Spurious correlations in simultaneous EEG-fMRI driven by in-scanner movement

Chronic brain functional ultrasound imaging in freely moving rodents performing cognitive tasks

BACKGROUND

Functional ultrasound imaging (fUS) is an emerging imaging technique that indirectly measures neural activity via changes in blood volume. Chronic fUS imaging during cognitive tasks in freely moving animals faces multiple exceptional challenges: performing large durable craniotomies with chronic implants, designing behavioral experiments matching the hemodynamic timescale, stabilizing the ultrasound probe during freely moving behavior, accurately assessing motion artifacts, and validating that the animal can perform cognitive tasks while tethered.

NEW METHOD

We provide validated solutions for those technical challenges. In addition, we present standardized step-by-step reproducible protocols, procedures, and data processing pipelines. Finally, we present proof-of-concept analysis of brain dynamics during a decision making task.

RESULTS

We obtain stable recordings from which we can robustly decode task variables from fUS data over multiple months. Moreover, we find that brain wide imaging through hemodynamic response is nonlinearly related to cognitive variables, such as task difficulty, as compared to sensory responses previously explored.

COMPARISON WITH EXISTING METHODS

Computational pipelines in fUS are nascent and we present an initial development of a full processing pathway to correct and segment fUS data.

CONCLUSIONS

Our methods provide stable imaging and analysis of behavior with fUS that will enable new experimental paradigms in understanding brain-wide dynamics in naturalistic behaviors.

Enhancing precision in human neuroscience

Human neuroscience has always been pushing the boundary of what is measurable. During the last decade, concerns about statistical power and replicability - in science in general, but also specifically in human neuroscience - have fueled an extensive debate. One important insight from this discourse is the need for larger samples, which naturally increases statistical power. An alternative is to increase the precision of measurements, which is the focus of this review. This option is often overlooked, even though statistical power benefits from increasing precision as much as from increasing sample size. Nonetheless, precision has always been at the heart of good scientific practice in human neuroscience, with researchers relying on lab traditions or rules of thumb to ensure sufficient precision for their studies. In this review, we encourage a more systematic approach to precision. We start by introducing measurement precision and its importance for well-powered studies in human neuroscience. Then, determinants for precision in a range of neuroscientific methods (MRI, M/EEG, EDA, Eye-Tracking, and Endocrinology) are elaborated. We end by discussing how a more systematic evaluation of precision and the application of respective insights can lead to an increase in reproducibility in human neuroscience.

Cognition is entangled with metabolism: relevance for resting-state EEG-fMRI

The brain is a living organ with distinct metabolic constraints. However, these constraints are typically considered as secondary or supportive of information processing which is primarily performed by neurons. The default operational definition of neural information processing is that (1) it is ultimately encoded as a change in individual neuronal firing rate as this correlates with the presentation of a peripheral stimulus, motor action or cognitive task. Two additional assumptions are associated with this default interpretation: (2) that the incessant background firing activity against which changes in activity are measured plays no role in assigning significance to the extrinsically evoked change in neural firing, and (3) that the metabolic energy that sustains this background activity and which correlates with differences in neuronal firing rate is merely a response to an evoked change in neuronal activity. These assumptions underlie the design, implementation, and interpretation of neuroimaging studies, particularly fMRI, which relies on changes in blood oxygen as an indirect measure of neural activity. In this article we reconsider all three of these assumptions in light of recent evidence. We suggest that by combining EEG with fMRI, new experimental work can reconcile emerging controversies in neurovascular coupling and the significance of ongoing, background activity during resting-state paradigms. A new conceptual framework for neuroimaging paradigms is developed to investigate how ongoing neural activity is "entangled" with metabolism. That is, in addition to being recruited to support locally evoked neuronal activity (the traditional hemodynamic response), changes in metabolic support may be independently "invoked" by non-local brain regions, yielding flexible neurovascular coupling dynamics that inform the cognitive context. This framework demonstrates how multimodal neuroimaging is necessary to probe the neurometabolic foundations of cognition, with implications for the study of neuropsychiatric disorders.

Anterior Cingulate Cortex Signals the Need to Control Intrusive Thoughts during Motivated Forgetting

How do people limit awareness of unwanted memories? When such memories intrude, a control process engages the right DLPFC (rDLPFC) to inhibit hippocampal activity and stop retrieval. It remains unknown how the need for control is detected, and whether control operates proactively to prevent unwelcome memories from being retrieved, or responds reactively, to counteract intrusions. We hypothesized that dorsal ACC (dACC) detects the emergence of an unwanted trace in awareness and transmits the need for inhibitory control to rDLPFC. During a memory suppression task, we measured in humans (both sexes) trial-by-trial variations in the theta power and N2 amplitude of dACC, two EEG markers that are thought to reflect the need for control. With simultaneous EEG-fMRI recordings, we tracked interactions among dACC, rDLPFC, and hippocampus during suppression. We found a clear role of dACC in detecting the need for memory control and upregulating prefrontal inhibition. Importantly, we identified distinct early (300-450 ms) and late (500-700 ms) dACC contributions, suggesting both proactive control before recollection and reactive control in response to intrusions. Stronger early activity was associated with reduced hippocampal activity and diminished BOLD signal in dACC and rDLPFC, suggesting that preempting retrieval reduced overall control demands. In the later window, dACC activity was larger, and effective connectivity analyses revealed robust communication from dACC to rDLPFC and from rDLPFC to hippocampus, which are tied to successful forgetting. Together, our findings support a model in which dACC detects the emergence of unwanted content, triggering top-down inhibitory control, and in which rDLPFC countermands intruding thoughts that penetrate awareness.SIGNIFICANCE STATEMENT Preventing unwanted memories from coming to mind is an adaptive ability of humans. This ability relies on inhibitory control processes in the prefrontal cortex to modulate hippocampal retrieval processes. How and when reminders to unwelcome memories come to trigger prefrontal control mechanisms remains unknown. Here we acquired neuroimaging data with both high spatial and temporal resolution as participants suppressed specific memories. We found that the anterior cingulate cortex detects the need for memory control, responding both proactively to early warning signals about unwelcome content and reactively to intrusive thoughts themselves. When unwanted traces emerge in awareness, anterior cingulate communicates with prefrontal cortex and triggers top-down inhibitory control over the hippocampus through specific neural oscillatory networks.

Striatal BOLD and Midfrontal Theta Power Express Motivation for Action

Action selection is biased by the valence of anticipated outcomes. To assess mechanisms by which these motivational biases are expressed and controlled, we measured simultaneous EEG-fMRI during a motivational Go/NoGo learning task (N = 36), leveraging the temporal resolution of EEG and subcortical access of fMRI. VmPFC BOLD encoded cue valence, importantly predicting trial-by-trial valence-driven response speed differences and EEG theta power around cue onset. In contrast, striatal BOLD encoded selection of active Go responses and correlated with theta power around response time. Within trials, theta power ramped in the fashion of an evidence accumulation signal for the value of making a "Go" response, capturing the faster responding to reward cues. Our findings reveal a dual nature of midfrontal theta power, with early components reflecting the vmPFC contribution to motivational biases, and late components reflecting their striatal translation into behavior, in line with influential recent "value of work" theories of striatal processing.

When Is Simultaneous Recording Necessary? A Guide for Researchers Considering Combined EEG-fMRI

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) provide non-invasive measures of brain activity at varying spatial and temporal scales, offering different views on brain function for both clinical and experimental applications. Simultaneous recording of these measures attempts to maximize the respective strengths of each method, while compensating for their weaknesses. However, combined recording is not necessary to address all research questions of interest, and experiments may have greater statistical power to detect effects by maximizing the signal-to-noise ratio in separate recording sessions. While several existing papers discuss the reasons for or against combined recording, this article aims to synthesize these arguments into a flow chart of questions that researchers can consider when deciding whether to record EEG and fMRI separately or simultaneously. Given the potential advantages of simultaneous EEG-fMRI, the aim is to provide an initial overview of the most important concepts and to direct readers to relevant literature that will aid them in this decision.

Tentative fMRI signatures of perceptual echoes in early visual cortex

The visual Impulse Response Function (IRF) can be estimated by cross-correlating random luminance sequences with concurrently recorded EEG. It typically contains a strong 10 Hz oscillatory component, suggesting that visual information reverberates in the human brain as a "perceptual echo". The neural origin of these echoes remains unknown. To address this question, we recorded EEG and fMRI in two separate sessions. In both sessions, a disk whose luminance followed a random (white noise) sequence was presented in the upper left quadrant. Individual IRFs were derived from the EEG session. These IRFs were then used as "response templates" to reconstruct an estimate of the EEG during the fMRI session, by convolution with the corresponding random luminance sequences. The 7-14 Hz (alpha, the main frequency component of the IRF) envelope of the reconstructed EEG was finally used as an fMRI regressor, to determine which brain voxels co-varied with the oscillations elicited by the luminance sequence, i.e., the "perceptual echoes". The reconstructed envelope of EEG alpha was significantly correlated with BOLD responses in V1 and V2. Surprisingly, this correlation was visible outside, but not within the directly (retinotopically) stimulated region. We tentatively interpret this lack of alpha modulation as a BOLD saturation effect, since the overall stimulus-induced BOLD response was inversely related, across voxels, to the signal variability over time. In conclusion, our results suggest that perceptual echoes originate in early visual cortex, driven by widespread activity in V1 and V2, not retinotopically restricted, but possibly reflecting the propagation of a travelling alpha wave.

Simultaneous EEG/fMRI recorded during ketamine infusion in patients with major depressive disorder

A single subanaesthetic dose of ketamine rapidly alleviates the symptoms of major depressive disorder (MDD). However, few studies have investigated the acute effects of ketamine on the BOLD pharmacological magnetic resonance imaging (phMRI) response and EEG spectra. In a randomised, double-blind, active placebo-controlled crossover trial, resting-state simultaneous EEG/fMRI was collected during infusion of ketamine or active placebo (remifentanil) in 30 participants with MDD. Montgomery-Asberg depression rating scale scores showed a significant antidepressant effect of ketamine compared to placebo (69% response rate). phMRI analyses showed BOLD signal increases in the anterior cingulate and medial prefrontal cortices and sensitivity of the decrease in subgenual anterior cingulate cortex (sgACC) BOLD signal to noise correction. EEG spectral analysis showed increased theta, high beta, low and high gamma power, and decreased delta, alpha, and low beta power with differing time-courses. Low beta and high gamma power time courses explained significant variance in the BOLD signal. Interestingly, the variance explained by high gamma power was significantly associated with non-response to ketamine, but significant associations were not found for other neurophysiological markers when noise correction was implemented. The results suggest that the decrease in sgACC BOLD signal is potentially noise and unrelated to ketamine's antidepressant effect, highlighting the importance of noise correction and multiple temporal regressors for phMRI analyses. The lack of effects significantly associated with antidepressant response suggests the phMRI methodology employed was unable to detect such effects, the effect sizes are relatively small, or that other processes, e.g. neural plasticity, underlie ketamine's antidepressant effect.

Modulation of simultaneously collected hemodynamic and electrophysiological functional connectivity by ketamine and midazolam

The pharmacological modulation of functional connectivity in the brain may underlie therapeutic efficacy for several neurological and psychiatric disorders. Functional magnetic resonance imaging (fMRI) provides a noninvasive method of assessing this modulation, however, the indirect nature of the blood‐oxygen level dependent signal restricts the discrimination of neural from physiological contributions. Here we followed two approaches to assess the validity of fMRI functional connectivity in developing drug biomarkers, using simultaneous electroencephalography (EEG)/fMRI in a placebo‐controlled, three‐way crossover design with ketamine and midazolam. First, we compared seven different preprocessing pipelines to determine their impact on the connectivity of common resting‐state networks. Independent components analysis (ICA)‐denoising resulted in stronger reductions in connectivity after ketamine, and weaker increases after midazolam, than pipelines employing physiological noise modelling or averaged signals from cerebrospinal fluid or white matter. This suggests that pipeline decisions should reflect a drug's unique noise structure, and if this is unknown then accepting possible signal loss when choosing extensive ICA denoising pipelines could engender more confidence in the remaining results. We then compared the temporal correlation structure of fMRI to that derived from two connectivity metrics of EEG, which provides a direct measure of neural activity. While electrophysiological estimates based on the power envelope were more closely aligned to BOLD signal connectivity than those based on phase consistency, no significant relationship between the change in electrophysiological and hemodynamic correlation structures was found, implying caution should be used when making cross‐modal comparisons of pharmacologically‐modulated functional connectivity.

Alpha/beta power decreases track the fidelity of stimulus-specific information

Massed synchronised neuronal firing is detrimental to information processing. When networks of task-irrelevant neurons fire in unison, they mask the signal generated by task-critical neurons. On a macroscopic level, such synchronisation can contribute to alpha/beta (8-30 Hz) oscillations. Reducing the amplitude of these oscillations, therefore, may enhance information processing. Here, we test this hypothesis. Twenty-one participants completed an associative memory task while undergoing simultaneous EEG-fMRI recordings. Using representational similarity analysis, we quantified the amount of stimulus-specific information represented within the BOLD signal on every trial. When correlating this metric with concurrently-recorded alpha/beta power, we found a significant negative correlation which indicated that as post-stimulus alpha/beta power decreased, stimulus-specific information increased. Critically, we found this effect in three unique tasks: visual perception, auditory perception, and visual memory retrieval, indicating that this phenomenon transcends both stimulus modality and cognitive task. These results indicate that alpha/beta power decreases parametrically track the fidelity of both externally-presented and internally-generated stimulus-specific information represented within the cortex.

Aberrant activity in conceptual networks underlies N400 deficits and unusual thoughts in schizophrenia

BACKGROUND

The N400 event-related potential (ERP) is triggered by meaningful stimuli that are incongruous, or unmatched, with their semantic context. Functional magnetic resonance imaging (fMRI) studies have identified brain regions activated by semantic incongruity, but their precise links to the N400 ERP are unclear. In schizophrenia (SZ), N400 amplitude reduction is thought to reflect overly broad associations in semantic networks, but the abnormalities in brain networks underlying deficient N400 remain unknown. We utilized joint independent component analysis (JICA) to link temporal patterns in ERPs to neuroanatomical patterns from fMRI and investigate relationships between N400 amplitude and neuroanatomical activation in SZ patients and healthy controls (HC).

METHODS

SZ patients (n = 24) and HC participants (n = 25) performed a picture-word matching task, in which words were either matched (APPLE→apple) by preceding pictures, or were unmatched by semantically related (in-category; IC, APPLE→lemon) or unrelated (out of category; OC, APPLE→cow) pictures, in separate ERP and fMRI sessions. A JICA "data fusion" analysis was conducted to identify the fMRI brain regions specifically associated with the ERP N400 component. SZ and HC loading weights were compared and correlations with clinical symptoms were assessed.

RESULTS

JICA identified an ERP-fMRI "fused" component that captured the N400, with loading weights that were reduced in SZ. The JICA map for the IC condition showed peaks of activation in the cingulate, precuneus, bilateral temporal poles and cerebellum, whereas the JICA map from the OC condition was linked primarily to visual cortical activation and the left temporal pole. Among SZ patients, fMRI activity from the IC condition was inversely correlated with unusual thought content.

CONCLUSIONS

The neural networks associated with the N400 ERP response to semantic violations depends on conceptual relatedness. These findings are consistent with a distributed network underlying neural responses to semantic incongruity including unimodal visual areas as well as integrative, transmodal areas. Unusual thoughts in SZ may reflect impaired processing in transmodal hub regions such as the precuneus, leading to overly broad semantic associations.

Age-related differences in the structural and effective connectivity of cognitive control: a combined fMRI and DTI study of mental arithmetic

Cognitive changes with aging are highly variable across individuals. This study investigated whether cognitive control performance might depend on preservation of structural and effective connectivity in older individuals. Specifically, we tested inhibition following working memory (WM) updating and maintenance. We analyzed diffusion tensor imaging and functional magnetic resonance imaging data in thirty-four young adults and thirty-four older adults, who performed an arithmetic verification task during functional magnetic resonance imaging. Results revealed larger arithmetic interference in older adults relative to young adults after WM updating, whereas both groups showed similar interference after WM maintenance. In both groups, arithmetic interference was associated with larger activations and stronger effective connectivity among bilateral anterior cingulate, bilateral inferior frontal gyrus, and left angular gyrus, with larger activations of frontal regions in older adults than in younger adults. In older adults, preservation of frontoparietal structural microstructure, especially involving the inferior frontaloccipital fasciculus, was associated with reduced interference, and stronger task-related effective connectivity. These results highlight how both structural and functional changes in the cognitive control network contribute to individual variability in performance during aging.

Temporal dynamics of the pharmacological MRI response to subanaesthetic ketamine in healthy volunteers: A simultaneous EEG/fMRI study

BACKGROUND

Pharmacological magnetic resonance imaging has been used to investigate the neural effects of subanaesthetic ketamine in healthy volunteers. However, the effect of ketamine has been modelled with a single time course and without consideration of physiological noise.

AIMS

This study aimed to investigate ketamine-induced alterations in resting neural activity using conventional pharmacological magnetic resonance imaging analysis techniques with physiological noise correction, and a novel analysis utilising simultaneously recorded electroencephalography data.

METHODS

Simultaneous electroencephalography/functional magnetic resonance imaging and physiological data were collected from 30 healthy male participants before and during a subanaesthetic intravenous ketamine infusion.

RESULTS

Consistent with previous literature, we show widespread cortical blood-oxygen-level dependent signal increases and decreased blood-oxygen-level dependent signals in the subgenual anterior cingulate cortex following ketamine. However, the latter effect was attenuated by the inclusion of motion regressors and physiological correction in the model. In a novel analysis, we modelled the pharmacological magnetic resonance imaging response with the power time series of seven electroencephalography frequency bands. This showed evidence for distinct temporal time courses of neural responses to ketamine. No electroencephalography power time series correlated with decreased blood-oxygen-level dependent signal in the subgenual anterior cingulate cortex.

CONCLUSIONS

We suggest the decrease in blood-oxygen-level dependent signals in the subgenual anterior cingulate cortex typically seen in the literature is the result of physiological noise, in particular cardiac pulsatility. Furthermore, modelling the pharmacological magnetic resonance imaging response with a single temporal model does not completely capture the full spectrum of neuronal dynamics. The use of electroencephalography regressors to model the response can increase confidence that the pharmacological magnetic resonance imaging is directly related to underlying neural activity.

Comparison of local spectral modulation, and temporal correlation, of simultaneously recorded EEG/fMRI signals during ketamine and midazolam sedation

RATIONALE AND OBJECTIVES

The identification of biomarkers of drug action can be supported by non-invasive brain imaging techniques, such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), with simultaneous collection plausibly overcoming the limitations of either modality alone. Despite this, few studies have assessed the feasibility and utility of recording simultaneous EEG/fMRI in a drug study.

METHODS

We used simultaneous EEG/fMRI to assess the modulation of neural activity by ketamine and midazolam, in a placebo-controlled, single-blind, three-way cross-over design. Specifically, we analysed the sensitivity and direction of the spectral effects of each modality and the temporal correlations between the modulations of power of the common EEG bands and the blood-oxygen-level-dependent (BOLD) signal.

RESULTS AND CONCLUSIONS

Demonstrating feasibility, local spectral effects were similar to those found in previous non-simultaneous EEG and fMRI studies. Ketamine administration resulted in a widespread reduction of BOLD fractional amplitude of low frequency fluctuations (fALFF) and a diverse pattern of effects in the different EEG bands. Midazolam increased fALFF in occipital, parietal, and temporal areas, and frontal delta and beta EEG power. While EEG spectra were more sensitive to pharmacological modulations than the fALFF bands, there was no clear spatial relationship between the two modalities. Additionally, ketamine modulated the temporal correlation strengths between the theta EEG band and the BOLD signal, whereas midazolam altered temporal correlations with the alpha and beta bands. Taken together, these results demonstrate the utility of simultaneous recording: each modality provides unique insights, and combinatorial analyses elicit more information than separate recordings.

Exploring the relative efficacy of motion artefact correction techniques for EEG data acquired during simultaneous fMRI

Simultaneous EEG‐fMRI allows multiparametric characterisation of brain function, in principle enabling a more complete understanding of brain responses; unfortunately the hostile MRI environment severely reduces EEG data quality. Simply eliminating data segments containing gross motion artefacts [MAs] (generated by movement of the EEG system and head in the MRI scanner's static magnetic field) was previously believed sufficient. However recently the importance of removal of all MAs has been highlighted and new methods developed. A systematic comparison of the ability to remove MAs and retain underlying neuronal activity using different methods of MA detection and post‐processing algorithms is needed to guide the neuroscience community. Using a head phantom, we recorded MAs while simultaneously monitoring the motion using three different approaches: Reference Layer Artefact Subtraction (RLAS), Moiré Phase Tracker (MPT) markers and Wire Loop Motion Sensors (WLMS). These EEG recordings were combined with EEG responses to simple visual tasks acquired on a subject outside the MRI environment. MAs were then corrected using the motion information collected with each of the methods combined with different analysis pipelines. All tested methods retained the neuronal signal. However, often the MA was not removed sufficiently to allow accurate detection of the underlying neuronal signal. We show that the MA is best corrected using the RLAS combined with post‐processing using a multichannel, recursive least squares (M‐RLS) algorithm. This method needs to be developed further to enable practical utility; thus, WLMS combined with M‐RLS currently provides the best compromise between EEG data quality and practicalities of motion detection.

Spatio-temporal patterns of cognitive control revealed with simultaneous electroencephalography and functional magnetic resonance imaging

Optimal performance depends in part on the ability to inhibit the automatic processing of irrelevant information and also on the adjusting the level of control from one trial to the next. In this study, we investigated the spatio-temporal neural correlates of cognitive control using simultaneous functional magnetic resonance imaging and electroencephalography, while 22 participants (10 women) performed a numerical Stroop task. We investigated the spatial and temporal dynamic of the conflict adaptation effects (i.e., reduced interference on items that follow an incongruent stimulus compared to after a congruent stimulus). Joint independent component analysis linked the N200 component to activation of anterior cingulate cortex (ACC) and the conflict slow potential to widespread activations within the fronto-parietal executive control network. Connectivity analyses with psychophysiological interactions and dynamic causal modeling demonstrated coordinated engagement of the cognitive control network after the processing of an incongruent item, and this was correlated with better behavioral performance. Our results combined high spatial and temporal resolution to propose the following network of conflict adaptation effect and specify the time course of activation within this model: first, the anterior insula and inferior frontal gyrus are activated when incongruence is detected. These regions then signal the need for higher control to the ACC, which in turn activates the fronto-parietal executive control network to improve the performance on the next trial.

Joint Estimation of Effective Brain Wave Activation Modes Using EEG/MEG Sensor Arrays and Multimodal MRI Volumes

In this letter, we present a new method for integration of sensor-based multifrequency bands of electroencephalography and magnetoencephalography data sets into a voxel-based structural-temporal magnetic resonance imaging analysis by utilizing the general joint estimation using entropy regularization (JESTER) framework. This allows enhancement of the spatial-temporal localization of brain function and the ability to relate it to morphological features and structural connectivity. This method has broad implications for both basic neuroscience research and clinical neuroscience focused on identifying disease-relevant biomarkers by enhancing the spatial-temporal resolution of the estimates derived from current neuroimaging modalities, thereby providing a better picture of the normal human brain in basic neuroimaging experiments and variations associated with disease states.

Exploring the origins of EEG motion artefacts during simultaneous fMRI acquisition: Implications for motion artefact correction

Motion artefacts (MAs) are induced within EEG data collected simultaneously with fMRI when the subject's head rotates relative to the magnetic field. The effects of these artefacts have generally been ameliorated by removing periods of data during which large artefact voltages appear in the EEG traces. However, even when combined with other standard post-processing methods, this strategy does not remove smaller MAs which can dominate the neuronal signals of interest. A number of methods are therefore being developed to characterise the MA by measuring reference signals and then using these in artefact correction. These methods generally assume that the head and EEG cap, plus any attached sensors, form a rigid body which can be characterised by a standard set of six motion parameters. Here we investigate the motion of the head/EEG cap system to provide a better understanding of MAs. We focus on the reference layer artefact subtraction (RLAS) approach, as this allows measurement of a separate reference signal for each electrode that is being used to measure brain activity.

Through a series of experiments on phantoms and subjects, we find that movement of the EEG cap relative to the phantom and skin on the forehead is relatively small and that this non-rigid body movement does not appear to cause considerable discrepancy in artefacts between the scalp and reference signals. However, differences in the amplitude of these signals is observed which may be due to differences in geometry of the system from which the reference signals are measured compared with the brain signals. In addition, we find that there is non-rigid body movement of the skull and skin which produces an additional MA component for a head shake, which is not present for a head nod. This results in a large discrepancy in the amplitude and temporal profile of the MA measured on the scalp and reference layer, reducing the efficacy of MA correction based on the reference signals.

Together our data suggest that the efficacy of the correction of MA using any reference-based system is likely to differ for different types of head movement with head shake being the hardest to correct. This provides new information to inform the development of hardware and post-processing methods for removing MAs from EEG data acquired simultaneously with fMRI data.

EEG-Informed fMRI: A Review of Data Analysis Methods

The simultaneous acquisition of electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data. On the EEG side, we focus on the correction for several MR-induced artifacts, particularly the gradient and pulse artifacts, as well as other sources of EEG artifacts. On the fMRI side, we consider image artifacts induced by the presence of EEG hardware inside the MR scanner, and the contamination of the fMRI signal by physiological noise of non-neuronal origin, including a review of several approaches to model and remove it. We then provide an overview of the approaches specifically employed for the integration of EEG and fMRI when using EEG to predict the blood oxygenation level dependent (BOLD) fMRI signal, the so-called EEG-informed fMRI integration strategy, the most commonly used strategy in EEG-fMRI research. Finally, we systematically review methods used for the extraction of EEG features reflecting neuronal phenomena of interest.

Spatial Mnemonic Encoding: Theta Power Decreases and Medial Temporal Lobe BOLD Increases Co-Occur during the Usage of the Method of Loci

The method of loci is one, if not the most, efficient mnemonic encoding strategy. This spatial mnemonic combines the core cognitive processes commonly linked to medial temporal lobe (MTL) activity: spatial and associative memory processes. During such processes, fMRI studies consistently demonstrate MTL activity, while electrophysiological studies have emphasized the important role of theta oscillations (3-8 Hz) in the MTL. However, it is still unknown whether increases or decreases in theta power co-occur with increased BOLD signal in the MTL during memory encoding. To investigate this question, we recorded EEG and fMRI separately, while human participants used the spatial method of loci or the pegword method, a similarly associative but nonspatial mnemonic. The more effective spatial mnemonic induced a pronounced theta power decrease source localized to the left MTL compared with the nonspatial associative mnemonic strategy. This effect was mirrored by BOLD signal increases in the MTL. Successful encoding, irrespective of the strategy used, elicited decreases in left temporal theta power and increases in MTL BOLD activity. This pattern of results suggests a negative relationship between theta power and BOLD signal changes in the MTL during memory encoding and spatial processing. The findings extend the well known negative relation of alpha/beta oscillations and BOLD signals in the cortex to theta oscillations in the MTL.