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The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx, project 3) is a prospective multicenter clinical observational study to identify early biomarkers of epileptogenesis after moderate-to-severe traumatic brain injury (TBI). We used a seed-based approach applied to acute (i.e., ≤14 days) fMRI imaging data, directly testing the hypothesis that the presence of seizures up to two years following brain trauma is associated with functional changes within hippocampi and thalami-cortical networks. Additionally, we hypothesized that the network connectivity involving thalami and hippocampi circuits underlying early and late-onset seizures would differ. Approximately 30% of the initial dataset was deemed unusable due to MRI issues. Approximately 50% of the enrolled sample was lost to a 2-year follow-up. After preprocessing the fMRI data, approximately 40% of the follow-up sample had to be excluded from the analysis due to excessive in-scanner movements, as assessed by state-of-the-art quality control protocols. Only 37 patients provided data that was suitable for the seed-based analysis. Despite these challenges, the remaining, high-quality data returned noteworthy findings. We identified specific hippocampi and thalami biomarkers associated with both early and late seizures following TBI (p

Background: The amygdala is highly implicated in an array of psychiatric disorders but is not accessible using currently available noninvasive neuromodulatory techniques. Low-intensity transcranial focused ultrasound (TFUS) is a neuromodulatory technique that has the capability of reaching subcortical regions noninvasively. Methods: We studied healthy older adult participants (N = 21, ages 48–79 years) who received TFUS targeting the right amygdala and left entorhinal cortex (active control region) using a 2-visit within-participant crossover design. Before and after TFUS, behavioral measures were collected via the State-Trait Anxiety Inventory and an emotional reactivity and regulation task utilizing neutral and negatively valenced images from the International Affective Picture System. Heart rate and self-reported emotional valence and arousal were measured during the emotional reactivity and regulation task to investigate subjective and physiological responses to the task. Results: Significant increases in both self-reported arousal in response to negative images and heart rate during emotional reactivity and regulation task intertrial intervals were observed when TFUS targeted the amygdala; these changes were not evident when the entorhinal cortex was targeted. No significant changes were found for state anxiety, self-reported valence to the negative images, cardiac response to the negative images, or emotion regulation. Conclusions: The results of this study provide preliminary evidence that a single session of TFUS targeting the amygdala may alter psychophysiological and subjective emotional responses, indicating some potential for future neuropsychiatric applications. However, more work on TFUS parameters and targeting optimization is necessary to determine how to elicit changes in a more clinically advantageous way.

Resting state functional magnetic resonance imaging (rsfMRI) provides researchers and clinicians with a powerful tool to examine functional connectivity across large-scale brain networks, with ever-increasing applications to the study of neurological disorders, such as traumatic brain injury (TBI). While rsfMRI holds unparalleled promise in systems neurosciences, its acquisition and analytical methodology across research groups is variable, resulting in a literature that is challenging to integrate and interpret. The focus of this narrative review is to address the primary methodological issues including investigator decision points in the application of rsfMRI to study the consequences of TBI. As part of the ENIGMA Brain Injury working group, we have collaborated to identify a minimum set of recommendations that are designed to produce results that are reliable, harmonizable, and reproducible for the TBI imaging research community. Part one of this review provides the results of a literature search of current rsfMRI studies of TBI, highlighting key design considerations and data processing pipelines. Part two outlines seven data acquisition, processing, and analysis recommendations with the goal of maximizing study reliability and between-site comparability, while preserving investigator autonomy. Part three summarizes new directions and opportunities for future rsfMRI studies in TBI patients. The goal is to galvanize the TBI community to gain consensus for a set of rigorous and reproducible methods, and to increase analytical transparency and data sharing to address the reproducibility crisis in the field.

EEG measurements in children with Angelman or duplication 15q11.2-13.1 syndrome reveal a dissociation between consciousness and sleep-like spectral content, with complexity-based measures superseding other markers of consciousness.

BackgroundLow intensity, transcranial focused ultrasound (tFUS) is a re-emerging brain stimulation technique with the unique capability of reaching deep brain structures non-invasively.Objective/HypothesisWe sought to demonstrate that tFUS can selectively and accurately target and modulate deep brain structures in humans important for emotional functioning as well as learning and memory. We hypothesized that tFUS would result in significant longitudinal changes in perfusion in the targeted brain region as well as selective modulation of BOLD activity and BOLD-based functional connectivity of the target region.MethodsIn this study, we collected MRI before, simultaneously during, and after tFUS of two deep brain structures on different days in sixteen healthy adults each serving as their own control. Using longitudinal arterial spin labeling (ASL) MRI and simultaneous blood oxygen level dependent (BOLD) functional MRI, we found changes in cerebral perfusion, regional brain activity and functional connectivity specific to the targeted regions of the amygdala and entorhinal cortex (ErC).ResultstFUS selectively increased perfusion in the targeted brain region and not in the contralateral homolog or either bilateral control region. Additionally, tFUS directly affected BOLD activity in a target specific fashion without engaging auditory cortex in any analysis. Finally, tFUS resulted in selective modulation of the targeted functional network connectivity.ConclusionWe demonstrate that tFUS can selectively modulate perfusion, neural activity and connectivity in deep brain structures and connected networks. Lack of auditory cortex findings suggests that the mechanism of tFUS action is not due to auditory or acoustic startle response but rather a direct neuromodulatory process. Our findings suggest that tFUS has the potential for future application as a novel therapy in a wide range of neurological and psychiatric disorders associated with subcortical pathology.

Over the last 30 years, there has been a growing trend in clinical trials towards assessing novel interventions not only against the benchmark of statistical significance, but also with respect to whether they lead to clinically meaningful changes for patients. In the context of Disorders of Consciousness (DOC), despite a growing landscape of experimental interventions, there is no agreed standard as to what counts as a minimal clinically important difference (MCID). In part, this issue springs from the fact that, by definition, DOC patients are either unresponsive (i.e., in a Vegetative State; VS) or non-communicative (i.e., in a Minimally Conscious State; MCS), which renders it impossible to assess any subjective perception of benefit, one of the two core aspects of MCIDs. Here, we develop a novel approach that leverages published, international diagnostic guidelines to establish a probability-based minimal clinically important difference (pMCID), and we apply it to the most validated and frequently used scale in DOC: the Coma Recovery Scale–Revised (CRS-R). This novel method is objective (i.e., based on published criteria for patient diagnosis) and easy to recalculate as the field refines its agreed-upon criteria for diagnosis. We believe this new approach can help clinicians determine whether observed changes in patients’ behavior are clinically important, even when patients cannot communicate their experiences, and can align the landscape of clinical trials in DOC with the practices in other medical fields.

Objective: Transcranial Focused Ultrasound (tFUS) is a promising new potential neuromodulation tool. However, the safety of tFUS neuromodulation has not yet been assessed adequately. Patients with refractory temporal lobe epilepsy electing to undergo an anterior temporal lobe resection present a unique opportunity to evaluate the safety and efficacy of tFUS neuromodulation. Histological changes in tissue after tFUS can be examined after surgical resection, while further potential safety concerns can be assessed using neuropsychological testing. Methods: Neuropsychological functions were assessed in eight patients before and after focused ultrasound sonication of the temporal lobe at intensities up to 5760 mW/cm2. Using the BrainSonix Pulsar 1002, tFUS was delivered under MR guidance, using the Siemens Magnetom 3T Prisma scanner. Neuropsychological changes were assessed using various batteries. Histological changes were assessed using hematoxylin and eosin staining, among others. Results: With respect to safety, the histological analysis did not reveal any detectable damage to the tissue, except for one subject for whom the histology findings were inconclusive. In addition, neuropsychological testing did not show any statistically significant changes in any test, except for a slight decrease in performance on one of the tests after tFUS. Significance: This study supports the hypothesis that low-intensity Transcranial Focused Ultrasound (tFUS) used for neuromodulation of brain circuits at intensities up to 5760 mW/cm2 may be safe for use in human research. However, due to methodological limitations in this study and inconclusive findings, more work is warranted to establish the safety. Future directions include greater number of sonications as well as longer exposure at higher intensity levels to further assess the safety of tFUS for modulation of neuronal circuits.

A dominant framework for understanding loss and recovery of consciousness in the context of severe brain injury, the mesocircuit hypothesis, focuses on the role of cortico-subcortical recurrent interactions, with a strong emphasis on excitatory thalamofugal projections. According to this view, excess inhibition from the internal globus pallidus (GPi) on central thalamic nuclei is key to understanding prolonged disorders of consciousness (DOC) and their characteristic, brain-wide metabolic depression. Recent work in healthy volunteers and patients, however, suggests a previously unappreciated role for the external globus pallidus (GPe) in maintaining a state of consciousness. This view is consistent with empirical findings demonstrating the existence of “direct” (i.e., not mediated by GPi/substantia nigra pars reticulata) GPe connections with cortex and thalamus in animal models, as well as their involvement in modulating arousal and sleep, and with theoretical work underscoring the role of GABA dysfunction in prolonged DOC. Leveraging 50 healthy subjects' high angular resolution diffusion imaging (HARDI) dataset from the Human Connectome Project, which provides a more accurate representation of intravoxel water diffusion than conventional diffusion tensor imaging approaches, we ran probabilistic tractography using extensive a priori exclusion criteria to limit the influence of indirect connections in order to better characterize “direct” pallidal connections. We report the first in vivo evidence of highly probable “direct” GPe connections with prefrontal cortex (PFC) and central thalamic nuclei. Conversely, we find direct connections between the GPi and PFC to be sparse (i.e., less likely indicative of true “direct” connectivity) and restricted to the posterior border of PFC, thus reflecting an extension from the cortical motor zones (i.e., motor association areas). Consistent with GPi's preferential connections with sensorimotor cortices, the GPi appears to predominantly connect with the sensorimotor subregions of the thalamus. These findings are validated against existing animal tracer studies. These findings suggest that contemporary mechanistic models of loss and recovery of consciousness following brain injury must be updated to include the GPe and reflect the actual patterns of GPe and GPi connectivity within large-scale cortico-thalamo-cortical circuits.

Low intensity focused ultrasound (LIFU) has been gaining traction as a non-invasive neuromodulation technology due to its superior spatial specificity relative to transcranial electrical/magnetic stimulation. Despite a growing literature of LIFU-induced behavioral modifications, the mechanisms of action supporting LIFU's parameter-dependent excitatory and suppressive effects are not fully understood. This review provides a comprehensive introduction to the underlying mechanics of both acoustic energy and neuronal membranes, defining the primary variables for a subsequent review of the field's proposed mechanisms supporting LIFU's neuromodulatory effects. An exhaustive review of the empirical literature was also conducted and studies were grouped based on the sonication parameters used and behavioral effects observed, with the goal of linking empirical findings to the proposed theoretical mechanisms and evaluating which model best fits the existing data. A neuronal intramembrane cavitation excitation model, which accounts for differential effects as a function of cell-type, emerged as a possible explanation for the range of excitatory effects found in the literature. The suppressive and other findings need additional theoretical mechanisms and these theoretical mechanisms need to have established relationships to sonication parameters.

Abstract Deep brain nuclei are integral components of large-scale circuits mediating important cognitive and sensorimotor functions. However, because they fall outside the domain of conventional non-invasive neuromodulatory techniques, their study has been primarily based on neuropsychological models, limiting the ability to fully characterize their role and to develop interventions in cases where they are damaged. To address this gap, we used the emerging technology of non-invasive low-intensity focused ultrasound (LIFU) to directly modulate left lateralized basal ganglia structures in healthy volunteers. During sonication, we observed local and distal decreases in blood oxygenation level dependent (BOLD) signal in the targeted left globus pallidus (GP) and in large-scale cortical networks. We also observed a generalized decrease in relative perfusion throughout the cerebrum following sonication. These results show, for the first time using functional MRI data, the ability to modulate deep-brain nuclei using LIFU while measuring its local and global consequences, opening the door for future applications of subcortical LIFU.

In the decade since its debut, the Mesocircuit Hypothesis (MH) has provided researchers a scaffolding for interpreting their findings by associating subcortical-cortical dysfunction with the loss and recovery of consciousness following severe brain injury. Here, we leverage new findings from human and rodent lesions, as well as chemo/optogenetic, tractography, and stimulation studies to propose the external segment of the globus pallidus (GPe) as an additional node in the MH, in hopes of increasing its explanatory power. Specifically, we discuss the anatomical and molecular mechanisms involving the GPe in sleep-wake control and propose a plausible mechanistic model explaining how the GPe can modulate cortical activity through its direct connections with the prefrontal cortex and thalamic reticular nucleus to initiate and maintain sleep. The inclusion of the GPe in the arousal circuitry has implications for understanding a range of phenomena, such as the effects of the adenosine (A2A) and dopamine (D2) receptors on sleep-wake cycles, the paradoxical effects of zolpidem in disorders of consciousness, and sleep disturbances in conditions such as Parkinson’s Disease.

Background: The complexity of neurophysiological brain responses to direct cortical stimulation, referred to as the perturbational complexity index (PCI), has been shown able to discriminate between consciousness and unconsciousness in patients surviving severe brain injury as well as several other conditions (e.g., wake, dreamless sleep, sleep and ketamine dreaming, anesthesia). Objective: This study asks whether, in patients with a disorder of consciousness (DOC), the complexity of the neurophysiological response to cortical stimulation is preferentially associated with atrophy within specific brain structures. Methods: We perform a retrospective analysis of 40 DOC patients and correlate their maximal PCI to MR-based measurements of cortical thinning and subcortical atrophy. Results: PCI was systematically and inversely associated with the degree of local atrophy within the globus pallidus, a region previously linked to electrocortical and behavioral arousal. Conversely, we fail to detect any association between variance in cortical ribbon thickness and PCI. Conclusion: These findings corroborate the previously reported association between pallidal atrophy and low behavioral arousal and suggest that this region’s role in maintaining the overall balance of excitation and inhibition may critically affect the emergence of complex cortical interactions in chronic disorders of consciousness. This finding thus also suggests a target for potential neuromodulatory intervention in DOC patients.

While electroencephalogram (EEG) burst-suppression is often induced therapeutically using sedatives in the intensive care unit (ICU), there is hitherto no evidence with respect to its association to outcome in moderate-to-severe neurological patients. We examined the relationship between sedation-induced burst-suppression (SIBS) and outcome at hospital discharge and at 6-month follow up in patients surviving moderate-to-severe traumatic brain injury (TBI). For each of 32 patients recovering from coma after moderate-to-severe TBI, we measured the EEG burst suppression ratio (BSR) during periods of low responsiveness as assessed with the Glasgow Coma Scale (GCS). The maximum BSR was then used to predict the Glasgow Outcome Scale extended (GOSe) at discharge and at 6 months post-injury. A multi-model inference approach was used to assess the combination of predictors that best fit the outcome data. We found that BSR was positively associated with outcomes at 6 months (P = 0.022) but did not predict outcomes at discharge. A mediation analysis found no evidence that BSR mediates the effects of barbiturates or propofol on outcomes. Our results provide initial observational evidence that burst suppression may be neuroprotective in acute patients with TBI etiologies. SIBS may thus be useful in the ICU as a prognostic biomarker.

What is the relationship between language and complex thought? In the context of deductive reasoning there are two main views. Under the first, which we label here the language-centric view, language is central to the syntax-like combinatorial operations of complex reasoning. Under the second, which we label here the language-independent view, these operations are dissociable from the mechanisms of natural language. We applied continuous theta burst stimulation (cTBS), a form of noninvasive neuromodulation, to healthy adult participants to transiently inhibit a subregion of Broca’s area (left BA44) associated in prior work with parsing the syntactic relations of natural language. We similarly inhibited a subregion of dorsomedial frontal cortex (left medial BA8) which has been associated with core features of logical reasoning. There was a significant interaction between task and stimulation site. Post hoc tests revealed that performance on a linguistic reasoning task, but not deductive reasoning task, was significantly impaired after inhibition of left BA44, and performance on a deductive reasoning task, but not linguistic reasoning task, was decreased after inhibition of left medial BA8 (however not significantly). Subsequent linear contrasts supported this pattern. These novel results suggest that deductive reasoning may be dissociable from linguistic processes in the adult human brain, consistent with the language-independent view.

Prior research has shown that during development, there is increased segregation between, and increased integration within, prototypical resting-state functional brain networks. Functional networks are typically defined by static functional connectivity over extended periods of rest. However, little is known about how time-varying properties of functional networks change with age. Likewise, a comparison of standard approaches to functional connectivity may provide a nuanced view of how network integration and segregation are reflected across the lifespan. Therefore, this exploratory study evaluated common approaches to static and dynamic functional network connectivity in a publicly available dataset of subjects ranging from 8 to 75 years of age. Analyses evaluated relationships between age and static resting-state functional connectivity, variability (standard deviation) of connectivity, and mean dwell time of functional network states defined by recurring patterns of whole-brain connectivity. Results showed that older age was associated with decreased static connectivity between nodes of different canonical networks, particularly between the visual system and nodes in other networks. Age was not significantly related to variability of connectivity. Mean dwell time of a network state reflecting high connectivity between visual regions decreased with age, but older age was also associated with increased mean dwell time of a network state reflecting high connectivity within and between canonical sensorimotor and visual networks. Results support a model of increased network segregation over the lifespan and also highlight potential pathways of top-down regulation among networks.

Traumatic brain injury (TBI) may cause secondary debilitating problems, such as post-traumatic epilepsy (PTE), which occurs with unprovoked recurrent seizures, months or even years after TBI. Currently, the Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) has been enrolling moderate-severe TBI patients with the goal to identify biomarkers of epileptogenesis that may help to prevent seizure occurrence and better understand the mechanism underlying PTE. In this work, we used a novel complex network approach based on segmenting T1-weighted Magnetic Resonance Imaging (MRI) scans in patches of the same dimension (network nodes) and measured pairwise patch similarities using Pearson's correlation (network connections). This network model allowed us to obtain a series of single and multiplex network metrics to comprehensively analyze the different interactions between brain components and capture structural MRI alterations related to seizure development. We used these complex network features to train a Random Forest (RF) classifier and predict, with an accuracy of 70 and a 95% confidence interval of [67, 73%], which subjects from EpiBioS4Rx have had at least one seizure after a TBI. This complex network approach also allowed the identification of the most informative scales and brain areas for the discrimination between the two clinical groups: seizure-free and seizure-affected subjects, demonstrating to be a promising pilot study which, in the future, may serve to identify and validate biomarkers of PTE.

The promotion of recovery in patients who have entered a disorder of consciousness (DOC; e.g., coma or vegetative states) following severe brain injury remains an enduring medical challenge despite an ever-growing scientific understanding of these conditions. Indeed, recent work has consistently implicated altered cortical modulation by deep brain structures (e.g., the thalamus and the basal ganglia) following brain damage in the arising of, and recovery from, DOCs. The (re)emergence of low-intensity focused ultrasound (LIFU) neuromodulation may provide a means to selectively modulate the activity of deep brain structures noninvasively for the study and treatment of DOCs. This technique is unique in its combination of relatively high spatial precision and noninvasive implementation. Given the consistent implication of the thalamus in DOCs and prior results inducing behavioral recovery through invasive thalamic stimulation, here we applied ultrasound to the central thalamus in 11 acute DOC patients, measured behavioral responsiveness before and after sonication, and applied functional MRI during sonication. With respect to behavioral responsiveness, we observed significant recovery in the week following thalamic LIFU compared with baseline. With respect to functional imaging, we found decreased BOLD signals in the frontal cortex and basal ganglia during LIFU compared with baseline. In addition, we also found a relationship between altered connectivity of the sonicated thalamus and the degree of recovery observed post-LIFU.

This article summarizes the field of focused ultrasound for use in neuromodulation and discusses different ways of targeting, delivering, and validating focused ultrasound. A discussion is focused on parameter space and different ongoing theories of ultrasonic neuromodulation. Current and future applications of the technique are discussed.

Over the last 15 years, network analysis approaches based on MR data have allowed a renewed understanding of the relationship between brain function architecture and consciousness. Application of this approach to Disorders of Consciousness (DOC) highlights the relationship between specific aspects of network topology and levels of consciousness. Nonetheless, such applications do not acknowledge that DOC patients present with a dramatic level of heterogeneity in structural connectivity (SC) across groups (e.g., etiology, diagnostic categories) and within individual patients (e.g., over time), which possibly affects the level and quality of functional connectivity (FC) patterns that can be expressed. In addition, it is rarely acknowledged that the most frequently employed outcome metrics in the study of brain connectivity (e.g., degree distribution, inter- or intra-resting state network connectivity, and clustering coefficient) are interrelated and cannot be assumed to be independent of each other. We present empirical data showing that, when the two points above are not taken into consideration with an appropriate analytic model, it can lead to a misinterpretation of the role of each outcome metric in the graph's structure and thus misinterpretation of FC results. We show that failing to account for either SC or the inter-relation between outcome measures can lead to inflated false positives (FP) and/or false negatives (FN) in inter- or intra-resting state network connectivity results (defined, respectively, as a positive or negative result in network connectivity that is present when not accounting for SC and/or outcome measure inter-relation, but becomes not significant when accounting for all variables). Overall, we find that unconscious patients have lower rates of FP and FN for within cortical connectivity, lower rates of FN for cortico-subcortical connectivity, and lower rates of FP for within subcortical connectivity. These lower rates in unconscious patients may reflect differences in their triadic closure and SC metrics, which bias the interpretations of the inter- or intra-resting state network connectivity if the SC metrics and triadic closure are not modeled. We suggest that future studies of functional connectivity in DOC patients (i) incorporate where possible SC metrics and (ii) properly account for the intercorrelated nature of outcome variables.

Cerebral acidosis is a consequence of secondary injury mechanisms following traumatic brain injury (TBI), including excitotoxicity and ischemia, with potentially significant clinical implications. However, there remains an unmet clinical need for technology for non-invasive, high resolution pH imaging of human TBI for studying metabolic changes following injury. The current study examined 17 patients with TBI and 20 healthy controls using amine chemical exchange saturation transfer echoplanar imaging (CEST EPI), a novel pH-weighted molecular MR imaging technique, on a clinical 3T MR scanner. Results showed significantly elevated pH-weighted image contrast (MTRasym at 3 ppm) in areas of T2 hyperintensity or edema (P

Objectives: Considering sensory stimulation programs (SSP) as a treatment for disorders of consciousness is still debated today. Previous studies investigating its efficacy were affected by various biases among which small sample size and spontaneous recovery. In this study, treatment-related changes were assessed using time-series design in patients with disorders of consciousness (i.e., vegetative state—VS and minimally conscious state—MCS).Methods: A withdrawal design (ABAB) was used. During B phases, patients underwent a SSP (3 days a week, including auditory, visual, tactile, olfactory, and gustatory stimulation). The program was not applied during A phases. To assess behavioral changes, the Coma Recovery Scale-Revised (CRS-R) was administered by an independent rater on a weekly basis, across all phases. Each phase lasted 4 weeks. In a subset of patients, resting state functional magnetic resonance imaging (fMRI) data were collected at the end of each phase.Results: Twenty nine patients (48 ± 19 years old; 15 traumatic; 21 > a year post-injury; 11 VS and 18 MCS) were included in our study. Higher CRS-R total scores (medium effect size) as well as higher arousal and oromotor subscores were observed in the B phases (treatment) as compared to A phases (no treatment), in the MCS group but not in the VS group. In the three patients who underwent fMRI analyses, a modulation of metabolic activity related to treatment was observed in middle frontal gyrus, superior temporal gyrus as well as ventro-anterior thalamic nucleus.Conclusion: Our results suggest that SSP may not be sufficient to restore consciousness. SSP might nevertheless lead to improved behavioral responsiveness in MCS patients. Our results show higher CRS-R total scores when treatment is applied, and more exactly, increased arousal and oromotor functions.

In recent years, the study of the neural basis of consciousness, particularly in the context of patients recovering from severe brain injury, has greatly benefited from the application of sophisticated network analysis techniques to functional brain data. Yet, current graph theoretic approaches, as employed in the neuroimaging literature, suffer from four important shortcomings. First, they require arbitrary fixing of the number of connections (i.e., density) across networks which are likely to have different “natural” (i.e., stable) density (e.g., patients vs. controls, vegetative state vs. minimally conscious state patients). Second, when describing networks, they do not control for the fact that many characteristics are interrelated, particularly some of the most popular metrics employed (e.g., nodal degree, clustering coefficient)—which can lead to spurious results. Third, in the clinical domain of disorders of consciousness, there currently are no methods for incorporating structural connectivity in the characterization of functional networks which clouds the interpretation of functional differences across groups with different underlying pathology as well as in longitudinal approaches where structural reorganization processes might be operating. Finally, current methods do not allow assessing the dynamics of network change over time. We present a different framework for network analysis, based on Exponential Random Graph Models, which overcomes the above limitations and is thus particularly well suited for clinical populations with disorders of consciousness. We demonstrate this approach in the context of the longitudinal study of recovery from coma. First, our data show that throughout recovery from coma, brain graphs vary in their natural level of connectivity (from 10.4 to 14.5%), which conflicts with the standard approach of imposing arbitrary and equal density thresholds across networks (e.g., time-points, subjects, groups). Second, we show that failure to consider the interrelation between network measures does lead to spurious characterization of both inter- and intra-regional brain connectivity. Finally, we show that Separable Temporal ERGM can be employed to describe network dynamics over time revealing the specific pattern of formation and dissolution of connectivity that accompany recovery from coma.