Continuous electroencephalography characteristics and acute symptomatic seizures in COVID-19 patients

ObjectiveAs concerns regarding neurological manifestations in COVID-19 (coronavirus disease 2019) patients increase, limited data exists on continuous electroencephalography (cEEG) findings in these patients. We present a retrospective cohort study of cEEG monitoring in COVID-19 patients to better explore this knowledge gap.MethodsAmong 22 COVID-19 patients, 19 underwent cEEGs, and 3 underwent routine EEGs (<1 h). Demographic and clinical variables, including comorbid conditions, discharge disposition, survival and cEEG findings, were collected.ResultscEEG was performed for evaluation of altered mental status (n = 17) or seizure-like events (n = 5). Five patients, including 2 with epilepsy, had epileptiform abnormalities on cEEG. Two patients had electrographic seizures without a prior epilepsy history. There were no acute neuroimaging findings. Periodic discharges were noted in one-third of patients and encephalopathic EEG findings were not associated with IV anesthetic use.ConclusionsInterictal epileptiform abnormalities in the absence of prior epilepsy history were rare. However, the discovery of asymptomatic seizures in two of twenty-two patients was higher than previously reported and is therefore of concern.SignificancecEEG monitoring in COVID-19 patients may aid in better understanding an epileptogenic potential of SARS-CoV2 infection. Nevertheless, larger studies utilizing cEEG are required to better examine acute epileptic risk in COVID-19 patients.     

Monitoring of patients with brainstem hemorrhage: A simultaneous study of quantitative electroencephalography and transcranial Doppler

ObjectiveTo explore whether quantitative electroencephalography (QEEG) and transcranial Doppler (TCD) can be used to evaluate patients with acute severe brainstem hemorrhage (ASBH).MethodsWe prospectively enrolled patients with ASBH and assessed their mortality at the 90-day follow-up. The patients' demographic data, serological data, and clinical factors were recorded. Quantitative brain function monitoring was performed using a TCD-QEEG recording system attached to the patient’s bedside.ResultsThirty-one patients (55.3 ± 10.6 years; 17 men) were studied. Mortality at 90 days was at 61.3%. There was no significant difference in TCD-related parameters between the survival group and the death group (p > 0.05). Among the QEEG-related indexes, only the (delta + theta)/(alpha + beta) ratio (DTABR) (odds ratio 11.555, 95%confidence interval 1.413–94.503, p = 0.022) was an independent predictor of clinical outcome; the area under the ROC curve of DTABR was 0.921, cut-off point was 3.88, sensitivity was 79%, and specificity was 100%.ConclusionsIn patients with ASBH, QEEG can effectively inform the clinical prognosis regarding 90-day mortality, while TCD cannot.SignificanceQEEG shows promise for informing the mortality prognosis of patients with ASBH.     

Quantitative EEG improves prediction of Sturge-Weber syndrome in infants with port-wine birthmark

ObjectivePort-wine birthmark (PWB) is a common occurrence in the newborn, and general pediatricians, dermatologists, and ophthalmologists are often called on to make an assessment of risk for Sturge-Weber syndrome (SWS) due to workforce shortages in pediatric neurologists and MRI’s low sensitivity for SWS brain involvement in infants. We therefore aimed to develop a quantitative EEG (qEEG) approach to safely screen young infants with PWB for SWS risk and optimal timing of diagnostic MRI.MethodsForty-eight infants (prior to first birthday) underwent EEG recording. Signal processing methods compared voltage between left and right sides using a previously defined pipeline and diagnostic threshold. In this test sample, we compared sensitivity/specificity of the qEEG metric against MRI performed after the first birthday. We also used likelihood ratio testing to determine whether qEEG adds incremental information beyond topographical extent of PWB, another risk marker of brain involvement.ResultsqEEG helped predict SWS risk in the first year of life (p = 0.031), with a sensitivity of 50% and a specificity of 81%. It added about 40% incremental information beyond PWB extent alone (p = 0.042).ConclusionqEEG adds information to risk prediction in infants with facial PWB.SignificanceqEEG can be used to help determine whether to obtain an MRI in the first year of life. The data collected can assist in developing a predictive model risk calculator that incorporates both PWB extent and qEEG results, which can be validated and then employed in the community.     

Phase-amplitude coupling of ripple activities during seizure evolution with theta phase

ObjectiveHigh-frequency activities (HFAs) and phase-amplitude coupling (PAC) are key neurophysiological biomarkers for studying human epilepsy. We aimed to clarify and visualize how HFAs are modulated by the phase of low-frequency bands during seizures.MethodsWe used intracranial electrodes to record seizures of focal epilepsy (12 focal-to-bilateral tonic-clonic seizures and three focal-aware seizures in seven patients). The synchronization index, representing PAC, was used to analyze the coupling between the amplitude of ripples (80–250 Hz) and the phase of lower frequencies. We created a video in which the intracranial electrode contacts were scaled linearly to the power changes of ripple.ResultsThe main low frequency band modulating ictal-ripple activities was the θ band (4–8 Hz), and after completion of ictal-ripple burst, δ (1–4 Hz)-ripple PAC occurred. The ripple power increased simultaneously with rhythmic fluctuations from the seizure onset zone, and spread to other regions.ConclusionsRipple activities during seizure evolution were modulated by the θ phase. The PAC phenomenon was visualized as rhythmic fluctuations.SignificanceRipple power associated with seizure evolution increased and spread with fluctuations. The θ oscillations related to the fluctuations might represent the common neurophysiological processing involved in seizure generation.     

Epileptogenic network of focal epilepsies mapped with cortico-cortical evoked potentials

ObjectiveThe goal of this study was to investigate the spatial extent and functional organization of the epileptogenic network through cortico-cortical evoked potentials (CCEPs) in patients being evaluated with intracranial stereoelectroencephalography.MethodsWe retrospectively included 25 patients. We divided the recorded sites into three regions: epileptogenic zone (EZ); propagation zone (PZ); and noninvolved zone (NIZ). The root mean square of the amplitudes was calculated to reconstruct effective connectivity network. We also analyzed the N1/N2 amplitudes to explore the responsiveness influenced by epileptogenicity. Prognostic analysis was performed by comparing intra-region and inter-region connectivity between seizure-free and non-seizure-free groups.ResultsOur results confirmed that stimulation of the EZ caused the strongest responses on other sites within and outside the EZ. Moreover, we found a hierarchical connectivity pattern showing the highest connectivity strength within EZ, and decreasing connectivity gradient from EZ, PZ to NIZ. Prognostic analysis indicated a stronger intra-EZ connection in the seizure-free group.ConclusionThe EZ showed highest excitability and dominantly influenced other regions. Quantitative CCEPs can be useful in mapping epileptic networks and predicting surgical outcome.SignificanceThe generated computational connectivity model may enhance our understanding of epileptogenic networks and provide useful information for surgical planning and prognosis prediction.     

Age-related characteristics and normative values of F waves in healthy infants

ObjectiveTo establish age-related characteristics and normative values of F waves in healthy Chinese infants.MethodsWe studied median, ulnar and tibial nerves on one side distally in 229 healthy Chinese infants (108 males) ranging from 1 to 12 months old.ResultsMinimal F-wave latencies (Fmin) showed a strong negative correlation to the age for median, ulnar and tibial nerves (P < 0.01) but no correlation to the height. Statistical analyses revealed a significant (P < 0.01) decrease of Fmin during the second month of life and no change (P > 0.05) thereafter. Dividing the infants into 1 month old (Group 1) and 2–12 months old (Group 2), normal values (Mean ± SD ms) of Fmin for tibial, median and ulnar nerves consisted of 23.38 ± 1.68, 17.19 ± 0.95 and 16.47 ± 1.06 for Group 1 and 21.42 ± 1.25, 14.50 ± 1.15 and 14.52 ± 0.90 for Group 2.ConclusionF-wave latencies shorten in the 2nd month of life and change little thereafter when age-related maturation counters the concomitant growth of the nerve length.SignificanceF waves can assess infantile neuropathies as a reliable measure, complementing the technically difficult conventional nerve conduction study in short limbs.     

Brain maturation in the first 3 months of life,measured by electroencephalogram: A comparison between preterm and term-born infants

ObjectivePreterm infants are at risk for altered brain maturation resulting in neurodevelopmental impairments. Topographical analysis of high-density electroencephalogram during sleep matches underlying brain maturation. Using such an EEG mapping approach could identify preterm infants at risk early in life.Methods20 preterm (gestational age < 32 weeks) and 20 term-born infants (gestational age > 37 weeks) were recorded by 18-channel daytime sleep-EEG at term age (GA 40 weeks for preterm and 2–3 days after birth for term infants) and 3 months (corrected age for preterm infants).ResultsPreterm infant’s power spectrum at term age is immature, leveling off with term infants at 3 months of age. Topographical distribution of maximal power density however, reveals qualitative differences between the groups until 3 months of age. Preterm infants exhibit more temporal than central activation at term age and more occipital than central activation at 3 months of age. Moreover, being less mature at term age predicts being less mature at 3 months of age.ConclusionTopographical analysis of sleep EEG reveals changes in brain maturation between term and preterm infants early in life.SignificanceIn future, automated analysis tools using topographical power distribution could help identify preterm infants at risk early in life.     

Quantitative assessment of muscle echogenicity in Charcot-Marie-Tooth disease type 1A by automatic thresholding methods

ObjectiveTo investigate the utility of automatic thresholding methods for quantitative muscle echogenicity assessment as a marker of disease severity in Charcot-Marie-Tooth disease type 1A (CMT1A).MethodsMuscle ultrasound was performed in 15 CMT1A patients and 7 healthy controls. Muscle echogenicity of six limb muscles in each subject was assessed by 16 automatic thresholding methods and conventional grey-scale analysis. Echogenicity of each method in CMT1A patients was compared with that in controls. A correlation between the echogenicity and CMT neuropathy score (CMTNS) was also analysed in CMT1A patients.ResultsSignificant differences in mean echogenicity of the 6 muscles between CMT1A patients and controls were found both in grey-scale analysis (p < 0.01) and 11 of the 16 automatic thresholding methods (p < 0.05 in each method). In CMT1A patients, mean echogenicity of the 6 muscles was positively correlated with CMTNS in 8 of the 16 automatic thresholding methods, but not in grey-scale analysis.ConclusionAutomatic thresholding methods can be used to detect the difference in muscle echogenicity between CMT1A patients and controls. Echogenicity parameters correlate with the disease severity.SignificanceQuantitative muscle echogenicity assessment by automatic thresholding methods shows potential as a surrogate marker of disease progression in CMT1A.     

Inter-ictal network of focal epilepsy and effects of clinical factors on network activity

ObjectiveAim of the study was to explore the inter-ictal, resting-state EEG network in patients with focal epilepsy (FE) and to specify clinical factors that influence network activity.MethodsFunctional EEG connectivity (EEGfC) differences were computed between 232 FE patients (FE group) and 77 healthy controls. EEGfC was computed among 23 cortical regions within each hemisphere, for 25 very narrow bands from 1 to 25 Hz. We computed independent effects for six clinical factors on EEGfC in the FE group, by ANOVA and post-hoc t-statistics, corrected for multiple comparisons by false discovery rate method.ResultsRobust, statistically significant EEGfC differences emerged between the FE and the healthy control groups. Etiology, seizure type, duration of the illness and antiepileptic treatment were independent factors that influenced EEGfC. Statistically significant results occurred selectively in one or a few very narrow bands and outlined networks. Most abnormal EEGfC findings occurred at frequencies that mediate integrative and motor activities.ConclusionsFE patients have abnormal resting-state EEGfC network activity. Clinical factors significantly modify EEGfC.SignificanceDelineation of the FE network and modifying factors can open the way for targeted investigations and introduction of EEGfC into epilepsy research and practice.     

Family nurture intervention alters relationships between preterm infant EEG delta brush characteristics and term age EEG power

ObjectiveFamily Nurture Intervention (FNI) facilitates mother/infant emotional connection, improves neurodevelopmental outcomes and increases electroencephalogram (EEG) power at term age. Here we explored whether delta brushes (DB), early EEG bursts that shape brain development, are altered by FNI and mediate later effects of FNI on EEG.MethodsWe assessed DB characteristics in EEG data from a randomized controlled trial comparing infants with standard care (SC, n = 31) versus SC + FNI (n = 33) at ~35 and ~40 weeks GA.ResultsCompared to SC infants, FNI infant DB amplitude increased more from ~35 to ~40 weeks, and FNI infants had longer duration DBs. DB parameters (rate, amplitude, brush frequency) at ~35 weeks were correlated with power at ~40 weeks, but only in SC infants. FNI effects on DB parameters do not mediate FNI effects on EEG power or coherence at term.ConclusionsDBs are related to subsequent brain activity and FNI alters DB parameters. However, FNI’s effects on electrocortical activity at term age are not dependent on its earlier effects on DBs.SignificanceWhile early DBs can have important effects on later brain activity in preterm infants, facilitating emotional connection with FNI may allow brain maturation to be less dependent on early bursts.     

Quantitative electrocorticographic biomarkers of clinical outcomes in mesial temporal lobe epileptic patients treated with the RNS® system

ObjectivesFind interictal electrocorticographic (ECoG) biomarkers of clinical outcomes in mesiotemporal lobe (MTL) epilepsy patients.MethodsIn the NeuroPace® RNS® System clinical trials with 256 patients, 20 MTL patients with the most reduction in clinical seizures at Year 7 compared to baseline (upper response quartile; −96.5% median change) and 20 with the least reduction in clinical seizures (lower response quartile; −17.4% median change) were evaluated. Clinical and interictal ECoG features from the two response quartiles were compared.ResultsDemographic and clinical features were similar in the upper and lower response quartiles. Interictal spike rate (ISR) was substantially lower (p < 0.0001) in the upper quartile patients, while normalized theta (4–8 Hz) and normalized gamma (>25 Hz) were also different (p < 0.05) between the two response quartiles. ISR was positively correlated (p < 0.05) with clinical seizure rates in 71% of the channels analyzed. ECoG records captured during months with no clinical seizures had the lowest ISR.ConclusionsISR is a strong differentiator of clinical response in MTL patients. Normalized theta and gamma also differentiates clinical response.SignificanceIn MTL patients, the interictal spike rate along with spectral power computed from chronic ambulatory baseline ECoGs may serve as biomarkers of clinical outcomes and maybe used as treatment endpoints.     

Sex differences in the inflammatory response to stress and risk of adverse cardiovascular outcomes among patients with coronary heart disease

Stress may contribute to progression of coronary heart disease (CHD) through inflammation, especially among women. Thus, we sought to examine whether increased inflammatory response to stress among patients with CHD is associated with a greater risk of cardiovascular events and whether this risk is higher in women. We examined inflammatory biomarkers known to increase with mental stress (speech task), including interleukin-6 (IL-6), monocyte chemoattractant protein-1 (MCP-1), and matrix metallopeptidase-9 (MMP-9) among 562 patients with stable CHD. Inflammatory response, the difference between post-stress and resting values, was examined as a predictor of major adverse cardiovascular events (MACE) using subdistribution hazards models for competing risks adjusting for demographics, cardiovascular risk factors, and medications. MACE was defined as a composite endpoint of cardiovascular death, myocardial infarction, unstable angina with revascularization, and heart failure. All biomarkers were standardized. The mean age was 63 years (range 34–79) and 24% were women. During a median follow-up of 3 years, 71 patients experienced MACE. Overall, there was no significant association between inflammatory response to stress and risk of MACE, but there were sex-based interactions for IL-6 (p = 0.001) and MCP-1 (p = 0.01). The risk of MACE increased 56% (HR: 1.56; 95% CI: 1.21, 2.01; p = 0.001) and 30% (HR: 1.30; 95% 1.09, 1.55; p = 0.004) for each standard deviation increase in IL-6 and MCP-1 response to mental stress for women, respectively, while there was no association among men. Increased inflammation in response to stress is associated with future adverse cardiovascular outcomes among women with CHD.     

Delayed neonatal visual evoked potentials are associated to asymmetric growth pattern in twins

ObjectivesTo study the association between intrauterine growth and visual pathways maturation by neonatal visual evoked potentials (VEPs) in twins, in view of a possible prognostic role.MethodsSeventy-four twin neonates from 37 pregnancies were selected based on gestational age of more than 30 weeks and uneventful perinatal clinical course. Flash VEPs were recorded at the same postmenstrual age in each twin pair. The association between P2 latency and anthropometric variables at birth was analyzed by comparison within each twin pair and regarding each variable as ordered difference between the two twins.ResultsAnalysis of differences within each twin pair highlighted that inter-twin difference in P2 latency was significantly related to difference in ponderal index (PI) (p = 0.048).Expressing the difference in latency as a categorical binary variable, the correlation was significant for both difference in PI, (median difference = −0.36, 95% CI −0.54 to −0.14, p = 0.001) and difference in body mass index (BMI), (median difference = −1.06, 95% CI −1.74 to −0.29, p = 0.006).ConclusionsLower values of PI and BMI differences are associated to delayed VEP latency in twin pairs.SignificanceVEP latency suggests reduced myelination of visual pathways when difference in growth pattern occurs in twins.     

Quantitative evaluation of WEB shape modification: A five-year follow-up study

Background and purposeWeb shape modification (WSM) has previously been associated with aneurysm recurrence. We report here our five-year experience of WEB device use with a quantitative approach of the WSM phenomenon.MethodsFrom July 2012 to July 2017, 50 patients with 51 unruptured aneurysms treated with the WEB device have been prospectively enrolled in our data base and retrospectively analyzed. An independent “core lab” evaluated anatomical results and potential WSM in DSA follow-up. We defined the WSM ratio (WSMr) as a relative index between the height and the width of the device in working projections which gave an evaluation of the device deformation over the time.ResultsDuring the total follow-up period, WSM was observed in 35/48 aneurysms (72.9%). Adequate occlusion rates were 87.0% and 92.6% with and without WSM respectively (P = 0.65). 30 out the 35 (85.7%) shape modifications were already noticed at short-term follow-up (6-month DSA). 33 patients had 2 DSA controls and WSMr measurements were available in 24 patients: 18 (75%) with WSM and 6 (25%) without WSM. In the group with WSM, WSMr values were 0.80 in post-embolization, 0.52 at the first DSA angiogram and 0.42 at the second DSA angiogram.ConclusionWEB shape modification was observed in more than half of cases but with no influence regarding adequate occlusion rate. This quantitative approach of WSM highlights that this phenomenon appears to be early and progressive over time. This supports the hypothesis that WSM could be more probably related to aneurysm healing rather than external compression.     

Measuring the effects of first antiepileptic medication in Temporal Lobe Epilepsy: Predictive value of quantitative-EEG analysis

ObjectiveTo determine the quantitative EEG responses in a population of drug-naïve patients with Temporal Lobe Epilepsy (TLE) after Levetiracetam (LEV) initiation as first antiepileptic drug (AED). We hypothesized that the outcome of AED treatment can be predicted from EEG data in patients with TLE.MethodsTwenty-three patients with TLE and twenty-five healthy controls were examined. Clinical outcome was dichotomized into seizure-free (SF) and non-seizure-free (NSF) after two years of LEV. EEG parameters were compared between healthy controls and patients with TLE at baseline (EEG^pre) and after three months of AED therapy (EEG^pre-post) and between SF and NSF patients. Receiver Operating Characteristic curves models were built to test whether EEG parameters predicted outcome.ResultsAED therapy induces an increase in EEG power for Alpha (p = 0.06) and a decrease in Theta (p < 0.05). Connectivity values were lower in SF compared to NSF patients (p < 0.001). Quantitative EEG predicted outcome after LEV treatment with an estimated accuracy varying from 65.2% to 91.3% (area under the curve [AUC] = 0.56–0.93) for EEG^pre and from 69.9% to 86.9% (AUC = 0.69–0.94) for EEG^pre-post.ConclusionsAED therapy induces EEG modifications in TLE patients, and such modifications are predictive of clinical outcome.SignificanceQuantitative EEG may help understanding the effect of AEDs in the central nervous system and offer new prognostic biomarkers for patients with epilepsy.     

Sleep modulates effective connectivity: A study using intracranial stimulation and recording

ObjectiveSleep is an active process with an important role in memory. Epilepsy patients often display a disturbed sleep architecture, with consequences on cognition. We aimed to investigate the effect of sleep on cortical networks’ organization.MethodsWe analyzed cortico-cortical evoked responses elicited by single pulse electrical stimulation (SPES) using intracranial depth electrodes in 25 patients with drug-resistant focal epilepsy explored using stereo-EEG. We applied the SPES protocol during wakefulness and NREM – N2 sleep. We analyzed 31,710 significant responses elicited by 799 stimulations covering most brain structures, epileptogenic or non-epileptogenic. We analyzed effective connectivity between structures using a graph-theory approach.ResultsSleep increases excitability in the brain, regardless of epileptogenicity. Local and distant connections are differently modulated by sleep, depending on the tissue epileptogenicity.In non-epileptogenic areas, frontal lobe connectivity is enhanced during sleep. There is increased connectivity between the hippocampus and temporal neocortex, while perisylvian structures are disconnected from the temporal lobe. In epileptogenic areas, we found a clear interhemispheric difference, with decreased connectivity in the right hemisphere during sleep.ConclusionsSleep modulates brain excitability and reconfigures functional brain networks, depending on tissue epileptogenicity.SignificanceWe found specific patterns of information flow during sleep in physiologic and pathologic structures, with possible implications for cognition.     

Recording cortico-cortical evoked potentials of the human arcuate fasciculus under general anaesthesia

ObjectiveWe examined the feasibility of using cortico-cortical evoked potentials (CCEPs) to monitor the major cortical white matter tract involved in language, the arcuate fasciculus (AF), during surgery under general anaesthesia.MethodsWe prospectively recruited nine patients undergoing surgery for lesions in the left peri-sylvian cortex, for whom awake surgery was not indicated. High angular resolution diffusion imaging (HARDI) tractography was used to localise frontal and temporal AF terminations, which guided intraoperative cortical strip placement.ResultsCCEPs were successfully evoked in 5/9 patients, showing a positive potential (P1) at 12 ms and a negative component (N1) at 21 ms when stimulating from the frontal lobe and recording in the temporal lobe. CCEP responses peaked in the posterior middle temporal gyrus. No CCEPs were evoked when stimulating temporal sites and recording from frontal contacts.ConclusionFor the first time, we show that CCEPs can be evoked from the peri-sylvian cortices also in adult patients who are not candidates for awake procedures. Our results are akin to those described in the awake setting and suggest the recorded activity is conveyed by the arcuate fasciculus.SignificanceThis intraoperative approach may have promising implications in reducing deficits in patients that require surgery in language areas under general anesthesia.     

EEG functional connectivity contributes to outcome prediction of postanoxic coma

ObjectiveTo investigate the additional value of EEG functional connectivity features, in addition to non-coupling EEG features, for outcome prediction of comatose patients after cardiac arrest.MethodsProspective, multicenter cohort study. Coherence, phase locking value, and mutual information were calculated in 19-channel EEGs at 12 h, 24 h and 48 h after cardiac arrest. Three sets of machine learning classification models were trained and validated with functional connectivity, EEG non-coupling features, and a combination of these. Neurological outcome was assessed at six months and categorized as “good” (Cerebral Performance Category [CPC] 1–2) or “poor” (CPC 3–5).ResultsWe included 594 patients (46% good outcome). A sensitivity of 51% (95% CI: 34–56%) at 100% specificity in predicting poor outcome was achieved by the best functional connectivity-based classifier at 12 h after cardiac arrest, while the best non-coupling-based model reached a sensitivity of 32% (0–54%) at 100% specificity using data at 12 h and 48 h. Combination of both sets of features achieved a sensitivity of 73% (50–77%) at 100% specificity.ConclusionFunctional connectivity measures improve EEG based prediction models for poor outcome of postanoxic coma.SignificanceFunctional connectivity features derived from early EEG hold potential to improve outcome prediction of coma after cardiac arrest.     

Neurophysiological adaptations to spaceflight and simulated microgravity

Changes in physiological functions after spaceflight and simulated spaceflight involve several mechanisms. Microgravity is one of them and it can be partially reproduced with models, such as head down bed rest (HDBR). Yet, only a few studies have investigated in detail the complexity of neurophysiological systems and their integration to maintain homeostasis. Central nervous system changes have been studied both in their structural and functional component with advanced techniques, such as functional magnetic resonance (fMRI), showing the main involvement of the cerebellum, cortical sensorimotor, and somatosensory areas, as well as vestibular-related pathways. Analysis of electroencephalography (EEG) led to contrasting results, mainly due to the different factors affecting brain activity. The study of corticospinal excitability may enable a deeper understanding of countermeasures' effect, since greater excitability has been shown being correlated with better preservation of functions. Less is known about somatosensory evoked potentials and peripheral nerve function, yet they may be involved in a homeostatic mechanism fundamental to thermoregulation. Extending the knowledge of such alterations during simulated microgravity may be useful not only for space exploration, but for its application in clinical conditions and for life on Earth, as well.     

Characterization of EEG-based functional brain networks in myotonic dystrophy type 1

ObjectiveIn the autosomal dominant, multisystem, chronic progressive disease myotonic dystrophy type 1 (DM1), cognitive deficits may originate from disrupted functional brain networks. We aimed to use network analysis of resting-state electro-encephalography (EEG) recordings of patients with DM1 and matched unaffected controls to investigate changes in network organization in large-scale functional brain networks and correlations with cognitive deficits.MethodsIn this cross-sectional study, 28 adult patients with genetically confirmed DM1 and 26 age-, sex- and education-matched unaffected controls underwent resting-state EEG and neuropsychological assessment. We calculated the Phase Lag Index (PLI) to determine EEG frequency-dependent functional connectivity between brain regions. Functional brain networks were characterized by applying concepts from graph theory and compared between-groups. Network topology was evaluated using the minimum spanning tree (MST). We evaluated correlations between network metrics and neuropsychological tests that showed statistically significant between-group differences.ResultsFunctional connectivity estimated as whole-brain median PLI for DM1 patients versus healthy controls was higher in theta band (0.141 [0.050] versus 0.125 [0.018], p = 0.029), and lower in the upper alpha band (0.154 [0.048] versus 0.182 [0.073], p = 0.038), respectively. Functional MST-constructed networks in DM1 patients were significantly dissimilar from healthy controls in the delta, (p = 0.009); theta, (p = 0.009); lower alpha, (p = 0.036); and upper alpha, (p = 0.008) bands. In evaluation of local MST network measures, trends toward networks with higher global integration in the theta band and lower global integration in the upper alpha band were observed. Compared to unaffected controls, DM1 patients performed worse on tests of attention, motor function, executive function and visuospatial memory. Visuospatial memory correlated with the global median PLI in the upper alpha band; the Stroop interference test correlated with betweenness centrality in this band.ConclusionThis study supports the hypothesis that brain changes in DM1 give rise to disrupted functional network organization, as modelled with EEG-based networks. Further study may help unravel the relations with clinical brain-related DM1 symptoms.SignificanceEEG network analysis has potential to help understand brain related DM1 phenotypes.FundingThis work was supported by the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 305697 (OPTIMISTIC) and the Marigold Foundation.