The release of dopamine (DA) during reward tasks is modulated by major depressive disorder (MDD) ¹. This multi-modal study of MDD used PET and fMRI simultaneously to detect and measure the neurochemical changes of DA by PET and neurovascular activity through BOLD contrast during monetary incentive delay tasks. Specifically, in this pilot study, different modeling methods of dynamic PET data were proposed and evaluated for concurrent PET-fMRI study with two sequential monetary incentive delay (MID) tasks in a single scan.

Data acquisition: We simultaneously acquired PET and fMRI data on a PET/MR system (GE Healthcare, Milwaukee). Six participants with major depressive disorder underwent a 50min or 40min PET scan with [¹¹C] raclopride and a 32min MR scan simultaneously. During the scan, participants performed two 10-min MID tasks (high ($5) and low ($1) stakes) sequentially, each divided into two conditions including reward (winning or not losing money) and punishment (losing money).

fMRI analysis: Slice-timing correction, motion correction, spatial smoothing and a quadratic detrending were performed for all fMRI data. Statistical analysis was performed using a two-stage mixed effect model. In the first stage, voxel-wise regression analysis of the data of each subject was performed. The hemodynamic response was modeled by convolving the task design with a canonical hemodynamic response function ². Each subject's brain data were normalized to the standard template provided by the Montreal Neurological Institute (MNI) template using SPM8 ³. In the second stage, one-sample t tests were calculated over images of the interested contrasts to obtain group activation maps.

PET analysis: For PET data, statistical analysis was performed using general linear model (GLM). The task related regressors were derived from the results obtained in the previous experiments in which variations due to endogenous dopamine release in the striatum were modeled using two exponential functions with time constants of 3 min. To detect task-related signal changes in response to two sequential MID tasks, three methods, quadratic fitting, gamma fitting of the average signal of striatum region with 1st or 2nd order detrend, have been tried by including them in the GLM as covariates of no interest. They were compared with the conventional kinetic model LSSRM ⁴.

Kinetic simulations were performed to simulate the time-activity curves (TACs) of the whole brain in order to evaluate the various modeling methods. In the first set of simulations, different amounts of task-related signal decreases were added to the TACs of voxels in striatum region and the proportion of activated voxels were calculated to examine the sensitivity of detecting ligand displacement. The second set of simulations examined the effect of noise on detection of signal using different modeling methods, and tested the false positive rate when there was no task added.

The analysis of the human studies used a GLM model constructed with different modeling methods as described above to obtain the activation maps during the two MID tasks. Group analysis was also performed using one-sample t test.

The results of kinetic simulations are shown in Fig. 1. The sensitivity of all methods to detect signal changes in striatum increased with the decrease of noise and the rise of signal changes. Fig. 2 shows examples of TACs for striatum and cerebellum and their corresponding fitting curves using different methods in the simulation and the human experiment. Single subject t statistical maps acquired from the three methods are compared in Fig. 3.

Fig. 4 illustrates the results of group analysis of both PET (using quadratic fitting) and fMRI. The significant effects due to dopamine release were found in ventral striatum bilaterally, close to the nucleus accumbens in both high and low stake tasks. Significant BOLD signals were located in putamen bilaterally when subjects were studied during reward tasks. But significance was only found at right putamen during high stake punishment tasks.

The PET kinetic simulations demonstrate the feasibility of all the methods to detect task-related signal changes in striatum with relatively low false positive rate. The agreements of the fitting curves and the single subject t statistical maps indicate the similar estimation characteristics of the three modeling methods.

Compared with the conventional kinetic model, quadratic and gamma fitting for PET data are more simple and flexible for different experimental designs and task strategies of concurrent PET-fMRI, and only quadratic fitting shows activations in striatum in group analysis in this study. The results of group analysis demonstrate the dopamine release and fMRI activations in the ventral striatum during the MID reward tasks for MDD patients.