Functional connectivity (FC) can be inferred from spontaneous fMRI signal fluctuations arising from low frequency brain activity¹. Assessment of FC has not only revealed the spatiotemporal organization of functional networks in the healthy and diseased human brain^1,2, but has also showed homologous organization between nonhuman primates and humans³. The majority of studies investigating FC have applied techniques that assume temporal stationary throughout the scan period^1-3. Recently, it has been shown that FC can undergo dynamic changes within timescales much shorter than a typical 5-10 min scan⁴. The time-varying characteristic of FC may relate to spontaneously shifting of network states and might be of mechanistic importance of FC^4,5. To date, there has been limited investigation into the effects of drugs on either static or dynamic properties of FC leaving many open questions as to the relationship between ongoing functional coupling and the underlying endogenous neurotransmission^6,7. In this study, we investigate pharmacological modulations of static and dynamic FC to opioid receptor selective drugs in nonhuman primates using simultaneous PET/MRI, allowing for the evaluation of FC changes before/after drug administration and concurrent quantification of μ-opioid receptor occupancies.

Ten simultaneous PET/MRI scans were acquired on two NHPs (male macaques, ~12 kg) anesthetized with isoflurane. Images were acquired on a 3T Siemens TIM-Trio with a BrainPET insert and a custom 8-channel coil. PET/MRI scans were acquired from each animal using a μ-opioid radiotracers, [¹¹C]carfentanil. Radiotracer (~10 mCi) was given as a bolus-infusion to obtain steady state equilibrium. PET data were collected for 90 min, stored in list mode and binned into 1-min frames. CBV-fMRI data were obtained following an iron oxide (Feraheme, 10 ug/kg, i.v.)⁸ injection. Graded doses of an opioid receptor antagonist, naloxone (baseline, 0.005, 0.01, 0.03, and 0.05 mg/kg) were given intravenously at 36 min post-radiotracer injection.

PET/MRI data were motion corrected, skull stripped, spatially smoothed, and registered to a standard NHP atlas9. PET data analyzed for receptor binding potentials were referenced to a non-displaceable compartment (BP_ND) using the simplified reference tissue model¹⁰. A gamma-variant function was used to model the PET and fMRI temporal response to drug challenge using a GLM. fMRI time-series were detrended and bandpass-filtered to 0.01-0.1 Hz before FC analysis. White matter, CSF signal and 6 motion parameters were used as nuisances. Fourteen regions were selected based on high-to-low PET BP_ND values. For static FC, fMRI data was broken into three 20-min (pre-, post-, and during drug infusion) sections. A voxel-wise, seed-based correlation analysis were calculated. For dynamic FC, a sliding window correlation analysis was applied on the truncated time-series data (60 sec windows with 50% overlap). ROI-to-ROI correlation coefficient within each window was calculated. The average correlation matrix was computed to show the overall dynamic patterns under different conditions. A k-mean clustering (k = 7) approach was used to group the dynamic FC into diffident functional states and the number of state transitions was calculate.

Naloxone induced robust dose-dependent μ-opioid receptor BP_ND and percent CBV changes (Fig 1). The largest BP_ND reductions were observed in the thalamus and caudate, while the largest CBV changes were observed in the putamen (Fig 1). This spatial mismatch between drug-induced PET and fMRI signals implies potential modulations of downstream brain activity¹¹. Among the 14 regions analyzed, an increase in local (within putamen) and distal (motor cortex and supplementary motor area) FC with putamen was found after naloxone challenge (Fig 2). Interestingly, an early human study investigating the effect of buprenorphine (mu-opioid partial agonist) on static FC showed a decrease between cortical (motor cortex, insula) and subcortical (thalamus) FC with putamen⁶. Cerebellum, an area devoid of μ-opioid receptors, showed an increase in FC with the thalamus during the drug injection period. Dynamic FC patterns were also modulated with naloxone as indicated by weaker pairwise correlations between regions (Fig 3) and larger number of dynamic state transitions. More sophisticated dynamic FC is currently ongoing to investigate the connectivity pattern of each functional state. Group-level analysis to evaluate dose-dependent modulation of FC will also be conducted. Future studies to directly compare the effects of μ-opioid agonists on static and dynamic FC are also of interest.Using simultaneous PET/MRI with pharmacological challenges in NHPs, we showed the engagement of the opioid system and the resulting CBV-fMRI changes in limbic basal ganglia. We found evidence of pharmacological modulation of both static and dynamic FC patterns. Simultaneous PET/MRI provides a powerful tool for studying the impact of neurotransmission on brain function, and has great potential to further our understanding of the neurochemical mechanisms underlying large-scale brain networks.