Neuroimaging-based drug discovery for amyloid clearance therapy in Alzheimer's disease using validated causation analysis.

Aging-induced hepatic dysfunction can impair cholesterol metabolism, reducing the availability of cholic acid (CA, bile-acid) in brain. CA is reported to have neuroprotective characteristics in preclinical investigations of Alzheimer's disease (AD). Our aim is to probe the causal-connectivity between the players: amyloid, cholic acid and cerebral-blood-flow, and thereby explore therapeutic applicability in AD. From AD neuroimaging initiative biospecimen platform, we evaluated serum cholic-acid (182 healthy/136 AD individuals). We also assessed 50 healthy/50 Alzheimer's subjects containing MRI-ASL scanning (cerebral blood-flow, CBF) and PET-AV45 scanning (amyloid-load). We performed computational causal connectivity to determine the cause-effect relationship among the parameters. Serum cholic acid in AD subjects substantially decreased to half of controls. Causal-connectivity revealed two novel causative pathways: (i) Decreasing serum CA markedly increased amyloid-load; (ii) Increasing amyloid-load distinctly decreased CBF. We substantiated these two causation pathways respectively with collateral available preclinical observations: (a) increased cholic acid reduces amyloid formation by diminishing gamma-secretase; (b) this decreased amyloid induces capillary-flow enhancement by relaxing vascular pericytes. Indeed, cholic acid can increase amyloid-clearance factor. Neuroimaging-based causal connectivity analysis showed that repositioned pharmacological modulation by cholate derivatives may have appreciable potential as novel window for therapeutic approach to AD. Indicative clinical validation is furnished from available therapeutic trial leads.

Structural brain network organization in children with prenatal alcohol exposure.

INTRODUCTION: There is growing evidence suggesting that children with prenatal alcohol exposure (PAE) struggle with cognitively demanding tasks, such as learning, attention, and language. Complex structural network analyses can provide insight into the neurobiological underpinnings of these functions, as they may be sensitive for characterizing the effects of PAE on the brain. However, investigations on how PAE affects brain networks are limited. We aim to compare diffusion magnetic resonance imaging (MRI) tractography-based structural networks between children with low-to-moderate PAE in trimester 1 only (T1) or throughout all trimesters (T1-T3) with those without alcohol exposure prenatally. METHODS: Our cohort included three groups of children aged 6 to 8 years: 1) no PAE (n = 24), 2) low-to-moderate PAE during T1 only (n = 30), 3) low-to-moderate PAE throughout T1-T3 (n = 36). Structural networks were constructed using the multi-shell multi-tissue constrained spherical deconvolution tractography technique. Quantitative group-wise analyses were conducted at three levels: (a) at the whole-brain network level, using both network-based statistical analyses and network centrality; and then using network centrality at (b) the modular level, and (c) per-region level, including the regions identified as brain hubs. RESULTS: Compared with the no PAE group, widespread brain network alterations were observed in the PAE T1-T3 group using network-based statistics, but no alterations were observed for the PAE T1 group. Network alterations were also detected at the module level in the PAE T1-T3 compared with the no PAE group, with lower eigenvector centrality in the module that closely represented the right cortico-basal ganglia-thalamo-cortical network. No significant group differences were found in network centrality at the per-region level, including the hub regions. CONCLUSIONS: This study demonstrated that low-to-moderate PAE throughout pregnancy may alter brain structural connectivity, which may explain the neurodevelopmental deficits associated with PAE. It is possible that timing and duration of alcohol exposure are crucial, as PAE in T1 only did not appear to alter brain structural connectivity.

Multiscale and multimodal signatures of structure-function coupling variability across the human neocortex.

The relationship between the brain's structural wiring and its dynamic activity is thought to vary regionally, implying that the mechanisms underlying structure-function coupling may differ depending on a region's position within the brain's hierarchy. To better bridge the gap between structure and function, it is crucial to identify the factors shaping this regionality, not only in terms of how static functional connectivity aligns with structure, but also regarding the time-domain variability of this interplay. Here we map structure - function coupling and its time-domain variability and relate them to the heterogeneity of the cortex. We show that these two properties split the cortical landscape into two districts anchored to the opposite ends of the brain's hierarchy. By looking at statistical relationships with layer-specific gene transcription, T1w/T2w ratio, and synaptic density, we show that macro-scale structure-function coupling may be rooted in the brain's microstructure and meso-scale laminar specialization. Finally, we demonstrate that a lower and more variable alignment of function and structure may bestow the emergence of unique functional dynamics.

Functional brain connectivity predictors of prospective substance use initiation and their environmental correlates.

BACKGROUND: Early substance use initiation (SUI) places youth at substantially higher risk for later substance use disorders. Furthermore, adolescence is a critical period for the maturation of brain networks, the pace and magnitude of which are susceptible to environmental influences and may shape risk for SUI. METHODS: We examined whether patterns of functional brain connectivity during rest (rsFC), measured longitudinally in pre-and-early adolescence, can predict future SUI. Next, in an independent sub-sample, we tested whether these patterns are associated with earlier environmental exposures, specifically neighborhood pollution and socioeconomic dimensions. We utilized data from the Adolescent Brain Cognitive Development (ABCD) Study®. SUI was defined as first-time use of at least one full dose of alcohol, nicotine, cannabis, or other drugs. We created a control group (N = 228) of participants without SUI who were matched with the SUI group (N = 233) on age, sex, race/ethnicity, and parental income and education. RESULTS: Multivariate analysis showed that whole-brain rsFC from 9-10 to 11-12 years of age (prior to SUI) prospectively differentiated the SUI and control groups. The SUI-related rsFC pattern was also related to aging in both groups, suggesting a pattern of accelerated maturation in the years prior to SUI. This same pattern of rsFC was predicted by higher pollution, but not neighborhood disadvantage (adjusted for family socioeconomic factors) in an independent sub-sample (N = 2,854). CONCLUSION: Brain functional connectivity patterns in early adolescence that are linked to accelerated maturation can predict SUI in youth and are associated with exposure to pollution.

Differences in Static and Dynamic Resting-State Functional Connectivity between Migraineurs with and without Photophobia, without Phonophobia or Osmophobia.

BACKGROUND: We have previously shown that static and dynamic resting-state functional connectivity differ between migraineurs with and without photophobia, phonophobia, or osmophobia. Furthermore, some patients with photophobia also experience phonophobia or osmophobia. To investigate the functional connectivity specific to migraineurs with photophobia, we examined the differences in static and dynamic resting-state functional connectivity between patients with and without photophobia, with no phonophobia or osmophobia. METHODS: Fifteen migraineurs with photophobia but without phonophobia or osmophobia, as well as 15 sex- and age-matched migraineurs without photophobia, phonophobia, or osmophobia, underwent 3-T functional magnetic resonance imaging during the interictal phase. Static and dynamic resting-state functional connectivity were compared using region-of-interest analyses of 91 cortical, 15 subcortical, and 26 cerebellar areas. RESULTS: Static resting-state functional connectivity analysis revealed ten significant connectivity pairs in patients with photophobia, while dynamic resting-state functional connectivity analysis revealed six significant connectivity pairs in patients with photophobia. Migraineurs with photophobia had significantly lower connectivity between the cerebellar hemisphere and the temporal region than those without photophobia in both static and dynamic studies. CONCLUSIONS: Our results show that lower resting-state functional connectivity between the cerebellar hemisphere and the temporal region is specific to migraineurs with photophobia.

The role of larval transport on recruitment dynamics of red mullet (Mullus barbatus) in the Central Mediterranean Sea.

Recruitment success depends on external forcing mechanisms such as ocean currents that affect the transport of eggs and larvae to favorable habitats. In this study, we investigated the role of larval transport in the recruitment of Mullus barbatus in the Central Mediterranean Sea by modeling the recruits' abundance as a function of both spawning stock size and dispersal rates of the species' early life stages. Our analysis involved twenty years of data on recruits and spawners abundance obtained from scientific trawl surveys, and data on larval dispersal rates derived from a combination of actualized published sources and original data. By calculating the estimates of retention, import and uniformity of the contribution of the spawning areas distributed among different Geographical Sub Areas (GSAs) in the Sicilian nurseries, we assessed their contribution to recruitment using modified Ricker stock size-recruits models. In particular, our results show that a high uniform contribution from spawning areas within GSA16, mainly related to the oceanographic patterns promoting larval retention, together with spawners abundance, significantly reduced the variability of red mullet recruitment. We further highlighted that when switching from a higher to a lower level of evenness of contribution to the recruit population from different spawning areas in the GSA16, the expected spawning stock abundance per recruit for a given fishing pattern can suffer a rapid short-term decline, which is likely to have negative consequences for stock assessment and management decisions. Our results suggest that larval transport plays a crucial role in explaining the interannual variability of recruitment, thereby contributing to a better understanding of stock size variation. Additionally, our study enhances the understanding of the spatial dynamics involved in the recruitment of this species, which is of increasing interest within fisheries management frameworks.

The brain's structural connectivity and pre-reading abilities in young children with prenatal alcohol exposure.

Children with prenatal alcohol exposure (PAE) may develop a range of neurological and behavioral deficits, including reading and language disorders. Studying the brain's structural connectivity and its relationship to pre-reading/reading skills in young children with PAE can help understand the roots of reading deficits associated with PAE. 363 diffusion MRI scans from 135 children (114 scans from 53 children with PAE) were collected between ages 3-7 years. Children completed NEPSY-II Phonological Processing and Speeded Naming to assess pre-reading skills at each scan. Structural brain network properties were assessed in 16 regions from both hemispheres using graph theory. Linear mixed models were used to account for repeated measures within participants. Children with PAE had significantly lower pre-reading scores than unexposed children, and significantly lower graph theory metrics across bilateral reading networks. Moreover, PAE significantly moderated the associations between Phonological Processing and global efficiency and nodal degree in the bilateral and left hemisphere reading networks, such that children with PAE had stronger associations than unexposed controls. No significant associations were found for Speeded Naming. Our results suggest that brain alterations may underlie early pre-reading difficulties in children with PAE.

Identification of asymmetrical abnormalities in functional connectivity and brain network topology for migraine sufferers: a preliminary study based on Resting-State fMRI data.

Research on the neural mechanisms underlying brain asymmetry in patients with migraine patients using fMRI is insufficient. This study proposed using lateralized algorithms for functional connectivity and brain network topology and investigated changes in their lateralization in patients with migraine. In study 1, laterality indices of functional connectivity (LFunctionCorr) and brain network topological properties (LBetweennessCentrality, LDegree, and LStrength) were defined. Differences between migraineurs and normal subjects were compared at whole-brain, half-brain, and region levels. In study 2, laterality indices were used to classify migraine and were validated using independent samples and the segment method for repeatability. In study 3, abnormal brain regions related to migraine were extracted based on the classification results and differences analysis. Study 1 found no significant differences related to in for migraine at the whole-brain level; however, significant differences were identified at the half-brain level for the hemispheric lateralization of the LFunctionCorr, while 11 significantly different brain regions were also identified at the brain region level. Furthermore, the classification accuracy in study 2 was 0.9366. With repeated validation, the accuracy reached 0.8561. Furthermore, after extending the samples according to the segmentation strategy, the classification accuracies were improved to 0.9408 and 0.8585. Study 3 identified 10 crucial brain regions with asymmetrical specificity based on laterality indices distributed across the visual network, the frontoparietal control network, the default mode network, the salience/ventral attention network and the limbic system. The results revealed novel insights and avenues for research into the mechanisms of migraine asymmetry and showed that the laterality indices could be used as a potential diagnostic imaging marker for migraine.

Alterations of Regional Homogeneity and Functional Connectivity in Different Hoehn and Yahr Stages of Parkinson's Disease.

PURPOSE: Using regional homogeneity (ReHo) and functional connectivity (FC) to assess alterations in brain function and their potential relation to different Hoehn and Yahr (H&Y) stages in Parkinson's disease (PD). MATERIALS AND METHODS: 66 patients with PD and 57 age- and sex-matched healthy control (HC) participants were recruited. All subjects underwent clinical assessments and resting-state functional magnetic resonance imaging (rs-fMRI) scanning. We analyzed alterations in regional brain activity using ReHo analyses in all subjects and further explored their relationship to disease severity. Finally, the brain region significantly associated with disease severity was used as a seed point to analyze the FC changes between it and other brain regions in the whole brain. RESULTS: Compared with HC participants, PD patients showed a significant decrease ReHo in the sensorimotor network (bilateral precentral and postcentral gyrus). The ReHo value of the left precentral gyrus in PD patients decreased with increasing H&Y stage and correlated negatively with Unified Parkinson's Disease Rating Scale (UPDRS) III scores. Further, FC analysis of the left precentral gyrus as a region of interest showed that functional activity between the left precentral gyrus and sensorimotor network, default network, and visual network was decreased. CONCLUSION: The left precentral gyrus plays an important role in the pathophysiological mechanisms of PD patients, and this finding further highlights the potential of the primary motor cortex (M1) as a non-invasive therapeutic target for neuromodulation in PD patients.

Enhancing Prediction of Human Traits and Behaviors through Ensemble Learning of Traditional and Novel Resting-State fMRI Connectivity Analyses.

Recent advances in cognitive neuroscience have focused on using resting-state functional connectivity (RSFC) data from fMRI scans to more accurately predict human traits and behaviors. Traditional approaches generally analyze RSFC by correlating averaged time-series data across regions of interest (ROIs) or networks, which may overlook important spatial signal patterns. To address this limitation, we introduced a novel linear regression technique that estimates RSFC by predicting spatial brain activity patterns in a target ROI from those in a seed ROI. We applied both traditional and our novel RSFC estimation methods to a large-scale dataset from the Human Connectome Project and the Brain Genomics Superstruct Project, analyzing resting-state fMRI data to predict sex, age, personality traits, and psychological task performance. To enhance prediction accuracy, we developed an ensemble learner that combines these qualitatively different methods using a weighted average approach. Our findings revealed that hierarchical clustering of RSFC patterns using our novel method displays distinct whole-brain grouping patterns compared to the traditional approach. Importantly, the ensemble model, integrating these diverse weak learners, outperformed the traditional RSFC method in predicting human traits and behaviors. Notably, the predictions from the traditional and novel methods showed relatively low similarity, indicating that our novel approach captures unique and previously undetected information about human traits and behaviors through fine-grained local spatial patterns of neural activation. These results highlight the potential of combining traditional and innovative RSFC analysis techniques to enrich our understanding of the neural basis of human traits and behaviors.

Differential induction of Parieto-motor plasticity in writer's cramp and cervical dystonia.

OBJECTIVES: To investigate the plastic effects of parieto-motor (PAR-MOT) cortico-cortical paired associative paired stimulation (cc-PAS) in patients with two forms of focal dystonia, writer's cramp and cervical dystonia, compared to healthy volunteers (HVs). METHODS: We used cc-PAS to induce associative plasticity using repeated time-locked paired transcranial magnetic stimulation (TMS) pulses over the parietal and motor cortices in 16 patients with writer's cramp (WC), 13 patients with cervical dystonia (CD), and 23 healthy volunteers. We measured parieto-motor corticocortical connectivity using posterior parietal cortex (PPC) to primary motor cortex (M1) facilitation and input-output curves (IOC) of the motor-evoked potential (MEP) before and after PAR-MOT cc-PAS. The PAR-MOT cc-PAS consisted of 100 pairs of TMS pulses every 5 s, with the conditioning pulse applied to the left angular gyrus in the intraparietal sulcus and the test pulse applied to the M1 hotspot of the first dorsal interosseous muscle. RESULTS: The cc-PAS increased the area under the IOC by increasing its maximum level in patients with WC but not in patients with CD or healthy volunteers. The cc-PAS had no significant effect on other IOC parameters. There were no significant differences in PPC to M1 facilitation changes after PAR-MOT cc-PAS among all groups. CONCLUSIONS: This study suggests that PAR-MOT cc-PAS abnormally increases M1 excitability in patients with WC but not in those with CD. Additionally, this increased plastic response in patients with WC does not appear to be directly linked to PPC to M1 corticocortical connectivity.

Age-related differences of the time-varying features in the brain functional connectivity and cognitive aging.

Brain functional modular organization changes with age. Considering the brain as a dynamic system, recent studies have suggested that time-varying connectivity provides more information on brain functions. However, the spontaneous reconfiguration of modular brain structures over time during aging remains poorly understood. In this study, we investigated the age-related dynamic modular reconfiguration using resting-state functional MRI data (615 participants, aged 18-88 years) from Cam-CAN. We employed a graph-based modularity analysis to investigate modular variability and the transition of nodes from one module to another in modular brain networks across the adult lifespan. Results showed that modular structure exhibits both linear and nonlinear age-related trends. The modular variability is higher in early and late adulthood, with higher modular variability in the association networks and lower modular variability in the primary networks. In addition, the whole-brain transition matrix showed that the times of transition from other networks to the dorsal attention network were the largest. Furthermore, the modular structure was closely related to the number of cognitive components and memory-related cognitive performance, suggesting a potential contribution to flexibility cognitive function. Our findings highlighted the notable dynamic characteristics in large-scale brain networks across the adult lifespan, which enhanced our understanding of the neural substrate in various cognitions during aging. These findings also provided further evidence that dedifferentiation and compensation are the outcomes of functional brain interactions.

Connectivity changes in two-channel prefrontal ERP associated with early cognitive decline in the elderly population: beta band responses to the auditory oddball stimuli.

Background: This study utilized recent advancements in electroencephalography (EEG) technology that enable the measurement of prefrontal event-related potentials (ERPs) to facilitate the early detection of mild cognitive impairment (MCI). We investigated two-channel prefrontal ERP signals obtained from a large cohort of elderly participants and compare among cognitively normal (CN), subjective cognitive decline (SCD), amnestic MCI (aMCI), and nonamnestic MCI (naMCI) groups. Methods: Signal processing and ERP component analyses, specifically adapted for two-channel prefrontal ERP signals evoked by the auditory oddball task, were performed on a total of 1,754 elderly participants. Connectivity analyses were conducted to assess brain synchronization, especially in the beta band involving the phase locking value (PLV) and coherence (COH). Time-frequency, time-trial, grand average, and further statistical analyses of the standard and target epochs were also conducted to explore differences among the cognition groups. Results: The MCI group's response to target stimuli was characterized by greater response time variability (p < 0.001) and greater variability in the P300 latency (p < 0.05), leading to less consistent responses than those of the healthy control (HC) group (CN+SCD subgroups). In the connectivity analyses of PLV and COH waveforms, significant differences were observed, indicating a loss of synchronization in the beta band in response to standard stimuli in the MCI group. In addition, the absence of event-related desynchronization (ERD) indicated that information processing related to readiness and task performance in the beta band was not efficient in the MCI group. Furthermore, the observed decline in the P200 amplitude as the standard trials progressed suggests the impaired attention and inhibitory processes in the MCI group compared to the HC group. The aMCI subgroup showed high variability in COH values, while the naMCI subgroup showed impairments in their overall behavioral performance. Conclusion: These findings highlight the variability and connectivity measures can be used as markers of early cognitive decline; such measures can be assessed with simple and fast two-channel prefrontal ERP signals evoked by both standard and target stimuli. Our study provides deeper insight of cognitive impairment and the potential use of the prefrontal ERP connectivity measures to assess early cognitive decline.

Structural and functional correlates of olfactory reward processing in behavioral variant frontotemporal dementia.

The behavioral variant of frontotemporal dementia (bvFTD) includes symptoms that reflect altered pursuit of rewards, including food, alcohol, and money. Little is known, however, about how these reward changes relate to atrophy and functional connectivity within reward-related regions. The goal of this study was to examine the structural and functional correlates of valence perception for olfactory rewards in 24 patients with bvFTD. Regression analysis of resting-state brain functional connectivity indicated that more positive valence ratings of olfactory stimuli were predicted by ventral pallidum connectivity to other reward circuit regions, particularly functional connectivity between ventral pallidum and bilateral anterior cingulate cortex/ventromedial prefrontal cortex. Structural analysis showed that atrophy of the anterior cingulate cortex was also significantly associated with perceiving stimuli as more rewarding. Finally, there was a significant interaction between ventral pallidum connectivity and atrophy of the anterior cingulate cortex. More specifically, the ventral pallidum connectivity had a greater effect on the positive perception of olfactory stimuli in the setting of low anterior cingulate cortex volume. These findings indicate that atrophy and functional connectivity within reward-relevant regions exert independent and interacting effects on the perception of pleasantness in bvFTD, potentially due to changes in hedonic "liking" signals.

Depression-induced changes in directed functional brain networks: A source-space resting-state EEG study.

Current research confirms abnormalities in resting-state electroencephalogram (EEG) power and functional connectivity (FC) patterns in specific brain regions of individuals with depression. To study changes in the flow of information between cortical regions of the brain in patients with depression, we used 64-channel EEG to record neural oscillatory activity in 68 relevant cortical regions in 22 depressed patients and 22 healthy adolescents using source-space EEG. The direction and strength of information flow between brain regions was investigated using directional phase transfer entropy (PTE). Compared to healthy controls, we observed an increased intensity of PTE information flow between the left and right hemispheres in the theta and alpha frequency bands in depressed subjects. The intensity of information flow between anterior and posterior regions within each hemisphere was reduced. Significant differences were found in the left supramarginal gyrus, right delta in the theta frequency band and bilateral lateral occipital lobe, and paracentral gyrus and parahippocampal gyrus in the alpha frequency band. The accuracy of cross-classification of directed PTE values with significant differences between groups was 91%. These findings suggest that altered information flow in the brains of depressed patients is related to the pathogenesis of depression, providing insights for patient identification and pathological studies.

Altered functional connectivity of unimodal sensory and multisensory integration networks is related to symptom severity in autism spectrum disorders.

BACKGROUND: Atypical sensory processing is a prevalent feature in autism spectrum disorders (ASD) and constitutes a core diagnostic criterion in the Diagnostic and Statistical Manual of Mental of Disorders, 5th edition (DSM-5). However, neurocognitive underpinnings of atypical unimodal and multimodal sensory processing and their relationships with autism symptoms remain unclear. METHODS: This study examined intrinsic functional connectivity (FC) patterns among five unimodal sensory and multisensory integration (MSI) networks in ASD with a large multi-site dataset (n = 646), and investigated the relationships among altered FC, atypical sensory processing, social communicative deficits, and overall autism symptoms with correlation and mediation analyses. RESULTS: Relative to typically developing (TD) controls, the ASD group demonstrated increased FC of the olfactory network, decreased FC within the MSI network, and decreased FC of the MSI-unimodal-sensory networks. Furthermore, altered FC was positively associated with autism symptom severity, and such associations were completely mediated by atypical sensory processing and social communicative deficits. CONCLUSIONS: ASD-specific olfactory overconnectivity and MSI-unimodal-sensory underconnectivity lend support to the Intense World Theory and Weak Central Coherence Theory, suggesting olfactory hypersensitivity at the expense of multisensory integration as potential neural mechanisms underlying atypical sensory processing in ASD. These atypical FC patterns further suggest potential targets for psychological and neuromodulatory interventions.

Disorganized thalamic subregional functional connectivity in bipolar I disorder.

Thalamus plays a pivotal role in the pathophysiology of neuropsychiatric conditions due to its strategic position and intricate connectivity with the cerebral cortex, limbic system, and other subcortical structures. In the present study, the potential involvement of the thalamus and subregions of the thalamus are explored in bipolar disorder (BD). In particular, functional and structural magnetic resonance imaging was performed on 73 adult patients with BD-I and 78 healthy controls (HCs). Seed-based thalamus and thalamic subregional functional connectivity (FC) were compared between the BD-I patients and HCs. Compared to HCs, patients with BD-I showed higher FC between the left thalamus and right lingual gyrus and altered FC between the dorsal thalamus and the default mode network and prefrontal regions, which may be correlated with mania symptomatology. In patients with BD-I, the anterior subregions of the thalamus had higher FC than the posterior subregions. No significant difference in gray matter volume or local functional activity was found in the thalamus and thalamic subregions between BD-I and HC. These findings provide evidence of disorganized thalamocortical FC in BD-I, suggesting that the thalamus and its subregions may play important and specific roles in the neural circuitry of BD.

Beta-Band Cortico-Muscular Phase Coherence in Hemiparetic Stroke.

Following a stroke, compensation for the loss of ipsilesional corticospinal and corticobulbar projections, results in increased reliance on contralesional motor pathways during paretic arm movement. Better understanding outcomes of post-stroke contralesional cortical adaptation outcomes may benefit more targeted post-stroke motor rehabilitation interventions. This proof-of-concept study involves eight healthy controls and ten post-stroke participants. Electroencephalographic (EEG) and deltoid electromyographic (EMG) data were collected during an upper-limb task. Phase coupling between beta-band motor cortex EEG and deltoid EMG was assessed using the Multi-Phase Locking Value (M-PLV) method. Different from classic cortico-muscular coherence, M-PLV allows for the calculation of dynamic phase coherence and delays, and is not affected by the non-stationary nature of EEG/EMG signals. Nerve conduction delay from the contralateral motor cortex to the deltoid muscle of the paretic arm was estimated. Our results show the ipsilateral (contralesional) motor cortex beta-band phase coherence behavior is altered in stroke participants, with significant differences in ipsilateral EEG-EMG coherence values, ipsilateral time course percentage above the significance threshold, and ipsilateral time course area above the significance threshold. M-PLV phase coherence analysis provides evidence for post-stroke contralesional motor adaptation, highlighting its increased role in the paretic shoulder abduction task. Nerve conduction delay between the motor cortices and deltoid muscle is significantly higher in stroke participants. Beta-band M-PLV phase coherence analysis shows greater phase-coherence distribution convergence between the ipsilateral (contralesional) and contralateral (ipsilesional) motor cortices in stroke participants, which is interpretable as evidence of maladaptive neural adaptation resulting from a greater reliance on the contralesional motor cortices.

Clinical Features and Electroencephalogram Analysis of Brain Network Functional Connectivity in Anti-Leucine-Rich Glioma-Inactivated 1 Antibody Encephalitis.

Purpose: To summarize the clinical manifestations, laboratory findings, and magnetic resonance imaging (MRI) characteristics of anti-leucine-rich glioma-inactivated 1 (LGI1) antibody encephalitis (anti-LGI1 antibody encephalitis) and explore the electroencephalogram (EEG) features. Patients and Methods: We retrospectively analyzed the medical history of 16 patients diagnosed with anti-LGI1 antibody encephalitis at the First Hospital of Hebei Medical University from 2021 to 2023. EEGs of patients with anti-LGI1 antibody encephalitis and healthy individuals were analyzed. Based on Video-EEG signal analysis of EEG δ, θ, α, ß frequency bands, weighted phase lag index values were calculated to form brain network matrices, studying differences in coherence between brain regions of patients with anti-LGI1 antibody encephalitis and healthy individuals. Results: Patients with anti-LGI1 antibody encephalitis often presented with subacute onset seizures and cognitive decline. Routine test of cerebrospinal fluid was mostly normal. Serum testing revealed hyponatremia in 62.50% of patients, along with positive serum antinuclear antibodies, decreased vitamin B12, and abnormal cytokines such as interleukin-6. Head MRI revealed abnormal lesions related to the disease in seven cases (43.75%), mainly located in the unilateral or bilateral frontal and temporal lobes of the hippocampus. The EEG mainly showed generalized and focal slow waves, sometimes with focal discharges. Brain network functional connectivity analysis found a significant weakening of functional connections in the frontal-temporal lobe in the δ and ß frequency bands. Intravenous pulse corticosteroids and intravenous immunoglobulin are first-line immunotherapies for anti-LGI1 antibody-related encephalitis. The disease recovery and cognitive decline improved in most patients. Conclusion: Anti-LGI1 antibody encephalitis is characterized by seizures and cognitive dysfunction. Serum may show abnormalities in immune indicators such as cytokines. Head MRI mainly reveals abnormal signals in the frontal-temporal lobes and the hippocampus. EEG brain network connectivity analysis reveals characteristic weakening of functional connections in the frontal-temporal lobe in the δ and ß frequency bands.

Connectivity of Parameter Regions of Multistationarity for Multisite Phosphorylation Networks.

The parameter region of multistationarity of a reaction network contains all the parameters for which the associated dynamical system exhibits multiple steady states. Describing this region is challenging and remains an active area of research. In this paper, we concentrate on two biologically relevant families of reaction networks that model multisite phosphorylation and dephosphorylation of a substrate at n sites. For small values of n, it had previously been shown that the parameter region of multistationarity is connected. Here, we extend these results and provide a proof that applies to all values of n. Our techniques are based on the study of the critical polynomial associated with these reaction networks together with polyhedral geometric conditions of the signed support of this polynomial.