Abulia is a common problem that manifests following various brain conditions, including brain surgeries. Abulia is felt to be related to dysfunction with the brain\'s dopamine-dependent circuitry. The role of default mode network (DMN) in its pathogenesis is crucial. In this case report, we detail the presentation of abulia in an elderly woman following surgical resection of a right frontal glioblastoma involving the DMN. Connectomic imaging was used pre-operatively and post-operatively, demonstrating disruption of regions integral to the DMN and the central executive network. We observed a significant cognitive improvement following the administration of levodopa and carbidopa. Preoperative assessment of both anatomical and functional networks can help ensure surgical safety and predict postoperative deficits. This evaluation not only enhances preparedness and facilitates early case diagnosis but also expedites the initiation of prompt and potentially targeted treatments. This case highlights the potential efficacy of levodopa and carbidopa in addressing DMN dysfunction and broadly suggests the potential for connectomics-guided post-operative therapies.

COVID-19 can induce neurological sequelae, negatively affecting the quality of life. Unravelling this illness\'s impact on structural brain connectivity, white-matter microstructure (WMM), and cognitive performance may help elucidate its implications. This cross-sectional study aimed to investigate differences in these factors between former hospitalised COVID-19 patients (COV) and healthy controls. Group differences in structural brain connectivity were explored using Welch-two sample t-tests and two-sample Mann-Whitney U tests. Multivariate linear models were constructed (one per region) to examine fixel-based group differences. Differences in cognitive performance between groups were investigated using Wilcoxon Rank Sum tests. Possible effects of bundle-specific FD measures on cognitive performance were explored using a two-group path model. No differences in whole-brain structural organisation were found. Bundle-specific metrics showed reduced fiber density (p = 0.012, Hedges\' g = 0.884) and fiber density cross-section (p = 0.007, Hedges\' g = 0.945) in the motor segment of the corpus callosum in COV compared to healthy controls. Cognitive performance on the motor praxis and digit symbol substitution tests was worse in COV than healthy controls (p < 0.001, r = 0.688; p = 0.013, r = 422, respectively). Associations between the cognitive performance and bundle-specific FD measures differed significantly between groups. WMM and cognitive performance differences were observed between COV and healthy controls.

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BACKGROUND: Patients with insulo-Sylvian gliomas continue to present with severe morbidity in cognitive functions primarily due to neurosurgeons\' lack of familiarity with non-traditional brain networks. We sought to identify the frequency of invasion and proximity of gliomas to portions of these networks.
METHODS: We retrospectively analyzed data from 45 patients undergoing glioma surgery centered in the insular lobe. Tumors were categorized based on their proximity and invasiveness of non-traditional cognitive networks and traditionally eloquent structures. Diffusion tensor imaging tractography was completed by creating a personalized brain atlas using Quicktome to determine eloquent and non-eloquent networks in each patient. Additionally, we prospectively collected neuropsychological data on 7 patients to compare tumor-network involvement with change in cognition. Lastly, 2 prospective patients had their surgical plan influenced by network mapping determined by Quicktome.
RESULTS: Forty-four of 45 patients demonstrated tumor involvement (< 1 cm proximity or invasion) with components of non-traditional brain networks involved in cognition such as the salience network (SN, 60%) and the central executive network (CEN, 56%). Of the seven prospective patients, all had tumors involved with the SN, CEN (5/7, 71%), and language network (5/7, 71%). The mean scores of MMSE and MOCA before surgery were 18.71 ± 6.94 and 17.29 ± 6.26, respectively. The two cases who received preoperative planning with Quicktome had a postoperative performance that was anticipated.
CONCLUSIONS: Non-traditional brain networks involved in cognition are encountered during surgical resection of insulo-Sylvian gliomas. Quicktome can improve the understanding of the presence of these networks and allow for more informed surgical decisions based on patient functional goals.

Connectomics enables the study of structural-functional relationships in the brain, and machine learning technologies have enabled connectome maps to be developed for individual brain tumor patients. We report our experience using connectomics to plan and guide an awake craniotomy for a tumor impinging on the language area. Preoperative connectomics imaging demonstrated proximity of the tumor to parcellations of the language area. Intraoperative awake language mapping was performed, revealing speech arrest and paraphasic errors at areas of the tumor boundary correlating to functional regions that explained these findings. This instructive case highlights the potential benefits of implementing connectomics into neurosurgical planning.

Connectome mapping may reveal new treatment targets for patients with neurological and psychiatric diseases. However, the long-term delayed recall based-network with structural and functional connectome is still largely unknown. Our objectives were to (1) identify the long-term delayed recall-based cortex-hippocampus network with structural and functional connectome and (2) investigate its relationships with various cognitive functions, age, and activities of daily living.
This case-control study enrolled 131 subjects (73 amnestic mild cognitive impairment [aMCI] patients and 58 age- and education-matched healthy controls [HCs]). All subjects completed a neuropsychological battery, activities of daily living assessment, and multimodal magnetic resonance imaging. Nodes of the cortical-hippocampal network related to long-term delayed recall were identified by probabilistic fiber tracking and functional connectivity (FC) analysis. Then, the main and interaction effects of the network on cognitive functions were assessed by a generalized linear model. Finally, the moderating effects of the network on the relationships between long-term delayed recall and clinical features were analyzed by multiple regression and Hayes\' bootstrap method. All the effects of cortex-hippocampus network were analyzed at the connectivity and network levels.
The result of a generalized linear model showed that the bilateral hippocampus, left dorsolateral superior frontal gyrus, right supplementary motor area, left lingual gyrus, left superior occipital gyrus, left superior parietal gyrus, left precuneus, and right temporal pole (superior temporal gyrus) are the left and right cortex-hippocampus network nodes related to long-term delayed recall (P < 0.05). Significant interaction effects were found between the Auditory Verbal Learning Test Part 5 (AVLT 5) scores and global properties of the left cortex-hippocampus network [hierarchy, clustering coefficient, characteristic path length, global efficiency, local efficiency, Sigma and synchronization (P < 0.05 Bonferroni corrected)]. Significant interaction effects were found between the general cognitive function/executive function/language and global properties of the left cortex-hippocampus network [Sigma and synchronization (P < 0.05 Bonferroni corrected)].
This study introduces a novel symptom-based network and describes relationships among cognitive functions, brain function, and age. The cortex-hippocampus network constrained by the structural and functional connectome is closely related to long-term delayed recall.

What is the reason for complex dynamical patterns registered from real biological neuronal networks? Noise and dynamical reconfiguring of a network (functional/dynamic connectome) were proposed as possible answers. In this case study, we report a complex dynamical pattern observed in a simple deterministic network of 25 excitatory neurons with fixed connectome. After a short initial stimulation, the network is engaged into a complex dynamics, which lasts for a long time. Eventually, with no external intervention, the dynamics comes to a periodic one with a short period. The long transient is positively checked for being chaotic. We conclude that the complex dynamics observed is the output of neural computation performed in the process of neuronal firings and spikes propagation.

Having a parent with Alzheimer\'s disease (AD) and related dementias confers a risk for developing these types of neurocognitive disorders in old age, but the mechanisms underlying this risk are understudied. Although the hippocampus is often one of the earliest brain regions to undergo change in the AD process, we do not know how early in the lifespan such changes might occur or whether they differ early in the lifespan as a function of family history of AD. Using a rare sample, young adults with a parent with late-onset dementia, we investigated whether brain abnormalities could already be detected compared with a matched sample. Moreover, we employed simple yet novel techniques to characterize resting brain activity (mean and standard deviation) and brain volume in the hippocampus. Young adults with a parent with dementia showed greater resting mean activity and smaller volumes in the left hippocampus compared to young adults without a parent with dementia. Having a parent with AD or a related dementia was associated with early aberrations in brain function and structure. This early hippocampal dysfunction may be due to aberrant neural firing, which may increase the risk for a diagnosis of dementia in old age.

BACKGROUND: Only a small proportion of schizophrenia patients present with catatonic symptoms. Imaging studies suggest that brain motor circuits are involved in the underlying pathology of catatonia. However, data about diffusivity dysregulation of these circuits in catatonic schizophrenia are scarce.
OBJECTIVE: To assess the involvement of brain motor circuits in schizophrenia patients with catatonia.
METHODS: Diffusion tensor imaging (DTI) was used to measure white matter signals in selected brain regions linked to motor circuits. Relevant DTI data of seven catatonic schizophrenia patients were compared to those of seven non-catatonic schizophrenia patients, matched for sex, age, and education level.
RESULTS: Significantly elevated fractional anisotropy values were found in the splenium of the corpus callosum, the right peduncle of the cerebellum, and the right internal capsule of the schizophrenia patients with catatonia compared to those without catatonia. This finding showed altered diffusivity in selected motor-related brain areas.
CONCLUSIONS: Catatonic schizophrenia is associated with dysregulation of the connectivity in specific motoric brain regions and corresponding circuits. Future DTI studies are needed to address the neural correlates of motor abnormalities in schizophrenia-related catatonia during the acute and remitted state of the illness to identify the specific pathophysiology of this disorder.

BACKGROUND: Outcome prediction for patients with disorders of consciousness (DOC) is essential yet challenging. Evidence showed that patients with DOC lasting 1 year or longer after a brain injury were less likely to recover. However, the reasons why outcomes of DOC patients differ greatly remain unclear. With a variety of analytical methods and through quantitative behavioral assessments, we aimed to track the progression of a patient with severe brain injury, in order to advance our understanding of the underlying mechanisms of DOC.
METHODS: We performed a longitudinal study for a 52-year-old male DOC patient who has remained in the state for 1.5 years with comprehensive rehabilitative therapies. The patient underwent 3 times of assessments of Coma Recovery Scale-Revised (CRS-R) and ultra-high-field 7 T magnetic resonance imaging (MRI). Both topologic properties and brain microstructure were analyzed to track disease progression. We observed dynamic increases of fiber densities with measurements at three time points (t1:1.5 M, t2:7.5 M t3:17.5 M). Specifically, fiber densities of the superior longitudinal fasciculus and arcuate fasciculus nerve fiber bundles improved mostly in the visual, verbal, and auditory subscales, which was consistent with the CRS-R scores. Moreover, the graph-theory analyses demonstrated that network topologic properties showed an improvement although the disease duration exceeded 1 year.
CONCLUSIONS: DOC patients with a course longer than 1 year remain possible to improve, and including evaluation methods such as WM connectome analysis and graph theory could be potentially valuable for a more precise assessment of patients with a longer course of DOC.