Altered functional connectivity within and between brain modules in absence epilepsy: a resting-state functional magnetic resonance imaging study

Altered neuromagnetic activity in default mode network in childhood absence epilepsy

Purpose

The electrophysiological characterization of resting state oscillatory functional connectivity within the default mode network (DMN) during interictal periods in childhood absence epilepsy (CAE) remains unclear. Using magnetoencephalographic (MEG) recordings, this study investigated how the connectivity within the DMN was altered in CAE.

Methods

Using a cross-sectional design, we analyzed MEG data from 33 children newly diagnosed with CAE and 26 controls matched for age and sex. The spectral power and functional connectivity of the DMN were estimated using minimum norm estimation combined with the Welch technique and corrected amplitude envelope correlation.

Results

Default mode network showed stronger activation in the delta band during the ictal period, however, the relative spectral power in other bands was significantly lower than that in the interictal period (pcorrected < 0.05 for DMN regions, except bilateral medial frontal cortex, left medial temporal lobe, left posterior cingulate cortex in the theta band, and the bilateral precuneus in the alpha band). It should be noted that the significant power peak in the alpha band was lost compared with the interictal data. Compared with controls, the interictal relative spectral power of DMN regions (except bilateral precuneus) in CAE patients was significantly increased in the delta band (pcorrected < 0.01), whereas the values of all DMN regions in the beta-gamma 2 band were significantly decreased (pcorrected < 0.01). In the higher frequency band (alpha-gamma1), especially in the beta and gamma1 band, the ictal node strength of DMN regions except the left precuneus was significantly higher than that in the interictal periods (pcorrected < 0.01), and the node strength of the right inferior parietal lobe increased most significantly in the beta band (Ictal: 3.8712 vs. Interictal: 0.7503, pcorrected < 0.01). Compared with the controls, the interictal node strength of DMN increased in all frequency bands, especially the right medial frontal cortex in the beta band (Controls: 0.1510 vs. Interictal: 3.527, pcorrected < 0.01). Comparing relative node strength between groups, the right precuneus in CAE children decreased significantly (β: Controls: 0.1009 vs. Interictal: 0.0475; γ 1: Controls:0.1149 vs. Interictal:0.0587, pcorrected < 0.01) such that it was no longer the central hub.

Conclusion

These findings indicated DMN abnormalities in CAE patients, even in interictal periods without interictal epileptic discharges. Abnormal functional connectivity in CAE may reflect abnormal anatomo-functional architectural integration in DMN, as a result of cognitive mental impairment and unconsciousness during absence seizure. Future studies are needed to examine if the altered functional connectivity can be used as a biomarker for treatment responses, cognitive dysfunction, and prognosis in CAE patients.

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.

EEG Oscillatory Networks in Peri-Ictal Period of Absence Epilepsy

Objective

To investigate the dynamical brain network changes before and after an absence seizure episode in absence epilepsy (AE).

Methods

21 AE patients with a current high frequency of seizures and 21 sex- and age-matched health control (HC) who reported no history of neurological or psychiatric disorders and visited the hospital for routine physical examinations were included. Each included subject underwent a 2-h and 19-channel video EEG examination. For AE patients, five epochs of 10-s EEG data in inter-ictal, pre-ictal, and post-ictal states were collected. For the HC group, five 10-s resting-state EEG epochs were extracted. Functional independent components analysis (ICA) was carried out using the LORETA KEY tool.

Results

Compared with the resting-state EEG data of the HC group, the EEG data from AE patients during inter-ictal periods showed decreased alpha oscillations in regions involving the superior frontal gyrus (SFG) (BA11). From inter-ictal to pre-ictal, SFG (BA10) showed maximum decreased delta oscillations. Additionally, from pre-ictal to post-ictal, superior temporal gyrus (STG) (BA 22) presented maximum increased neural activity in the alpha band. Moreover, compared with inter-ictal EEG, post-ictal EEG showed significantly decreased theta activity in SFG (BA8).

Conclusion

The changes in SFG alpha oscillations are the key brain network differences between inter-ictal EEG of AE patients and resting-state EEG of HCs. The brain networks of EEG oscillatory during peri-ictal episodes are mainly involving SFG and STG. Our study suggests that altered EEG brain networks dynamics exist between inter-ictal EEG of AE patients and resting-state EEG of HCs and between pre- and post-ictal EEG in AE patients.

Altered peri-seizure EEG microstate dynamics in patients with absence epilepsy

OBJECTIVE

To investigate whether the parameters of EEG microstates changed before and after an absence seizure episode.

METHODS

AE patients with a current high frequency of seizures were included (n=21). Each included subject underwent a two-hour and 19-channel video EEG examination. Five epochs of 10-second EEG data in interictal, pre-seizure, and post-seizure states were collected from each AE patient. Five 10-second resting-state EEG epochs from sex- and age-matched HCs who reported no history of neurological or psychiatric disorders and visited the hospital for routine physical examinations were collected. Microstate analysis and source localization of microstates were performed using the LORETA KEY tool.

RESULTS

Compared with the resting-state EEGs of HCs, the interictal EEGs of AE patients showed a higher relative transition rate from microstates B to D (p<0.05). From interictal to pre-seizure EEG, the total time ratio of microstate C and the occurrence of microstate B decreased significantly, while the duration of microstate B increased significantly (p<0.05). Compared with pre-seizure EEGs, microstate C in post-seizure EEGs showed a significantly downregulated total time percentage and occurrence (p<0.05). The source localization of each microstate in each condition also varied and showed spatial recovery tends from pre- to post-seizure states.

CONCLUSION

Altered EEG microstate dynamics exist between inter-ictal EEGs of AE patients and resting-state EEGs of HCs and between pre- and post-seizure EEGs in AE patients. The EEG microstates of epileptic patients before and after absence seizures are characterized by a "slowdown" in transitions between microstates. Microstates might be used as an index to evaluate the temporal and spatial recovery process of absence seizures in AE.

Ketamine changes the local resting-state functional properties of anesthetized-monkey brain

OBJECTIVE

Ketamine is a well-known anesthetic. 'Recreational' use of ketamine common induces psychosis-like symptoms and cognitive impairments. The acute and chronic effects of ketamine on relevant brain circuits have been studied, but the effects of single-dose ketamine administration on the local resting-state functional properties of the brain remain unknown. In this study, we aimed to assess the effects of single-dose ketamine administration on the brain local intrinsic properties.

METHODS

We used resting-state functional magnetic resonance imaging (rs-fMRI) to explore the ketamine-induced alterations of brain intrinsic properties. Seven adult rhesus monkeys were imaged with rs-fMRI to examine the fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) in the brain before and after ketamine injection. Paired comparisons were used to detect the significantly altered regions.

RESULTS

Results showed that the fALFF of the prefrontal cortex (p=0.046), caudate nucleus (left side, p=0.018; right side, p=0.025), and putamen (p=0.020) in post-injection stage significantly increased compared with those in pre-injection period. The ReHo of nucleus accumbens (p=0.049), caudate nucleus (p=0.037), and hippocampus (p=0.025) increased after ketamine injection, but that of prefrontal cortex decreased (p<0.05).

CONCLUSIONS

These findings demonstrated that single-dose ketamine administration can change the regional intensity and synchronism of brain activity, thereby providing evidence of ketamine-induced abnormal resting-state functional properties in primates. This evidence may help further elucidate the effects of ketamine on the cerebral resting status.

Altered Effective Connectivity Network in Childhood Absence Epilepsy: A Multi-frequency MEG Study

Using multi-frequency magnetoencephalography (MEG) data, we investigated whether the effective connectivity (EC) network of patients with childhood absence epilepsy (CAE) is altered during the inter-ictal period in comparison with healthy controls. MEG data from 13 untreated CAE patients and 10 healthy controls were recorded. Correlation analysis and Granger causality analysis were used to construct an EC network at the source level in eight frequency bands. Alterations in the spatial pattern and topology of the network in CAE were investigated by comparing the patients with the controls. The network pattern was altered mainly in 1-4 Hz, showing strong connections within the frontal cortex and weak connections in the anterior-posterior pathways. The EC involving the precuneus/posterior cingulate cortex (PC/PCC) significantly decreased in low-frequency bands. In addition, the parameters of graph theory were significantly altered in several low- and high-frequency bands. CAE patients display frequency-specific abnormalities in the network pattern even during the inter-ictal period, and the frontal cortex and PC/PCC might play crucial roles in the pathophysiology of CAE. The EC network of CAE patients was over-connective and random during the inter-ictal period. This study is the first to reveal the frequency-specific alteration in the EC network during the inter-ictal period in CAE patients. Multiple-frequency MEG data are useful in investigating the pathophysiology of CAE, which can serve as new biomarkers of this disorder.

Brain structural connectivity distinguishes patients at risk for cognitive decline after carotid interventions

While brain connectivity analyses have been demonstrated to identify ill patients for a number of diseases, their ability to predict cognitive impairment after brain injury is not well established. Traditional post brain injury models, such as stroke, are limited for this evaluation because pre-injury brain connectivity patterns are infrequently available. Patients with severe carotid stenosis, in contrast, often undergo non-emergent revascularization surgery, allowing the collection of pre and post-operative imaging, may experience brain insult due to perioperative thrombotic/embolic infarcts or hypoperfusion, and can suffer post-operative cognitive decline. We hypothesized that a distributed function such as memory would be more resilient in patients with brains demonstrating higher degrees of modularity. To test this hypothesis, we analyzed preoperative structural connectivity graphs (using T1 and DWI MRI) for 34 patients that underwent carotid intervention, and evaluated differences in graph metrics using the Brain Connectivity Toolbox. We found that patients with lower binary component number, binary community number and weighted community number prior to surgery were at greater risk for developing cognitive decline. These findings highlight the promise of brain connectivity analyses to predict cognitive decline following brain injury and serve as a clinical decision support tool. Hum Brain Mapp 37:2185-2194, 2016. © 2016 Wiley Periodicals, Inc.

Alteration of brain regional homogeneity of monkeys with spinal cord injury: A longitudinal resting-state functional magnetic resonance imaging study

PURPOSE

To investigate the longitudinal brain regional homogeneity (ReHo) changes in nonhuman primate after spinal cord injury (SCI) by resting-state functional magnetic resonance imaging (fMRI).

METHODS

Three adult female rhesus monkeys underwent unilateral thoracic cord injury. A resting-state fMRI examination was performed in the healthy stage and 4, 8, and 12 weeks after the injury. The ReHo value of each voxel in the monkey brain was calculated and compared between pre- and post-SCI monkeys with paired t test. The regions of interest (ROIs) in the significantly changed ReHo regions were set. The correlations between the ReHo change and the time after injury were also determined.

RESULTS

Compared with those in healthy period, the ReHo values of the left premotor cortex and the anterior cingulate cortex (ACC) in post-SCI rhesus monkeys significantly increased in 4-week follow-up examinations. The ReHo values of posterior cingulate cortex, left precuneus, left temporal parietooccipital area, and bilateral superior parietal lobules decreased at 8-week follow-up examinations. In 12-week follow-up examinations, the ReHo values of the left postcentral gyrus, right caudate nucleus, and superior temporal gyrus increased. Correlation analysis showed positive correlations between left ACC and the postoperative time.

CONCLUSION

SCI can change the regional synchronism of brain activity in sensorimotor system and the default mode network. These findings may help us to understand the potential pathophysiological changes in the central nervous system after SCI.

Age-related reorganizational changes in modularity and functional connectivity of human brain networks

The human brain undergoes both morphological and functional modifications across the human lifespan. It is important to understand the aspects of brain reorganization that are critical in normal aging. To address this question, one approach is to investigate age-related topological changes of the brain. In this study, we developed a brain network model using graph theory methods applied to the resting-state functional magnetic resonance imaging data acquired from two groups of normal healthy adults classified by age. We found that brain functional networks demonstrated modular organization in both groups with modularity decreased with aging, suggesting less distinct functional divisions across whole brain networks. Local efficiency was also decreased with aging but not with global efficiency. Besides these brain-wide observations, we also observed consistent alterations of network properties at the regional level in the elderly, particularly in two major functional networks-the default mode network (DMN) and the sensorimotor network. Specifically, we found that measures of regional strength, local and global efficiency of functional connectivity were increased in the sensorimotor network while decreased in the DMN with aging. These results indicate that global reorganization of brain functional networks may reflect overall topological changes with aging and that aging likely alters individual brain networks differently depending on the functional properties. Moreover, these findings highly correspond to the observation of decline in cognitive functions but maintenance of primary information processing in normal healthy aging, implying an underlying compensation mechanism evolving with aging to support higher-level cognitive functioning.

Mechanisms regulating neuronal excitability and seizure development following mTOR pathway hyperactivation

The phosphatidylinositol-3-kinase/phosphatase and tensin homolog (PTEN)-mammalian target of rapamycin (mTOR) pathway regulates a variety of neuronal functions, including cell proliferation, survival, growth, and plasticity. Dysregulation of the pathway is implicated in the development of both genetic and acquired epilepsies. Indeed, several causal mutations have been identified in patients with epilepsy, the most prominent of these being mutations in PTEN and tuberous sclerosis complexes 1 and 2 (TSC1, TSC2). These genes act as negative regulators of mTOR signaling, and mutations lead to hyperactivation of the pathway. Animal models deleting PTEN, TSC1, and TSC2 consistently produce epilepsy phenotypes, demonstrating that increased mTOR signaling can provoke neuronal hyperexcitability. Given the broad range of changes induced by altered mTOR signaling, however, the mechanisms underlying seizure development in these animals remain uncertain. In transgenic mice, cell populations with hyperactive mTOR have many structural abnormalities that support recurrent circuit formation, including somatic and dendritic hypertrophy, aberrant basal dendrites, and enlargement of axon tracts. At the functional level, mTOR hyperactivation is commonly, but not always, associated with enhanced synaptic transmission and plasticity. Moreover, these populations of abnormal neurons can affect the larger network, inducing secondary changes that may explain paradoxical findings reported between cell and network functioning in different models or at different developmental time points. Here, we review the animal literature examining the link between mTOR hyperactivation and epileptogenesis, emphasizing the impact of enhanced mTOR signaling on neuronal form and function.