Epileptogenic Tubers Are Associated with Increased Kurtosis of Susceptibility Values: A Combined Quantitative Susceptibility Mapping and Stereoelectroencephalography Pilot Study.

BACKGROUND AND PURPOSE: Prior studies have found an association between calcification and the epileptogenicity of tubers in tuberous sclerosis complex. Quantitative susceptibility mapping is a novel tool sensitive to magnetic susceptibility alterations due to tissue calcification. We assessed the utility of quantitative susceptibility mapping in identifying putative epileptogenic tubers in tuberous sclerosis complex using stereoelectroencephalography data as ground truth. MATERIALS AND METHODS: We studied patients with tuberous sclerosis complex undergoing stereoelectroencephalography at a single center who had multiecho gradient-echo sequences available. Quantitative susceptibility mapping and R2* values were extracted for all tubers on the basis of manually drawn 3D ROIs using T1- and T2-FLAIR sequences. Characteristics of quantitative susceptibility mapping and R2* distributions from implanted tubers were compared using binary logistic generalized estimating equation models designed to identify ictal (involved in seizure onset) and interictal (persistent interictal epileptiform activity) tubers. These models were then applied to the unimplanted tubers to identify potential ictal and interictal tubers that were not sampled by stereoelectroencephalography. RESULTS: A total of 146 tubers were identified in 10 patients, 76 of which were sampled using stereoelectroencephalography. Increased kurtosis of the tuber quantitative susceptibility mapping values was associated with epileptogenicity (P = .04 for the ictal group and P = .005 for the interictal group) by the generalized estimating equation model. Both groups had poor sensitivity (35.0% and 44.1%, respectively) but high specificity (94.6% and 78.6%, respectively). CONCLUSIONS: Our finding of increased kurtosis of quantitative susceptibility mapping values (heavy-tailed distribution) was highly specific, suggesting that it may be a useful biomarker to identify putative epileptogenic tubers in tuberous sclerosis complex. This finding motivates the investigation of underlying tuber mineralization and other properties driving kurtosis changes in quantitative susceptibility mapping values.

Evaluation of DISORDER: Retrospective Image Motion Correction for Volumetric Brain MRI in a Pediatric Setting.

BACKGROUND AND PURPOSE: Head motion causes image degradation in brain MR imaging examinations, negatively impacting image quality, especially in pediatric populations. Here, we used a retrospective motion correction technique in children and assessed image quality improvement for 3D MR imaging acquisitions. MATERIALS AND METHODS: We prospectively acquired brain MR imaging at 3T using 3D sequences, T1-weighted MPRAGE, T2-weighted TSE, and FLAIR in 32 unsedated children, including 7 with epilepsy (age range, 2-18 years). We implemented a novel motion correction technique through a modification of k-space data acquisition: Distributed and Incoherent Sample Orders for Reconstruction Deblurring by using Encoding Redundancy (DISORDER). For each participant and technique, we obtained 3 reconstructions as acquired (Aq), after DISORDER motion correction (Di), and Di with additional outlier rejection (DiOut). We analyzed 288 images quantitatively, measuring 2 objective no-reference image quality metrics: gradient entropy (GE) and MPRAGE white matter (WM) homogeneity. As a qualitative metric, we presented blinded and randomized images to 2 expert neuroradiologists who scored them for clinical readability. RESULTS: Both image quality metrics improved after motion correction for all modalities, and improvement correlated with the amount of intrascan motion. Neuroradiologists also considered the motion corrected images as of higher quality (Wilcoxon z = -3.164 for MPRAGE; z = -2.066 for TSE; z = -2.645 for FLAIR; all P < .05). CONCLUSIONS: Retrospective image motion correction with DISORDER increased image quality both from an objective and qualitative perspective. In 75% of sessions, at least 1 sequence was improved by this approach, indicating the benefit of this technique in unsedated children for both clinical and research environments.

Modulation of epileptic networks by transient interictal epileptic activity: A dynamic approach to simultaneous EEG-fMRI.

Epileptic networks, defined as brain regions involved in epileptic brain activity, have been mapped by functional connectivity in simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) recordings. This technique allows to define brain hemodynamic changes, measured by the Blood Oxygen Level Dependent (BOLD) signal, associated to the interictal epileptic discharges (IED), which together with ictal events constitute a signature of epileptic disease. Given the highly time-varying nature of epileptic activity, a dynamic functional connectivity (dFC) analysis of EEG-fMRI data appears particularly suitable, having the potential to identify transitory features of specific connections in epileptic networks. In the present study, we propose a novel method, defined dFC-EEG, that integrates dFC assessed by fMRI with the information recorded by simultaneous scalp EEG, in order to identify the connections characterised by a dynamic profile correlated with the occurrence of IED, forming the dynamic epileptic subnetwork. Ten patients with drug-resistant focal epilepsy were included, with different aetiology and showing a widespread (or multilobar) BOLD activation, defined as involving at least two distinct clusters, located in two different lobes and/or extended to the hemisphere contralateral to the epileptic focus. The epileptic focus was defined from the IED-related BOLD map. Regions involved in the occurrence of interictal epileptic activity; i.e., forming the epileptic network, were identified by a general linear model considering the timecourse of the fMRI-defined focus as main regressor. dFC between these regions was assessed with a sliding-window approach. dFC timecourses were then correlated with the sliding-window variance of the IED signal (VarIED), to identify connections whose dynamics related to the epileptic activity; i.e., the dynamic epileptic subnetwork. As expected, given the very different clinical picture of each individual, the extent of this subnetwork was highly variable across patients, but was but was reduced of at least 30% with respect to the initially identified epileptic network in 9/10 patients. The connections of the dynamic subnetwork were most commonly close to the epileptic focus, as reflected by the laterality index of the subnetwork connections, reported higher than the one within the original epileptic network. Moreover, the correlation between dFC timecourses and VarIED was predominantly positive, suggesting a strengthening of the dynamic subnetwork associated to the occurrence of IED. The integration of dFC and scalp IED offers a more specific description of the epileptic network, identifying connections strongly influenced by IED. These findings could be relevant in the pre-surgical evaluation for the resection or disconnection of the epileptogenic zone and help in reaching a better post-surgical outcome. This would be particularly important for patients characterised by a widespread pathological brain activity which challenges the surgical intervention.

Phase-amplitude coupling and the BOLD signal: A simultaneous intracranial EEG (icEEG) - fMRI study in humans performing a finger-tapping task.

Although it has been consistently found that local blood-oxygen-level-dependent (BOLD) changes are better modelled by a combination of the power of multiple EEG frequency bands rather than by the power of a unique band alone, the local electro-haemodynamic coupling function is not yet fully characterised. Electrophysiological studies have revealed that the strength of the coupling between the phase of low- and the amplitude of high- frequency EEG activities (phase-amplitude coupling - PAC) has an important role in brain function in general, and in preparation and execution of movement in particular. Using electrocorticographic (ECoG) and functional magnetic resonance imaging (fMRI) data recorded simultaneously in humans performing a finger-tapping task, we investigated the single-trial relationship between the amplitude of the BOLD signal and the strength of PAC and the power of α, ß, and γ bands, at a local level. In line with previous studies, we found a positive correlation for the γ band, and negative correlations for the PACßγ strength, and the α and ß bands. More importantly, we found that the PACßγ strength explained variance of the amplitude of the BOLD signal that was not explained by a combination of the α, ß, and γ band powers. Our main finding sheds further light on the distinct nature of PAC as a functionally relevant mechanism and suggests that the sensitivity of EEG-informed fMRI studies may increase by including the PAC strength in the BOLD signal model, in addition to the power of the low- and high- frequency EEG bands.

A study of the electro-haemodynamic coupling using simultaneously acquired intracranial EEG and fMRI data in humans.

In current fMRI studies designed to map BOLD changes related to interictal epileptiform discharges (IED), which are recorded on simultaneous EEG, the information contained in the morphology and field extent of the EEG events is exclusively used for their classification. Usually, a BOLD predictor based on IED onset times alone is constructed, effectively treating all events as identical. We used intracranial EEG (icEEG)-fMRI data simultaneously recorded in humans to investigate the effect of including any of the features: amplitude, width (duration), slope of the rising phase, energy (area under the curve), or spatial field extent (number of contacts over which the sharp wave was observed) of the fast wave of the IED (the sharp wave), into the BOLD model, to better understand the neurophysiological origin of sharp wave-related BOLD changes, in the immediate vicinity of the recording contacts. Among the features considered, the width was the only one found to explain a significant amount of additional variance, suggesting that the amplitude of the BOLD signal depends more on the duration of the underlying field potential (reflected in the sharp wave width) than on the degree of neuronal activity synchrony (reflected in the sharp wave amplitude), and, consequently, that including inter-event variations of the sharp wave width in the BOLD signal model may increase the sensitivity of forthcoming EEG-fMRI studies of epileptic activity.

Social responsiveness to inanimate entities: Altered white matter in a 'social synaesthesia'.

Judgments about personalities and social traits can be made by relatively brief exposure to animate living things. Here we show that unusual architecture in the microstructure of the human brain is related to atypical mental projections of personality and social structure onto things that are neither living nor animate. Our participants experience automatic, life-long and consistent crossmodal associations between language sequences (e.g., letters, numbers and days) and complex personifications (e.g., A is a businessman; 7 a good-natured woman). Participants with this 'Ordinal Linguistic Personification' (Simner and Hubbard, 2006) which we describe here as a form of social synaesthesia, showed lower fractional anisotropy (FA) values in five clusters at whole-brain significance, compared with non-synaesthetes (in the pre-postcentral gyrus/dorsal corticospinal tract, left superior corona radiata, and the genu, body and left side of the corpus callosum). We found no regions of the brain with increased FA in synaesthetes. A number of these regions with reduced FA play a role in social responsiveness, and our study is the first to show that unusual differences in white matter microstructure in these regions is associated with compelling feelings of social cohesion and personality towards non-animate entities. We show too that altered patterns of connectivity known to typify synaesthesia are not limited to variants involving a 'merging of the senses', but also extend to what might be thought of as a cogno-social variant of synaesthesia, linking language and personality attributes in this surprising way.

Second fractures among older adults in the year following hip, shoulder, or wrist fracture.

UNLABELLED: We report on second fracture occurrence in the year following a hip, shoulder or wrist fracture using insurance claims. Among 273,330 people, 4.3 % had a second fracture; risk did not differ by first fracture type. Estimated adjusted second fracture probabilities may facilitate population-based evaluation of secondary fracture prevention strategies. INTRODUCTION: The purpose of this study was estimate second fracture risk for the older US population in the year following a hip, shoulder, or wrist fracture. METHODS: Observational cohort study of Medicare fee-for-service beneficiaries with an index hip, shoulder, or wrist fragility fracture in 2009. Time-to-event analyses using Cox proportional hazards models to characterize the relationship between index fracture type (hip, shoulder, wrist) and patient factors (age, gender, and comorbidity) on second fracture risk in the year following the index fracture. RESULTS: Among 273,330 individuals with fracture, 11,885 (4.3 %) sustained a second hip, shoulder or wrist fracture within one year. Hip fracture was most common, regardless of the index fracture type. Comparing adjusted second fracture risks across index fracture types reveals that the magnitude of second fracture risk within each age-comorbidity group is similar regardless of the index fracture. Men and women face similar risks with frequently overlapping confidence intervals, except among women aged 85 years or older who are at greater risk. CONCLUSIONS: Regardless of index fracture type, second fractures are common in the year following hip, shoulder or wrist fracture. Secondary fracture prevention strategies that take a population perspective should be informed by these estimates which take competing mortality risks into account.

Cross-modal tactile-taste interactions in food evaluations.

Detecting the taste components within a flavoured substance relies on exposing chemoreceptors within the mouth to the chemical components of ingested food. In our paper, we show that the evaluation of taste components can also be influenced by the tactile quality of the food. We first discuss how multisensory factors might influence taste, flavour and smell for both typical and atypical (synaesthetic) populations and we then present two empirical studies showing tactile-taste interactions in the general population. We asked a group of non-synaesthetic adults to evaluate the taste components of flavoured food substances, whilst we presented simultaneous cross-sensory visuo-tactile cues within the eating environment. Specifically, we presented foodstuffs between subjects that were otherwise identical but had a rough versus smooth surface, or were served on a rough versus smooth serving-plate. We found no effect of the serving-plate, but we found the rough/smoothness of the foodstuff itself significantly influenced perception: food was rated as significantly more sour if it had a rough (versus smooth) surface. In modifying taste perception via ostensibly unrelated dimensions, we demonstrate that the detection of tastes within flavours may be influenced by higher level cross-sensory cues. Finally, we suggest that the direction of our cross-sensory associations may speak to the types of hedonic mapping found both in normal multisensory integration, and in the unusual condition of synaesthesia.

Pasture-derived greenhouse gas emissions in cow-calf production systems.

There is a lack of information regarding carbon dioxide (CO), methane (CH), and nitrous oxide (NO) emissions from pasture soils and the effects of grazing. The objective of this study was to quantify greenhouse gas (GHG) fluxes from pasture soils grazed with cow-calf pairs managed with different stocking rates and densities. The central hypothesis was that irrigated low-density stocking systems (SysB) would result in greater GHG emissions from pasture soils than nonirrigated high-density stocking systems (SysA) and grazing-exclusion (GRE) pasture sites. The nonirrigated high-density stocking systems consisted of 120 cow-calf pairs rotating on a total of 120 ha (stocking rate 1 cow/ha, stocking density 112,000 kg BW/ha, rest period of 60 to 90 d). The irrigated low-density stocking systems consisted of 64 cow-calf pairs rotating on a total of 26 ha of pasture (stocking rate 2.5 cows/ha, stocking density 32,700 kg BW/ha, rest period of 18 to 30 d). Both systems consisted of mixed cool-season grass-legume pastures. Static chambers were randomly placed for collection of CO, CH, and NO samples. Soil temperature (ST), ambient temperature (temperature inside the chamber; AT), and soil water content (WC) were monitored and considered explanatory variables for GHG emissions. GHG fluxes were monitored for 3 yr (2011 to 2013) at the beginning (P1) and at the end (P2) of the grazing season, always postgrazing. Paddock was the experimental unit (3 pseudoreplicates per treatment), and chambers (30 chambers per paddock) were considered multiple measurements of each experimental unit. A completely randomized design considered the term year × period as a repeated measure and chamber nested within paddock and treatment as the random term. Generally, SysB had greater CO emissions than SysA and GRE pasture sites across years and periods ( < 0.01). Soil temperature, AT, and WC had effects on CO emissions. Methane and NO emissions were observed from pasture sites of the 3 systems, but the effect of grazing was not constantly significant for CH and NO emissions. In addition, ST, AT, and WC did not conclusively explain CH and NO emissions. No clear trade-offs between GHG were observed; generally, GHG emissions increased from 2011 to 2013, which was likely associated with weather conditions, such as higher daily temperature and precipitation events. The central hypothesis that SysB would result in greater GHG emissions from pasture soils than SysA and GRE was not confirmed.

Enteric methane from lactating beef cows managed with high- and low-input grazing systems.

The objective of this study was to compare methane (CH) emissions from lactating beef cows grazed with different combinations of stocking rate and density. We hypothesized that a low stocking rate coupled with high-stocking-density grazing management would result in poorer forage quality, thereby increasing enteric CH emissions. System A (SysA) consisted of 120 cow-calf pairs rotating on a total of 120 ha divided into 2-ha pastures (stocking rate 1 cow/ha, stocking density 112,000 kg BW/ha, rest period of 60 to 90 d). System B (SysB) consisted of 16 groups of 4 cow-calf pairs each rotating on a 1.6-ha pasture (stocking rate 2.5 cows/ha, stocking density 32,000 kg BW/ha, rest period of 18 to 30 d). Enteric CH measurements were collected using a sulfur hexafluoride (SF) tracer gas method. Sampling occurred during 2012 and 2013 in 2 periods: the beginning (P1) and end of the grazing season (P2). Cannulated Angus cows were stratified by weight, age, and parity and were assigned to each treatment ( = 6) in a crossover design with a doubly repeated measures design, with period and day as repeated measures (α = 0.05). Dry matter intake was determined using chromic oxide (CrO) as a marker. Forage samples were collected ( = 3) for nutrient composition analyses and total forage mass determination. Forage botanical composition was determined using the dry-weight-rank method. Postgrazing herbage mass was greater for SysA during P2 in 2012 ( < 0.01) and 2013 ( = 0.01). Grasses were predominant and represented 67% to 96% of pastures; legumes contributed 3% to 21% of pastures across periods and treatments. The proportion of legumes tended to be higher in SysB pasture sites in P2 than in P1. There were no treatment effects on DMI. There was a period effect on DMI ( < 0.01); DMI of SysA and SysB cows increased from P1 to P2 (4 and 1.1 kg DMI/d increase, respectively). Cows ingested, on average, 2.6% (SysA) and 2.8% (SysB) of their BW. There was no year effect on CH emissions ( = 0.16). Daily enteric CH emissions did not vary with treatment and ranged from 195 to 249 g CH/d across treatment. Enteric CH emissions per unit GE intake varied with treatment during P1 (6.4% and 3.8% for SysA and SysB, respectively; < 0.01). Across treatments and periods, enteric CH emission per unit GE intake was 4.6%, which could be considered low for grazing lactating beef cows. It is likely that cows in the present study were selecting high-quality forage and produced comparatively lower CH emissions.

Validating a standardised test battery for synesthesia: Does the Synesthesia Battery reliably detect synesthesia?

Synesthesia is a neurological condition that gives rise to unusual secondary sensations (e.g., reading letters might trigger the experience of colour). Testing the consistency of these sensations over long time intervals is the behavioural gold standard assessment for detecting synesthesia (e.g., Simner, Mulvenna et al., 2006). In 2007 however, Eagleman and colleagues presented an online 'Synesthesia Battery' of tests aimed at identifying synesthesia by assessing consistency but within a single test session. This battery has been widely used but has never been previously validated against conventional long-term retesting, and with a randomly recruited sample from the general population. We recruited 2847 participants to complete The Synesthesia Battery and found the prevalence of grapheme-colour synesthesia in the general population to be 1.2%. This prevalence was in line with previous conventional prevalence estimates based on conventional long-term testing (e.g., Simner, Mulvenna et al., 2006). This reproduction of similar prevalence rates suggests that the Synesthesia Battery is indeed a valid methodology for assessing synesthesia.

Classification of EEG abnormalities in partial epilepsy with simultaneous EEG-fMRI recordings.

Scalp EEG recordings and the classification of interictal epileptiform discharges (IED) in patients with epilepsy provide valuable information about the epileptogenic network, particularly by defining the boundaries of the "irritative zone" (IZ), and hence are helpful during pre-surgical evaluation of patients with severe refractory epilepsies. The current detection and classification of epileptiform signals essentially rely on expert observers. This is a very time-consuming procedure, which also leads to inter-observer variability. Here, we propose a novel approach to automatically classify epileptic activity and show how this method provides critical and reliable information related to the IZ localization beyond the one provided by previous approaches. We applied Wave_clus, an automatic spike sorting algorithm, for the classification of IED visually identified from pre-surgical simultaneous Electroencephalogram-functional Magnetic Resonance Imagining (EEG-fMRI) recordings in 8 patients affected by refractory partial epilepsy candidate for surgery. For each patient, two fMRI analyses were performed: one based on the visual classification and one based on the algorithmic sorting. This novel approach successfully identified a total of 29 IED classes (compared to 26 for visual identification). The general concordance between methods was good, providing a full match of EEG patterns in 2 cases, additional EEG information in 2 other cases and, in general, covering EEG patterns of the same areas as expert classification in 7 of the 8 cases. Most notably, evaluation of the method with EEG-fMRI data analysis showed hemodynamic maps related to the majority of IED classes representing improved performance than the visual IED classification-based analysis (72% versus 50%). Furthermore, the IED-related BOLD changes revealed by using the algorithm were localized within the presumed IZ for a larger number of IED classes (9) in a greater number of patients than the expert classification (7 and 5, respectively). In contrast, in only one case presented the new algorithm resulted in fewer classes and activation areas. We propose that the use of automated spike sorting algorithms to classify IED provides an efficient tool for mapping IED-related fMRI changes and increases the EEG-fMRI clinical value for the pre-surgical assessment of patients with severe epilepsy.

Simultaneous intracranial EEG-fMRI in humans: protocol considerations and data quality.

We have recently performed simultaneous intracranial EEG and fMRI recordings (icEEG-fMRI) in patients with epilepsy. In this technical note, we examine limited thermometric data for potential electrode heating during our protocol and found that heating was ≤0.1 °C in-vitro at least 10 fold less than in-vivo limits. We quantify EEG quality, which can be degraded by MRI scanner-induced artefacts, and fMRI image (gradient echo echo-planar imaging: GE-EPI) signal quality around the electrodes, which can be degraded by electrode interactions with B1 (radiofrequency) and B0 (static) magnetic fields. We recorded EEG outside and within the MRI scanner with and without scanning. EEG quality was largely preserved during scanning and in particular heartbeat-related artefacts were small compared to epileptic events. To assess the GE-EPI signal reduction around the electrodes, we compared image signal intensity along paths into the brain normal to its surface originating from the individual platinum-iridium electrode contacts. GE-EPI images were obtained at 1.5 T with an echo time (TE) of 40 ms and repetition time (TR) of 3000 ms and a slice thickness of 2.5 mm. We found that GE-EPI signal intensity reduction was confined to a 10 mm radius and that it was reduced on average by less than 50% at 5mm from the electrode contacts. The GE-EPI image signal reduction also varied with electrode orientation relative to the MRI scanner axes; in particular, cortical grid contacts with a normal along the scanner's main magnetic field (B(0)) axis have higher artefact levels relative to those with a normal perpendicular to the z-axis. This suggests that the artefacts were predominantly susceptibility-related rather than due to B1 interactions. This information can be used to guide interpretation of results of icEEG-fMRI experiments proximal to the electrodes, and to optimise artefact reduction strategies.

Improving the sensitivity of EEG-fMRI studies of epileptic activity by modelling eye blinks, swallowing and other video-EEG detected physiological confounds.

RATIONALE: To improve the sensitivity and specificity of simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) it is prudent to devise modelling strategies explaining the residual variance. The purpose of this study is to investigate the potential value of including additional regressors for physiological activities, derived from video-EEG, in the modelling of haemodynamic patterns linked to interictal epileptiform discharges (IEDs) using simultaneously recorded video-EEG-fMRI. METHODS: Ten patients with IED (focal epilepsy: 6, idiopathic generalized epilepsy (IGE):4) were studied. BOLD-sensitive fMRI images were acquired on a 3T MRI scanner. 64-channel EEG was recorded using MR-compatible system. A custom made, dual-video-camera system synchronised with EEG was used to record video simultaneously. IEDs and physiological activities were identified and labelled on video-EEG using Brain Analyzer2. fMRI time-series data were pre-processed and analysed using SPM5 software. Two general linear models (GLM) were created; GLM1: IEDs were convolved with the canonical haemodynamic response function and its derivatives. Realignment parameters and pulse regressors were included in the design matrix as confounds, GLM2: GLM1 and additional regressors identified on video-EEG including: eye blinks, hand or foot movement, chewing and swallowing were also included in the design matrix. SPM [F] maps (p<0.05, corrected for family wise error and p<0.001, uncorrected) were generated for both models. We compared the resulting blood oxygen level dependent (BOLD) maps for cluster size, statistical significance and degree of concordance with the irritative zone. RESULTS: BOLD changes relating to physiological activities were generally seen in expected brain areas. In patients with focal epilepsy, the extent and Z-score of the IED-related global maximum BOLD clusters increased in 4/6 patients and additional IED-related BOLD clusters were observed in 3/6 patients for GLM2. Also, the degree of concordance of IED-related maps with irritative zone improved for one patient for GLM2 and was unchanged for the other cases. In patients with IGE, the size and statistical significance for global maximum and other BOLD clusters increased in 2/4 patients. We conclude that the inclusion of additional regressors, derived from video based information, in the design matrix explains a greater amount of variance and can reveal additional IED-related BOLD clusters which may be part of the epileptic networks.

First Report of Pepino mosaic virus Infecting Tomato in South Africa.

Pepino mosaic virus (PepMV) (genus Potexvirus) is a highly infectious virus that is responsible for significant losses in yield of tomato fruit (Solanum lycopersicum) across Europe, Asia, and the Americas in the last decade (1). During the winter growing season of 2008, uneven discoloration of tomato fruit from farms in Limpopo Province, South Africa, was detected at the Pretoria fresh produce market. Twenty fruit were randomly selected from five different suppliers in this region and the 100 samples were batched into subsamples of five fruit. Leaves with suspect mosaic and bubbling symptoms were also detected from farms in Limpopo and were thus sampled. Leaf and fruit samples were tested by double antibody-sandwich (DAS)-ELISA (2) using polyclonal antibodies against PepMV (Agdia, Elkhart, IN) combined with appropriate positive and negative controls. Fruit samples from two of the suppliers, and all leaf samples tested, reacted strongly with PepMV antibodies. Inoculum was prepared from pooled DAS-ELISA-positive leaf samples and inoculated onto 10, 4-week-old, susceptible S. lycopersicum cv. Rooikhaki seedlings. After 3 weeks, all inoculated plants had developed characteristic PepMV symptoms (2) including leaf bubbling, distortion, and curled leaves. Older leaves developed yellow spots and light/dark green leaf mosaic while apical regions were stunted and branches were distorted to form 'nettle-head' symptoms. Fruit surfaces were marbled or displayed flaming and uneven discoloration. Leaves from symptomatic plants were sampled for confirmation of PepMV infection by DAS-ELISA and all samples reacted positively with PepMV antibodies. Total RNA was extracted from 500-µg replicates of pooled leaf samples from infected plants with the RNeasy Plant Mini Kit (Qiagen, Hilden, Germany), and amplified by conventional two-step reverse-transcription-PCR using a PepMV-specific primer set: Ker 1 (2) and PepCP-R (4) for a 986-bp region, including the coat protein, of the PepMV genome. PCR products were cloned into pTZ57R/T vector (Fermentas, Vilnius, Lithuania [UAB]) and six clones were purified and sequenced using universal M13 primers (3). Phylogenetic analysis clustered the sequence with EU (European), LP (Peruvian), US1 (United States)/CH1 (Chilean) and US2/CH2 PepMV isolates. The PepMV isolate accessions for US2/CH2 (AY509927, FJ612601, EF408821, FJ212288, and DQ000985) were identified as the closest relatives based on 98 to 99% nucleotide similarity obtained using BLASTN. The coat protein sequence of the South African isolate was submitted to GenBank (Accession No. HQ872607). To our knowledge, this is the first confirmed report of PepMV in South Africa. Further studies are necessary to determine its incidence and spread in this country. The presence of PepMV signals the urgent need for adoption of appropriate phytosanitary measures to restrict the spread and impact of this virus. References: (1) I. M. Hanssen and B. P. H. J. Thomma. Mol. Plant Pathol. 11:179, 2010. (2) I. M. Hanssen et al. Plant Pathol. 58:450, 2009. (3) J. Messing. Method Enzymol. 101:20, 1983. (4) I. Pagán et al. Phytopathology 96:274, 2006.

Imaging haemodynamic changes related to seizures: comparison of EEG-based general linear model, independent component analysis of fMRI and intracranial EEG.

BACKGROUND: Simultaneous EEG-fMRI can reveal haemodynamic changes associated with epileptic activity which may contribute to understanding seizure onset and propagation. METHODS: Nine of 83 patients with focal epilepsy undergoing pre-surgical evaluation had seizures during EEG-fMRI and analysed using three approaches, two based on the general linear model (GLM) and one using independent component analysis (ICA): The results were compared with intracranial EEG. RESULTS: The canonical GLM analysis revealed significant BOLD signal changes associated with seizures on EEG in 7/9 patients, concordant with the seizure onset zone in 4/7. The Fourier GLM analysis revealed changes in BOLD signal corresponding with the results of the canonical analysis in two patients. ICA revealed components spatially concordant with the seizure onset zone in all patients (8/9 confirmed by intracranial EEG). CONCLUSION: Ictal EEG-fMRI visualises plausible seizure related haemodynamic changes. The GLM approach to analysing EEG-fMRI data reveals localised BOLD changes concordant with the ictal onset zone when scalp EEG reflects seizure onset. ICA provides additional information when scalp EEG does not accurately reflect seizures and may give insight into ictal haemodynamics.

Continuous EEG source imaging enhances analysis of EEG-fMRI in focal epilepsy.

INTRODUCTION: EEG-correlated fMRI (EEG-fMRI) studies can reveal haemodynamic changes associated with Interictal Epileptic Discharges (IED). Methodological improvements are needed to increase sensitivity and specificity for localising the epileptogenic zone. We investigated whether the estimated EEG source activity improved models of the BOLD changes in EEG-fMRI data, compared to conventional << event-related >> designs based solely on the visual identification of IED. METHODS: Ten patients with pharmaco-resistant focal epilepsy underwent EEG-fMRI. EEG Source Imaging (ESI) was performed on intra-fMRI averaged IED to identify the irritative zone. The continuous activity of this estimated IED source (cESI) over the entire recording was used for fMRI analysis (cESI model). The maps of BOLD signal changes explained by cESI were compared to results of the conventional IED-related model. RESULTS: ESI was concordant with non-invasive data in 13/15 different types of IED. The cESI model explained significant additional BOLD variance in regions concordant with video-EEG, structural MRI or, when available, intracranial EEG in 10/15 IED. The cESI model allowed better detection of the BOLD cluster, concordant with intracranial EEG in 4/7 IED, compared to the IED model. In 4 IED types, cESI-related BOLD signal changes were diffuse with a pattern suggestive of contamination of the source signal by artefacts, notably incompletely corrected motion and pulse artefact. In one IED type, there was no significant BOLD change with either model. CONCLUSION: Continuous EEG source imaging can improve the modelling of BOLD changes related to interictal epileptic activity and this may enhance the localisation of the irritative zone.

The spatio-temporal mapping of epileptic networks: combination of EEG-fMRI and EEG source imaging.

Simultaneous EEG-fMRI acquisitions in patients with epilepsy often reveal distributed patterns of Blood Oxygen Level Dependant (BOLD) change correlated with epileptiform discharges. We investigated if electrical source imaging (ESI) performed on the interictal epileptiform discharges (IED) acquired during fMRI acquisition could be used to study the dynamics of the networks identified by the BOLD effect, thereby avoiding the limitations of combining results from separate recordings. Nine selected patients (13 IED types identified) with focal epilepsy underwent EEG-fMRI. Statistical analysis was performed using SPM5 to create BOLD maps. ESI was performed on the IED recorded during fMRI acquisition using a realistic head model (SMAC) and a distributed linear inverse solution (LAURA). ESI could not be performed in one case. In 10/12 remaining studies, ESI at IED onset (ESIo) was anatomically close to one BOLD cluster. Interestingly, ESIo was closest to the positive BOLD cluster with maximal statistical significance in only 4/12 cases and closest to negative BOLD responses in 4/12 cases. Very small BOLD clusters could also have clinical relevance in some cases. ESI at later time frame (ESIp) showed propagation to remote sources co-localised with other BOLD clusters in half of cases. In concordant cases, the distance between maxima of ESI and the closest EEG-fMRI cluster was less than 33 mm, in agreement with previous studies. We conclude that simultaneous ESI and EEG-fMRI analysis may be able to distinguish areas of BOLD response related to initiation of IED from propagation areas. This combination provides new opportunities for investigating epileptic networks.

Recent advances in recording electrophysiological data simultaneously with magnetic resonance imaging.

Simultaneous recording of brain activity by different neurophysiological modalities can yield insights that reach beyond those obtained by each technique individually, even when compared to those from the post-hoc integration of results from each technique recorded sequentially. Success in the endeavour of real-time multimodal experiments requires special hardware and software as well as purpose-tailored experimental design and analysis strategies. Here, we review the key methodological issues in recording electrophysiological data in humans simultaneously with magnetic resonance imaging (MRI), focusing on recent technical and analytical advances in the field. Examples are derived from simultaneous electroencephalography (EEG) and electromyography (EMG) during functional MRI in cognitive and systems neuroscience as well as in clinical neurology, in particular in epilepsy and movement disorders. We conclude with an outlook on current and future efforts to achieve true integration of electrical and haemodynamic measures of neuronal activity using data fusion models.

Independent component analysis of interictal fMRI in focal epilepsy: comparison with general linear model-based EEG-correlated fMRI.

The general linear model (GLM) has been used to analyze simultaneous EEG-fMRI to reveal BOLD changes linked to interictal epileptic discharges (IED) identified on scalp EEG. This approach is ineffective when IED are not evident in the EEG. Data-driven fMRI analysis techniques that do not require an EEG derived model may offer a solution in these circumstances. We compared the findings of independent components analysis (ICA) and EEG-based GLM analyses of fMRI data from eight patients with focal epilepsy. Spatial ICA was used to extract independent components (IC) which were automatically classified as either BOLD-related, motion artefacts, EPI-susceptibility artefacts, large blood vessels, noise at high spatial or temporal frequency. The classifier reduced the number of candidate IC by 78%, with an average of 16 BOLD-related IC. Concordance between the ICA and GLM-derived results was assessed based on spatio-temporal criteria. In each patient, one of the IC satisfied the criteria to correspond to IED-based GLM result. The remaining IC were consistent with BOLD patterns of spontaneous brain activity and may include epileptic activity that was not evident on the scalp EEG. In conclusion, ICA of fMRI is capable of revealing areas of epileptic activity in patients with focal epilepsy and may be useful for the analysis of EEG-fMRI data in which abnormalities are not apparent on scalp EEG.