In functional magnetic resonance imaging (fMRI), neural activity is inferred from the associated hemodynamic response. However, the degree to which hemodynamics can track dynamic changes in neuronal activity, and thus the ultimate temporal resolution of fMRI, remains unknown. To evaluate the detectability of stimulus-driven high-frequency blood oxygenation level dependent (BOLD) signal oscillations in functionally and vascularly distinct cerebral cortical areas, stimuli up to 0.5 Hz were used to evoke activation in the primary somatosensory and motor cortex. Despite their functional and vascular differences, a similar frequency dependence was observed in both cortical areas. We then proceeded to investigate these signals at different levels of the cortical vascular hierarchy, using cortical depth as a proxy. We observed that, above 0.33 Hz, the BOLD response amplitude decreased faster with increasing frequency near the pial surface than in the parenchyma, suggesting that, in addition to exhibiting high spatial specificity, parenchymal signals—accessible with high spatial resolution imaging—also attenuate less rapidly when the stimulus frequency is increased. In addition, as the stimulus frequency increased, we observed larger relative phase differences in the BOLD oscillations across cortical depths. When averaged across depths, these signals can thus interfere destructively, suggesting that high spatial resolutions can avoid this phase cancellation and thereby aid in the detection of rapid BOLD oscillations.

Recently, a new method was introduced to detect neuronal activity using Magnetic Resonance Imaging (MRI). The method, referred to as DIANA, showed MRI signals with millisecond temporal resolution that correlated with local field potentials measured invasively in mice. Troublingly, attempts by other groups to detect the DIANA signals in humans at 7 Tesla and mice at 15.2 Tesla have failed. So far, attempts to reproduce DIANA in small rodents have focused on paradigms using whisker pad stimulation, which were expected to produce a 0.1–0.15% signal change. However, the Supplementary Material accompanying the original DIANA paper showed that visual stimulation produced a three times larger signal, which should be much easier to detect. Therefore, we attempted to find the DIANA signal in rats using a visual stimulation paradigm. Experiments were performed at 17.2 Tesla but also at 7.0 Tesla to see if the DIANA signal appears at a lower field strength where T2 is longer and BOLD contributions are reduced. In addition, simulations were performed to investigate the theoretical detectability of synthetic DIANA signals in noisy data. Although our data indicated that a 0.1% signal change would have been detectable, we did not observe a DIANA signal. We did observe neuronally driven hemodynamic signal variations that were much larger than the anticipated DIANA signal. The amplitude of these signal changes was relatively similar at 7.0 and 17.2 Tesla (0.7% vs 1.1%). Numerical simulations indicated, however, that the measured hemodynamic signal changes would not interfere with the detection of DIANA signals. Therefore, it is reasonable to expect that measurements at higher field strength with improved SNR would have a better chance to detect the DIANA signal. Yet, we, among others, were unable to find it.

Functional MRI (fMRI) has been widely used to study activity patterns in the human brain. It infers neuronal activity from the associated hemodynamic response, which fundamentally limits its spatiotemporal specificity. In mice, the Direct Imaging of Neuronal Activity (DIANA) method revealed MRI signals that correlated with extracellular electric activity, showing high spatiotemporal specificity. In this work, we attempted DIANA in humans. Five experimental paradigms were tested, exploring different stimulus types (flickering noise patterns, and naturalistic images), stimulus durations (50–200 ms), and imaging resolution (2 × 2 × 5 mm 3 and 1 × 1 × 5 mm 3 ). Regions of interest (ROI) were derived from Blood Oxygen Level Dependent (BOLD) fMRI acquisitions (both EPI and FLASH based) and T1-weighted anatomical scans. In Paradigm I ( n = 1), using flickering noise patterns, signals were detected that resembled possible functional activity from a small ROI. However, changes in stimulus duration did not lead to corresponding signal changes (Paradigm II; n = 1). Therefore, care should be taken not to mistake artifacts for neuronal activity. In Paradigm III ( n = 3), when averaged across multiple subjects, a ~200 ms long 0.02% signal increase was observed ~100 ms after the stimulus onset (10x smaller than the expected signal). However, white matter control ROIs showed similarly large signal fluctuations. In Paradigm IV ( n = 3), naturalistic image stimuli were used, but did not reveal signs of a potential functional signal. To reduce partial voluming effects and improve ROI definition, in Paradigm V ( n = 3), we acquired data with higher resolution (1 × 1 × 5 mm 3 ) using naturalistic images. However, no sign of activation was found. It is important to note that repetitive experiments with short interstimulus intervals were found to be strenuous for the subjects, which likely impacted data quality. To obtain better data, improvements in sequence and stimulus designs are needed to maximize the DIANA signal and minimize confounds. However, without a clear understanding of DIANA’s biophysical underpinnings it is difficult to do so. Therefore, it may be more effective to first investigate DIANA signals with simultaneously recorded electrophysiological signals in more controlled settings, e.g., in anesthetized mice.