BOLD fMRI
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BACKGROUND: Spatial and temporal resolution of brain network activity can be improved by combining different modalities. Functional Magnetic Resonance Imaging (fMRI) provides full brain coverage with limited temporal resolution, while electroencephalography (EEG), estimates cortical activity with high temporal resolution. Combining them may provide improved network characterization. NEW METHOD: We examined relationships between EEG spatiospectral pattern timecourses and concurrent fMRI BOLD signals using canonical hemodynamic response function (HRF) with its 1st and 2nd temporal derivatives in voxel-wise general linear models (GLM). HRF shapes were derived from EEG-fMRI time courses during "resting-state", visual oddball and semantic decision paradigms. RESULTS: The resulting GLM F-maps self-organized into several different large-scale brain networks (LSBNs) often with different timing between EEG and fMRI revealed through differences in GLM-derived HRF shapes (e.g., with a lower time to peak than the canonical HRF). We demonstrate that some EEG spatiospectral patterns (related to concurrent fMRI) are weakly task-modulated. COMPARISON WITH EXISTING METHOD(S): Previously, we demonstrated 14 independent EEG spatiospectral patterns within this EEG dataset, stable across the resting-state, visual oddball and semantic decision paradigms. Here, we demonstrate that their time courses are significantly correlated with fMRI dynamics organized into LSBN structures. EEG-fMRI derived HRF peak appears earlier than the canonical HRF peak, which suggests limitations when assuming a canonical HRF shape in EEG-fMRI. CONCLUSIONS: This is the first study examining EEG-fMRI relationships among independent EEG spatiospectral patterns over different paradigms. The findings highlight the importance of considering different HRF shapes when spatiotemporally characterizing brain networks using EEG and fMRI.
- MeSH
- dospělí MeSH
- elektroencefalografie metody MeSH
- funkční zobrazování neurálních procesů metody MeSH
- lidé MeSH
- magnetická rezonanční tomografie metody MeSH
- mladý dospělý MeSH
- nervová síť diagnostické zobrazování fyziologie MeSH
- neurovaskulární vazba fyziologie MeSH
- psycholingvistika MeSH
- velký mozek diagnostické zobrazování fyziologie MeSH
- zraková percepce fyziologie MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
OBJECTIVE: Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. APPROACH: The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component's time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. MAIN RESULTS: We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. SIGNIFICANCE: Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral constraints are applied on the EEG data.
- MeSH
- časové faktory MeSH
- dospělí MeSH
- elektroencefalografie metody MeSH
- lidé MeSH
- magnetická rezonanční tomografie metody MeSH
- mladý dospělý MeSH
- mozek diagnostické zobrazování fyziologie MeSH
- nervová síť diagnostické zobrazování fyziologie MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Several laboratories have consistently reported small concentration changes in lactate, glutamate, aspartate, and glucose in the human cortex during prolonged stimuli. However, whether such changes correlate with blood oxygenation level-dependent functional magnetic resonance imaging (BOLD-fMRI) signals have not been determined. The present study aimed at characterizing the relationship between metabolite concentrations and BOLD-fMRI signals during a block-designed paradigm of visual stimulation. Functional magnetic resonance spectroscopy (fMRS) and fMRI data were acquired from 12 volunteers. A short echo-time semi-LASER localization sequence optimized for 7 Tesla was used to achieve full signal-intensity MRS data. The group analysis confirmed that during stimulation lactate and glutamate increased by 0.26 ± 0.06 μmol/g (~30%) and 0.28 ± 0.03 μmol/g (~3%), respectively, while aspartate and glucose decreased by 0.20 ± 0.04 μmol/g (~5%) and 0.19 ± 0.03 μmol/g (~16%), respectively. The single-subject analysis revealed that BOLD-fMRI signals were positively correlated with glutamate and lactate concentration changes. The results show a linear relationship between metabolic and BOLD responses in the presence of strong excitatory sensory inputs, and support the notion that increased functional energy demands are sustained by oxidative metabolism. In addition, BOLD signals were inversely correlated with baseline γ-aminobutyric acid concentration. Finally, we discussed the critical importance of taking into account linewidth effects on metabolite quantification in fMRS paradigms.
- MeSH
- dospělí MeSH
- GABA metabolismus MeSH
- glukosa metabolismus MeSH
- kyselina glutamová metabolismus MeSH
- kyselina mléčná metabolismus MeSH
- kyslík krev MeSH
- lidé středního věku MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- mladý dospělý MeSH
- světelná stimulace * MeSH
- zrakové korové centrum fyziologie MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Research Support, N.I.H., Extramural MeSH
Dopamine depletion in the axons of Parkinson's disease (PD) patients precedes depletion in cell bodies thus proposing that macroscopic connectivity can be used to understand disease mechanism. A novel multivariate functional connectivity analysis, based on high order coherence among four fMRI BOLD signals was applied on resting-state fMRI data of controls and PD patients (OFF and ON medication states) and unidirectional multiple-region pathways in the sensorimotor system were identified. Pathways were classified as "preserved" (unaffected by the disease), "damaged" (not observed in patients) and "corrected" (observed in controls and in PD-ON state). The majority of all pathways were feedforward, most of them with the pattern "S1→M1→SMA." Of these pathways, 67% were "damaged," 28% "preserved," and 5% "corrected." Prefrontal cortex (PFC) afferent and efferent pathways that corresponded to goal directed and habitual activities corresponded to recurrent circuits. Eighty-one percent of habitual afferent had internal cue (i.e., M1→S1→), of them 79% were "damaged" and the rest "preserved." All goal-directed afferent had external cue (i.e., S1→M1→) with third "damaged," third "preserved," and third "corrected." Corrected pathways were initiated in the dorsolateral PFC. Reduced connectivity of the SMA and PFC resulted from reduced sensorimotor afferent to these regions. Reduced sensorimotor internal cues to the PFC resulted with reduced habitual processes. Levodopa effects were for pathways that started in region reach with dopamine receptors. This methodology can enrich understudying of PD mechanisms in other (e.g., the default mode network) systems.
- MeSH
- levodopa MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- mapování mozku MeSH
- nervové dráhy MeSH
- odpočinek MeSH
- Parkinsonova nemoc * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Abnormalities in both time processing and dopamine (DA) neurotransmission have been observed in schizophrenia. Time processing seems to be linked to DA neurotransmission. The cognitive dysmetria hypothesis postulates that psychosis might be a manifestation of the loss of coordination of mental processes due to impaired timing. The objective of the present study was to analyze timing abilities and their corresponding functional neuroanatomy in schizophrenia. We performed a functional magnetic resonance imaging (fMRI) study using a predictive motor timing paradigm in 28 schizophrenia patients and 27 matched healthy controls (HC). The schizophrenia patients showed accelerated time processing compared to HC; the amount of the acceleration positively correlated with the degree of positive psychotic symptoms and negatively correlated with antipsychotic dose. This dysfunctional predictive timing was associated with BOLD signal activity alterations in several brain networks, especially those previously described as timing networks (basal ganglia, cerebellum, SMA, and insula) and reward networks (hippocampus, amygdala, and NAcc). BOLD signal activity in the cerebellar vermis was negatively associated with accelerated time processing. Several lines of evidence suggest a direct link between DA transmission and the cerebellar vermis that could explain their relevance for the neurobiology of schizophrenia.
- MeSH
- dospělí MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- mapování mozku MeSH
- mozek patofyziologie MeSH
- nervová síť patofyziologie MeSH
- pohybová aktivita fyziologie MeSH
- schizofrenie patofyziologie MeSH
- vermis cerebelli patofyziologie MeSH
- vnímání času fyziologie MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
Hypokinetic dysarthria (HD) is a difficult-to-treat symptom affecting quality of life in patients with Parkinson's disease (PD). Levodopa may partially alleviate some symptoms of HD in PD, but the neural correlates of these effects are not fully understood. The aim of our study was to identify neural mechanisms by which levodopa affects articulation and prosody in patients with PD. Altogether 20 PD patients participated in a task fMRI study (overt sentence reading). Using a single dose of levodopa after an overnight withdrawal of dopaminergic medication, levodopa-induced BOLD signal changes within the articulatory pathway (in regions of interest; ROIs) were studied. We also correlated levodopa-induced BOLD signal changes with the changes in acoustic parameters of speech. We observed no significant changes in acoustic parameters due to acute levodopa administration. After levodopa administration as compared to the OFF dopaminergic condition, patients showed task-induced BOLD signal decreases in the left ventral thalamus (p = 0.0033). The changes in thalamic activation were associated with changes in pitch variation (R = 0.67, p = 0.006), while the changes in caudate nucleus activation were related to changes in the second formant variability which evaluates precise articulation (R = 0.70, p = 0.003). The results are in line with the notion that levodopa does not have a major impact on HD in PD, but it may induce neural changes within the basal ganglia circuitries that are related to changes in speech prosody and articulation.
- MeSH
- antiparkinsonika škodlivé účinky MeSH
- dysartrie etiologie komplikace MeSH
- kvalita života MeSH
- levodopa * škodlivé účinky MeSH
- lidé MeSH
- magnetická rezonanční tomografie metody MeSH
- Parkinsonova nemoc * komplikace diagnostické zobrazování farmakoterapie MeSH
- poruchy řeči diagnostické zobrazování etiologie MeSH
- řeč fyziologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Different strategies have been developed using Independent Component Analysis (ICA) to automatically de-noise fMRI data, either focusing on removing only certain components (e.g. motion-ICA-AROMA, Pruim et al., 2015a) or using more complex classifiers to remove multiple types of noise components (e.g. FIX, Salimi-Khorshidi et al., 2014 Griffanti et al., 2014). However, denoising data obtained in an acute setting might prove challenging: the presence of multiple noise sources may not allow focused strategies to clean the data enough and the heterogeneity in the data may be so great to critically undermine complex approaches. The purpose of this study was to explore what automated ICA based approach would better cope with these limitations when cleaning fMRI data obtained from acute stroke patients. The performance of a focused classifier (ICA-AROMA) and a complex classifier (FIX) approaches were compared using data obtained from twenty consecutive acute lacunar stroke patients using metrics determining RSN identification, RSN reproducibility, changes in the BOLD variance, differences in the estimation of functional connectivity and loss of temporal degrees of freedom. The use of generic-trained FIX resulted in misclassification of components and significant loss of signal (< 80%), and was not explored further. Both ICA-AROMA and patient-trained FIX based denoising approaches resulted in significantly improved RSN reproducibility (p < 0.001), localized reduction in BOLD variance consistent with noise removal, and significant changes in functional connectivity (p < 0.001). Patient-trained FIX resulted in higher RSN identifiability (p < 0.001) and wider changes both in the BOLD variance and in functional connectivity compared to ICA-AROMA. The success of ICA-AROMA suggests that by focusing on selected components the full automation can deliver meaningful data for analysis even in population with multiple sources of noise. However, the time invested to train FIX with appropriate patient data proved valuable, particularly in improving the signal-to-noise ratio.
- MeSH
- analýza hlavních komponent * MeSH
- cévní mozková příhoda diagnostické zobrazování MeSH
- kyslík krev MeSH
- lidé MeSH
- magnetická rezonanční tomografie * MeSH
- nervové dráhy diagnostické zobrazování MeSH
- počítačové zpracování obrazu * MeSH
- reprodukovatelnost výsledků MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
Although essential tremor is the most common movement disorder, there is little knowledge about the pathophysiological mechanisms of this disease. Therefore, we explored brain connectivity based on slow spontaneous fluctuations of blood oxygenation level dependent (BOLD) signal in patients with essential tremor (ET). A cohort of 19 ET patients and 23 healthy individuals were scanned in resting condition using functional magnetic resonance imaging (fMRI). General connectivity was assessed by eigenvector centrality (EC) mapping. Selective connectivity was analyzed by correlations of the BOLD signal between the preselected seed regions and all the other brain areas. These measures were then correlated with the tremor severity evaluated by the Fahn-Tolosa-Marin Tremor Rating Scale (FTMTS). Compared to healthy subjects, ET patients were found to have lower EC in the cerebellar hemispheres and higher EC in the anterior cingulate and in the primary motor cortices bilaterally. In patients, the FTMTS score correlated positively with the EC in the putamen. In addition, the FTMTS score correlated positively with selective connectivity between the thalamus and other structures (putamen, pre-supplementary motor area (pre-SMA), parietal cortex), and between the pre-SMA and the putamen. We observed a selective coupling between a number of areas in the sensorimotor network including the basal ganglia and the ventral intermediate nucleus of thalamus, which is widely used as neurosurgical target for tremor treatment. Finally, ET was marked by suppression of general connectivity in the cerebellum, which is in agreement with the concept of ET as a disorder with cerebellar damage.
- MeSH
- dospělí MeSH
- esenciální tremor patofyziologie MeSH
- interpretace obrazu počítačem MeSH
- lidé středního věku MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- mapování mozku metody MeSH
- mladý dospělý MeSH
- mozek patofyziologie MeSH
- nervové dráhy patofyziologie MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
