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Reliability and Correlation of Fmri, Ecog and EEG During Natural Stimulus Processing

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Reliability and Correlation of Fmri, Ecog and EEG During Natural Stimulus Processing bioRxiv preprint doi: https://doi.org/10.1101/207456; this version posted January 26, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. Reliability and correlation of fMRI, ECoG and EEG during natural stimulus processing Stefan Haufe1,2,3, , Paul DeGuzman4, Simon Henin5, Michael Arcaro6, Christopher J. Honey7, Uri Hasson8, and Lucas C. Parra4,2, 1Technische Universität Berlin 2City College New York 3Columbia University 4Neuromatters LLC 5NYU Langone Medical Center 6Harvard Medical School 7Johns Hopkins University 8Princeton University Human brain mapping relies heavily on fMRI, ECoG and is, therefore, of interest to quantify and map out the amount EEG, which capture different physiological signals. Rela- of task-related information that each imaging modality con- tionships between these signals have been established in tains in order to decide on the appropriate technique for a the context of specific tasks or during resting state, of- particular study. ten using spatially confined concurrent recordings in ani- mals. But it is not certain whether these correlations gen- At the same time, it is an ongoing endeavor to reveal the eralize to other contexts relevant for human cognitive neu- relationships between brain imaging techniques in order to roscience. Here, we address the case of complex natural- better understand the physiological foundations underlying istic stimuli and ask two basic questions. First, how reli- these methods. There have been significant efforts to re- able are the responses evoked by a naturalistic audio-visual late the electrical neural signal measured with EEG/ECoG stimulus in each of these imaging methods, and second, (Buzsáki et al., 2012) to the hemodynamic blood-oxygen- how similar are stimulus-related responses across meth- level dependent (BOLD) signal captured by fMRI (Logo- ods? To this end, we investigated a wide range of brain re- thetis, 2003). In respective experiments, imaging modalities gions and frequency bands. We presented the same movie are linked either through simultaneous recordings or through clip twice to three different cohorts of subjects (N = 45, EEG separate recordings tied together by a common task. Simulta- NfMRI = 11, NECoG = 5) and assessed stimulus-driven cor- relations across viewings and between imaging methods, neous fMRI–EEG recordings in human have been performed thereby ruling out task-irrelevant confounds. All three imag- in Laufs et al. (2003); Moosmann et al. (2003); Ritter et al. ing methods had similar repeat-reliability across viewings (2009); Ritter and Villringer (2006); Scheeringa et al. (2008, when fMRI and EEG data were averaged across subjects, 2011, 2016). Simultaneous fMRI–ECoG recordings are only highlighting the potential to achieve large signal-to-noise ra- available in animals (Logothetis et al., 2001; Magri et al., tio by leveraging large sample sizes. The fMRI signal cor- 2012; Niessing et al., 2005) with a recent exception in hu- related positively with high-frequency ECoG power across man (Carmichael et al., 2017). Most human studies have multiple task-related cortical structures but positively with relied instead on a common task (Harvey et al., 2013; Her- low-frequency EEG and ECoG power. In contrast to previous mes et al., 2012; Mukamel et al., 2005; Nir et al., 2007; studies, these correlations were as strong for low-frequency Winawer et al., 2013). The main findings of these studies as for high frequency ECoG. We also observed links be- are that high-frequency power in the ECoG correlates pos- tween fMRI and infra-slow EEG voltage fluctuations. These results extend previous findings to the case of natural stim- itively with fMRI, while low frequencies correlates nega- ulus processing. tively with fMRI. These effects may, however, not be uni- formly distributed across cortical brain structures, and can fMRI | ECoG | EEG | repeat-reliability | inter-method correlation display frequency-dependent spatial variations (Harvey et al., Correspondence: [email protected] (SH), [email protected] (LCP) 2013; Scheeringa et al., 2008, 2009). The observed corre- lations may also depend on the specific task (Maier et al., Introduction 2008; Muthukumaraswamy and Singh, 2009). Recent evi- The most frequently-used functional neuroimaging tech- dence suggests that the correlations between hemodynamic niques are functional magnetic resonance imaging (fMRI) and electrical activity can have a non-neuronal physiologi- and electroencephalography (EEG). Both are complementary cal origin (Mateo et al., 2017), which can be decoupled from in that fMRI provides high spatial but low temporal reso- task-related neural processing (Winder et al., 2017). Thus, lution, while the opposite is true for EEG. Invasive meth- it is not certain whether the results of previous studies apply ods such as electrocorticography (ECoG), on the other hand, also in more realistic stimulus condition in humans, nor is combine high temporal resolution with relatively high spatial it clear which of these relationships persist once controlling resolution; however, such procedures are only used in small for physiological confounds unrelated to the brain functions cohorts of neurological patients. ECoG, EEG and fMRI also under study. differ in their underlying neurophysiological origin, are sus- The link between scalp EEG and invasive electrical record- ceptible to different noise sources (e.g., artifacts, patholog- ings has been explored predominantly in non-human pri- ical activity), and generally differ in terms of their inherent mates using simple visual stimuli. While visually evoked signal-to-noise ratio (SNR). From a practical perspective, it gamma activity generally correlates in the two imaging Haufe et al. | bioRχiv | January 26, 2018 | 1–19 bioRxiv preprint doi: https://doi.org/10.1101/207456; this version posted January 26, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. modalities (Whittingstall and Logothetis, 2009), there ap- ‘raw’ broad-band signals of all imaging methods as well as pears to be a complex relationship between lower frequency of EEG/ECoG power fluctuations in five frequency bands: activity in the EEG and high-frequency intracranial activity q (4–8 Hz), a (8–12 Hz), b (12–28 Hz), g (28–56 Hz) and the (Snyder et al., 2015). In human, the link between ECoG and high frequencies (HF, 64–116 Hz). To quantifying the effects EEG has been explored mostly in the context of epileptic ac- that can be resolved from entire cohorts of realistic sizes, we tivity, but we are not aware of a systematic analysis of dif- performed grand-averaging (GA) of the EEG and fMRI data ferent frequency bands. Such an analysis may be warranted, after spatial normalization. In ECoG, averaging across sub- given that results on visual evoked gamma activity, for in- jects is not possible, as electrode montages differ between stance, do not seem to readily extend to humans (Juergens subject; we, therefore, combined the ECoG channels of all et al., 1999) and likely depend on the stimulus (Scheeringa subjects into a single dataset (without averaging). For com- et al., 2016). parison we also present fMRI and EEG results obtained on Here, we consider the case of a complex audio-visual movie single subjects. stimulus and ask two basic questions that have not been suf- ficiently addressed in the previous literature. First, how re- Reliability of responses within imaging methods liable are the responses evoked by such a stimulus in EEG, To assess the repeat-reliability of stimulus-related brain ac- fMRI and ECoG, considering the cohort sizes that are typi- tivity for each method, we calculated the correlation of the cally available in respective studies? And, second, to what continuous neural responses across the two renditions of the extent are these three imaging modalities reflecting the same stimulus, which we refer to as the inter-viewing correla- stimulus-related brain activity? tion (IVC). Correlations were assessed separately for each To study these questions, we analyzed correlations within and anatomical location using Pearson’s r, and their statistical between EEG, fMRI and ECoG recordings across different significance was assessed by comparing observed values to brain structures and frequency bands. Data were acquired a null distribution obtained from surrogate data. The result- from three different cohorts of subjects within separate EEG, ing z-scores correct for unequal variances of the estimated ECoG and fMRI studies, in which subjects watched an audio- correlation coefficients that arise from different sampling fre- visual movie. The richness of the movie stimulus thereby en- quencies and data-dependent auto-correlation spectra. We sured that not only auditory, visual and multi-sensory systems interpret z-scores as objective measures of how much the were engaged in the viewing task, but also a host of higher- observed correlations stand out against random fluctuations level cognitive functions such as language, memory, and at- in the data. They can be directly compared across different tention. Using the same movie for all subjects allowed us imaging methods and differing sampling rates, whereas r- to temporally
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