Functional Networks In Patients Research Articles

Single-dose psilocybin alters resting state functional networks in patients with body dysmorphic disorder

Body dysmorphic disorder (BDD) is a severe psychiatric condition characterized by preoccupation with perceived flaws in one's appearance, which the individual views as defective or ugly. Psilocybin, a serotonin 2A receptor agonist with psychedelic properties, has emerged as a potential therapeutic agent for depression and other psychiatric disorders. This study aimed to identify subacute neural changes predicting symptomatic response to psilocybin treatment in adults with BDD. Eight adults with moderate-to-severe nondelusional BDD were administered a single oral 25 mg dose of psilocybin, accompanied by psychological support, and underwent resting state functional magnetic resonance imaging assessments 1 day before and 1 day after the dosing. Both a region of interest (ROI)-to-ROI analysis and multivariate pattern analysis (MVPA) were used to identify changes in resting state functional connectivity (rsFC) at day 1 after dosing that predicted treatment response at week 1, measured by change in Yale-Brown Obsessive Compulsive Disorder Scale Modified for BDD (BDD-YBOCS) score. All participants completed the dosing and follow-up assessments over 12 weeks. BDD-YBOCS scores decreased at week 1 and week 12 after dosing (p<0.001 for both). MVPA revealed a significant increase in rsFC within the Executive Control Network (ECN) at day 1. Increased rsFC within the ECN (dlPFC – Superior Parietal Lobule [FPL]), between the ECN and Default Mode Network (dlPFC – Precuneus), and between the ECN and the Salience Network (dlPFC – insula) were predictive of improvement in BDD symptoms at week 1. These findings are the first report of subacute brain effects of psilocybin in patients with BDD. Given the small sample size and uncontrolled design of the study, larger controlled studies are necessary to validate these observations. Clinical Trials Registration: Clinicaltrials.gov ID: NCT04656301

Resting State Functional Networks in Gliomas: Validation With Direct Electric Stimulation of a New Tool for Planning Brain Resections.

Precise mapping of functional networks in patients with brain tumor is essential for tailoring personalized treatment strategies. Resting-state functional MRI (rs-fMRI) offers an alternative to task-based fMRI, capable of capturing multiple networks within a single acquisition, without necessitating task engagement. This study demonstrates a strong concordance between preoperative rs-fMRI maps and the gold standard intraoperative direct electric stimulation (DES) mapping during awake surgery. We conducted an analysis involving 28 patients with glioma who underwent awake surgery with DES mapping. A total of 100 DES recordings were collected to map sensorimotor (SMN), language (LANG), visual (VIS), and speech articulation cognitive domains. Preoperative rs-fMRI maps were generated using an updated version of the ReStNeuMap software, specifically designed for rs-fMRI data preprocessing and automatic detection of 7 resting-state networks (SMN, LANG, VIS, speech articulation, default mode, frontoparietal, and visuospatial). To evaluate the agreement between these networks and those mapped with invasive cortical mapping, we computed patient-specific distances between them and intraoperative DES recordings. Automatically detected preoperative functional networks exhibited excellent agreement with intraoperative DES recordings. When we spatially compared DES points with their corresponding networks, we found that SMN, VIS, and speech articulatory DES points fell within the corresponding network (median distance = 0 mm), whereas for LANG a median distance of 1.6 mm was reported. Our findings show the remarkable consistency between key functional networks mapped noninvasively using presurgical rs-fMRI and invasive cortical mapping. This evidence highlights the utility of rs-fMRI for personalized presurgical planning, particularly in scenarios where awake surgery with DES is not feasible to protect eloquent areas during tumor resection. We have made the updated tool for automated functional network estimation publicly available, facilitating broader utilization of rs-fMRI mapping in various clinical contexts, including presurgical planning, functional reorganization over follow-up periods, and informing future treatments such as radiotherapy.

Effects of computerized cognitive training on functional brain networks in patients with vascular cognitive impairment and no dementia.

Previous neuroimaging studies of vascular cognitive impairment, no dementia (VCIND), have reported functional alterations, but far less is known about the effects of cognitive training on functional connectivity (FC) of intrinsic connectivity networks (ICNs) and how they relate to intervention-related cognitive improvement. This study provides comprehensive research on the changes in intra- and inter-brain functional networks in patients with VCIND who received computerized cognitive training, with a focus on the underlying mechanisms and potential therapeutic strategies. We prospectively collected 60 patients with VCIND who were randomly divided into the training group (N = 30) receiving computerized cognitive training and the control group (N = 30) receiving fixed cognitive training. Functional MRI scans and cognitive assessments were performed at baseline, at the 7-week training, and at the 6-month follow-up. Utilizing templates for ICNs, the study employed a linear mixed model to compare intra- and inter-network FC changes between the two groups. Pearson correlation was applied to calculate the relationship between FC and cognitive function. We found significantly decreased intra-network FC within the default mode network (DMN) following computerized cognitive training at Month 6 (p = 0.034), suggesting a potential loss of functional specialization. Computerized training led to increased functional coupling between the DMN and sensorimotor network (SMN) (p = 0.01) and between the language network (LN) and executive control network (ECN) at Month 6 (p < 0.001), indicating compensatory network adaptations in patients with VCIND. Notably, the intra-LN exhibited enhanced functional specialization after computerized cognitive training (p = 0.049), with significant FC increases among LN regions, which correlated with improvements in neuropsychological measures (p < 0.05), emphasizing the targeted impact of computerized cognitive training on language abilities. This study provides insights into neuroplasticity and adaptive changes resulting from cognitive training in patients with VCIND, with implications for potential therapeutic strategies.

Disrupted Functional Brain Network Architecture in Sufferers with Boxing-Related Repeated Mild Traumatic Brain Injury: A Resting-State EEG Study.

Repetitive mild traumatic brain injury (rmTBI) often occurs in individuals engaged in contact sports, particularly boxing. This study aimed to elucidate the effects of rmTBI on phase-locking value (PLV)-based graph theory and functional network architecture in individuals with boxing-related injuries in five frequency bands by employing resting-state electroencephalography (EEG). Twenty-fore professional boxers and 25 matched healthy controls were recruited to perform a resting-state task, and their noninvasive scalp EEG data were collected simultaneously. Based on the construction of PLV matrices for boxers and controls, phase synchronization and graph-theoretic characteristics were identified in each frequency band. The significance of the calculated functional brain networks between the two populations was analyzed using a network-based statistical (NBS) approach. Compared to controls, boxers exhibited an increasing trend in PLV synchronization and notable differences in the distribution of functional centers, especially in the gamma frequency band. Additionally, attenuated nodal network parameters and decreased small-world measures were observed in the theta, beta, and gamma bands, suggesting that the functional network efficiency and small-world characteristics were significantly weakened in boxers. NBS analysis revealed that boxers exhibited a significant increase in network connectivity strength compared to controls in the theta, beta, and gamma frequency bands. The functional connectivity of the significance subnetworks exhibited an asymmetric distribution between the bilateral hemispheres, indicating that the optimized organization of information integration and segregation for the resting-state networks was imbalanced and disarranged for boxers. This is the first study to investigate the underlying deficits in PLV-based graph-theoretic characteristics and NBS-based functional networks in patients with rmTBI from the perspective of whole-brain resting-state EEG. Joint analyses of distinctive graph-theoretic representations and asymmetrically hyperconnected subnetworks in specific frequency bands may serve as an effective method to assess the underlying deficiencies in resting-state network processing in patients with sports-related rmTBI.

Abnormal functional connectivity of white-matter networks and gray-white matter functional networks in patients with NMOSD

Cognitive impairment (CI) has been reported in 29–70% of patients with neuromyelitis optica spectrum disorder (NMOSD). Abnormal white matter (WM) functional networks that correlate with cognitive functions have not been studied well in patients with NMOSD. The aim of the current study was to investigate functional connectivity (FC), spontaneous activity, and functional covariance connectivity (FCC) abnormalities of WM functional networks in patients with NMOSD and their correlation with cognitive performance. Twenty-four patients with NMOSD and 24 healthy controls (HCs) were included in the study. Participants underwent brain resting-state functional magnetic resonance imaging (fMRI) and the Montreal Cognitive Assessment (MoCA). Eight WM networks and nine gray matter (GM) networks were created. In patients, WM networks, including WM1–4, WM1–8, WM2–6, WM2–7, WM2–8, WM4–8, WM5–8 showed reduced FC (P < 0.05). All WM networks except WM1 showed decreased spontaneous activity (P < 0.05). The major GM networks demonstrated increased/decreased FC (P < 0.05), whereas GM7-WM7, GM8-WM4, GM8-WM6 and GM8-WM8 displayed decreased FC (P < 0.05). The MoCA results showed that two-thirds (16/24) of the patients had CI. FC and FCC in WM networks were correlated negatively with the MoCA scores (P < 0.05). WM functional networks are multi-layered. Abnormal FC of WM functional networks and GM functional networks may be responsible for CI.

Low and high-order topological disruption of functional networks in multiple system atrophy with freezing of gait: A resting-state study

ObjectiveFreezing of gait (FOG), a specific survival-threatening gait impairment, needs to be urgently explored in patients with multiple system atrophy (MSA), which is characterized by rapid progression and death within 10 years of symptom onset. The objective of this study was to explore the topological organisation of both low- and high-order functional networks in patients with MAS and FOG. MethodLow-order functional connectivity (LOFC) and high-order functional connectivity FC (HOFC) networks were calculated and further analysed using the graph theory approach in 24 patients with MSA without FOG, 20 patients with FOG, and 25 healthy controls. The relationship between brain activity and the severity of freezing symptoms was investigated in patients with FOG. ResultsRegarding global topological properties, patients with FOG exhibited alterations in the whole-brain network, dorsal attention network (DAN), frontoparietal network (FPN), and default network (DMN), compared with patients without FOG. At the node level, patients with FOG showed decreased nodal centralities in sensorimotor network (SMN), DAN, ventral attention network (VAN), FPN, limbic regions, hippocampal network and basal ganglia network (BG), and increased nodal centralities in the FPN, DMN, visual network (VIN) and, cerebellar network. The nodal centralities of the right inferior frontal sulcus, left lateral amygdala and left nucleus accumbens (NAC) were negatively correlated with the FOG severity. ConclusionThis study identified a disrupted topology of functional interactions at both low and high levels with extensive alterations in topological properties in MSA patients with FOG, especially those associated with damage to the FPN. These findings offer new insights into the dysfunctional mechanisms of complex networks and suggest potential neuroimaging biomarkers for FOG in patients with MSA.

Variability of large timescale functional networks in patients with disorders of consciousness.

Most brain function assessments for disorders of consciousness (DOC) utilized quantified characteristics, measured only once, ignoring the variation of patients' brain states. The study aims to investigate the brain activities of patients with DOC from a new perspective: variability of a large timescale functional network. Forty-nine patients were enrolled in this study and performed a 1-week behavioral assessment. Subsequently, each patient received electroencephalography (EEG) recordings five times daily at 2-h intervals. Functional connectivity and networks were measured by weighted phase lag index and complex network parameters (characteristic path length, cluster coefficient, and betweenness centrality). The relative coefficient of variation (CV) of network parameters was measured to evaluate functional network variability. Functional networks of patients with vegetative state/unresponsive wakefulness syndrome (VS/UWS) showed significantly higher segregation (characteristic path length) and lower centrality (betweenness centrality) than emerging from the minimal conscious state (EMCS) and minimal conscious state (MCS), as well as lower integration (cluster coefficient) than MCS. The functional networks of VS/UWS patients consistently presented the highest variability in segregation and integration (i.e., highest CV values of characteristic path length and cluster coefficient) on a larger time scale than MCS and EMCS. Moreover, the CV values of characteristic path length and cluster coefficient showed a significant inverse correlation with the Coma Recovery Scale-Revised scores (CRS-R). The CV values of network betweenness centrality, particularly of the cento-parietal region, showed a positive correlation with the CRS-R. The functional networks of VS/UWS patients present the most invariant segregation and integration but divergent centrality on the large time scale networks than MCS and EMCS. The variations observed within large timescale functional networks significantly correlate with the degree of consciousness impairment. This finding augments our understanding of the neurophysiological mechanisms underpinning disorders of consciousness.

Altered whole-brain functional network in patients with frontal low-grade gliomas: a resting-state functional MRI study.

Gliomas are the most common primary brain tumor. Currently, topological alterations of whole-brain functional network caused by gliomas are not fully understood. The work here clarified the topological reorganization of the functional network in patients with unilateral frontal low-grade gliomas (LGGs). A total of 45 patients with left frontal LGGs, 19 with right frontal LGGs, and 25 healthy controls (HCs) were enrolled. All the resting-state functional MRI (rs-fMRI) images of the subjects were preprocessed to construct the functional network matrix, which was used for graph theoretical analysis. A two-sample t-test was conducted to clarify the differences in global and nodal network metrics between patients and HCs. A network-based statistic approach was used to identify the altered specific pairs of regions in which functional connectivity in patients with LGGs. The local efficiency, clustering coefficient, characteristic path length, and normalized characteristic path length of patients with unilateral frontal LGGs were significantly lower than HCs, while there were no significant differences of global efficiency and small-worldness between patients and HCs. Compared with the HCs, betweenness centrality, degree centrality, and nodal efficiency of several brain nodes were changed significantly in patients. Around the tumor and its adjacent areas, the inter- and intra-hemispheric connections were significantly decreased in patients with left frontal LGGs. The patients with unilateral frontal LGGs have altered global and nodal network metrics and decreased inter- and intra-hemispheric connectivity. These topological alterations may be involved in functional impairment and compensation of patients.

Alterations of resting-state functional network connectivity in patients with noise-induced hearing loss: A study based on independent component analysis.

Functional reorganization is a response to auditory deficits or deprivation, and less is known about the overall brain network alterations involving resting-state networks (RSNs) and multiple functional networks in patients with occupational noise-induced hearing loss (NIHL). So this study evaluated resting-state functional network connectivity (FNC) alterations in occupational NIHL using an independent component analysis (ICA). In total, 79 mild NIHL patients (MP), 32 relatively severe NIHL patients (RSP), and 84 age- and education- matched healthy controls (HC) were recruited. All subjects were tested using the Mini-mental State Examination scale, the tinnitus Handicap Inventory scale, the Hamilton Anxiety scale (HAMA) and scanned by T1-3DFSPGR, resting-state functional magnetic resonance imaging sequence in 3.0 T and analysed by the ICA. Seven RSNs were identified, compared with the HC, the MP showed increased FNC within the executive control network (ECN) and enhanced FNC within the default mode network (DMN) and the visual network (VN); compared with the HC, the RSP showed decreased FNC within the ECN and auditory network (AUN), DMN and VN; no significant changes in FNC were found in the MP compared with the RSP. Furthermore, the correlation analysis between the noise exposure time and hearing loss level, HAMA were both negative, and there were no significant correlations between the abnormal RSNs and the hearing level, noise exposure time and HAMA. These findings indicate that different degrees of NIHL involve different alterations in RSNs connectivity and may reveal the neural mechanisms related to emotion-related features and functional abnormalities following long-term NIHL.

Alterations in the hub structure of whole-brain functional networks in patients with drug-naïve schizophrenia: Insights from electroencephalography-based research.

This study aimed to identify atypical hubs in the whole-brain networks of patients with schizophrenia (SZ) and examine the effects of antipsychotic medications, using electroencephalography (EEG) data. We estimated the functional connectivity across all electrodes by applying the phase lag index to the EEG signals of 21 drug-naïve patients with SZ and 31 age-matched healthy controls. Betweenness centrality (BC), a measure of hub status, was calculated for each electrode and frequency band. Data from 14 patients were re-evaluated after initiating treatment with antipsychotic medications. BC values decreased significantly at the Fz site in the beta band, decreased significantly at Pz in the gamma band, and increased significantly at O1 in the gamma band among patients with SZ. These changes persisted after antipsychotic treatment and were unrelated to clinical symptoms. The abnormal hub topology we observed, especially in the high-frequency band, may reflect the pathophysiology of SZ, and this study highlights the utility of BC analysis of EEG data for detecting alterations in the whole-brain networks of patients with SZ.

Effects of electroconvulsive therapy on functional brain networks in patients with schizophrenia

BackgroundSchizophrenia is a kind of intractable brain disorder. Electroconvulsive therapy (ECT) has been used to rapidly improve the clinical symptoms of patients with schizophrenia, but the effect of ECT on topological attributes of brain functional network in patients with schizophrenia has not been clear. The purpose of this study was to investigate the brain functional network mechanism of ECT against schizophrenia.MethodsThirty-one patients with schizophrenia and fifty healthy controls matching age, gender, and years of education were included. All participants underwent general data collection and magnetic resonance imaging scanning before ECT, and clinical symptoms were assessed using the Positive And Negative Syndrome Scale (PANSS). MRI and clinical symptoms were collected again after the first and eighth ECT application. The functional brain network was constructed on the basis of magnetic resonance imaging, and the global and node topological properties were analyzed. Repeated measure variance analysis was used to explore the changes of the topological attribute values and clinical symptom scores before and after ECT, and Bonferroni post hoc analysis was performed. The independent sample t-test was used to compare the differences in the topological attribute values between patients and healthy controls at three time points before and after ECT. Partial correlation analysis was performed for topological attribute values and clinical symptom scores of abnormal brain regions in the patient groups and their changes during ECT. A general linear regression model was used to predict the outcome after the final eighth ECT using the patient's response to the first ECT.Results(1) One ECT can restore the gamma(γ), lamuda(λ), sigma(σ), nodal global efficiency (Ne) of right insular gyrus ventral agranular insula (INS_R_vIa) and nodal local efficiency (NLe) of bilateral fusiform gyrus medioventral area37 (FuG_A37mv). Eight ECT can also restore the NLe of cortex rostral lingual gyrus (MVOcC _R_rLinG). Eight ECT did not improve the Ne of right superior parietal lobule rostral area 7 (SPL_R_A7r) and NLe of left superior frontal gyrus medial area 6 (SFG_L_A6m). (2) Even after only the first use of ECT, total PANSS scores began to decrease (mean ΔPANSSECT1 was 11.7%; Range, 2%-32.8%), decreased significantly after the eighth application (mean ΔPANSSECT8 was 86.0%; Range,72.5% to 97.9%). Five patients met the response criteria after ECT1 (20% reduction in PANSS total score), and all patients met the response criteria after ECT8. (3) Linear regression analysis showed that ΔPANSSECT1 was a significant predictor of ΔPANSSECT8 (F=5.387, P=0.028), and ΔPANSSECT1 explained 15.7% of the variance of ΔPANSSECT8 (R2=0.157).ConclusionsECT was able to normalize γ, λ, σ, Ne of INS_R_vIa, NLe of bilateral FuG_A37mv in SZ patients after the first treatment, and NLe of MVOcC_R_rLinG after the eighth ECT. ECT significantly alleviates psychotic symptoms in patients with SZ, and its efficacy after eight sessions can be predicted by the patient's response to the first session of ECT.

Abnormal large-scale resting-state functional networks in anti-N-methyl-D-aspartate receptor encephalitis.

Patients with anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis often experience severe symptoms. Resting-state functional MRI (rs-fMRI) has revealed widespread impairment of functional networks in patients. However, the changes in information flow remain unclear. This study aims to investigate the intrinsic functional connectivity (FC) both within and between resting-state networks (RSNs), as well as the alterations in effective connectivity (EC) between these networks. Resting-state functional MRI (rs-fMRI) data were collected from 25 patients with anti-NMDAR encephalitis and 30 healthy controls (HCs) matched for age, sex, and educational level. Changes in the intrinsic functional connectivity (FC) within and between RSNs were analyzed using independent component analysis (ICA). The functional interaction between RSNs was identified by granger causality analysis (GCA). Compared to HCs, patients with anti-NMDAR encephalitis exhibited lower performance on the Wisconsin Card Sorting Test (WCST), both in terms of correct numbers and correct categories. Additionally, these patients demonstrated decreased scores on the Montreal Cognitive Assessment (MoCA). Neuroimaging studies revealed abnormal intra-FC within the default mode network (DMN), increased intra-FC within the visual network (VN) and dorsal attention network (DAN), as well as increased inter-FC between VN and the frontoparietal network (FPN). Furthermore, aberrant effective connectivity (EC) was observed among the DMN, DAN, FPN, VN, and somatomotor network (SMN). Patients with anti-NMDAR encephalitis displayed noticeable deficits in both memory and executive function. Notably, these patients exhibited widespread impairments in intra-FC, inter-FC, and EC. These results may help to explain the pathophysiological mechanism of anti-NMDAR encephalitis.

Abnormal Spatial and Temporal Overlap of Time-Varying Brain Functional Networks in Patients with Schizophrenia.

Schizophrenia (SZ) is a complex psychiatric disorder with unclear etiology and pathological features. Neuroscientists are increasingly proposing that schizophrenia is an abnormality in the dynamic organization of brain networks. Previous studies have found that the dynamic brain networks of people with SZ are abnormal in both space and time. However, little is known about the interactions and overlaps between hubs of the brain underlying spatiotemporal dynamics. In this study, we aimed to investigate different patterns of spatial and temporal overlap of hubs between SZ patients and healthy individuals. Specifically, we obtained resting-state functional magnetic resonance imaging data from the public dataset for 43 SZ patients and 49 healthy individuals. We derived a representation of time-varying functional connectivity using the Jackknife Correlation (JC) method. We employed the Betweenness Centrality (BC) method to identify the hubs of the brain's functional connectivity network. We then applied measures of temporal overlap, spatial overlap, and hierarchical clustering to investigate differences in the organization of brain hubs between SZ patients and healthy controls. Our findings suggest significant differences between SZ patients and healthy controls at the whole-brain and subnetwork levels. Furthermore, spatial overlap and hierarchical clustering analysis showed that quasi-periodic patterns were disrupted in SZ patients. Analyses of temporal overlap revealed abnormal pairwise engagement preferences in the hubs of SZ patients. These results provide new insights into the dynamic characteristics of the network organization of the SZ brain.

Functional disruptions of the brain network in low back pain: a graph-theoretical study.

The aim of this study was to investigate alterations in the topological organization of whole-brain functional networks in patients with chronic low back pain (CLBP) and characterize the relationship of these alterations with pain characteristics. Thirty-three CLBP patients and 34 matched healthy controls (HCs) underwent fMRI scans. A graph-theoretical approach was applied to identify brain network changes in patients suffering from chronic low back pain given its nonspecific etiology and complexity. Graph theory-based analysis was used to construct functional connectivity matrices and extract the features of small-world networks of the brain in both groups. Then, the whole-brain functional connectivity differences were characterized by network-based statistics (NBS) analysis, and the relationship between the altered brain features and clinical measures was explored. At the global level, patients with CLBP showed significantly decreased gamma, sigma, global efficiency, and local efficiency and increased lambda and shortest path length compared with HCs. At the regional level, there were deficits in nodal efficiency within the default mode network and salience network. NBS analysis demonstrated that decreased functional connectivity was present in the CLBP patients, mainly in the frontolimbic circuit and temporal regions. Furthermore, aspects of topological dysfunctions in CLBP were correlated with pain severity. This study highlighted the aberrant topological organization of functional brain networks in CLBP, which may shed light on the pathophysiology of CLBP and support the development of pain management approaches.

Effect of High-Frequency rTMS combined with bilateral arm training on brain functional network in patients with chronic stroke: An fNIRS study

ObjectiveNeurological evidence for the combinational intervention coupling rTMS with motor training for stroke rehabilitation remains limited. This study aimed to investigate the effects of rTMS combined with bilateral arm training (BAT) on the brain functional reorganization in patients with chronic stroke via functional near-infrared spectroscopy (fNIRS). MethodsFifteen stroke patients and fifteen age-matched healthy participants were enrolled and underwent single BAT session (s-BAT) and BAT immediately after 5-Hz rTMS over the ipsilesional M1 (rTMS-BAT), measured cerebral haemodynamics by fNIRS. Functional connectivity (FC), the clustering coefficient (Ccoef), and local efficiency (Eloc) were applied to evaluate the functional response to the training paradigms. ResultsThe differences in FC responses to the two training paradigms were more pronounced in stroke patients than in healthy controls. In the resting state, stroke patients exhibited significantly lower FC than controls in both hemispheres. rTMS-BAT induced no significant difference in FC between groups. Compared to the resting state, rTMS-BAT induced significant decreases in Ccoef and Eloc of the contralesional M1 and significant increases in Eloc of the ipsilesional M1 in stroke patients. Additionally, these above two network metrics of the ipsilesional motor area were significantly positively correlated with the motor function of stroke patients. ConclusionsThese results suggest that the rTMS-BAT paradigm had additional effects on task-dependent brain functional reorganization. The engagement of the ipsilesional motor area in the functional network was associated with the motor impairment severity of stroke patients. fNIRS-based assessments may provide information about the neural mechanisms underlying combination interventions for stroke rehabilitation.

Effects of Combined Intervention of rTMS and Neurotransmitter Drugs on the Brain Functional Networks in Patients with Cognitive Impairment.

Alzheimer's disease (AD) causes extensive neural network dysfunction. Memantine and donepezil are commonly used as monotherapy or in combination with non-drug interventions, such as repetitive transcranial magnetic stimulation (rTMS), for its treatment. However, no studies have reported any differences between the effects of combined neurotransmitter and rTMS interventions versus rTMS alone on the brain networks of patients with cognitive impairment. Therefore, it is crucial to explore the advantages of different intervention methods to guide clinical practice. We used resting-state functional magnetic resonance imaging (rs-fMRI) to investigate the impact of neurotransmitter superimposed rTMS and rTMS alone on the brain functional network of patients with cognitive impairment. We divided patients with cognitive impairment who had received rTMS into two groups based on whether they received neurotransmitters: the combined intervention group and the rTMS-alone intervention group. We conducted rs-fMRI scans and comprehensively assessed cognitive function in these patients. To examine the effects of the superimposed interventions, we utilized independent component analysis to evaluate the functional connectivity of brain networks in these patients. Compared to the rTMS-alone intervention group, co-intervention of neurotransmitter drugs and rTMS exhibited potential for cognitive enhancement via the reconstructed inter-network connectivity of the cerebellum and the enhanced intra-network connectivity of the frontal-parietal regions in these patients with cognitive impairment. We hypothesized that the combination of neurotransmitter drugs and rTMS intervention could have greater clinical benefits than rTMS intervention alone, leading to improved cognitive function in patients with cognitive impairment.

Differences in intrinsic functional networks in patients with essential tremor who had good and poor long-term responses after thalamotomy performed using MR-guided ultrasound.

Thalamotomy at the nucleus ventralis intermedius using MR-guided focused ultrasound has been an effective treatment method for essential tremor (ET). However, this is not true for all cases, even for successful ablation. How the brain differs in patients with ET between those with long-term good and poor outcomes is not clear. To analyze the functional connectivity difference between patients in whom thalamotomy was effective and those in whom thalamotomy was ineffective and its prognostic role in ET treatment, the authors evaluated preoperative resting-state functional MRI in thalamotomy-treated patients. Preoperative resting-state functional MRI data in 85 patients with ET, who were experiencing tremor relief at the time of treatment and were followed up for a minimum of 6 months after the procedure, were collected for the study. The authors conducted a graph independent component analysis of the functional connectivity matrices of tremor-related networks. The patients were divided into thalamotomy-effective and thalamotomy-ineffective groups (thalamotomy-effective group, ≥ 50% motor symptom reduction; thalamotomy-ineffective group, < 50% motor symptom reduction at 6 months after treatment) and the authors compared network components between groups. Seventy-two (84.7%) of the 85 patients showed ≥ 50% tremor reduction from baseline at 6 months after thalamotomy. The network analysis shows significant suppression of functional network components with connections between the areas of the cerebellum and the basal ganglia and thalamus, but enhancement of those between the premotor cortex and supplementary motor area in the noneffective group compared to the effective group. The present study demonstrates that patients in the noneffective group have suppressed functional subnetworks in the cerebellum and subcortex regions and have enhanced functional subnetworks among motor-sensory cortical networks compared to the thalamotomy-effective group. Therefore, the authors suggest that the functional connectivity pattern might be a possible predictive factor for outcomes of MR-guided focused ultrasound thalamotomy.

Altered functional hubs and connectivity in type 2 diabetes mellitus with and without mild cognitive impairment.

Cognitive impairment in type 2 diabetes mellitus (T2DM) is associated with functional and structural abnormalities of brain networks, especially the damage to hub nodes in networks. This study explored the abnormal hub nodes of brain functional networks in patients with T2DM under different cognitive states. Sixty-five patients with T2DM and 34 healthy controls (HCs) underwent neuropsychological assessment. Then, degree centrality (DC) analysis and seed-based functional connectivity (FC) analysis were performed to identify the abnormal hub nodes and the FC patterns of these hubs in T2DM patients with mild cognitive impairment (MCI) (DMCI group, N = 31) and without MCI (DMCN group, N = 34). Correlation analyzes examined the relationship between abnormal DC and FC and clinical/cognitive variables. Compared with HCs, both T2DM groups showed decreased DC values in the visual cortex, and the T2DM patients with MCI (DMCI) showed more extensive alterations in the right parahippocampal gyrus (PHG), bilateral posterior cingulate cortex (PCC), and left superior frontal gyrus (SFG) regions than T2DM patients with normal cognitive function. Seed-based FC analysis of PHG and PCC nodes showed that functional disconnection mainly occurred in visual and memory connectivity in patients with DMCI. Multiple abnormal DC values correlated with neuropsychological tests in patients with T2DM. In conclusion, this study found that the DMCI group displayed more extensive alterations in hub nodes and FC in vision and memory-related brain regions, suggesting that visual-related regions dysfunctions and disconnection may be involved in the neuropathology of visuospatial function impairment in patients with DMCI.

Detecting residual brain networks in disorders of consciousness: A resting-state fNIRS study

Functional near infrared spectroscopy (fNIRS) is an emerging non-invasive technique that allows bedside measurement of blood oxygenation level-dependent hemodynamic signals. We aimed to examine the efficacy of resting-state fNIRS in detecting the residual functional networks in patients with disorders of consciousness (DOC). We performed resting-state fNIRS in 23 DOC patients of whom 12 were in minimally conscious state (MCS) and 11 were in unresponsive wakefulness state (UWS). Ten regions of interest (ROIs) in the prefrontal cortex (PFC) were selected: both sides of Brodmann area (BA) 9, BA10, BA44, BA45, and BA46. Graph-theoretical analysis and seed-based correlation analyses were used to investigate the network topology and the strength of pairwise connections between ROIs and channels. MCS and UWS exhibited varying degrees of the loss of topological architecture, and the regional nodal properties of BA10 were significantly different between them (Nodal degree, PLeft BA10 = 0.01, PRight BA10 < 0.01; nodal efficiency, PLeft BA10 = 0.03, PRight BA10 < 0.01). Compared to healthy controls, UWS had impaired functions in both short- and long-distance connectivity, however, MCS had significantly impaired functions only in long-distance connectivity. The functional connectivity of right BA10 (AUC = 0.88) and the connections between left BA46 and right BA10 (AUC = 0.86) had excellent performance in differentiating MCS and UWS. MCS and UWS have different patterns of topological architecture and short- and long-distance connectivity in PFC. Intraconnections within BA10 and interhemispheric connections between BA10 and 46 are excellent resting-state fNIRS classifiers for distinguishing between MCS and UWS.

Altered topological organization of resting-state functional networks in children with infantile spasms.

Covering neuroimaging evidence has demonstrated that epileptic symptoms are associated with the disrupted topological architecture of the brain network. Infantile spasms (IS) as an age-specific epileptic encephalopathy also showed abnormal structural or functional connectivity in specific brain regions or specific networks. However, little is known about the topological alterations of whole-brain functional networks in patients with IS. To fill this gap, we used the graph theoretical analysis to investigate the topological properties (whole-brain small-world property and modular interaction) in 17 patients with IS and 34 age- and gender-matched healthy controls. The functional networks in both groups showed efficient small-world architecture over the sparsity range from 0.05 to 0.4. While patients with IS showed abnormal global properties characterized by significantly decreased normalized clustering coefficient, normalized path length, small-worldness, local efficiency, and significantly increased global efficiency, implying a shift toward a randomized network. Modular analysis revealed decreased intra-modular connectivity within the default mode network (DMN) and fronto-parietal network but increased inter-modular connectivity between the cingulo-opercular network and occipital network. Moreover, the decreased intra-modular connectivity in DMN was significantly negatively correlated with seizure frequency. The inter-modular connectivity between the cingulo-opercular and occipital network also showed a significant correlation with epilepsy frequency. Together, the current study revealed the disrupted topological organization of the whole-brain functional network, which greatly advances our understanding of neuronal architecture in IS and may contribute to predict the prognosis of IS as disease biomarkers.