Mapping general anesthesia states based on electro-encephalogram transition phases.

Cortical electro-encephalography (EEG) served as the clinical reference for monitoring unconsciousness during general anesthesia. The existing EEG-based monitors classified general anesthesia states as underdosed, adequate, or overdosed, lacking predictive power due to the absence of transition phases among these states. In response to this limitation, we undertook an analysis of the EEG signal during isoflurane-induced general anesthesia in mice. Adopting a data-driven approach, we applied signal processing techniques to track θ- and δ-band dynamics, along with iso-electric suppressions. Combining this approach with machine learning, we successfully developed an automated algorithm. The findings of our study revealed that the dampening of the δ-band occurred several minutes before the onset of significant iso-electric suppression episodes. Furthermore, a distinct γ-frequency oscillation was observed, persisting for several minutes during the recovery phase subsequent to isoflurane-induced overdose. As a result of our research, we generated a map summarizing multiple brain states and their transitions, offering a tool for predicting and preventing overdose during general anesthesia. The transition phases identified, along with the developed algorithm, have the potential to be generalized, enabling clinicians to prevent inadequate anesthesia and, consequently, tailor anesthetic regimens to individual patients.

Multisite thalamic recordings to characterize seizure propagation in the human brain.

Neuromodulation of the anterior nuclei of the thalamus (ANT) has shown to be efficacious in a subset of patients with refractory focal epilepsy. One important uncertainty is to what extent thalamic subregions other than the ANT could be recruited more prominently in the propagation of focal onset seizures. We designed the current study to simultaneously monitor the engagement of the ANT, mediodorsal (MD) and pulvinar (PUL) nuclei during seizures in patients who could be candidates for thalamic neuromodulation. We studied 11 patients with clinical manifestations of presumed temporal lobe epilepsy (TLE) undergoing invasive stereo-encephalography (sEEG) monitoring to confirm the source of their seizures. We extended cortical electrodes to reach the ANT, MD and PUL nuclei of the thalamus. More than one thalamic subdivision was simultaneously interrogated in nine patients. We recorded seizures with implanted electrodes across various regions of the brain and documented seizure onset zones (SOZ) in each recorded seizure. We visually identified the first thalamic subregion to be involved in seizure propagation. Additionally, in eight patients, we applied repeated single pulse electrical stimulation in each SOZ and recorded the time and prominence of evoked responses across the implanted thalamic regions. Our approach for multisite thalamic sampling was safe and caused no adverse events. Intracranial EEG recordings confirmed SOZ in medial temporal lobe, insula, orbitofrontal and temporal neocortical sites, highlighting the importance of invasive monitoring for accurate localization of SOZs. In all patients, seizures with the same propagation network and originating from the same SOZ involved the same thalamic subregion, with a stereotyped thalamic EEG signature. Qualitative visual reviews of ictal EEGs were largely consistent with the quantitative analysis of the corticothalamic evoked potentials, and both documented that thalamic nuclei other than ANT could have the earliest participation in seizure propagation. Specifically, pulvinar nuclei were involved earlier and more prominently than ANT in more than half of the patients. However, which specific thalamic subregion first demonstrated ictal activity could not be reliably predicted based on clinical semiology or lobar localization of SOZs. Our findings document the feasibility and safety of bilateral multisite sampling from the human thalamus. This may allow more personalized thalamic targets to be identified for neuromodulation. Future studies are needed to determine if a personalized thalamic neuromodulation leads to greater improvements in clinical outcome.

Impact of surrounding tissue-type and peri-electrode gap in stereoelectroencephalography guided (SEEG) radiofrequency thermocoagulation (RF-TC): a computational study.

PURPOSE: To use computational modeling to provide a complete and logical description of the electrical and thermal behavior during stereoelectroencephalography-guided (SEEG) radiofrequency thermo-coagulation (RF-TC). METHODS: A coupled electrical-thermal model was used to obtain the temperature distributions in the tissue during RF-TC. The computer model was first validated by an ex vivo model based on liver fragments and later used to study the impact of three different factors on the coagulation zone size: 1) the difference in the tissue surrounding the electrode (gray/white matter), 2) the presence of a peri-electrode gap occupied by cerebrospinal fluid (CSF), and 3) the energy setting used (power-duration). RESULTS: The model built for the experimental validation was able to predict both the evolution of impedance and the short diameter of the coagulation zone (error < 0.01 mm) reasonably well but overestimated the long diameter by 2 - 3 mm. After adapting the model to clinical conditions, the simulation showed that: 1) Impedance roll-off limited the coagulation size but involved overheating (around 100 °C); 2) The type of tissue around the contacts (gray vs. white matter) had a moderate impact on the coagulation size (maximum difference 0.84 mm), and 3) the peri-electrode gap considerably altered the temperature distributions, avoided overheating, although the diameter of the coagulation zone was not very different from the no-gap case (<0.2 mm). CONCLUSIONS: This study showed that computer modeling, especially subject- and scenario-specific modeling, can be used to estimate in advance the electrical and thermal performance of the RF-TC in brain tissue.

Frame-based versus robot-assisted stereo-electro-encephalography for drug-resistant epilepsy.

BACKGROUND: Stereoelectroencephalography (SEEG) is an effective presurgical invasive evaluation for drug-resistant epilepsies. The introduction of robotic devices provides a simplified, accurate, and safe alternative to the conventional SEEG technique. We report our institutional experience with robot-assisted SEEG and compare its in vivo accuracy, operation efficiency, and safety with the more traditional SEEG workflow. METHODS: All patients with medically refractory focal epilepsy who underwent SEEG depth electrode implantation between 2014 and 2022 were included in this study. Technical advancements of the robot-assisted technique are described. Analyses of patient demographics, electrode implantation accuracy, operation time, and procedure-related complications were performed. RESULTS: One hundred and sixty-six patients underwent 167 SEEG procedures. The first 141 procedures were performed using a conventional approach involving a Leksell stereotactic system, and the last 26 procedures were robot-assisted. Among the 1726 depth electrodes that were inserted, the median entry point localization error was as follows: conventional (1.0 mm; range, 0.1-33.5 mm) and robot-assisted (1.1 mm; range, 0-4.8 mm) (P = 0.17). The median target point localization error was as follows: conventional (2.8 mm; range, 0.1-49 mm) and robot-assisted (1.8 mm; range, 0-30.3 mm) (P < 0.001). The median operation time was significantly reduced with the robot-assisted workflow (90 min vs. 77.5 min; P < 0.01). Total complication rates were as follows: conventional (17.7%) and robot-assisted (11.5%) (P = 0.57). Major complication rates were 3.5% and 7.7% (P = 0.77), respectively. CONCLUSIONS: SEEG is a safe and highly accurate method that provides essential guidance for epilepsy surgery. Implementing SEEG in conjunction with multimodal planning systems and robotic devices can further increase safety margin, surgical efficiency, and accuracy.

Religiosity, Financial Risk Taking, and Reward Processing: An Experimental Study.

The present study investigated the extent to which financial risk-taking (FRT) perspectives and religiosity influenced an individual's performance on financial decision-making tasks under risk and/or uncertainty. It further investigated the potential to measure this interaction using electro-encephalogram (EEG) assessments through reward-related event-related potentials (P3 and FRN). EEG data were collected from 37 participants undergoing four decision-making tasks comprising the Balloon Analogue Risk Task (BART), Iowa Gambling Test (IGT), Mixed-Gamble Loss-Aversion Task (MGLAT), and MGLA-Success Task (MGLAST). The present study found that BART performance may be affected by an interaction of FRT perspectives and religiosity. The physiological effects of task feedback were also distinguished between religious and non-religious individuals objectively with EEG data. Overall, while religiosity and FRT may not significantly influence IGT and MGLA performance, and interact with BART in a complex way, physiological reaction towards feedback after BART performance appears to be strongly affected by religiosity and FRT perspectives.

Evaluation and Treatment of Seizures and Epilepsy During the COVID-19 Pandemic.

PURPOSE OF REVIEW: Seizures, including status epilepticus, have been reported in association with acute COVID-19 infection. People with epilepsy (PWE) have suffered from seizure exacerbations during the pandemic. This article reviews the data for clinical and electrographic seizures associated with COVID-19, technical EEG considerations for reducing risk of transmission, and factors contributing to seizure exacerbations in PWE as well as strategies to address this issue. RECENT FINDINGS: An increasing number of studies of larger cohorts, accounting for a variety of variables and often utilizing EEG with standardized terminology, are assessing the prevalence of seizures in hospitalized patients with acute COVID-19 infections, and gaining insight into the prevalence of seizures and their effect on outcomes. Additionally, recent studies are evaluating the effect of the pandemic on PWE, barriers faced, and the usefulness of telehealth. Although there is still much to learn regarding COVID-19, current studies help in assessing the risk of seizures, guiding EEG utilization, and optimizing the use of telehealth during the pandemic.

Neurovascular networks in epilepsy: Correlating ictal blood perfusion with intracranial electrophysiology.

Perfusion patterns observed in Subtraction Ictal SPECT Co-registered to MRI (SISCOM) assist in focus localization and surgical planning for patients with medically intractable focal epilepsy. While the localizing value of SISCOM has been widely investigated, its relationship to the underlying electrophysiology has not been extensively studied and is therefore not well understood. In the present study, we set to investigate this relationship in a cohort of 70 consecutive patients who underwent ictal and interictal SPECT studies and subsequent stereo-electroencephalography (SEEG) monitoring for localization of the epileptogenic focus and surgical intervention. Seizures recorded during SEEG evaluation (SEEG seizures) were matched to semiologically-similar seizures during the preoperative ictal SPECT evaluation (SPECT seizures) by comparing the semiological changes in the course of each seizure. The spectral changes of the ictal SEEG with respect to interictal ones over 7 traditional frequency bands (0.1 to 150Hz) were analyzed at each SEEG site. Neurovascular (SEEG/SPECT) relations were assessed by comparing the estimated spectral power density changes of the SEEG at each site with the perfusion changes (SISCOM z-scores) estimated from the acquired SISCOM map at that site. Across patients, a significant correlation (p<0.05) was observed between spectral changes during the SEEG seizure and SISCOM perfusion z-scores. Brain sites with high perfusion z-score exhibited higher increased SEEG power in theta to ripple frequency bands with concurrent suppression in delta and theta frequency bands compared to regions with lower perfusion z-score. The dynamics of the correlation of SISCOM perfusion and SEEG spectral power from ictal onset to seizure end and immediate postictal period were also derived. Forty-six (46) of the 70 patients underwent resective epilepsy surgery. SISCOM z-score and power increase in beta to ripple frequency bands were significantly higher in resected than non-resected sites in the patients who were seizure-free following surgery. This study provides for the first time concrete evidence that both hyper-perfusion and hypo-perfusion patterns observed in SISCOM maps have strong electrophysiological underpinnings, and that integration of the information from SISCOM and SEEG can shed light on the location and dynamics of the underlying epileptic brain networks, and thus advance our anatomo-electro-clinical understanding and approaches to targeted diagnostic and therapeutic interventions.

Dynamics of task-related electrophysiological networks: a benchmarking study.

Motor, sensory and cognitive functions rely on dynamic reshaping of functional brain networks. Tracking these rapid changes is crucial to understand information processing in the brain, but challenging due to the great variety of dimensionality reduction methods used at the network-level and the limited evaluation studies. Using Magnetoencephalography (MEG) combined with Source Separation (SS) methods, we present an integrated framework to track fast dynamics of electrophysiological brain networks. We evaluate nine SS methods applied to three independent MEG databases (N=95) during motor and memory tasks. We report differences between these methods at the group and subject level. We seek to help researchers in choosing objectively the appropriate SS method when tracking fast reconfiguration of functional brain networks, due to its enormous benefits in cognitive and clinical neuroscience.

Effects of familiarity on child brain networks when listening to a storybook reading: A magneto-encephalographic study.

Parent-child book reading is important for fostering the development of various lifelong cognitive and social abilities in young children. Despite numerous reports describing the effects of familiarity on shared reading for children, the exact neural basis of the functional network architecture remains unclear. We conducted Magnet-Encephalographic (MEG) experiments using graph theory to elucidate the role of familiarity in shared reading in a child's brain network and to measure the connectivity dynamics of a child while Listening to Storybook Reading (LSBR), which represents the daily activity of shared book reading between the child and caregiver. The LSBR task was performed with normally developing preschool- and school-age children (N = 15) under two conditions: reading by their own mother (familiar condition) vs. an experimenter (unfamiliar condition). We used the phase lag index (PLI), which captures synchronization of MEG signals, to estimate functional connectivity. For the whole brain network topology, an undirected weighted graph was produced using 68 brain regions as nodes and interregional PLI values as edges for five frequency bands. Behavioral data (i.e., the degree of attention and facial expressions) were evaluated from video images of the child's face during the two conditions. Our results showed enhanced widespread functional connectivity in the alpha band during the mother condition. In the mother condition, the whole brain network in the alpha band exhibited topographically high local segregation with high global integration, indicating an increased small-world property. Results of the behavioral analysis revealed that children were more attentive and showed more positive facial expressions in the mother condition than in the experimenter condition. Behavioral data were significantly correlated with graph metrics in the mother condition but not in the experimenter condition. In this study, we identified the neural correlates of a familiarity effect in children's brain connectivity dynamics during LSBR. Furthermore, these familiarity-related brain dynamics were closely linked to the child's behavior. Graph theory applied to MEG data may provide useful insight into the familiarity-related child brain response in a naturalistic setting and its relevance to child attitudes.

Improving the sensitivity of spin-echo fMRI at 3T by highly accelerated acquisitions.

PURPOSE: Spin-echo (SE) functional MRI (fMRI) can be highly advantageous compared to gradient-echo (GE) fMRI with respect to magnetic field-inhomogeneity artifacts. However, at 3T, the majority of blood oxygenation level-dependent (BOLD) fMRI experiments are performed using T2∗ -weighted GE sequences because of their superior sensitivity compared to SE-fMRI. The presented SE implementation of a highly accelerated GE pulse sequence therefore aims to improve the sensitivity of SE-fMRI while profiting from a reduction of susceptibility-induced signal dropout. METHODS: Spin-echo MR encephalography (SE-MREG) is compared with the more conventionally used spin-echo echo-planar imaging (SE-EPI) and spin-echo simultaneous multislice (SE-SMS) at 3T in terms of capability to detect neuronal activations and resting-state functional connectivity. For activation analysis, healthy subjects underwent consecutive SE-MREG (pulse repetition time [TR] = 0.25 seconds), SE-SMS (TR = 1.3 seconds), and SE-EPI (TR = 4.4 seconds) scans in pseudorandomized order applied to a visual block design paradigm for generation of t-statistics maps. For the investigation of functional connectivity, additional resting-state data were acquired for 5 minutes and a seed-based correlation analysis using Stanford's FIND (Functional Imaging in Neuropsychiatric Disorders) atlas was performed. RESULTS: The increased sampling rate of SE-MREG relative to SE-SMS and SE-EPI improves the sensitivity to detect BOLD activation by 33% and 54%, respectively, and increases the capability to extract resting-state networks. Compared with a brain region that is not affected by magnetic field inhomogeneities, SE-MREG shows 2.5 times higher relative signal strength than GE-MREG in mesial temporal structures. CONCLUSION: SE-MREG offers a viable possibility for whole-brain fMRI with consideration of brain regions that are affected by strong susceptibility-induced magnetic field gradients.

Factors associated with neurodevelopment in preterm infants with systematic inflammation.

BACKGROUND: Several studies have suggested that adverse neurodevelopment could be induced by systemic inflammation in preterm infants. We aimed to investigate whether preterm infants with systemic inflammation would have impaired neurodevelopment and which biomarkers and neurophysiologic studies during inflammation are associated with poor neurodevelopment. METHODS: This prospective cohort study enrolled infants born before 30 weeks of gestation or with birth weight < 1250 g. Infants were grouped according to the presence of systemic inflammation: Control (no inflammation, n = 49), I (systemic inflammation, n = 45). Blood and cerebrospinal fluid samples for markers of brain injury and inflammation were collected and amplitude-integrated electroencephalography (aEEG) was performed within 4 h of septic workup. We evaluated aEEG at 35 weeks postmenstrual age (PMA), head circumference at 36 weeks PMA, and brain MRI at discharge. The Bayley Scales of Infant and Toddler Development III (Bayley-III) was performed at a corrected age (CA) of 18 months. RESULTS: The I group had more white matter injuries (2 vs. 26.7%, Control vs. I, respectively) at the time of discharge, lower brain functional maturation (9.5 vs. 8), and smaller head size (z-score - 1.45 vs. -2.12) at near-term age and poorer neurodevelopment at a CA of 18 months than the control (p < 0.05). Among the I group, the proportion of immature neutrophils (I/T ratios) and IL-1 beta levels in the CSF were associated with aEEG measures at the day of symptom onset (D0). Seizure spike on aEEG at D0 was significantly correlated with motor and social-emotional domains of Bayley-III (p < 0.05). The I/T ratio and CRP and TNF-α levels of blood at D0, white matter injury on MRI at discharge, head circumference and seizure spikes on aEEG at near-term age were associated with Bayley-III scores at a CA of 18 months. CONCLUSIONS: Systemic inflammation induced by clinical infection and NEC are associated with neurodevelopmental impairment in preterm infants. The seizure spike on aEEG, elevated I/T ratio, CRP, and plasma TNF-alpha during inflammatory episodes are associated with poor neurodevelopment.

Early initial video-electro-encephalography combined with variant location predict prognosis of KCNQ2-related disorder.

BACKGROUND: The clinical features of KCNQ2-related disorders range from benign familial neonatal seizures 1 to early infantile epileptic encephalopathy 7. The genotype-phenotypic association is difficult to establish. OBJECTIVE: To explore potential factors in neonatal period that can predict the prognosis of neonates with KCNQ2-related disorder. METHODS: Infants with KCNQ2-related disorder were retrospectively enrolled in our study in Children's Hospital of Fudan University in China from Jan 2015 to Mar 2020. All infants were older than age of 12 months at time of follow-up, and assessed by Bayley Scales of Infant and Toddler Development-Third Edition (BSID-III) or Wechsler preschool and primary scale of intelligence-fourth edition (WPPSI-IV), then divided into three groups based on scores of BSID-III or WPPSI-IV: normal group, mild impairment group, encephalopathy group. We collected demographic variables, clinical characteristics, neuroimaging data. Considered variables include gender, gestational age, birth weight, age of the initial seizures, early interictal VEEG, variant location, delivery type. Variables predicting prognosis were identified using multivariate ordinal logistic regression analysis. RESULTS: A total of 52 infants were selected in this study. Early interictal video-electro-encephalography (VEEG) (ß = 2.77, 1.20 to 4.34, P = 0.001), and variant location (ß = 2.77, 0.03 to 5.5, P = 0.048) were independent risk factors for prognosis. The worse the early interictal VEEG, the worse the prognosis. Patients with variants located in the pore-lining domain or S4 segment are more likely to have a poor prognosis. CONCLUSIONS: The integration of early initial VEEG and variant location can predict prognosis. An individual whose KCNQ2 variant located in voltage sensor, the pore domain, with worse early initial VEEG background, often had an adverse outcome.

Electrocerebral Signature of Cardiac Death.

BACKGROUND: Electroencephalography (EEG) findings following cardiovascular collapse in death are uncertain. We aimed to characterize EEG changes immediately preceding and following cardiac death. METHODS: We retrospectively analyzed EEGs of patients who died from cardiac arrest while undergoing standard EEG monitoring in an intensive care unit. Patients with brain death preceding cardiac death were excluded. Three events during fatal cardiovascular failure were investigated: (1) last recorded QRS complex on electrocardiogram (QRS0), (2) cessation of cerebral blood flow (CBF0) estimated as the time that blood pressure and heart rate dropped below set thresholds, and (3) electrocerebral silence on EEG (EEG0). We evaluated EEG spectral power, coherence, and permutation entropy at these time points. RESULTS: Among 19 patients who died while undergoing EEG monitoring, seven (37%) had a comfort-measures-only status and 18 (95%) had a do-not-resuscitate status in place at the time of death. EEG0 occurred at the time of QRS0 in five patients and after QRS0 in two patients (cohort median - 2.0, interquartile range - 8.0 to 0.0), whereas EEG0 was seen at the time of CBF0 in six patients and following CBF0 in 11 patients (cohort median 2.0 min, interquartile range - 1.5 to 6.0). After CBF0, full-spectrum log power (p < 0.001) and coherence (p < 0.001) decreased on EEG, whereas delta (p = 0.007) and theta (p < 0.001) permutation entropy increased. CONCLUSIONS: Rarely may patients have transient electrocerebral activity following the last recorded QRS (less than 5 min) and estimated cessation of cerebral blood flow. These results may have implications for discussions around cardiopulmonary resuscitation and organ donation.

Evidence accumulation during perceptual decision-making is sensitive to the dynamics of attentional selection.

The ability to select and combine multiple sensory inputs in support of accurate decisions is a hallmark of adaptive behaviour. Attentional selection is often needed to prioritize task-relevant stimuli relative to irrelevant, potentially distracting stimuli. As most studies of perceptual decision-making to date have made use of task-relevant stimuli only, relatively little is known about how attention modulates decision making. To address this issue, we developed a novel 'integrated' decision-making task, in which participants judged the average direction of successive target motion signals while ignoring concurrent and spatially overlapping distractor motion signals. In two experiments that varied the role of attentional selection, we used regression to quantify the influence of target and distractor stimuli on behaviour. Using electroencephalography, we characterised the neural correlates of decision making, attentional selection and feature-specific responses to target and distractor signals. While targets strongly influenced perceptual decisions and associated neural activity, we also found that concurrent and spatially coincident distractors exerted a measurable bias on both behaviour and brain activity. Our findings suggest that attention operates as a real-time but imperfect filter during perceptual decision-making by dynamically modulating the contributions of task-relevant and irrelevant sensory inputs.

Exploring the Correlation Between M/EEG Source-Space and fMRI Networks at Rest.

Magneto/electro-encephalography (M/EEG) source connectivity is an emerging approach to estimate brain networks with high temporal and spatial resolutions. Here, we aim to evaluate the effect of functional connectivity (FC) methods on the correlation between M/EEG source-space and fMRI networks at rest. Two main FC families are tested: (i) FC methods that do not remove zero-lag connectivity including Phase Locking Value (PLV) and Amplitude Envelope Correlation (AEC) and (ii) FC methods that remove zero-lag connections such as Phase Lag Index (PLI) and two orthogonalisation approaches combined with PLV (PLVCol, PLVPas) and AEC (AECCol, AECPas). Methods are evaluated on resting state M/EEG signals recorded from healthy participants at rest (N = 74). Networks obtained by each FC method are compared with fMRI networks (obtained from the Human Connectome Project). Results show low correlations for all FC methods, however PLV and AEC networks are significantly correlated with fMRI networks (ρ = 0.12, p = 1.93 × 10-8 and ρ = 0.06, p = 0.007, respectively), while other methods are not. These observations are consistent for all M/EEG frequency bands and for different FC matrices threshold. Our main message is to be careful in selecting FC methods when comparing or combining M/EEG with fMRI. We consider that more comparative studies based on simulation and real data and at different levels (node, module or sub networks) are still needed in order to improve our understanding on the relationships between M/EEG source-space networks and fMRI networks at rest.

Decision-making in temporal lobe epilepsy surgery based on invasive stereo-electroencephalography (sEEG).

In medical refractory temporal lobe epilepsy (TLE), the epileptogenic zone can be difficult to identify and therefore difficult to treat, especially in the absence of clear MRI pathologies and specific results from presurgical evaluation. Invasive monitoring with stereo-electroencephalography (sEEG) is a tool for a better determination of the epileptogenic zone. Here, we investigate the impact of sEEG on decision-making in temporal lobe epilepsy surgery. We reviewed patients with TLE who underwent further investigation with sEEG in our epilepsy unit. We examined specifically how sEEG findings influenced our decision regarding indication for a surgical procedure and resection volume. From 2013 to 2017, we performed 152 temporal resections in epilepsy patients. Twenty-one of these patients were designated for further preoperative investigation with sEEG due to incongruent findings in presurgical evaluation. Six patients were implanted bitemporally. In five cases, the hypothesis for the epileptogenic zone and localization had to be changed due to sEEG findings and resulted in a different tailored resection than intended. In three cases, sEEG findings led to the cancelation of the originally intended temporal resection as the epileptogenic zone was not definable or bilateral. In another three cases, the prognosis for reduction of seizures postoperatively had to be reduced due to the sEEG findings. However, the resection was performed after interdisciplinary discussion and informed consent of the patient. The examination by sEEG led to a change of plan for further treatment in 13 patients (61.9%) suffering TLE in total. Invasive monitoring with sEEG electrodes had a strong impact on decision-making for further treatment in patients suffering from temporal lobe epilepsy with incongruent findings in presurgical examination designated for epilepsy surgery. This applies to resection volumes as well as to prediction of seizure outcome.

The potential of MR-Encephalography for BCI/Neurofeedback applications with high temporal resolution.

Real-time functional magnetic resonance imaging (rt-fMRI) enables the update of various brain-activity measures during an ongoing experiment as soon as a new brain volume is acquired. However, the recorded Blood-oxygen-level dependent (BOLD) signal also contains physiological artifacts such as breathing and heartbeat, which potentially cause misleading false positive effects especially problematic in brain-computer interface (BCI) and neurofeedback (NF) setups. The low temporal resolution of echo planar imaging (EPI) sequences (which is in the range of seconds) prevents a proper separation of these artifacts from the BOLD signal. MR-Encephalography (MREG) has been shown to provide the high temporal resolution required to unalias and correct for physiological fluctuations and leads to increased specificity and sensitivity for mapping task-based activation and functional connectivity as well as for detecting dynamic changes in connectivity over time. By comparing a simultaneous multislice echo planar imaging (SMS-EPI) sequence and an MREG sequence using the same nominal spatial resolution in an offline analysis for three different experimental fMRI paradigms (perception of house and face stimuli, motor imagery, Stroop task), the potential of this novel technique for future BCI and NF applications was investigated. First, adapted general linear model pre-whitening which accounts for the high temporal resolution in MREG was implemented to calculate proper statistical results and be able to compare these with the SMS-EPI sequence. Furthermore, the respiration- and cardiac pulsation-related signals were successfully separated from the MREG signal using independent component analysis which were then included as regressors for a GLM analysis. Only the MREG sequence allowed to clearly separate cardiac pulsation and respiration components from the signal time course. It could be shown that these components highly correlate with the recorded respiration and cardiac pulsation signals using a respiratory belt and fingertip pulse plethysmograph. Temporal signal-to-noise ratios of SMS-EPI and MREG were comparable. Functional connectivity analysis using partial correlation showed a reduced standard error in MREG compared to SMS-EPI. Also, direct time course comparisons by down-sampling the MREG signal to the SMS-EPI temporal resolution showed lower variance in MREG. In general, we show that the higher temporal resolution is beneficial for fMRI time course modeling and this aspect can be exploited in offline application but also, is especially attractive, for real-time BCI and NF applications.

The human sensorimotor cortex fosters muscle synergies through cortico-synergy coherence.

In neuromotor control, the dimensionality of complex muscular activation patterns is effectively reduced through the emergence of muscle synergies. Muscle synergies are tailored to task-specific biomechanical needs. Traditionally, they are considered as low-dimensional neural output of the spinal cord and as such their coherent cortico-muscular pathways have remained underexplored in humans. We investigated whether muscle synergies have a higher-order origin, especially, whether they are manifest in the cortical motor network. We focused on cortical muscle synergy representations involved in balance control and examined changes in cortico-synergy coherence accompanying short-term balance training. We acquired electromyography and electro-encephalography and reconstructed cortical source activity using adaptive spatial filters. The latter were based on three muscle synergies decomposed from the activity of nine unilateral leg muscles using non-negative matrix factorization. The corresponding cortico-synergy coherence displayed phase-locked activity at the Piper rhythm, i.e., cortico-spinal synchronization around 40 Hz. Our study revealed the presence of muscle synergies in the motor cortex, in particular, in the paracentral lobule, known for the representation of lower extremities. We conclude that neural oscillations synchronize between the motor cortex and spinal motor neuron pools signifying muscle synergies. The corresponding cortico-synergy coherence around the Piper rhythm decreases with training-induced balance improvement.

Neural gain control measured through cortical gamma oscillations is associated with sensory sensitivity.

Gamma oscillations facilitate information processing by shaping the excitatory input/output of neuronal populations. Recent studies in humans and nonhuman primates have shown that strong excitatory drive to the visual cortex leads to suppression of induced gamma oscillations, which may reflect inhibitory-based gain control of network excitation. The efficiency of the gain control measured through gamma oscillations may in turn affect sensory sensitivity in everyday life. To test this prediction, we assessed the link between self-reported sensitivity and changes in magneto-encephalographic gamma oscillations as a function of motion velocity of high-contrast visual gratings. The induced gamma oscillations increased in frequency and decreased in power with increasing stimulation intensity. As expected, weaker suppression of the gamma response correlated with sensory hypersensitivity. Robustness of this result was confirmed by its replication in the two samples: neurotypical subjects and people with autism, who had generally elevated sensory sensitivity. We conclude that intensity-related suppression of gamma response is a promising biomarker of homeostatic control of the excitation-inhibition balance in the visual cortex.

Quantitative Analysis of [18F]FFMZ and [18F]FDG PET Studies in the Localization of Seizure Onset Zone in Drug-Resistant Temporal Lobe Epilepsy.

BACKGROUND: Positron emission tomography (PET) imaging in epilepsy is an in vivo technique that allows the localization of a possible seizure onset zone (SOZ) during the interictal period. Stereo-electro-encephalography (SEEG) is the gold standard to define the SOZ. The objective of this research was to evaluate the accuracy of PET imaging in localizing the site of SOZ compared with SEEG. METHODS: Seven patients with refractory temporal lobe epilepsy (Ep) and 2 healthy controls (HC) underwent 2 PET scans, one with 2-[18F]-fluoro-2-deoxy-D-glucose (FDG) and another with 2'-[18F]fluoroflumazenil (FFMZ), acquired 1 day apart. FDG was acquired for 10 min (static scan) 1 h after administration. An FFMZ scan was acquired for 60 min from radiopharmaceutical administration in a dynamic mode. Each brain PET image was segmented using a standard template implemented in PMOD 3.8. The pons was used as the reference region for modeling of the nondisplaceable binding potential (BPND)for FFMZ, and to obtain uptake ratios for FDG. SEEG studies of patients were performed as a part of their surgical evaluation to define the SOZ. RESULTS: Well-defined differences between HC and Ep were found with both radiopharmaceuticals, showing the utility to identify abnormal brain regions using quantitative PET imaging. Lateralization of the SOZ findings by PET (lower uptake/binding in a specific brain hemisphere) matched in 86% for FFMZ and 71% for FDG with SEEG data. CONCLUSION: Quantitative PET imaging is an excellent complementary tool that matches reasonably well with SEEG to define SOZ in presurgical evaluation.