detection accuracy.

Results: A benchmarking platform comprising 921 face diagnostic images, 6 benchmark methods, and 4 evaluation metrics was established. The experimental results demonstrate that our method significantly improves SZ detection performance with a 3-10% increase in accuracy scores. Additionally, it is found that facial regions rank in descending order according to importance in SZ detection as eyes, mouth, forehead, cheeks, and nose, which is exactly consistent with the clinical traditional Chinese medicine experience.

Conclusions: Our method fully leverages semantic feature representations of first-introduced face diagnosis images in SZ, offering strong interpretability and visualization capabilities. It not only opens a new path for SZ detection but also brings new tools and concepts to the research and application in the field of mental illness.

Background/objectives: Noninvasive brain stimulation (NIBS) can boost motor recovery after a stroke. Certain movement phases are more responsive to NIBS, so a system that auto-detects these phases would optimize stimulation timing. This study assessed the effectiveness of various machine learning models in identifying movement phases in hemiparetic individuals undergoing simultaneous NIBS and EEG recordings. We hypothesized that transcranial direct current stimulation (tDCS), a form of NIBS, would enhance EEG signals related to movement phases and improve classification accuracy compared to sham stimulation.

Methods: EEG data from 10 chronic stroke patients and 11 healthy controls were recorded before, during, and after tDCS. Eight machine learning algorithms and five ensemble methods were used to classify two movement phases (hold posture and reaching) during each of these periods. Data preprocessing included z-score normalization and frequency band power binning.

Results: In chronic stroke participants who received active tDCS, the classification accuracy for hold vs. reach phases increased from pre-stimulation to the late intra-stimulation period (72.2% to 75.2%, p < 0.0001). Late active tDCS surpassed late sham tDCS classification (75.2% vs. 71.5%, p < 0.0001). Linear discriminant analysis was the most accurate (74.6%) algorithm with the shortest training time (0.9 s). Among ensemble methods, low gamma frequency (30-50 Hz) achieved the highest accuracy (74.5%), although this result did not achieve statistical significance for actively stimulated chronic stroke participants.

Conclusions: Machine learning algorithms showed enhanced movement phase classification during active tDCS in chronic stroke participants. These results suggest their feasibility for real-time movement detection in neurorehabilitation, including brain-computer interfaces for stroke recovery.

Background: Cognitive functions are the basis for the development of language skills. Cognitive disorders occur in schizophrenia and may be present even before the first symptoms of psychosis. Language deficits are also mentioned as one of the diagnostic symptoms of this disease.

Methods: A literature search was performed using the PubMed database. Articles comparing linguistic and cognitive functioning in schizophrenia were searched for. Following the inclusion and exclusion criteria, twenty-six original articles were selected.

Results: Most studies have observed a partial correlation between language and cognitive deficits. The correlation most often involved some cognitive functions or some components of language assessment.

Conclusions: The correlation reported in many studies shows that there is a correlation between language and cognitive deficits in schizophrenia. However, numerous studies contradict these reports. It is, therefore, possible that this correlation exists, but not in all patients. Future research should therefore be aimed at identifying in which patients this correlation is present.