Altered Effective Connectivity of the Pain Matrix in Herpes Zoster and Postherpetic Neuralgia Patients: Granger Causality Analysis of Resting-State fMRI.

BACKGROUND: Shingles can cause long-term pain and negative emotions, along with changes in brain function. In this study, Granger Causality Analysis (GCA) was used to compare herpes zoster (HZ) and postherpetic neuralgia (PHN) differences in effective connections within the "pain matrix" between patients and healthy controls to further understand patterns of interaction between brain regions and explore the relationship between changes in effective connections and clinical features. METHODS: Resting-state functional magnetic resonance imaging (fMRI) scans were performed on 55 HZ; 55 PHN; and 50 age-, sex- matched healthy controls (HCs). The brain regions associated with the pain matrix are used as the seeds of effective connectivity. GCA was used to analyze effective connections in brain regions that differed significantly between groups. Then the correlation between GCA values and clinical indicators was studied. RESULTS: Compared with HC, GCA values between the thalamus and the amygdala, between the thalamus and the precentral gyrus, from the thalamus to the postcentral gyrus, and from the parahippocampal gyrus to the amygdala, anterior cingulate gyrus were significantly reduced in HZ patients. Compared with HC, GCA values between the insular and the postcentral gyrus, from the insular to the inferior parietal lobe, and from the postcentral gyrus to the amygdala were significantly reduced in PHN patients. Compared with HZ, GCA values between the inferior parietal lobe and the parahippocampal gyrus, between the inferior parietal lobe and the anterior cingulate gyrus, and from the anterior cingulate gyrus to the amygdala were significantly increased in PHN patients. The visual analogue scale (VAS) score of PHN patients was positively correlated with the GCA value from the central posterior lobe to the insula. CONCLUSIONS: PHN and HZ patients showed a broad reduction in effective connections, mainly reflected in abnormal pain pathway regulation, pain perception, negative emotion and memory production, providing new perspectives to understand the neuroimaging mechanisms of shingles.

Effective Connectivity of Default Mode Network Subsystems in Parkinson's Disease with Mild Cognitive Impairment Based on Spectral Dynamic Causal Modeling.

OBJECTIVE: The objective of this study is to compare the differences in effective connectivity within the default mode network (DMN) subsystems between patients with Parkinson's disease with mild cognitive impairment (PD-MCI) and patients with Parkinson's disease with normal cognition (PD-CN). The mechanisms underlying DMN dysfunction in PD-MCI patients and its association with clinical cognitive function in PD-MCI are aimed to be investigated. METHODS: The spectral dynamic causal model (spDCM) was employed to analyze the effective connectivity of functional magnetic resonance imaging (fMRI) data in the resting state for the DMN subsystems, which include the medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC), left and right angular gyrus (LAG, RAG) in 23 PD-MCI and 22 PD-CN patients, respectively. The effective connectivity values of DMN subsystems in the two groups were statistically analyzed using a two-sample t-test. The Spearman correlation analysis was used to test the correlation between the effective connectivity values of the subsystems with significant differences between the two groups and the clinical cognitive function (as measured by Montreal Cognitive Assessment Scale (MoCA) score). RESULTS: Statistical analysis revealed significant differences in the effective connections of MPFC-LAG and LAG-PCC between the two patient groups (MPFC-LAG: t = -2.993, p < 0.05; LAG-PCC: t = 2.174, p < 0.05). CONCLUSIONS: The study findings suggest that abnormal strength and direction of effective connections between DMN subsystems are found in PD-MCI patients.

The effective connection of default mode network changes in patients with type 2 diabetes mellitus / 中国糖尿病杂志

Objective To investigate the influence of type 2 diabetes mellitus(T2DM)on cognitive function and the effective connectivity with in the default mode network(DMN)in the brain.Methods A total of 93 hospitalized patients diagnosed with T2DM were enrolled in this study as T2DM group from The First Affiliated Hospital of Guangzhou University of Chinese Medicine during September 2021 to December 2022.Simultaneously,108 healthy individuals were recruited from the community as normal control(NC)group.The cognitive functions were evaluated in the two groups.A random dynamic causal modeling approach was employed to analyze the effective connectivity within DMN in both groups.Additionally,Pearson correlation analysis was performed to examine the association between differential connectivity,clinical indicators,and cognitive scores in both groups.Results In comparison to the NC group,T2DM individuals exhibited statistically significant reductions in scores in the auditory verbal learning test(AVLT)for immediate recall and the digit symbol substitution test(DSST)(P＜0.05).Additionally,they displayed a notable decrease in effective connectivity from the left lateral parietal cortex(LLPC)to the posterior cingulate cortex(PCC),as well as from the LLPC to the right lateral parietal cortex(RLPC)within the DMN(P＜0.05).Pearson correlation analysis unveiled a negative association between HbA1c levels and the strength of effective connectivity from LLPC to PCC.Conversely,a positive correlation was observed between AVLT(immediate)scores and the strength of effective connectivity from LLPC to PCC and LLPC to RLPC.Additionally,DSST scores displayed a positive correlation with the strength of effective connectivity from LLPC to PCC(P＜0.05).Conclusion Patients with T2DM display compromised effective connectivity from LLPC to PCC and LLPC to RLPC within the DMN network,and this alteration may associated with cognitive impairment.

Frequency-dependent effective connections between local signals and the global brain signal during resting-state.

The psychological and physiological meanings of resting-state global brain signal (GS) and GS topography have been well confirmed. However, the causal relationship between GS and local signals was largely unknown. Based on the Human Connectome Project dataset, we investigated the effective GS topography using the Granger causality (GC) method. In consistent with GS topography, both effective GS topographies from GS to local signals and from local signals to GS showed greater GC values in sensory and motor regions in most frequency bands, suggesting that the unimodal superiority is an intrinsic architecture of GS topography. However, the significant frequency effect for GC values from GS to local signals was primarily located in unimodal regions and dominated at slow 4 frequency band whereas that from local signals to GS was mainly located in transmodal regions and dominated at slow 6 frequency band, consisting with the opinion that the more integrated the function, the lower the frequency. These findings provided valuable insight for the frequency-dependent effective GS topography, improving the understanding of the underlying mechanism of GS topography. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-022-09831-0.

Localization of Epileptogenic Zone Based on Cortico-Cortical Evoked Potential (CCEP): A Feature Extraction and Graph Theory Approach.

OBJECTIVE: Epilepsy is a chronic brain disease, which is prone to relapse and affects individuals of all ages worldwide, particularly the very young and elderly. Up to one-third of these patients are medically intractable and require resection surgery. However, the outcomes of epilepsy surgery rely upon the clear identification of epileptogenic zone (EZ). The combination of cortico-cortical evoked potential (CCEP) and electrocorticography (ECoG) provides an opportunity to observe the connectivity of human brain network and more comprehensive information that may help the clinicians localize the epileptogenic focus more precisely. However, there is no standard analysis method in the clinical application of CCEPs, especially for the quantitative analysis of abnormal connectivity of epileptic networks. The aim of this paper was to present an approach on the batch processing of CCEPs and provide information relating to the localization of EZ for clinical study. METHODS: Eight medically intractable epilepsy patients were included in this study. Each patient was implanted with subdural grid electrodes and electrical stimulations were applied directly to their cortex to induce CCEPs. After signal preprocessing, we constructed three effective brain networks at different spatial scales for each patient, regarding the amplitudes of CCEPs as the connection weights. Graph theory was then applied to analyze the brain network topology of epileptic patients, and the topological metrics of EZ and non-EZ (NEZ) were compared. RESULTS: The effective connectivity network reconstructed from CCEPs was asymmetric, both the number and the amplitudes of effective CCEPs decreased with increasing distance between stimulating and recording sites. Besides, the distribution of CCEP responses was associated with the locations of EZ which tended to have higher degree centrality (DC) and nodal shortest path length (NLP) than NEZ. CONCLUSION: Our results indicated that the brain networks of epileptics were asymmetric and mainly composed of short-distance connections. The DC and NLP were highly consistent to the distribution of the EZ, and these topological parameters have great potential to be readily applied to the clinical localization of the EZ.

Altered effective brain connectivity at early response of antipsychotics in first-episode schizophrenia with auditory hallucinations.

OBJECTIVE: This study aimed to examine the alterations of cortical connectivity in first-episode schizophrenia (FES) with auditory hallucinations at early response of antipsychotics. METHODS: This was a nonexperimental control of medication study. We measured the cortical activity of 20 medicated patients with FES (medicated group), 19 nonmedicated patients with FES (nonmedicated group), and 22 healthy controls using electroencephalogram during eye-open resting state. Source reconstruction analysis was performed to determine the brain regions that showed significant group difference. A dynamic causal modelling (DCM) analysis was used to estimate the effective connectivity between sources. RESULT: Both FES groups expressed increased activity in the right middle frontal gyrus (RMFG) and left/right superior temporal gyrus (L/RSTG) relative to that in the controls (p<0.05), and the nonmedicated group presented even higher activity than the medicated group (p<0.05). The effective connectivity from RMFG to LSTG was weaker in the nonmedicated group relative to that in the medicated group (p<0.01), although patients in the medicated group showed no difference with healthy controls in RMFG to L/RSTG connections. The Bayesian model selection analysis found modulatory lateralization in the nonmedicated group. CONCLUSION: The patients with FES showed frontotemporal hyperactivity and disconnectivity. The effective connections accompanied with modulation were improved when hallucination diminished at early response of routine medication. SIGNIFICANCE: This study provided the first evidence of early drug response-related alterations in effective brain connectivity.