Multimodal Neuroimaging Approach to Variability of Functional Connectivity in Disorders of Consciousness: A PET/MRI Pilot Study

Task-based EEG and fMRI paradigms in a multimodal clinical diagnostic framework for disorders of consciousness

Disorders of consciousness (DoC) are generally diagnosed by clinical assessment, which is a predominantly motor-driven process and accounts for up to 40 % of non-communication being misdiagnosed as unresponsive wakefulness syndrome (UWS) (previously known as prolonged/persistent vegetative state). Given the consequences of misdiagnosis, a more reliable and objective multimodal protocol to diagnosing DoC is needed, but has not been produced due to concerns regarding their interpretation and reliability. Of the techniques commonly used to detect consciousness in DoC, task-based paradigms (active paradigms) produce the most unequivocal result when findings are positive. It is well-established that command following (CF) reliably reflects preserved consciousness. Task-based electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can detect motor-independent CF and reveal preserved covert consciousness in up to 14 % of UWS patients. Accordingly, to improve the diagnostic accuracy of DoC, we propose a practical multimodal clinical decision framework centered on task-based EEG and fMRI, and complemented by measures like transcranial magnetic stimulation (TMS-EEG).

Evaluation of consciousness rehabilitation via neuroimaging methods

Accurate evaluation of patients with disorders of consciousness (DoC) is crucial for personalized treatment. However, misdiagnosis remains a serious issue. Neuroimaging methods could observe the conscious activity in patients who have no evidence of consciousness in behavior, and provide objective and quantitative indexes to assist doctors in their diagnosis. In the review, we discussed the current research based on the evaluation of consciousness rehabilitation after DoC using EEG, fMRI, PET, and fNIRS, as well as the advantages and limitations of each method. Nowadays single-modal neuroimaging can no longer meet the researchers` demand. Considering both spatial and temporal resolution, recent studies have attempted to focus on the multi-modal method which can enhance the capability of neuroimaging methods in the evaluation of DoC. As neuroimaging devices become wireless, integrated, and portable, multi-modal neuroimaging methods will drive new advancements in brain science research.

Validation of a pharmacological imaging challenge using 11C-buprenorphine and 18F-2-fluoro-2-deoxy-D-glucose positron emission tomography to study the effects of buprenorphine to the rat brain

Aim

Buprenorphine mainly acts as an agonist of mu-opioid receptors (mu-OR). High dose buprenorphine does not cause respiratory depression and can be safely administered to elicit typical opioid effects and explore pharmacodynamics. Acute buprenorphine, associated with functional and quantitative neuroimaging, may therefore provide a fully translational pharmacological challenge to explore the variability of response to opioids in vivo. We hypothesized that the CNS effects of acute buprenorphine could be monitored through changes in regional brain glucose metabolism, assessed using ¹⁸F-FDG microPET in rats.

Materials and methods

First, level of receptor occupancy associated with a single dose of buprenorphine (0.1 mg/kg, s.c) was investigated through blocking experiments using ¹¹C-buprenorphine PET imaging. Behavioral study using the elevated plus-maze test (EPM) was performed to assess the impact of the selected dose on anxiety and also locomotor activity. Then, brain PET imaging using ¹⁸F-FDG was performed 30 min after injection of unlabeled buprenorphine (0.1 mg/kg, s.c) vs. saline. Two different ¹⁸F-FDG PET acquisition paradigms were compared: (i) ¹⁸F-FDG injected i.v. under anesthesia and (ii) ¹⁸F-FDG injected i.p. in awake animals to limit the impact of anesthesia.

Results

The selected dose of buprenorphine fully blocked the binding of ¹¹C-buprenorphine in brain regions, suggesting complete receptor occupancy. This dose had no significant impact on behavioral tests used, regardless of the anesthetized/awake handling paradigm. In anesthetized rats, injection of unlabeled buprenorphine decreased the brain uptake of ¹⁸F-FDG in most brain regions except in the cerebellum which could be used as a normalization region. Buprenorphine treatment significantly decreased the normalized brain uptake of ¹⁸F-FDG in the thalamus, striatum and midbrain (p < 0.05), where binding of ¹¹C-buprenorphine was the highest. The awake paradigm did not improve sensitivity and impact of buprenorphine on brain glucose metabolism could not be reliably estimated.

Conclusion

Buprenorphine (0.1 mg/kg, s.c) combined with ¹⁸F-FDG brain PET in isoflurane anesthetized rats provides a simple pharmacological imaging challenge to investigate the CNS effects of full receptor occupancy by this partial mu-OR agonist. Sensitivity of the method was not improved in awake animals. This strategy may be useful to investigate de desensitization of mu-OR associated with opioid tolerance in vivo.

Relationships between serotonin availability and frontolimbic response to fearful and threatening faces

Serotonin is a critical neurotransmitter in the regulation of emotional behavior. Although emotion processing is known to engage a corticolimbic circuit, including the amygdala and prefrontal cortex, exactly how this brain system is modulated by serotonin remains unclear. Here, we hypothesized that serotonin modulates variability in excitability and functional connectivity within this circuit. We tested whether this modulation contributes to inter-individual differences in emotion processing. Using a multimodal neuroimaging approach with a simultaneous PET-3T fMRI scanner, we simultaneously acquired BOLD signal while participants viewed emotional faces depicting fear and anger, while also measuring serotonin transporter (SERT) levels, regulating serotonin functions. Individuals with higher activity of the medial amygdala BOLD in response to fearful or angry facial expressions, who were temperamentally more anxious, also exhibited lower SERT availability in the dorsal raphe nucleus (DRN). Moreover, higher connectivity of the medial amygdala with the left dorsolateral prefrontal and the anterior cingulate cortex was associated with lower levels of SERT availability in the DRN. These results demonstrate the association between the serotonin transporter level and emotion processing through changes in functional interactions between the amygdala and the prefrontal areas in healthy humans.

Is frontoparietal electroencephalogram activity related to the level of functional disability in patients emerging from a minimally conscious state? A preliminary study

Objective

When regaining consciousness, patients who emerge from a minimally conscious state (EMCS) present with different levels of functional disability, which pose great challenges for treatment. This study investigated the frontoparietal activity in EMCS patients and its effects on functional disability.

Materials and methods

In this preliminary study, 12 EMCS patients and 12 healthy controls were recruited. We recorded a resting-state scalp electroencephalogram (EEG) for at least 5 min for each participant. Each patient was assessed using the disability rating scale (DRS) to determine the level of functional disability. We analyzed the EEG power spectral density and sensor-level functional connectivity in relation to the patient’s functional disability.

Results

In the frontoparietal region, EMCS patients demonstrated lower relative beta power (P < 0.01) and higher weighted phase lag index (wPLI) values in the theta (P < 0.01) and gamma (P < 0.01) bands than healthy controls. The frontoparietal theta wPLI values of EMCS patients were positively correlated with the DRS scores (r_s = 0.629, P = 0.029). At the whole-brain level, EMCS patients only had higher wPLI values in the theta band (P < 0.01) than healthy controls. The whole-brain theta wPLI values of EMCS patients were also positively correlated with the DRS scores (r_s = 0.650, P = 0.022). No significant difference in the power and connectivity between the frontoparietal region and the whole brain in EMCS patients was observed.

Conclusion

EMCS patients still experience neural dysfunction, especially in the frontoparietal region. However, the theta connectivity in the frontoparietal region did not increase specifically. At the level of the whole brain, the same shift could also be seen. Theta functional connectivity in the whole brain may underlie different levels of functional disability.

Simultaneous electroencephalography-functional magnetic resonance imaging for assessment of human brain function

Electroencephalography (EEG) and functional Magnetic Resonance Imaging (MRI) have long been used as tools to examine brain activity. Since both methods are very sensitive to changes of synaptic activity, simultaneous recording of EEG and fMRI can provide both high temporal and spatial resolution. Therefore, the two modalities are now integrated into a hybrid tool, EEG-fMRI, which encapsulates the useful properties of the two. Among other benefits, EEG-fMRI can contribute to a better understanding of brain connectivity and networks. This review lays its focus on the methodologies applied in performing EEG-fMRI studies, namely techniques used for the recording of EEG inside the scanner, artifact removal, and statistical analysis of the fMRI signal. We will investigate simultaneous resting-state and task-based EEG-fMRI studies and discuss their clinical and technological perspectives. Moreover, it is established that the brain regions affected by a task-based neural activity might not be limited to the regions in which they have been initiated. Advanced methods can help reveal the regions responsible for or affected by a developed neural network. Therefore, we have also looked into studies related to characterization of structure and dynamics of brain networks. The reviewed literature suggests that EEG-fMRI can provide valuable complementary information about brain neural networks and functions.

Diagnostic Developments in Differentiating Unresponsive Wakefulness Syndrome and the Minimally Conscious State

When treating patients with a disorder of consciousness (DOC), it is essential to obtain an accurate diagnosis as soon as possible to generate individualized treatment programs. However, accurately diagnosing patients with DOCs is challenging and prone to errors when differentiating patients in a Vegetative State/Unresponsive Wakefulness Syndrome (VS/UWS) from those in a Minimally Conscious State (MCS). Upwards of ~40% of patients with a DOC can be misdiagnosed when specifically designed behavioral scales are not employed or improperly administered. To improve diagnostic accuracy for these patients, several important neuroimaging and electrophysiological technologies have been proposed. These include Positron Emission Tomography (PET), functional Magnetic Resonance Imaging (fMRI), Electroencephalography (EEG), and Transcranial Magnetic Stimulation (TMS). Here, we review the different ways in which these techniques can improve diagnostic differentiation between VS/UWS and MCS patients. We do so by referring to studies that were conducted within the last 10 years, which were extracted from the PubMed database. In total, 55 studies met our criteria (clinical diagnoses of VS/UWS from MCS as made by PET, fMRI, EEG and TMS- EEG tools) and were included in this review. By summarizing the promising results achieved in understanding and diagnosing these conditions, we aim to emphasize the need for more such tools to be incorporated in standard clinical practice, as well as the importance of data sharing to incentivize the community to meet these goals.

Consciousness and complexity: a consilience of evidence

Over the last years, a surge of empirical studies converged on complexity-related measures as reliable markers of consciousness across many different conditions, such as sleep, anesthesia, hallucinatory states, coma, and related disorders. Most of these measures were independently proposed by researchers endorsing disparate frameworks and employing different methods and techniques. Since this body of evidence has not been systematically reviewed and coherently organized so far, this positive trend has remained somewhat below the radar. The aim of this paper is to make this consilience of evidence in the science of consciousness explicit. We start with a systematic assessment of the growing literature on complexity-related measures and identify their common denominator, tracing it back to core theoretical principles and predictions put forward more than 20 years ago. In doing this, we highlight a consistent trajectory spanning two decades of consciousness research and provide a provisional taxonomy of the present literature. Finally, we consider all of the above as a positive ground to approach new questions and devise future experiments that may help consolidate and further develop a promising field where empirical research on consciousness appears to have, so far, naturally converged.

Autonomic responses to emotional linguistic stimuli and amplitude of low-frequency fluctuations predict outcome after severe brain injury

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Acute DOC patients with favourable outcome show preserved event-related electrodermal response.

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Acute DOC patients showed reduced fALFF in the posterior cingulate cortex.

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Event-related electrodermal activity correlated with the fALFFs in the PCC in the acute phase.

An accurate prognosis on the outcome of brain-injured patients with disorders of consciousness (DOC) remains a significant challenge, especially in the acute stage. In this study, we applied a multiple-technique approach to provide accurate predictions on functional outcome after 6 months in 15 acute DOC patients. Electrophysiological correlates of implicit cognitive processing of verbal stimuli and data-driven voxel-wise resting-state fMRI signals, such as the fractional amplitude of low-frequency fluctuations (fALFF), were employed. Event-related electrodermal activity, an index of autonomic activation, was recorded in response to emotional words and pseudo-words at baseline (T0). On the same day, patients also underwent a resting-state fMRI scan. Six months later (T1), patients were classified as outcome-negative and outcome-positive using a standard functional outcome scale. We then revisited the baseline measures to test their predictive power for the functional outcome measured at T1. We found that only outcome-positive patients had an earlier, higher autonomic response for words compared to pseudo-words, a pattern similar to that of healthy awake controls. Furthermore, DOC patients showed reduced fALFF in the posterior cingulate cortex (PCC), a brain region that contributes to autonomic regulation and awareness. The event-related electrodermal marker of residual cognitive functioning was found to have a significant correlation with residual local neuronal activity in the PCC. We propose that a residual autonomic response to cognitively salient stimuli, together with a preserved resting-state activity in the PCC, can provide a useful prognostic index in acute DOC.

Contribution of PET-MRI in brain diseases in clinical practice

PURPOSE OF REVIEW

Hybrid PET- MRI is a technique that has the ability to improve diagnostic accuracy in many applications, whereas PET and MRI performed separately often fail to provide accurate responses to clinical questions. Here, we review recent studies and current developments in PET-MRI, focusing on clinical applications.

RECENT FINDINGS

The combination of PET and MRI imaging methods aims at increasing the potential of each individual modality. Combined methods of image reconstruction and correction of PET-MRI attenuation are being developed, and a number of applications are being introduced into clinical practice. To date, the value of PET-MRI has been demonstrated for the evaluation of brain tumours in epilepsy and neurodegenerative diseases. Continued advances in data analysis regularly improve the efficiency and the potential application of multimodal biomarkers.

SUMMARY

PET-MRI provides simultaneous of anatomical, functional, biochemical and metabolic information for the personalized characterization and monitoring of neurological diseases. In this review, we show the advantage of the complementarity of different biomarkers obtained using PET-MRI data. We also present the recent advances made in this hybrid imaging modality and its advantages in clinical practice compared with MRI and PET separately.

Consciousness and the Dimensionality of DOC Patients via the Generalized Ising Model

The data from patients with severe brain injuries show complex brain functions. Due to the difficulties associated with these complex data, computational modeling is an especially useful tool to examine the structure-function relationship in these populations. By using computational modeling for patients with a disorder of consciousness (DoC), not only we can understand the changes of information transfer, but we also can test changes to different states of consciousness by hypothetically changing the anatomical structure. The generalized Ising model (GIM), which specializes in using structural connectivity to simulate functional connectivity, has been proven to effectively capture the relationship between anatomical structures and the spontaneous fluctuations of healthy controls (HCs). In the present study we implemented the GIM in 25 HCs as well as in 13 DoC patients diagnosed at three different states of consciousness. Simulated data were analyzed and the criticality and dimensionality were calculated for both groups; together, those values capture the level of information transfer in the brain. Ratifying previous studies, criticality was observed in simulations of HCs. We were also able to observe criticality for DoC patients, concluding that the GIM is generalizable for DoC patients. Furthermore, dimensionality increased for the DoC group as compared to healthy controls, and could distinguish different diagnostic groups of DoC patients.

Gliosis and Neurodegenerative Diseases: The Role of PET and MR Imaging

Glial activation characterizes most neurodegenerative and psychiatric diseases, often anticipating clinical manifestations and macroscopical brain alterations. Although imaging techniques have improved diagnostic accuracy in many neurological conditions, often supporting diagnosis, prognosis prediction and treatment outcome, very few molecular imaging probes, specifically focused on microglial and astrocytic activation, have been translated to a clinical setting. In this context, hybrid positron emission tomography (PET)/magnetic resonance (MR) scanners represent the most advanced tool for molecular imaging, combining the functional specificity of PET radiotracers (e.g., targeting metabolism, hypoxia, and inflammation) to both high-resolution and multiparametric information derived by MR in a single imaging acquisition session. This simultaneity of findings achievable by PET/MR, if useful for reciprocal technical adjustments regarding temporal and spatial cross-modal alignment/synchronization, opens still debated issues about its clinical value in neurological patients, possibly incompliant and highly variable from a clinical point of view. While several preclinical and clinical studies have investigated the sensitivity of PET tracers to track microglial (mainly TSPO ligands) and astrocytic (mainly MAOB ligands) activation, less studies have focused on MR specificity to this topic (e.g., through the assessment of diffusion properties and T2 relaxometry), and only few exploiting the integration of simultaneous hybrid acquisition. This review aims at summarizing and critically review the current state about PET and MR imaging for glial targets, as well as the potential added value of hybrid scanners for characterizing microglial and astrocytic activation.

Simultaneous EEG-fMRI for Functional Neurological Assessment

The increasing incidence of neurodegenerative and psychiatric diseases requires increasingly sophisticated tools for their diagnosis and monitoring. Clinical assessment takes advantage of objective parameters extracted by electroencephalogram and magnetic resonance imaging (MRI) among others, to support clinical management of neurological diseases. The complementarity of these two tools can be now emphasized by the possibility of integrating the two technologies in a hybrid solution, allowing simultaneous acquisition of the two signals by the novel EEG-fMRI technology. This review will focus on simultaneous EEG-fMRI technology and related early studies, dealing about issues related to the acquisition and processing of simultaneous signals, and including critical discussion about clinical and technological perspectives.