Simultaneous EEG and fMRI reveals stronger sensitivity to orthographic strings in the left occipito-temporal cortex of typical versus poor beginning readers.
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ABSTRACT:
SUBMITTER: Pleisch G
PROVIDER: S-EPMC6974919 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Absence seizures cause transient impairment of consciousness. Typical absence seizures occur in children, and are accompanied by 3-4-Hz spike-wave discharges (SWDs) on electroencephalography (EEG). Prior EEG-functional magnetic resonance imaging (fMRI) studies of SWDs have shown a network of cortical and subcortical changes during these electrical events. However, fMRI during typical childhood absence seizures with confirmed impaired consciousness has not been previously investigated.We performed EEG-fMRI with simultaneous behavioral testing in 37 children with typical childhood absence epilepsy (CAE). Attentional vigilance was evaluated by a continuous performance task (CPT), and simpler motor performance was evaluated by a repetitive tapping task (RTT).SWD episodes were obtained during fMRI scanning from 9 patients among the 37 studied. fMRI signal increases during SWDs were observed in the thalamus, frontal cortex, primary visual, auditory, somatosensory, and motor cortex, and fMRI decreases were seen in the lateral and medial parietal cortex, cingulate gyrus, and basal ganglia. Omission error rate (missed targets) with SWDs during fMRI was 81% on CPT and 39% on RTT. For those seizure epochs during which CPT performance was impaired, fMRI changes were seen in cortical and subcortical structures typically involved in SWDs, whereas minimal changes were observed for the few epochs during which performance was spared.These findings suggest that typical absence seizures involve a network of cortical-subcortical areas necessary for normal attention and primary information processing. Identification of this network may improve understanding of cognitive impairments in CAE, and may help guide development of new therapies for this disorder.
| S-EPMC2953613 | biostudies-literature
Project description:Background: Potentially curative epilepsy surgery can be offered if a single, discrete epileptogenic zone (EZ) can be identified. For individuals in whom there is no clear concordance between clinical localization, scalp EEG, and imaging data, intracranial EEG (icEEG) may be needed to confirm a predefined hypothesis regarding irritative zone (IZ), seizure onset zone (SOZ), and EZ prior to surgery. However, icEEG has limited spatial sampling and may fail to reveal the full extent of epileptogenic network if predefined hypothesis is not correct. Simultaneous icEEG-fMRI has been safely acquired in humans and allows exploration of neuronal activity at the whole-brain level related to interictal epileptiform discharges (IED) captured intracranially. Methods: We report icEEG-fMRI in eight patients with refractory focal epilepsy who had resective surgery and good postsurgical outcome. Surgical resection volume in seizure-free patients post-surgically reflects confirmed identification of the EZ. IEDs on icEEG were classified according to their topographic distribution and localization (Focal, Regional, Widespread, and Non-contiguous). We also divided IEDs by their location within the surgical resection volume [primary IZ (IZ1) IED] or outside [secondary IZ (IZ2) IED]. The distribution of fMRI blood oxygen level-dependent (BOLD) changes associated with individual IED classes were assessed over the whole brain using a general linear model. The concordance of resulting BOLD map was evaluated by comparing localization of BOLD clusters with surgical resection volume. Additionally, we compared the concordance of BOLD maps and presence of BOLD clusters in remote brain areas: precuneus, cuneus, cingulate, medial frontal, and thalamus for different IED classes. Results: A total of 38 different topographic IED classes were identified across the 8 patients: Focal (22) and non-focal (16, Regional = 9, Widespread = 2, Non-contiguous = 5). Twenty-nine IEDs originated from IZ1 and 9 from IZ2. All IED classes were associated with BOLD changes. BOLD maps were concordant with the surgical resection volume for 27/38 (71%) IED classes, showing statistical global maximum BOLD cluster or another cluster in the surgical resection volume. The concordance of BOLD maps with surgical resection volume was greater (p < 0.05) for non-focal (87.5%, 14/16) as compared to Focal (59%, 13/22) IED classes. Additionally, BOLD clusters in remote cortical and deep brain areas were present in 84% (32/38) of BOLD maps, more commonly (15/16; 93%) for non-focal IED-related BOLD maps. Conclusions: Simultaneous icEEG-fMRI can reveal BOLD changes at the whole-brain level for a wide range of IEDs on icEEG. BOLD clusters within surgical resection volume and remote brain areas were more commonly seen for non-focal IED classes, suggesting that a wider hemodynamic network is at play.
| S-EPMC8490636 | biostudies-literature
Project description:Rising life expectancies coupled with an increasing awareness of age-related cognitive decline have led to the unwarranted use of psychopharmaceuticals, including acetylcholinesterase inhibitors (AChEIs), by significant numbers of healthy older individuals. This trend has developed despite very limited data regarding the effectiveness of such drugs on non-clinical groups and recent work indicates that AChEIs can have negative cognitive effects in healthy populations. For the first time, we use a combination of EEG and simultaneous EEG/fMRI to examine the effects of a commonly prescribed AChEI (donepezil) on cognition in healthy older participants. The short- and long-term impact of donepezil was assessed using two double-blind, placebo-controlled trials. In both cases, we utilised cognitive (paired associates learning (CPAL)) and electrophysiological measures (resting EEG power) that have demonstrated high-sensitivity to age-related cognitive decline. Experiment 1 tested the effects of 5 mg/per day dosage on cognitive and EEG markers at 6-hour, 2-week and 4-week follow-ups. In experiment 2, the same markers were further scrutinised using simultaneous EEG/fMRI after a single 5 mg dose. Experiment 1 found significant negative effects of donepezil on CPAL and resting Alpha and Beta band power. Experiment 2 replicated these results and found additional drug-related increases in the Delta band. EEG/fMRI analyses revealed that these oscillatory differences were associated with activity differences in the left hippocampus (Delta), right frontal-parietal network (Alpha), and default-mode network (Beta). We demonstrate the utility of simple cognitive and EEG measures in evaluating drug responses after acute and chronic donepezil administration. The presentation of previously established markers of age-related cognitive decline indicates that AChEIs can impair cognitive function in healthy older individuals. To our knowledge this is the first study to identify the precise neuroanatomical origins of EEG drug markers using simultaneous EEG/fMRI. The results of this study may be useful for evaluating novel drugs for cognitive enhancement.
| S-EPMC3169575 | biostudies-literature
Project description:ObjectiveThe concurrent recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is a technique that has received much attention due to its potential for combined high temporal and spatial resolution. However, the ballistocardiogram (BCG), a large-amplitude artifact caused by cardiac induced movement contaminates the EEG during EEG-fMRI recordings. Removal of BCG in software has generally made use of linear decompositions of the corrupted EEG. This is not ideal as the BCG signal propagates in a manner which is non-linearly dependent on the electrocardiogram (ECG). In this paper, we present a novel method for BCG artifact suppression using recurrent neural networks (RNNs).MethodsEEG signals were recovered by training RNNs on the nonlinear mappings between ECG and the BCG corrupted EEG. We evaluated our model's performance against the commonly used Optimal Basis Set (OBS) method at the level of individual subjects, and investigated generalization across subjects.ResultsWe show that our algorithm can generate larger average power reduction of the BCG at critical frequencies, while simultaneously improving task relevant EEG based classification.ConclusionThe presented deep learning architecture can be used to reduce BCG related artifacts in EEG-fMRI recordings.SignificanceWe present a deep learning approach that can be used to suppress the BCG artifact in EEG-fMRI without the use of additional hardware. This method may have scope to be combined with current hardware methods, operate in real-time and be used for direct modeling of the BCG.
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Project description:It has been proposed that poor reading abilities in deaf readers might be related to weak connections between the orthographic and lexical-semantic levels of processing. Here we used event related potentials (ERPs), known for their excellent time resolution, to examine whether lexical feedback modulates early orthographic processing. Twenty congenitally deaf readers made lexical decisions to target words and pseudowords. Each of those target stimuli could be preceded by a briefly presented matched-case or mismatched-case identity prime (e.g., ALTAR-ALTAR vs. altar- ALTAR). Results showed an early effect of case overlap at the N/P150 for all targets. Critically, this effect disappeared for words but not for pseudowords, at the N250-an ERP component sensitive to orthographic processing. This dissociation in the effect of case for word and pseudowords targets provides strong evidence of early automatic lexical-semantic feedback modulating orthographic processing in deaf readers. Interestingly, despite the dissociation found in the ERP data, behavioural responses to words still benefited from the physical overlap between prime and target, particularly in less skilled readers and those with less experience with words. Overall, our results support the idea that skilled deaf readers have a stronger connection between the orthographic and the lexical-semantic levels of processing.
| S-EPMC6707270 | biostudies-literature
Project description:Due to its millisecond-scale temporal resolution, EEG allows to assess neural correlates with precisely defined temporal relationship relative to a given event. This knowledge is generally lacking in data from functional magnetic resonance imaging (fMRI) which has a temporal resolution on the scale of seconds so that possibilities to combine the two modalities are sought. Previous applications combining event-related potentials (ERPs) with simultaneous fMRI BOLD generally aimed at measuring known ERP components in single trials and correlate the resulting time series with the fMRI BOLD signal. While it is a valuable first step, this procedure cannot guarantee that variability of the chosen ERP component is specific for the targeted neurophysiological process on the group and single subject level. Here we introduce a newly developed data-driven analysis procedure that automatically selects task-specific electrophysiological independent components (ICs). We used single-trial simultaneous EEG/fMRI analysis of a visual Go/Nogo task to assess inhibition-related EEG components, their trial-to-trial amplitude variability, and the relationship between this variability and the fMRI. Single-trial EEG/fMRI analysis within a subgroup of 22 participants revealed positive correlations of fMRI BOLD signal with EEG-derived regressors in fronto-striatal regions which were more pronounced in an early compared to a late phase of task execution. In sum, selecting Nogo-related ICs in an automated, single subject procedure reveals fMRI-BOLD responses correlated to different phases of task execution. Furthermore, to illustrate utility and generalizability of the method beyond detecting the presence or absence of reliable inhibitory components in the EEG, we show that the IC selection can be extended to other events in the same dataset, e.g., the visual responses.
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Project description:Functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), and diffusion tensor imaging (DTI) recording have complementary spatiotemporal resolution limitations but can be powerful methods when used together to enable both functional and anatomical modeling, with each neuroimaging procedure used to maximum advantage. We recorded EEGs during event-related fMRI followed by DTI in 15 healthy volunteers and 12 patients with schizophrenia using an omission mismatch negativity (MMN) paradigm. Blood oxygenation level-dependent (BOLD) signal changes were calculated in a region of interest (ROI) analysis, and fractional anisotropy (FA) in the white matter fibers related to each area was compared between groups using tract-specific analysis. Patients with schizophrenia had reduced BOLD activity in the left middle temporal gyrus, and BOLD activity in the right insula and right parahippocampal gyrus significantly correlated with positive symptoms on the Positive and Negative Syndrome Scale (PANSS) and hostility subscores. BOLD activation of Heschl's gyri also correlated with the limbic system, including the insula. FA values in the left anterior cingulate cortex (ACC) significantly correlated with changes in the BOLD signal in the right superior temporal gyrus (STG), and FA values in the right ACC significantly correlated with PANSS scores. This is the first study to examine MMN using simultaneous fMRI, EEG, and DTI recording in patients with schizophrenia to investigate the potential implications of abnormalities in the ACC and limbic system, including the insula and parahippocampal gyrus, as well as the STG. Structural changes in the ACC during schizophrenia may represent part of the neural basis for the observed MMN deficits. The deficits seen in the feedback/feedforward connections between the prefrontal cortex and STG modulated by the ACC and insula may specifically contribute to impaired MMN generation and clinical manifestations.
| S-EPMC6508624 | biostudies-literature
Project description:The current study investigated the influence of morphological structure on the earliest stages of Arabic reading acquisition. More specifically, we aimed at examining the role of root and pattern units in beginners from Grade 1 to 3. A first set of reading tasks evaluated the presence of a morphology facilitation effect in word and pseudoword reading by manipulating independently the frequency of roots and patterns. Additional tasks aimed at examining the contribution of morphological awareness to reading performance. The results suggest that reading ability is early influenced by the awareness of morphological composition. Children read faster and more accurately pseudowords composed of frequent morphemes. Furthermore, regression analyses revealed, for every reading measure, a significant contribution of one morphological test in addition to grapheme knowledge. Results are discussed taking into account the differences obtained depending on lexicality and morpheme type (root or pattern).
| S-EPMC7538675 | biostudies-literature
Project description:Accurately characterising the brain networks involved in seizure activity may have important implications for our understanding of epilepsy. Intracranial EEG-fMRI can be used to capture focal epileptic events in humans with exquisite electrophysiological sensitivity and allows for identification of brain structures involved in this phenomenon over the entire brain. We investigated ictal BOLD networks using the simultaneous intracranial EEG-fMRI (icEEG-fMRI) in a 30 year-old male undergoing invasive presurgical evaluation with bilateral depth electrode implantations in amygdalae and hippocampi for refractory temporal lobe epilepsy. One spontaneous focal electrographic seizure was recorded. The aims of the data analysis were firstly to map BOLD changes related to the ictal activity identified on icEEG and secondly to compare different fMRI modelling approaches. Visual inspection of the icEEG showed an onset dominated by beta activity involving the right amygdala and hippocampus lasting 6.4 s (ictal onset phase), followed by gamma activity bilaterally lasting 14.8 s (late ictal phase). The fMRI data was analysed using SPM8 using two modelling approaches: firstly, purely based on the visually identified phases of the seizure and secondly, based on EEG spectral dynamics quantification. For the visual approach the two ictal phases were modelled as 'ON' blocks convolved with the haemodynamic response function; in addition the BOLD changes during the 30 s preceding the onset were modelled using a flexible basis set. For the quantitative fMRI modelling approach two models were evaluated: one consisting of the variations in beta and gamma bands power, thereby adding a quantitative element to the visually-derived models, and another based on principal components analysis of the entire spectrogram in attempt to reduce the bias associated with the visual appreciation of the icEEG. BOLD changes related to the visually defined ictal onset phase were revealed in the medial and lateral right temporal lobe. For the late ictal phase, the BOLD changes were remote from the SOZ and in deep brain areas (precuneus, posterior cingulate and others). The two quantitative models revealed BOLD changes involving the right hippocampus, amygdala and fusiform gyrus and in remote deep brain structures and the default mode network-related areas. In conclusion, icEEG-fMRI allowed us to reveal BOLD changes within and beyond the SOZ linked to very localised ictal fluctuations in beta and gamma activity measured in the amygdala and hippocampus. Furthermore, the BOLD changes within the SOZ structures were better captured by the quantitative models, highlighting the interest in considering seizure-related EEG fluctuations across the entire spectrum.
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Project description:The presence of a change in a visual scene can influence brain activity and behavior, even in the absence of full conscious report. It may be possible for us to sense that such a change has occurred, even if we cannot specify exactly where or what it was. Despite existing evidence from electroencephalogram (EEG) and eye-tracking data, it is still unclear how this partial level of awareness relates to functional magnetic resonance imaging (fMRI) blood oxygen level dependent (BOLD) activation. Using EEG, fMRI, and a change blindness paradigm, we found multi-modal evidence to suggest that sensing a change is distinguishable from being blind to it. Specifically, trials during which participants could detect the presence of a colour change but not identify the location of the change (sense trials), were compared to those where participants could both detect and localise the change (localise or see trials), as well as change blind trials. In EEG, late parietal positivity and N2 amplitudes were larger for localised changes only, when compared to change blindness. However, ERP-informed fMRI analysis found no voxels with activation that significantly co-varied with fluctuations in single-trial late positivity amplitudes. In fMRI, a range of visual (BA17,18), parietal (BA7,40), and mid-brain (anterior cingulate, BA24) areas showed increased fMRI BOLD activation when a change was sensed, compared to change blindness. These visual and parietal areas are commonly implicated as the storage sites of visual working memory, and we therefore argue that sensing may not be explained by a lack of stored representation of the visual display. Both seeing and sensing a change were associated with an overlapping occipitoparietal network of activation when compared to blind trials, suggesting that the quality of the visual representation, rather than the lack of one, may result in partial awareness during the change blindness paradigm.
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