Accurate removal of magnetic resonance imaging (MRI) signal outside the brain, a.k.a., skull stripping, is a key step in the brain image pre-processing pipelines. In rodents, this is mostly achieved by manually editing a brain mask, which is time-consuming and operator dependent. Automating this step is particularly challenging in rodents as compared to humans, because of differences in brain/scalp tissue geometry, image resolution with respect to brain-scalp distance, and tissue contrast around the skull. In this study, we proposed a deep-learning-based framework, U-Net, to automatically identify the rodent brain boundaries in MR images. The U-Net method is robust against inter-subject variability and eliminates operator dependence. To benchmark the efficiency of this method, we trained and validated our model using both in-house collected and publicly available datasets. In comparison to current state-of-the-art methods, our approach achieved superior averaged Dice similarity coefficient to ground truth T2-weighted rapid acquisition with relaxation enhancement and T2 *-weighted echo planar imaging data in both rats and mice (all p < 0.05), demonstrating robust performance of our approach across various MRI protocols.

Glutamate is ubiquitous throughout the brain and serves as the primary excitatory neurotransmitter. Neurons require energy to fire, and energetic substrates (i.e., O2, glucose) are renewed via cerebral blood flow (CBF) to maintain metabolic homeostasis. Magnetic resonance brain functionality studies rely on the assumption that CBF and neuronal activity are coupled consistently throughout the brain; however, the origin of neuronal activity does not always coincide with signals indicative of energy consumption (e.g., O2 decreases) at high spatial resolutions. Therefore, relationships between excitatory neurotransmission and energy use must be evaluated at higher resolutions. In this study, we showed that both endogenously released and exogenously ejected glutamate decrease local tissue O2 concentrations, but whether hyperemic O2 restoration followed depended on the stimulus method. Electrically stimulating the glutamatergic corticostriatal pathway evoked biphasic O2 responses at striatal terminals: first O2 decreased, then concentrations increased above baseline. Using iontophoresis to locally eject ionotropic glutamate receptor antagonists revealed that these receptors only influenced the O2 decrease. We compared electrical stimulation to iontophoretic glutamate stimulation, and measured concurrent single-unit activity and O2 to limit both stimulation and recordings to <50 μm radius from our sensor. Similarly, iontophoretic glutamate delivery elicited monophasic O2 decreases without subsequent increases.

Microiontophoresis is a drug delivery method in which an electric current is used to eject molecular species from a micropipette. It has been primarily utilized for neurochemical investigations, but is limited due to difficulty controlling and determining the ejected quantity. Consequently the concentration of an ejected species and the extent of the affected region are relegated to various methods of approximation. To address this, we investigated the principles underlying ejection rates and examined the concentration distribution in microiontophoresis using a combination of electrochemical, chromatographic, and fluorescence-based approaches. This involved a principal focus on how the iontophoretic barrel solution affects ejection characteristics. The ion ejection rate displayed a direct correspondence to the ionic mole fraction, regardless of the ejection current polarity. In contrast, neutral molecules are ejected by electroosmotic flow (EOF) at a rate proportional to the barrel solution concentration. Furthermore, the presence of EOF was observed from barrels containing high ionic strength solutions. In practice, use of a retaining current draws extracellular ions into the barrel and will alter the barrel solution composition. Even in the absence of a retaining current, diffusional exchange at the barrel tip will occur. Thus behavior of successive ejections may slightly differ. To account for this, electrochemical or fluorescence markers can be incorporated into the barrel solution in order to compare ejection quantities. These may also be used to provide an estimate of the ejected amount and distribution provided accurate use of calibration procedures.

The vascular contributions of neurotransmitters to the hemodynamic response are gaining more attention in neuroimaging studies, as many neurotransmitters are vasomodulatory. To date, well-established electrochemical techniques that detect neurotransmission in high magnetic field environments are limited. Here, we propose an experimental setting enabling simultaneous fast-scan cyclic voltammetry (FSCV) and blood oxygenation level-dependent functional magnetic imaging (BOLD fMRI) to measure both local tissue oxygen and dopamine responses, and global BOLD changes, respectively. By using MR-compatible materials and the proposed data acquisition schemes, FSCV detected physiological analyte concentrations with high temporal resolution and spatial specificity inside of a 9.4 T MRI bore. We found that tissue oxygen and BOLD correlate strongly, and brain regions that encode dopamine amplitude differences can be identified via modeling simultaneously acquired dopamine FSCV and BOLD fMRI time-courses. This technique provides complementary neurochemical and hemodynamic information and expands the scope of studying the influence of local neurotransmitter release over the entire brain.