Multimodal Functional Network Connectivity: An EEG-fMRI Fusion in Network Space

EEG and fMRI recordings measure the functional activity of multiple coherent networks distributed in the cerebral cortex. Identifying network interaction from the complementary neuroelectric and hemodynamic signals may help to explain the complex relationships between different brain regions. In this paper, multimodal functional network connectivity (mFNC) is proposed for the fusion of EEG and fMRI in network space. First, functional networks (FNs) are extracted using spatial independent component analysis (ICA) in each modality separately. Then the interactions among FNs in each modality are explored by Granger causality analysis (GCA). Finally, fMRI FNs are matched to EEG FNs in the spatial domain using network-based source imaging (NESOI). Investigations of both synthetic and real data demonstrate that mFNC has the potential to reveal the underlying neural networks of each modality separately and in their combination. With mFNC, comprehensive relationships among FNs might be unveiled for the deep exploration of neural activities and metabolic responses in a specific task or neurological state

The Human Connectome Project's neuroimaging approach

Noninvasive human neuroimaging has yielded many discoveries about the brain. Numerous methodological advances have also occurred, though inertia has slowed their adoption. This paper presents an integrated approach to data acquisition, analysis and sharing that builds upon recent advances, particularly from the Human Connectome Project (HCP). The 'HCP-style' paradigm has seven core tenets: (i) collect multimodal imaging data from many subjects; (ii) acquire data at high spatial and temporal resolution; (iii) preprocess data to minimize distortions, blurring and temporal artifacts; (iv) represent data using the natural geometry of cortical and subcortical structures; (v) accurately align corresponding brain areas across subjects and studies; (vi) analyze data using neurobiologically accurate brain parcellations; and (vii) share published data via user-friendly databases. We illustrate the HCP-style paradigm using existing HCP data sets and provide guidance for future research. Widespread adoption of this paradigm should accelerate progress in understanding the brain in health and disease

Donepezil Impairs Memory in Healthy Older Subjects: Behavioural, EEG and Simultaneous EEG/fMRI Biomarkers

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

Performance evaluation of ensemble empirical mode decomposition

Empirical mode decomposition (EMD) is an adaptive, data-driven algorithm that decomposes any time series into its intrinsic modes of oscillation, which can then be used in the calculation of the instantaneous phase and frequency. Ensemble EMD (EEMD), where the final EMD is estimated by averaging numerous EMD runs with the addition of noise, was an advancement introduced by Wu and Huang (2008) to try increasing the robustness of EMD and alleviate some of the common problems of EMD such as mode mixing. In this work, we test the performance of EEMD as opposed to normal EMD, with emphasis on the effect of selecting different stopping criteria and noise levels. Our results indicate that EEMD, in addition to slightly increasing the accuracy of the EMD output, substantially increases the robustness of the results and the confidence in the decomposition. © 2009 World Scientific Publishing Company

Removal of FMRI environment artifacts from EEG data using optimal basis sets.

The combination of functional magnetic resonance imaging (FMRI) and electroencephalography (EEG) has received much recent attention, since it potentially offers a new tool for neuroscientists that makes simultaneous use of the strengths of the two modalities. However, EEG data collected in such experiments suffer from two kinds of artifact. First, gradient artifacts are caused by the switching of magnetic gradients during FMRI. Second, ballistocardiographic (BCG) artifacts related to cardiac activities further contaminate the EEG data. Here we present new methods to remove both kinds of artifact. The methods are based primarily on the idea that temporal variations in the artifacts can be captured by performing temporal principal component analysis (PCA), which leads to the identification of a set of basis functions which describe the temporal variations in the artifacts. These basis functions are then fitted to, and subtracted from, EEG data to produce artifact-free results. In addition, we also describe a robust algorithm for the accurate detection of heart beat peaks from poor quality electrocardiographic (ECG) data that are collected for the purpose of BCG artifact removal. The methods are tested and are shown to give superior results to existing methods. The methods also demonstrate the feasibility of simultaneous EEG/FMRI experiments using the relatively low EEG sampling frequency of 2048 Hz

Simultaneous recording of laser-evoked brain potentials and continuous, high-field functional magnetic resonance imaging in humans.

Simultaneous recording of event-related electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) responses has the potential to provide information on how the human brain reacts to an external stimulus with unique spatial and temporal resolution. However, in most studies combining the two techniques, the acquisition of functional MR images has been interleaved with the recording of evoked potentials. In this study we investigated the feasibility of recording pain-related evoked potentials during continuous and simultaneous collection of blood oxygen level-dependent (BOLD) functional MR images at 3 T. Brain potentials were elicited by selective stimulation of cutaneous Adelta and C nociceptors using brief radiant laser pulses (laser-evoked potentials, LEPs). MR-induced artifacts on EEG data were removed using a novel algorithm. Latencies, amplitudes, and scalp distribution of LEPs recorded during fMRI were not significantly different from those recorded in a control session outside of the MR scanner using the same equipment and experimental design. Stability tests confirmed that MR-image quality was not impaired by the evoked potential recording, beyond signal loss related to magnetic susceptibility differences local to the electrodes. fMRI results were consistent with our previous studies of brain activity in response to nociceptive stimulation. These results demonstrate the feasibility of recording reliable pain-related LEPs and fMRI responses simultaneously. Because LEPs collected during fMRI and those collected in a control session show remarkable similarity, for many experimental designs the integration of LEP and fMRI data collected in separate, single-modality acquisitions may be appropriate. Truly simultaneous recording of LEPs and fMRI is still desirable in specific experimental conditions, such as single-trial, learning, and pharmacological studies

Preparation and Characterization of Highly Porous Direct Compression Carrier Particles with Improved Drug Loading During an Interactive Mixing Process

The aim of this study was to prepare highly porous carrier particles by emulsion solvent evaporation and compare the loading capacity of these beads with two traditional carriers, sugar beads, and microcrystalline cellulose granules during an interactive mixing process. The porous carrier particles were prepared by an emulsion solvent evaporation process using cellulose propionate as a binder, anhydrous dibasic calcium phosphate, and ion exchange resins as a fillers, and polyethylene glycol as a pore inducer. Micronized furosemide or griseofulvin powder was mixed with the same volume of each carrier in an interactive mixing process. The tableting properties, drug loading per unit volume of carrier, content uniformity of the mixtures, and dissolution of the drugs from the mixtures were measured. The results showed that highly porous microcapsules with desirable hardness equivalent to that of sugar beads and MCC granules were successfully prepared. On average the loading capacity of the new carrier was 310% that of sugar beads and 320% that of MCC granules during an interactive mixing process with very good content uniformity. The tableting properties of the microcapsules were equivalent to that of microcrystalline cellulose granules, and the dissolution of the drugs from interactive mixtures prepared with the new carrier was equivalent to that of drug suspensions. This showed that the prepared microcapsule carrier could be used to improve the loading capacity during an interactive mixing and to prepare tablets by direct compression