Brain communications最新文献

This scientific commentary refers to 'Clinical parameters affect the structure and function of superficial pyramidal neurons in the adult human neocortex', by Lenz et al. (https://doi.org/10.1093/braincomms/fcae351).

Despite grey matter atrophy in cortical and subcortical regions has been related to cognitive impairment in multiple sclerosis, only a few studies evaluated its predictive value for alterations in the long-term. We aimed to determine early predictors of cognitive status after 20 years of multiple sclerosis. In this longitudinal retrospective study, participants underwent a 1.5 T MRI scanning at diagnosis (T0) and after two years (T2), which included the evaluation of regional grey matter volume loss patterns. All individuals with multiple sclerosis underwent a comprehensive neuropsychological assessment at the end of the study and were classified considering their global and specific cognitive domains status (memory, attention/information processing speed, executive functioning). Clinical and MRI characteristics were assessed as predictors of long-term cognitive impairment. Analysis of covariance, t-test, unadjusted and adjusted (for age, sex, disease duration, volume of white matter lesions, volume of cortical lesions) logistic regression were conducted. One hundred seventy-five people with multiple sclerosis (118 females; mean ± SD age at the end of study = 47.7 ± 9.4 years) clinically followed for 20 years from onset (mean ± SD = 19.9 ± 5.1) were evaluated. At the end of the study, 81 (47%) were classified as cognitively impaired: 38 as mildly impaired (22%), and 43 as severely impaired (25%). In particular, 46 were impaired in memory (27%), 66 were impaired in attention/information processing speed (38%), and 71 were impaired in executive functioning (41%). Regression models identified precuneus (adjusted odds ratio = 3.37; P < 0.001), insula (adjusted odds ratio = 2.33; P = 0.036), parahippocampal gyrus (adjusted odds ratio = 2.07; P < 0.001) and cingulate (adjusted odds ratio = 1.81; P = 0.009) as the most associated regions with global cognitive impairment and domains-specific cognitive alterations after a mean of 20 years of multiple sclerosis, after adjusting for demographic and clinical variables as well as for focal white matter and grey matter damage. Early grey matter volume loss of specific cortical and deep grey matter regions predicts global and domain cognitive alterations after 20 years from multiple sclerosis diagnosis.

Experimental and clinical studies of consciousness identify brain states (i.e. quasi-stable functional cerebral organization) in a non-systematic manner and largely independent of the research into brain state modulation. In this narrative review, we synthesize advances in the identification of brain states associated with consciousness in animal models and physiological (sleep), pharmacological (anaesthesia) and pathological (disorders of consciousness) states of altered consciousness in humans. We show that in reduced consciousness the frequencies in which the brain operates are slowed down and that the pattern of functional communication is sparser, less efficient, and less complex. The results also highlight damaged resting-state networks, in particular the default mode network, decreased connectivity in long-range connections and especially in the thalamocortical loops. Next, we show that therapeutic approaches to treat disorders of consciousness, through pharmacology (e.g. amantadine, zolpidem), and (non-) invasive brain stimulation (e.g. transcranial direct current stimulation, deep brain stimulation) have shown partial effectiveness in promoting consciousness recovery. Although some features of conscious brain states may improve in response to neuromodulation, targeting often remains non-specific and does not always lead to (behavioural) improvements. The fields of brain state identification and neuromodulation of brain states in relation to consciousness are showing fascinating developments that, when integrated, might propel the development of new and better-targeted techniques for disorders of consciousness. We here propose a therapeutic framework for the identification and modulation of brain states to facilitate the interaction between the two fields. We propose that brain states should be identified in a predictive setting, followed by theoretical and empirical testing (i.e. in animal models, under anaesthesia and in patients with a disorder of consciousness) of neuromodulation techniques to promote consciousness in line with such predictions. This framework further helps to identify where challenges and opportunities lay for the maturation of brain state research in the context of states of consciousness. It will become apparent that one angle of opportunity is provided through the addition of computational modelling. Finally, it aids in recognizing possibilities and obstacles for the clinical translation of these diagnostic techniques and neuromodulation treatment options across both the multimodal and multi-species approaches outlined throughout the review.

Convolutional neural networks (CNN) show great promise for translating decades of research on structural abnormalities in temporal lobe epilepsy into clinical practice. Three-dimensional CNNs typically outperform two-dimensional CNNs in medical imaging. Here we explore for the first time whether a three-dimensional CNN outperforms a two-dimensional CNN for identifying temporal lobe epilepsy-specific features on MRI. Using 1178 T1-weighted images (589 temporal lobe epilepsy, 589 healthy controls) from 12 surgical centres, we trained 3D and 2D CNNs for temporal lobe epilepsy versus healthy control classification, using feature visualization to identify important regions. The 3D CNN was compared to the 2D model and to a randomized model (comparison to chance). Further, we explored the effect of sample size with subsampling, examined model performance based on single-subject clinical characteristics, and tested the impact of image harmonization on model performance. Across 50 datapoints (10 runs with 5-folds each) the 3D CNN median accuracy was 86.4% (35.3% above chance) and the median F1-score was 86.1% (33.3% above chance). The 3D model yielded higher accuracy compared to the 2D model on 84% of datapoints (median 2D accuracy, 83.0%), a significant outperformance for the 3D model (binomial test: P < 0.001). This advantage of the 3D model was only apparent at the highest sample size. Saliency maps exhibited the importance of medial-ventral temporal, cerebellar, and midline subcortical regions across both models for classification. However, the 3D model had higher salience in the most important regions, the ventral-medial temporal and midline subcortical regions. Importantly, the model achieved high accuracy (82% accuracy) even in patients without MRI-identifiable hippocampal sclerosis. Finally, applying ComBat for harmonization did not improve performance. These findings highlight the value of 3D CNNs for identifying subtle structural abnormalities on MRI, especially in patients without clinically identified temporal lobe epilepsy lesions. Our findings also reveal that the advantage of 3D CNNs relies on large sample sizes for model training.

It is established that one of the best predictors of a future diagnosis of Parkinson's disease is a current diagnosis of rapid eye movement behaviour disorder (RBD). In such patients, this provides a unique opportunity to study brain physiology and behavioural motor features of RBD that may precede early-stage Parkinson's disease. Based on prior work in early-stage Parkinson's disease, we aim to determine if the function of corticostriatal and cerebellar regions are impaired in RBD using task-based functional MRI and if structural changes can be detected within the caudate, putamen and substantia nigra in RBD using free-water imaging. To assess motor function, we measured performance on the Purdue Pegboard Test, which is affected in patients with RBD and Parkinson's disease. A cohort of 24 RBD, 39 early-stage Parkinson's disease and 25 controls were investigated. All participants were imaged at 3 Telsa. Individuals performed a unimanual grip force task during functional imaging. Participants also completed scales to assess cognition, sleep and motor symptoms. We found decreased functional activity in both RBD and Parkinson's disease within the motor cortex, caudate, putamen and thalamus compared with controls. There was elevated free-water-corrected fractional anisotropy in the putamen in RBD and Parkinson's disease and elevated free-water in the putamen and posterior substantia nigra in Parkinson's disease compared with controls. Participants with RBD and Parkinson's disease performed significantly worse on all tasks of the Purdue Pegboard Test compared with controls. The both hands task of the Purdue Pegboard Test was most sensitive in distinguishing between groups. A subgroup analysis of early-stage RBD (<2 years diagnosis) confirmed similar findings as those in the larger RBD group. These findings provide new evidence that the putamen is affected in early-stage RBD using both functional and free-water imaging. We also found evidence that the striatum, thalamus and motor cortex have reduced functional activity in early-stage RBD and Parkinson's disease. While the substantia nigra shows elevated free-water in Parkinson's disease, we did not observe this effect in early-stage RBD. These findings point to the corticostriatal and thalamocortical circuits being impaired in RBD patients.

This scientific commentary refers to 'Increased beta synchronization underlies perception-action hyperbinding in functional movement disorders', by Pastötter et al. (https://doi.org/10.1093/braincomms/fcae301).

The grey matter of the brain develops and declines in coordinated patterns during the lifespan. Such covariation patterns of grey matter structure can be quantified as grey matter networks, which can be measured with magnetic resonance imaging. In Alzheimer's disease, the global organization of grey matter networks becomes more random, which is captured by a decline in the small-world coefficient. Such decline in the small-world value has been robustly associated with cognitive decline across clinical stages of Alzheimer's disease. The biological mechanisms causing this decline in small-world values remain unknown. Cerebrospinal fluid (CSF) protein biomarkers are available for studying diverse pathological mechanisms in humans and can provide insight into decline. We investigated the relationships between 10 CSF proteins and small-world coefficient in mutation carriers (N = 219) and non-carriers (N = 136) of the Dominantly Inherited Alzheimer Network Observational study. Abnormalities in Amyloid beta, Tau, synaptic (Synaptosome associated protein-25, Neurogranin) and neuronal calcium-sensor protein (Visinin-like protein-1) preceded loss of small-world coefficient by several years, while increased levels in CSF markers for inflammation (Chitinase-3-like protein 1) and axonal injury (Neurofilament light) co-occurred with decreasing small-world values. This suggests that axonal loss and inflammation play a role in structural grey matter network changes.

The use of ultra-high-field 7-Tesla (7T) MRI in multiple sclerosis (MS) research has grown significantly over the past two decades. With recent regulatory approvals of 7T scanners for clinical use in 2017 and 2020, the use of this technology for routine care is poised to continue to increase in the coming years. In this context, the North American Imaging in MS Cooperative (NAIMS) convened a workshop in February 2023 to review the previous and current use of 7T technology for MS research and potential future research and clinical applications. In this workshop, experts were tasked with reviewing the current literature and proposing a series of consensus statements, which were reviewed and approved by the NAIMS. In this review and consensus paper, we provide background on the use of 7T MRI in MS research, highlighting this technology's promise for identification and quantification of aspects of MS pathology that are more difficult to visualize with lower-field MRI, such as grey matter lesions, paramagnetic rim lesions, leptomeningeal enhancement and the central vein sign. We also review the promise of 7T MRI to study metabolic and functional changes to the brain in MS. The NAIMS provides a series of consensus statements regarding what is currently known about the use of 7T MRI in MS, and additional statements intended to provide guidance as to what work is necessary going forward to accelerate 7T MRI research in MS and translate this technology for use in clinical practice and clinical trials. This includes guidance on technical development, proposals for a universal acquisition protocol and suggestions for research geared towards assessing the utility of 7T MRI to improve MS diagnostics, prognostics and therapeutic efficacy monitoring. The NAIMS expects that this article will provide a roadmap for future use of 7T MRI in MS.

Functional movement disorders are amongst the most common and disabling neurological conditions, placing a significant burden on the healthcare system. Despite the frequency and importance of functional movement disorders, our understanding of the underlying pathophysiology is limited, hindering the development of causal treatment options. Traditionally, functional movement disorders were considered as a psychiatric condition, associated with involuntary movements triggered by psychological stressors. Recent neurophysiological studies have unveiled cognitive alterations in affected individuals, suggesting that functional movement disorders might be better characterized by overarching neural principles governing cognitive functions. For instance, recent research has shown that the retrieval of stimulus-response bindings is altered in patients with functional movement disorders. Building upon these recent findings, our study delves into whether the initial integration of stimulus and response information is also disrupted in patients with functional movement disorders. To accomplish this, we reanalysed previously collected EEG data using refined analysis methods that provide insights into oscillatory activity and functional neuroanatomy associated with the integration of stimulus-response bindings. Our results demonstrate that post-movement beta synchronization (i) predicts behavioural stimulus-response binding and (ii) is significantly increased in patients with functional movement disorders compared to healthy controls. Utilizing beamformer analysis, we localized the difference effect to a cluster centred around the left supplementary motor area and the correlation effect to the right supplementary motor area. Extending beyond recent research that focused on the retrieval of stimulus-response bindings, our present findings reveal that the integration of stimulus and response information is already impaired in patients with functional movement disorders. These results uncover a phenomenon of hyperbinding between perception and action, which may represent a fundamental mechanism contributing to the movement impairments in patients with functional movement disorders.

Concussion is a public health crisis that results in a complex cascade of neurochemical changes that can have life-changing consequences. Subconcussions are generally considered less serious, but we now realize repetitive subconcussions can lead to serious neurological deficits. Subconcussions are common in contact sports and the military where certain personnel are exposed to repetitive occupational blast overpressure. Post-mortem studies show subconcussion is a better predictor than concussion for chronic traumatic encephalopathy-a progressive and fatal neurodegenerative tauopathy, only diagnosable post-mortem-thus, an in vivo biomarker would be transformative. Magnetoencephalography captures the dynamics of neuronal electrochemical action, and functional MRI shows that functional connectivity is associated with tauopathy patterns. Therefore, both imaging modalities could provide surrogate markers of tauopathy. In this cross-sectional study, we examined the effects of repetitive subconcussion on neuronal activity and functional connectivity using magnetoencephalography and functional MRI, and on neurological symptoms and mental health in a military sample. For magnetoencephalography and outcome analyses, 81 participants were split into 'high' and 'low' blast exposure groups using the generalized blast exposure value: n = 41 high blast (26.4-65.7 years; 4 females) and n = 40 low blast (28.0-63.3 years; 8 females). For functional MRI, two high blast male participants without data were excluded: n = 39 (29.6-65.7 years). Magnetoencephalography revealed disrupted neuronal activity in participants with a greater history of repetitive subconcussions, including neural slowing (higher delta activity) in right fronto-temporal lobes and subcortical regions (hippocampus, amygdala, caudate, pallidum and thalamus), and functional dysconnectivity in the posterior default mode network (lower connectivity at low and high gamma). These abnormalities were independent of concussion or traumatic stress history, and magnetoencephalography showed functional dysconnectivity not detected in functional MRI. Besides magnetoencephalography changes, those with higher blast exposure had poorer somatic and cognitive outcomes, with no blast-related differences in mental health or associations between neurological symptoms and neuronal activity. This study suggests that repetitive subconcussions have deleterious effects on brain function and that magnetoencephalography provides an avenue for both treatment targets by identifying affected brain regions and in prevention by identifying those at risk of cumulative subconcussive neurotrauma.