215,430 research outputs found
Dynamic BOLD functional connectivity in humans and its electrophysiological correlates
No full textNeural oscillations subserve many human perceptual and cognitive operations. Accordingly, brain functional connectivity is not static in time, but fluctuates dynamically following the synchronization and desynchronization of neural populations. This dynamic functional connectivity has recently been demonstrated in spontaneous fluctuations of the Blood Oxygen Level-Dependent (BOLD) signal, measured with functional Magnetic Resonance Imaging (fMRI). We analyzed temporal fluctuations in BOLD connectivity and their electrophysiological correlates, by means of long (≈50 min) joint electroencephalographic (EEG) and fMRI recordings obtained from two populations: 15 awake subjects and 13 subjects undergoing vigilance transitions. We identified positive and negative correlations between EEG spectral power (extracted from electrodes covering different scalp regions) and fMRI BOLD connectivity in a network of 90 cortical and subcortical regions (with millimeter spatial resolution). In particular, increased alpha (8-12 Hz) and beta (15-30 Hz) power were related to decreased functional connectivity, whereas gamma (30-60 Hz) power correlated positively with BOLD connectivity between specific brain regions. These patterns were altered for subjects undergoing vigilance changes, with slower oscillations being correlated with functional connectivity increases. Dynamic BOLD functional connectivity was reflected in the fluctuations of graph theoretical indices of network structure, with changes in frontal and central alpha power correlating with average path length. Our results strongly suggest that fluctuations of BOLD functional connectivity have a neurophysiological origin. Positive correlations with gamma can be interpreted as facilitating increased BOLD connectivity needed to integrate brain regions for cognitive performance. Negative correlations with alpha suggest a temporary functional weakening of local and long-range connectivity, associated with an idling state
The BOLD MRI response of the brain to alterations in arterial blood pressure
No full textThe impact of blood pressure changes on cerebral blood flow is an important area of investigation. The cerebral autoregulation mechanism acts to maintain blood supply to the brain, despite changes in blood pressure. Blood flow alterations are closely linked to neuronal activation, and this activity can be visualised using blood oxygenation level dependent magnetic resonance imaging (BOLD MRI) – functional MRI. The aim of this project is to investigate the effect of dynamic blood pressure stimuli on the BOLD MRI signal in the brain. Two blood pressure stimuli were employed; thigh cuff deflation and the Valsalva manoeuvre. BOLD MRI signal changes were measured throughout both challenges. Arterial and venous blood pressure and tympanic membrane displacement (TMD) measurements were also made during these challenges. Blood pressure data was used to drive two linked models. The first model represented cerebral vascular physiology (Ursino) and this fed into a second model (Buxton), which predicted the resulting BOLD signal changes. This allowed comparison with experimental BOLD data. TMD data was also compared to intracranial pressure changes predicted by the Ursino model. The experimental BOLD data was found to agree reasonably well with the BOLD signal changes predicted by the modelling. BOLD signal changes are most influenced by deoxyhaemoglobin changes, predominantly as a result of blood flow alterations during the blood pressure challenges, which are not immediately compensated for by the autoregulation mechanism. TMD changes did not reflect intracranial pressure changes predicted by the modelling. In conclusion, if such blood pressure changes do occur during a functional MRI experiment, they may cause changes in the BOLD signal that are not due to neuronal activation. These signal changes may be employed to investigate the cerebral autoregulation mechanism across the brain, or to correct for inaccuracies in functional MRI data in patients with impaired cerebral autoregulatio
An investigation of the relationship between BOLD and perfusion signal changes during epileptic generalised spike wave activity
No full textIn pathological conditions interpretation of functional magnetic resonance imaging (fMRI) results can be difficult. This is due to a reliance on the assumed coupling between neuronal activity and changes in cerebral blood flow (CBF) and oxygenation. We wanted to investigate the coupling between blood oxygen level dependant contrast (BOLD) and CBF time courses in epilepsy patients with generalised spike wave activity (GSW) to better understand the underlying mechanisms behind the EEG-fMRI signal changes observed, especially in regions of negative BOLD response (NBR). Four patients with frequent GSW were scanned with simultaneous electroencephalographic (EEG)-fMRI with BOLD and arterial spin labeling (ASL) sequences. We examined the relationship between simultaneous CBF and BOLD measurements by looking at the correlation of the two signals in terms of percentage signal change on a voxel-by-voxel basis. This method is not reliant on coincident activation. BOLD and CBF were positively correlated in patients with epilepsy during background EEG activity and GSW. The subject average value of the ΔCBF/ΔBOLD slope lay between +19 and +36 and also showed spatial variation which could indicate areas with altered vascular response. There was not a significant difference between ΔCBF/ΔBOLD during GSW, suggesting that neurovascular coupling to BOLD signal is generally maintained between states and, in particular, within areas of NBR
Boosting BOLD fMRI by K-Space density weighted echo planar imaging
No full textFunctional magnetic resonance imaging (fMRI) has become a powerful and influential method to non-invasively study neuronal brain activity. For this purpose, the blood oxygenation level-dependent (BOLD) effect is most widely used. T2* weighted echo planar imaging (EPI) is BOLD sensitive and the prevailing fMRI acquisition technique. Here, we present an alternative to its standard Cartesian recordings, i.e. k-space density weighted EPI, which is expected to increase the signal-to-noise ratio in fMRI data. Based on in vitro and in vivo pilot measurements, we show that fMRI by k-space density weighted EPI is feasible and that this new acquisition technique in fact boosted spatial and temporal SNR as well as the detection of local fMRI activations. Spatial resolution, spatial response function and echo time were identical for density weighted and conventional Cartesian EPI. The signal-to-noise ratio gain of density weighting can improve activation detection and has the potential to further increase the sensitivity of fMRI investigations
Noncanonical spike-related BOLD responses in focal epilepsy
No full textTill now, most studies of the Blood Oxygen Level-Dependent (BOLD) response to interictal epileptic discharges (IED) have assumed that its time course matches closely to that of brief physiological stimuli, commonly called the canonical event-related haemodynamic response function (canonical HRF). Analyses based on that assumption have produced significant response patterns that are generally concordant with prior electroclinical data. In this work, we used a more flexible model of the event-related response, a Fourier basis set, to investigate the presence of other responses in relation to individual IED in 30 experiments in patients with focal epilepsy. We found significant responses that had a noncanonical time course in 37% of cases, compared with 40% for the conventional, canonical HRF-based approach. In two cases, the Fourier analysis suggested activations where the conventional model did not. The noncanonical activations were almost always remote from the presumed generator of epileptiform activity. In the majority of cases with noncanonical responses, the noncanonical responses in single-voxel clusters were suggestive of artifacts. We did not find evidence for IED-related noncanonical HRFs arising from areas of pathology, suggesting that the BOLD response to IED is primarily canonical. Noncanonical responses may represent a number of phenomena, including artefacts and propagated epileptiform activity
From Blood Oxygenation Level Dependent (BOLD) signals to brain temperature maps
No full textA theoretical framework is presented for converting Blood Oxygenation Level Dependent (BOLD) images to temperature maps, based on the idea that disproportional local changes in cerebral blood flow (CBF) as compared with cerebral metabolic rate of oxygen consumption (CMRO2) during functional brain activity, lead to both brain temperature changes and the BOLD effect. Using an oxygen limitation model and a BOLD signal model we obtain a transcendental equation relating CBF and CMRO2 changes with the corresponding BOLD signal, which is solved in terms of the Lambert W function. Inserting this result in the dynamic bio-heat equation describing the rate of temperature changes in the brain, we obtain a non autonomous ordinary differential equation that depends on the BOLD response, which is solved numerically for each brain voxel. In order to test the method, temperature maps obtained from a real BOLD dataset are calculated showing temperature variations in the range: (-0.15, 0.1) which is consistent with experimental results. The method could find potential clinical uses as it is an improvement over conventional methods which require invasive probes and can record only few locations simultaneously. Interestingly, the statistical analysis revealed that significant temperature variations are more localized than BOLD activations. This seems to exclude the use of temperature maps for mapping neuronal activity as areas where it is well known that electrical activity occurs (such as V5 bilaterally) are not activated in the obtained maps. But it also opens questions about the nature of the information processing and the underlying vascular network in visual areas that give rise to this result
Analysis of excellence efforts at the fruit trade division of Bold Agro Kft.
No full textKiválósági törekvések vizsgálata a Bold Agro Kft.-nél, az efqm modell segítségével és benchmarkok keresése a szervezeten belülKEVállalkozásfejlesztésMSc/M
The spatio-temporal mapping of epileptic networks: Combination of EEG–fMRI and EEG source imaging
No full textSimultaneous 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
Continuous EEG source imaging enhances analysis of EEG-fMRI in focal epilepsy
No full textIntroduction: 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
Links between properties of system dynamics captured by the PLRNN-BOLD-SSM and behavioral task performance.
No full textA. Average power spectra for PLRNN-generated time series when external inputs were excluded (left) and included (right), and for the original BOLD traces (yellow). M = 9 latent states were used in this analysis, as at this M the number of stable and unstable objects appeared to roughly plateau (S2A Fig). The left grey line marks the frequency of one entire task sequence cycle (3⋅72s = 216s = .0046Hz) and the right grey line the frequency of one task and resting block (36s+36s = 72s = .0139 Hz). The peaks in the power spectra of the model-generated time series at these points indicate that the PLRNN has captured the periodic reoccurrence of single task blocks as well as that of the whole task block sequence in its limit cycle activity. B. Relation of the number of stable and unstable dynamical objects (see Methods) to behavioral performance for models without external inputs (M = 9; see S2B Fig for data pooled across M = 2…10). Low and high performance groups were formed according to median splits over correct responses during the CMT. A repeated measures ANOVA with between-subject factor ‘performance’ (‘low’ vs. ‘high’ percentage of correct responses) and within-subject factor ‘stability’ (‘stable’ vs. ‘unstable’ objects) revealed a significant 2-way ‘performance x stability’ interaction (F(1,24) = 5.28, p = .031). We focused on the CMT for this analysis since for the other two tasks performance was close to a ceiling effect (although results still hold when averaging across tasks, p = .012).</p
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