Functional MRI (fMRI) cannot detect primary neuronal activity directly but only secondary hemodynamic responses¹. To probe the neuronal basis of fMRI responses, it is possible to use simultaneous EEG and fMRI measurements (for review, see 2). However, it has been shown that measuring EEG and fMRI inside the magnet has many technical challenges, including the contamination of signal when MRI gradient coil is switching². This gradient artifact (GA) has been commonly addressed by subtracting an artifact template, created from averaging fMRI acquisitions, from the contaminated fMRI measurements³. However, subject’s head motion, the jittering between EEG and fMRI measurements, and insufficient EEG dynamic range can limit the performance of such average artifact subtraction. Here we propose to minimize the fMRI acquisition duration and to maximize the EEG acquisition duration in order to measure BOLD signals and high-quality EEG at the same time. Specifically, inverse imaging (InI), a highly parallel fMRI method capable of completing the whole-head measurement with 5 mm resolution at cortex in 0.1 s⁴, intermittently measured the BOLD signal once every 2 s, in order to minimize GA in concurrent EEG recordings. Experimental results show that our acquisition strategy allows for fMRI similar to that of EPI and event-related potentials measured outside MRI.InI (coronal projection images) only sampled the first 100 ms in 2-s TR. This left a period of 1.9 s (95% of the duty cycle) without artifacts related to MRI magnetization and spatial encoding. Meanwhile, EEG (31 electrodes with impedance < 20 kΩ, reference electrode = FCz) was recorded continuously by a MRI-compatible system (BrainAmp MR Plus, Brain Products GmbH) with 5 kHz sampling rate. Importantly, EEG was temporally synchronized to InI via a 10 MHz clock in the MR scanner. Auditory stimulus (1000 Hz; 200 ms duration) was delivered randomly between 0.2 and 1.4 s after the onset of each TR. There were 50 trials randomly distributed over a 5-minute scan. For comparison, we also recorded the EEG outside MRI with the same auditory stimuli. Conventional multi-slice EPI was also measured concurrently with EEG inside MRI to evaluate how BOLD signal and auditory evoked potentials (AEP) changed by the measurement environment (Figure 1). The InI analysis began by first reconstructing volumetric images the using minimum-norm estimate⁴., EPI were pre-processed by a customized stream (https://git.becs.aalto.fi/bml/bramila). Both InI and EPI were further analyzed by General Linear Model using canonical models to estimate hemodynamic response. The significance of BOLD signals (t-statistics) were morphed to inflated hemispheres of a standard template (fsaverage in FreeSurfer). The EEG analysis started by first removing gradient artifacts using a MRI artifact template estimated directly from EEG-InI recording³. Subsequently, epochs of EEG were created by taking 0.2 s and 0.5 s before and after each onset of auditory stimuli, respectively. AEP was calculated by taking average over epochs and low-pass filtering (50 Hz) was also applied to AEP.Figure 2 shows that significant hemodynamic activity was found at the superior temporal gyrus of both hemispheres by EPI and InI. This suggests that both EPI and InI has similar sensitivity and spatial specificity to detect the BOLD signal elicited by auditory stimuli. Figure 3 shows AEPs at the T7 electrode (close to the left temporal lobe) measured outside MRI, inside MRI with EEG, and inside MRI with InI. AEP’s before and after 50-Hz low-pass filtering were shown. These results suggest that while low-pass filtering on EEG-EPI measurements can generate acceptable AEP, we still found significantly distorted AEP waveforms (before N1 and after P2). On the contrary, EEG-InI can avoid such artifacts without losing information at high frequency and much similar AEP to that measured outside MRI.We proposed a simultaneous EEG-fMRI acquisition method by intermittently measuring the BOLD signal (2 s TR) using ultra-fast fMRI acquisition (InI with 0.1 s sampling time) and concurrent EEG recording. High quality neuronal and hemodynamic response were measured. While we used InI in this study, it is possible to replace it with other fast imaging methods, such as simultaneous-multi-slice CAIPI EPI⁵ to further trade-off between fMRI spatiotemporal resolution and EEG artifacts. In addition to GA, the other prominent noise in EEG acquired inside MRI is the ballistocardiogram (BCG), which is induced EEG signal due to cardiac pulsation. Luckily, BCG is typically below 15 Hz⁶. In experiments interested in cognitive functions, which are physiologically more related to neuronal oscillation beta (~ 20 Hz) and gamma (> 40 Hz) bands, BCG can be effectively suppressed by low-pass filtering.