Single-trial EEG-informed fMRI reveals spatial dependency of BOLD signal on early and late IC-ERP amplitudes during face recognition

Wirsich, Jonathan; Bénar, Christian; Ranjeva, Jean‐Philippe; Descoins, Médéric; Soulier, Elisabeth; Troter, Arnaud Le; Confort‐Gouny, Sylviane; Liégeois‐Chauvel, Catherine; Guye, Maxime

doi:10.1016/j.neuroimage.2014.05.075

Cited by 25 publications

(12 citation statements)

References 73 publications

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“…We can observe that the N170 component is mostly associated with activations in the occipital and lingual gyrus (marked with yellow rectangle), the left superior Occipital cortex (red rectangle), the middle temporal gyrus (blue rectangle) and the precentral gyrus (green rectangle). These regions match the ones reported by other studies [33] and confirm that results of the decomposition. These initial results indicate that CPLS is able uncover meaningful components that co-vary between the two datasets.…”

Section: A Evaluation Using the Average Erp And Fmrisupporting

confidence: 92%

“…On the other hand, the fMRI CPLS component reveals areas that co-vary with the EEG component and are in agreement with other studies regarding the areas involved in the generation of N170 [33]. Significant areas of activations were calculated by thresholding the Z transformed loadings of the fMRI component.…”

Section: A Evaluation Using the Average Erp And Fmrisupporting

confidence: 88%

“…In this case, the components project significantly to all periods and therefore is expected to have more active regions than in the case of the average ERP. The additional activations are located mainly in the inferior and superior frontal gyri (red) and are related to ERP components that appear later in time (as the P600) [33].…”

Section: B Evaluation Using the Fisher Score And Fmrimentioning

confidence: 99%

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Fusion of EEG Topograhic Features and fMRI Using Canonical Partial Least Squares

Michalopoulos

Bourbakis

2014

2014 IEEE International Conference on Bioinformatics and Bioengineering

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In this paper we present a novel method for describing the EEG as a sequence of topographies, based on the notion of microstates. We use Hidden Markov Models (HMM) to model the temporal evolution of the topography of the average Event Related Potential (ERP) and we calculate the Fisher score of the sequence by taking the gradient of the trained model parameters given the sequence. In this context, the average Event Related Potential (ERP) is described as a sequence of topographies and the Fisher score describes how this sequence deviates from the learned HMM. This alternative modeling of the ERP is used to fuse EEG information, as expressed by the temporal evolution of the topography, and Functional Magnetic Resonance Imaging (fMRI). We use Canonical Partial Least Squares (CPLS) for the fusion of the Fisher score with fMRI features. In order to test the effectiveness of this method, we compare the results of this methodology with the results of CPLS using the average ERP signal of a single channel. Using this methodology we are able to derive components that co-vary between EEG and fMRI and present significant differences between the two tasks. The results indicate that this descriptor effectively characterizes the temporal evolution of the ERP topography and can be used for fusing EEG and fMRI for the discrimination of the brain activity on different tasks.

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Section: A Evaluation Using the Average Erp And Fmrisupporting

confidence: 92%

Section: A Evaluation Using the Average Erp And Fmrisupporting

confidence: 88%

Section: B Evaluation Using the Fisher Score And Fmrimentioning

confidence: 99%

See 1 more Smart Citation

Fusion of EEG Topograhic Features and fMRI Using Canonical Partial Least Squares

Michalopoulos

Bourbakis

2014

2014 IEEE International Conference on Bioinformatics and Bioengineering

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“…The here observed duality of mutual and discrepant contributions of hemodynamic and electrophysiological recordings has also been discussed in task-paradigm studies. Taking face recognition tasks as an example, mutual contributions of EEG and fMRI have been readily observed (Walz et al, 2013; Wirsich et al, 2014). However, face recognition tasks also engage discrepant contributions across the two modalities; It has been shown that while the face-selective N170 originating from the fusiform gyrus in MEG is not modulated by attention, fMRI show a strong modulation in the same region (Furey et al, 2006).…”

Section: Discussionmentioning

confidence: 99%

Multi-timescale hybrid components of the functional brain connectome: A bimodal EEG-fMRI decomposition

Wirsich

Amico²,

Guye

et al. 2019

Preprint

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Concurrent electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) bridge brain connectivity across timescales. During concurrent EEG-fMRI resting-state recordings, whole-brain functional connectivity (FC) strength is spatially correlated across modalities. However, cross-modal investigations have commonly remained correlational, and joint analysis of EEG-fMRI connectivity is largely unexplored.Here we investigated if there exist (spatially) independent FC networks linked between modalities. We applied the recently proposed hybrid connectivity independent component analysis (connICA) framework to two concurrent EEG-fMRI resting state datasets (total 40 subjects). Two robust components were found across both datasets. The first component has a uniformly distributed EEG-frequency fingerprint linked mainly to intrinsic connectivity networks (ICNs) in both modalities. Conversely, the second component is sensitive to different EEG-frequencies and is primarily linked to intra-ICN connectivity in fMRI but to inter-ICN connectivity in EEG.The first hybrid component suggests that connectivity dynamics within well-known ICNs span timescales, from millisecond-range in all canonical frequencies of FCEEG to second-range of FCfMRI. Conversely, the second component additionally exposes linked but spatially divergent neuronal processing at the two timescales. This work reveals the existence of joint spatially independent components, suggesting that parts of resting-state connectivity are co-expressed in a linked manner across EEG and fMRI over individuals.

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“…In another study in which animal and non-animal natural scenes were shown, PowerPoint was employed as stimuli presentation software [13]. Apart from these, nonfree and commercial stimuli presentation software like E-Prime [14][15][16] and STIM2 [17,18] can be used in EEG experiments. Moreover, free but complicated software like PsychoPy [19] and OpenSeSame [20] can be preferred for building and running stimuli experiments in neurophysiology studies [21].…”

Section: Introductionmentioning

confidence: 99%

STIPRESOFT: an alternative stimuli presentation software synchronizing with current acquisition systems in EEG experiments

Özbeyaz

2019

SN Appl. Sci.

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Since analyzing of visual evoked potentials is crucial in neuropsychology experiments, stimuli presentation software should be meticulously designed. In such experiments, synchronizing stimuli presentation software with existing biomedical instruments, and marking EEG signals are difficult problems to overcome. In EEG experiments, these kinds of problems have been still tried to be overcome with the simple and unprofessional software like PowerPoint. Furthermore, commercial software is costly and may be incompatible with the current laboratory resources. In this study, free and simple STIPRESOFT software which could synchronize stimuli presentation software with available EEG devices and could mark EEG signals at the time of visual stimulus was developed. In the applied experiments, the time latency between the stimulus and marking times were more successful with 0.028 ms according to the competitors. In the software, the advantages of the Win-API were benefited. In STIPRESOFT, two API were exploited to improve timing precision, and to enable synchronization. Furthermore, time stamps related to stimuli on EEG signals were recorded in a text file during the experiment. Consequently, the developed software presents an alternative free and simple solution for researchers who need to adjust synchronization between stimuli presentation and existing EEG device in the scientific studies.

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Single-trial EEG-informed fMRI reveals spatial dependency of BOLD signal on early and late IC-ERP amplitudes during face recognition

Cited by 25 publications

References 73 publications

Fusion of EEG Topograhic Features and fMRI Using Canonical Partial Least Squares

Fusion of EEG Topograhic Features and fMRI Using Canonical Partial Least Squares

Multi-timescale hybrid components of the functional brain connectome: A bimodal EEG-fMRI decomposition

STIPRESOFT: an alternative stimuli presentation software synchronizing with current acquisition systems in EEG experiments

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