Brainstem atrophy in focal epilepsy destabilizes brainstem-brain interactions: Preliminary findings

Advances in functional and structural imaging of the brainstem: implications for disease

PURPOSE OF REVIEW

The brainstem's complex anatomy and relatively small size means that structural and functional assessment of this structure is done less frequently compared to other brain areas. However, recent years have seen substantial progress in brainstem imaging, enabling more detailed investigations into its structure and function, as well as its role in neuropathology.

RECENT FINDINGS

Advancements in ultrahigh field MRI technology have allowed for unprecedented spatial resolution in brainstem imaging, facilitating the new creation of detailed brainstem-specific atlases. Methodological improvements have significantly enhanced the accuracy of physiological (cardiac and respiratory) noise correction within brainstem imaging studies. These technological and methodological advancements have allowed for in-depth analyses of the brainstem's anatomy, including quantitative assessments and examinations of structural connectivity within both gray and white matter. Furthermore, functional studies, including assessments of activation patterns and functional connectivity, have revealed the brainstem's roles in both specialized functions and broader neural integration. Notably, these investigations have identified alterations in brainstem structure and function associated with various neurological disorders.

SUMMARY

The aforementioned developments have allowed for a greater appreciation of the importance of the brainstem in the wider context of neuroscience and clinical neurology.

Arousal and salience network connectivity alterations in surgical temporal lobe epilepsy

OBJECTIVE

It is poorly understood why patients with mesial temporal lobe epilepsy (TLE) have cognitive deficits and brain network changes that extend beyond the temporal lobe, including altered extratemporal intrinsic connectivity networks (ICNs). However, subcortical arousal structures project broadly to the neocortex, are affected by TLE, and thus may contribute to these widespread network effects. The authors' objective was to examine functional connectivity (FC) patterns between subcortical arousal structures and neocortical ICNs, possible neurocognitive relationships, and FC changes after epilepsy surgery.

METHODS

The authors obtained resting-state functional magnetic resonance imaging (fMRI) in 50 adults with TLE and 50 controls. They compared nondirected FC (correlation) and directed FC (Granger causality laterality index) within the salience network, default mode network, and central executive network, as well as between subcortical arousal structures; these 3 ICNs were also compared between patients and controls. They also used an fMRI-based vigilance index to relate alertness to arousal center FC. Finally, fMRI was repeated in 29 patients > 12 months after temporal lobe resection.

RESULTS

Nondirected FC within the salience (p = 0.042) and default mode (p = 0.0008) networks, but not the central executive network (p = 0.79), was decreased in patients in comparison with controls (t-tests, corrected). Nondirected FC between the salience network and subcortical arousal structures (nucleus basalis of Meynert, thalamic centromedian nucleus, and brainstem pedunculopontine nucleus) was reduced in patients in comparison with controls (p = 0.0028-0.015, t-tests, corrected), and some of these connectivity abnormalities were associated with lower processing speed index, verbal comprehension, and full-scale IQ. Interestingly, directed connectivity measures suggested a loss of top-down influence from the salience network to the arousal nuclei in patients. After resection, certain FC patterns between the arousal nuclei and salience network moved toward control values in the patients, suggesting that some postoperative recovery may be possible. Although an fMRI-based vigilance measure suggested that patients exhibited reduced alertness over time, FC abnormalities between the salience network and arousal structures were not influenced by the alertness levels during the scans.

CONCLUSIONS

FC abnormalities between subcortical arousal structures and ICNs, such as the salience network, may be related to certain neurocognitive deficits in TLE patients. Although TLE patients demonstrated vigilance abnormalities, baseline FC perturbations between the arousal and salience networks are unlikely to be driven solely by alertness level, and some may improve after surgery. Examination of the arousal network and ICN disturbances may improve our understanding of the downstream clinical effects of TLE.

Regional variation in brain tissue texture in patients with tonic-clonic seizures

Patients with epilepsy, who later succumb to sudden unexpected death, show altered brain tissue volumes in selected regions. It is unclear whether the alterations in brain tissue volume represent changes in neurons or glial properties, since volumetric procedures have limited sensitivity to assess the source of volume changes (e.g., neuronal loss or glial cell swelling). We assessed a measure, entropy, which can determine tissue homogeneity by evaluating tissue randomness, and thus, shows tissue integrity; the measure is easily calculated from T1-weighted images. T1-weighted images were collected with a 3.0-Tesla MRI from 53 patients with tonic-clonic (TC) seizures and 53 healthy controls; images were bias-corrected, entropy maps calculated, normalized to a common space, smoothed, and compared between groups (TC patients and controls using ANCOVA; covariates, age and sex; SPM12, family-wise error correction for multiple comparisons, p<0.01). Decreased entropy, indicative of increased tissue homogeneity, appeared in major autonomic (ventromedial prefrontal cortex, hippocampus, dorsal and ventral medulla, deep cerebellar nuclei), motor (sensory and motor cortex), or both motor and autonomic regulatory sites (basal-ganglia, ventral-basal cerebellum), and external surfaces of the pons. The anterior and posterior thalamus and midbrain also showed entropy declines. Only a few isolated regions showed increased entropy. Among the spared autonomic regions was the anterior cingulate and anterior insula; the posterior insula and cingulate were, however, affected. The entropy alterations overlapped areas of tissue changes found earlier with volumetric measures, but were more extensive, and indicate widespread injury to tissue within critical autonomic and breathing regulatory areas, as well as prominent damage to more-rostral sites that exert influences on both breathing and cardiovascular regulation. The entropy measures provide easily-collected supplementary information using only T1-weighted images, showing aspects of tissue integrity other than volume change that are important for assessing function.

A multimodal AI system for out-of-distribution generalization of seizure identification

Artificial intelligence (AI) and health sensory data-fusion hold the potential to automate many laborious and time-consuming processes in hospitals or ambulatory settings, e.g. home monitoring and telehealth. One such unmet challenge is rapid and accurate epileptic seizure annotation. An accurate and automatic approach can provide an alternative way to label seizures in epilepsy or deliver a substitute for inaccurate patient self-reports. Multimodal sensory fusion is believed to provide an avenue to improve the performance of AI systems in seizure identification. We propose a state-of-the-art performing AI system that combines electroencephalogram (EEG) and electrocardiogram (ECG) for seizure identification, tested on clinical data with early evidence demonstrating generalization across hospitals. The model was trained and validated on the publicly available Temple University Hospital (TUH) dataset. To evaluate performance in a clinical setting, we conducted non-patient-specific pseudo-prospective inference tests on three out-of-distribution datasets, including EPILEPSIAE (30 patients) and the Royal Prince Alfred Hospital (RPAH) in Sydney, Australia (31 neurologists-shortlisted patients and 30 randomly selected). Our multimodal approach improves the area under the receiver operating characteristic curve (AUC-ROC) by an average margin of 6.71% and 14.42% for deep learning techniques using EEG-only and ECG-only, respectively. Our model's state-of-the-art performance and robustness to out-of-distribution datasets show the accuracy and efficiency necessary to improve epilepsy diagnoses. To the best of our knowledge, this is the first pseudo-prospective study of an AI system combining EEG and ECG modalities for automatic seizure annotation achieved with fusion of two deep learning networks.

A comparative study of AI systems for epileptic seizure recognition based on EEG or ECG

The majority of studies for automatic epileptic seizure (ictal) detection are based on electroencephalogram (EEG) data, but electrocardiogram (ECG) presents a simpler and more wearable alternative for long-term ambulatory monitoring. To assess the performance of EEG and ECG signals, AI systems offer a promising way forward for developing high performing models in securing both a reasonable sensitivity and specificity. There are crucial needs for these AI systems to be developed with more clinical relevance and inference generalization. In this work, we implement an ECG-specific convolutional neural network (CNN) model with residual layers and an EEG-specific convolutional long short-term memory (ConvLSTM) model. We trained, validated, and tested these models on a publicly accessible Temple University Hospital (TUH) dataset for reproducibility and performed a non-patient-specific inference-only test on patient EEG and ECG data of The Royal Prince Alfred Hospital (RPAH) in Sydney, Australia. We selected 31 adult patients to balance groups with the following seizure types: generalized, frontal, frontotemporal, temporal, parietal, and unspecific focal epilepsy. Our tests on both EEG and ECG of these patients achieve an AUC score of 0.75. Our results show ECG outperforms EEG with an average improvement of 0.21 and 0.11 AUC score in patients with frontal and parietal focal seizures, respectively.Clinical relevance-Prior research has demonstrated the value of using ECG for seizure documentation. It is believed that specific epileptic foci (seizure origin) may involve network inputs to the autonomic nervous system. Our result indicates that ECG could outperform EEG for individuals with specific seizure origin, particularly in the frontal and parietal lobes.

The Underappreciated But Potentially Lethal Role of Brainstem Dysfunction in Epilepsy

Association of Peri-Ictal Brainstem Posturing With Seizure Severity and Breathing Compromise in Patients With Generalized Convulsive Seizures

Vilella L, Lacuey N, Hampson JP, et al. Neurology. 2021;96(3):e352-e365. doi:10.1212/WNL.0000000000011274

Objective:

To analyze the association between peri-ictal brainstem posturing semiologies with postictal generalized electroencephalographic suppression (PGES) and breathing dysfunction in generalized convulsive seizures (GCS).

Methods:

In this prospective, multicenter analysis of GCS, ictal brainstem semiology was classified as (1) decerebration (bilateral symmetric tonic arm extension), (2) decortication (bilateral symmetric tonic arm flexion only), (3) hemi-decerebration (unilateral tonic arm extension with contralateral flexion), and (4) absence of ictal tonic phase. Postictal posturing was also assessed. Respiration was monitored with thoracoabdominal belts, video, and pulse oximetry.

Results:

Two hundred ninety-five seizures (180 patients) were analyzed. Ictal decerebration was observed in 122 (41.4%) of 295, decortication in 47 (15.9%) of 295, and hemi-decerebration in 28 (9.5%) of 295 seizures. Tonic phase was absent in 98 (33.2%) of 295 seizures. Postictal posturing occurred in 18 (6.1%) of 295 seizures. Postictal generalized electroencephalographic suppression risk increased with ictal decerebration (odds ratio [OR]: 14.79, 95% CI: 6.18-35.39, P < .001), decortication (OR: 11.26, 95% CI: 2.96-42.93, P < .001), or hemi-decerebration (OR: 48.56, 95% CI: 6.07-388.78, P < .001). Ictal decerebration was associated with longer PGES (P = .011). Postictal posturing was associated with postconvulsive central apnea (PCCA; P = .004), longer hypoxemia (P < .001), and Spo2 recovery (P = .035).

Conclusions:

Ictal brainstem semiology is associated with increased PGES risk. Ictal decerebration is associated with longer PGES. Postictal posturing is associated with a 6-fold increased risk of PCCA, longer hypoxemia, and Spo2 recovery. Peri-ictal brainstem posturing may be a surrogate biomarker for GCS severity identifiable without in-hospital monitoring.

Classification of evidence:

This study provides Class III evidence that peri-ictal brainstem posturing is associated with the GCS with more prolonged PGES and more severe breathing dysfunction.

Acute and chronic cardiorespiratory consequences of focal intrahippocampal administration of seizure-inducing agents. Implications for SUDEP

The risk factors for SUDEP are undoubtedly heterogenous but the main factor is the frequency of generalized tonic-clonic seizures with apnoea and/or cardiac abnormalities likely precipitating the lethal event. By its very nature modelling SUDEP experimentally is challenging, yet insights into the nature of the lethal event and precipitating factors are vital in order to understand and prevent fatalities. Acute animal models, which induce status epilepticus (SE), can be used to help understand pathophysiological processes during and following seizures, which sometimes lead to death. The most commonly used method to induce seizures and status epilepticus is systemic administration of an ictogenic agent. Microinjection of such agents into restricted regions within the brain induces a more localised epileptic focus and circumvents the risk of direct actions on cardiorespiratory control centres. Both approaches have revealed substantial cardiovascular and respiratory consequences, including death as a result of apnoea, which may be of central origin, obstructive due to laryngospasm or, at least in genetically modified mice, a result of spreading depolarisation to medullary respiratory control centres. SUDEP is by definition a result of epilepsy, which in turn is diagnosed on the basis of two or more unprovoked seizures. The incidence of tonic-clonic seizures is the main risk factor, raising the possibility that repeated seizures cause cumulative pathological and/or pathophysiological changes that contribute to the risk of SUDEP. Chronic experimental models, which induce repeated seizures that in some cases lead to death, do show progressive development of pathophysiological changes in the myocardium, e.g. prolongation of QT the interval of the ECG or, over longer periods, ventricular hypertrophy. However, the currently available evidence indicates that seizure-related deaths are primarily due to apnoeas, but cardiac factors, particularly cumulative cardiac pathophysiologies due to repeated seizures, are potential contributing factors.

Morphological, Structural, and Functional Networks Highlight the Role of the Cortical-Subcortical Circuit in Individuals With Subjective Cognitive Decline

Subjective cognitive decline (SCD) is considered the earliest stage of the clinical manifestations of the continuous progression of Alzheimer’s Disease (AD). Previous studies have suggested that multimodal brain networks play an important role in the early diagnosis and mechanisms underlying SCD. However, most of the previous studies focused on a single modality, and lacked correlation analysis between different modal biomarkers and brain regions. In order to further explore the specific characteristic of the multimodal brain networks in the stage of SCD, 22 individuals with SCD and 20 matched healthy controls (HCs) were recruited in the present study. We constructed the individual morphological, structural and functional brain networks based on 3D-T1 structural magnetic resonance imaging (sMRI), diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rs-fMRI), respectively. A t-test was used to select the connections with significant difference, and a multi-kernel support vector machine (MK-SVM) was applied to combine the selected multimodal connections to distinguish SCD from HCs. Moreover, we further identified the consensus connections of brain networks as the most discriminative features to explore the pathological mechanisms and potential biomarkers associated with SCD. Our results shown that the combination of three modal connections using MK-SVM achieved the best classification performance, with an accuracy of 92.68%, sensitivity of 95.00%, and specificity of 90.48%. Furthermore, the consensus connections and hub nodes based on the morphological, structural, and functional networks identified in our study exhibited abnormal cortical-subcortical connections in individuals with SCD. In addition, the functional networks presented more discriminative connections and hubs in the cortical-subcortical regions, and were found to perform better in distinguishing SCD from HCs. Therefore, our findings highlight the role of the cortical-subcortical circuit in individuals with SCD from the perspective of a multimodal brain network, providing potential biomarkers for the diagnosis and prediction of the preclinical stage of AD.

Cardiorespiratory findings in epilepsy: A recent review on outcomes and pathophysiology

Epilepsy is a debilitating disorder of uncontrollable recurrent seizures that occurs as a result of imbalances in the brain excitatory and inhibitory neuronal signals, that could stem from a range of functional and structural neuronal impairments. Globally, nearly 70 million people are negatively impacted by epilepsy and its comorbidities. One such comorbidity is the effect epilepsy has on the autonomic nervous system (ANS), which plays a role in the control of blood circulation, respiration and gastrointestinal function. These epilepsy-induced impairments in the circulatory and respiratory systems may contribute toward sudden unexpected death in epilepsy (SUDEP). Although, various hypotheses have been proposed regarding the role of epilepsy on ANS, the linking pathological mechanism still remains unclear. Channelopathies and seizure-induced damages in ANS-control brain structures were some of the causal/pathological candidates of cardiorespiratory comorbidities in epilepsy patients, especially in those who were drug resistant. However, emerging preclinical research suggest that neurotransmitter/receptor dysfunction and synaptic changes in the ANS may also contribute to the epilepsy-related autonomic disorders. Thus, pathological mechanisms of cardiorespiratory dysfunction should be elucidated by considering the modifications in anatomy and physiology of the autonomic system caused by seizures. In this regard, we present a comprehensive review of the current literature, both clinical and preclinical animal studies, on the cardiorespiratory findings in epilepsy and elucidate the possible pathological mechanisms of these findings, in hopes to prevent SUDEP especially in patients who are drug resistant.

Role of the Nucleus Basalis as a Key Network Node in Temporal Lobe Epilepsy

OBJECTIVE

To determine whether the nucleus basalis of Meynert (NBM) may be a key network structure of altered functional connectivity in temporal lobe epilepsy (TLE), we examined fMRI with network-based analyses.

METHODS

We acquired resting-state fMRI in 40 adults with TLE and 40 matched healthy control participants. We calculated functional connectivity of NBM and used multiple complementary network-based analyses to explore the importance of NBM in TLE networks without biasing our results by our approach. We compared patients to controls and examined associations of network properties with disease metrics and neurocognitive testing.

RESULTS

We observed marked decreases in connectivity between NBM and the rest of the brain in patients with TLE (0.91 ± 0.88, mean ± SD) vs controls (1.96 ± 1.13, p < 0.001, t test). Larger decreases in connectivity between NBM and fronto-parietal-insular regions were associated with higher frequency of consciousness-impairing seizures (r = -0.41, p = 0.008, Pearson). A core network of altered nodes in TLE included NBM ipsilateral to the epileptogenic side and bilateral limbic structures. Furthermore, normal community affiliation of ipsilateral NBM was lost in patients, and this structure displayed the most altered clustering coefficient of any node examined (3.46 ± 1.17 in controls vs 2.23 ± 0.93 in patients). Abnormal connectivity between NBM and subcortical arousal community was associated with modest neurocognitive deficits. Finally, a logistic regression model incorporating connectivity properties of ipsilateral NBM successfully distinguished patients from control datasets with moderately high accuracy (78%).

CONCLUSIONS

These results suggest that while NBM is rarely studied in epilepsy, it may be one of the most perturbed network nodes in TLE, contributing to widespread neural effects in this disabling disorder.

The gray matter structural connectome and its relationship to alcohol relapse: Reconnecting for recovery

Gray matter (GM) atrophy associated with alcohol use disorders (AUD) affects predominantly the frontal lobes. Less is known how frontal lobe GM loss affects GM loss in other regions and how it influences drinking behavior or relapse after treatment. The profile similarity index (PSI) combined with graph analysis allows to assess how GM loss in one region affects GM loss in regions connected to it, ie, GM connectivity. The PSI was used to describe the pattern of GM connectivity in 21 light drinkers (LDs) and in 54 individuals with AUD (ALC) early in abstinence. Effects of abstinence and relapse were determined in a subgroup of 36 participants after 3 months. Compared with LD, GM losses within the extended brain reward system (eBRS) at 1-month abstinence were similar between abstainers (ABST) and relapsers (REL), but REL had also GM losses outside the eBRS. Lower GM connectivities in ventro-striatal/hypothalamic and dorsolateral prefrontal regions and thalami were present in both ABST and REL. Between-networks connectivity loss of the eBRS in ABST was confined to prefrontal regions. About 3 months later, the GM volume and connectivity losses had resolved in ABST, and insula connectivity was increased compared with LD. GM losses and GM connectivity losses in REL were unchanged. Overall, prolonged abstinence was associated with a normalization of within-eBRS connectivity and a reconnection of eBRS structures with other networks. The re-formation of structural connectivities within and across networks appears critical for cognitive-behavioral functioning related to the capacity to maintain abstinence after outpatient treatment.

Insights into human cognition from intracranial EEG: A review of audition, memory, internal cognition, and causality

By recording neural activity directly from the human brain, researchers gain unprecedented insight into how neurocognitive processes unfold in real time. We first briefly discuss how intracranial electroencephalography (iEEG) recordings, performed for clinical practice, are used to study human cognition with the spatiotemporal and single-trial precision traditionally limited to non-human animal research. We then delineate how studies using iEEG have informed our understanding of issues fundamental to human cognition: auditory prediction, working and episodic memory, and internal cognition. We also discuss the potential of iEEG to infer causality through the manipulation or 'engineering' of neurocognitive processes via spatiotemporally precise electrical stimulation. We close by highlighting limitations of iEEG, potential of burgeoning techniques to further increase spatiotemporal precision, and implications for future research using intracranial approaches to understand, restore, and enhance human cognition.

Increased ACh-Associated Immunoreactivity in Autonomic Centers in PTZ Kindling Model of Epilepsy

Experimental and clinical studies of cardiac pathology associated with epilepsy have demonstrated an impact on the autonomic nervous system (ANS). However, the underlying molecular mechanism has not been fully elucidated. Molecular investigation of the neurotransmitters related receptor and ion channel directing ANS might help in understanding the associated mechanism. In this paper, we investigated the role of acetylcholine (ACh), which demonstrates both sympathetic and parasympathetic roles in targeted expression in terms of the relevant receptor and ion channel. Inwardly rectifying potassium (Kir) channels play a significant role in maintaining the resting membrane potential and controlling cell excitability and are prominently expressed in both the excitable and non-excitable tissues. The immunoreactivity of ACh-activated Kir3.1 channel and muscarinic ACh receptors (M2) in autonomic centers such as the brainstem, vagus nerve (VN) and atria of heart was confirmed by both histological staining and pathological tissue analysis. Significant upregulations of Kir3.1 and M2 receptors were observed in pentylenetetrazol (PTZ)-kindled epileptic rats for all related tissues investigated, whereas no pathological difference was observed. These findings provide proof-of-concept that changes in ACh-associated immunoreactivity might be linked to the ANS dysfunctions associated with epilepsy.

Somatosensory evoked fields predict response to vagus nerve stimulation

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There is a need to preoperatively identify children who will respond to VNS.

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There is similarity between the afferent vagus and median nerve projections to S1.

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Median nerve somatosensory evoked fields identify those who will respond to VNS.

There is an unmet need to develop robust predictive algorithms to preoperatively identify pediatric epilepsy patients who will respond to vagus nerve stimulation (VNS). Given the similarity in the neural circuitry between vagus and median nerve afferent projections to the primary somatosensory cortex, the current study hypothesized that median nerve somatosensory evoked field(s) (SEFs) could be used to predict seizure response to VNS. Retrospective data from forty-eight pediatric patients who underwent VNS at two different institutions were used in this study. Thirty-six patients (“Discovery Cohort”) underwent preoperative electrical median nerve stimulation during magnetoencephalography (MEG) recordings and 12 patients (“Validation Cohort”) underwent preoperative pneumatic stimulation during MEG. SEFs and their spatial deviation, waveform amplitude and latency, and event-related connectivity were calculated for all patients. A support vector machine (SVM) classifier was trained on the Discovery Cohort to differentiate responders from non-responders based on these input features and tested on the Validation Cohort by comparing the model-predicted response to VNS to the known response. We found that responders to VNS had significantly more widespread SEF localization and greater functional connectivity within limbic and sensorimotor networks in response to median nerve stimulation. No difference in SEF amplitude or latencies was observed between the two cohorts. The SVM classifier demonstrated 88.9% accuracy (0.93 area under the receiver operator characteristics curve) on cross-validation, which decreased to 67% in the Validation cohort. By leveraging overlapping neural circuitry, we found that median nerve SEF characteristics and functional connectivity could identify responders to VNS.

Impaired vigilance networks in temporal lobe epilepsy: Mechanisms and clinical implications

Mesial temporal lobe epilepsy (mTLE) is a neurological disorder in which patients suffer from frequent consciousness-impairing seizures, broad neurocognitive deficits, and diminished quality of life. Although seizures in mTLE originate focally in the hippocampus or amygdala, mTLE patients demonstrate cognitive deficits that extend beyond temporal lobe function-such as decline in executive function, cognitive processing speed, and attention-as well as diffuse decreases in neocortical metabolism and functional connectivity. Given prior observations that mTLE patients exhibit impairments in vigilance, and that seizures may disrupt the activity and long-range connectivity of subcortical brain structures involved in vigilance regulation, we propose that subcortical activating networks underlying vigilance play a critical role in mediating the widespread neural and cognitive effects of focal mTLE. Here, we review evidence for impaired vigilance in mTLE, examine clinical implications and potential network underpinnings, and suggest neuroimaging strategies for determining the relationship between vigilance, brain connectivity, and neurocognition in patients and healthy controls.

SUDEP: The Worst in Epilepsy and the Hardest to Image

Altered Brain Connectivity in Sudden Unexpected Death in Epilepsy (SUDEP) Revealed Using Resting-State fMRI

Allen LA, Harper RM, Guye M, et al. Neuroimage Clin. 2019;24:102060.

The circumstances surrounding sudden unexpected death in epilepsy (SUDEP) suggest autonomic or respiratory collapse, implying central failure of regulation or recovery. Characterization of the communication among brain areas mediating such processes may shed light on mechanisms and noninvasively indicate risk. We used rs-fMRI to examine network properties among brain structures in people with epilepsy who suffered SUDEP (n = 8) over an 8-year follow-up period, compared with matched high- and low-risk subjects (n = 16/group) who did not suffer SUDEP during that period and a group of healthy controls (n = 16). Network analysis was employed to explore connectivity within a “regulatory subnetwork” of brain regions involved in autonomic and respiratory regulation and over the whole brain. Modularity, the extent of network organization into separate modules, was significantly reduced in the regulatory subnetwork, and the whole-brain, in SUDEP and high-risk groups. Increased participation, a local measure of intermodular belonging, was evident in SUDEP and high-risk groups, particularly among thalamic structures. The medial prefrontal thalamus was increased in SUDEP compared with all other control groups, including high-risk group. Patterns of hub topology were similar in SUDEP and high-risk groups but were more extensive in low-risk patients who displayed greater hub prevalence and a radical reorganization of hubs in the subnetwork. Sudden unexpected death in epilepsy is associated with reduced functional organization among cortical and subcortical brain regions mediating autonomic and respiratory regulation. Living high-risk subjects demonstrated similar patterns, suggesting such network measures may provide prospective risk-indicating value, though a crucial difference between SUDEP and high-risk groups was altered connectivity of the medial thalamus in SUDEP, which was also elevated compared with all subgroups. Disturbed thalamic connectivity may reflect a potential noninvasive marker of elevated SUDEP risk.