la Fougere, C. | Search bioRxiv

bioRxiv2025

From stomach to striatum: Ghrelin infusions increase work for rewards

Preclinical evidence demonstrates that gut signals influence motivated behavior through the dopaminergic system. However, translational research in humans is scarce, and it is not known if surges of the stomach-derived hormone ghrelin acutely boost motivation via dopamine transmission. To close this gap, we investigated the effects of acyl ghrelin infusions (vs. saline) on instrumental work for rewards, brain responses, and dopamine transmission in healthy adults in a double-blind, randomized and placebo-controlled crossover study with [11C]raclopride PET-fMRI. In line with preclinical findings, ghrelin enhanced hunger sensations (p = .007), and effort for food and small rewards. Crucially, ghrelin enhanced functional connectivity between the hypothalamus and the striatum (NAcc: pSVC = .016), as well as within the striatum (NAcc<>Putamen: pSVC = .001), pointing to an enhanced coupling between homeostatic and motivational circuits. However, ghrelin did not alter dopamine binding potential (reflecting changes in endogenous tone), but boosted task-free phasic pulses of the NAcc BOLD signal (p = .020), which were negatively associated with binding potential (p = .034). During the task, ghrelin increased cue- (precentral gyrus: pFWE = .003) and effort-evoked brain responses (e.g., VTA/SN: psvc = .002) in accordance with increases in motivation. Together, these findings recapitulate preclinical work that ghrelin primarily boosts phasic dopamine release, reflecting enhanced incentive salience of food and smaller rewards. This highlights the potential of targeting gut-brain interactions to improve motivational symptoms, such as loss of appetite or anhedonia. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/691596v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@4321e6org.highwire.dtl.DTLVardef@166bda5org.highwire.dtl.DTLVardef@2ca69dorg.highwire.dtl.DTLVardef@16e93a9_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2022

Linking neuronal and hemodynamic network signatures in the resting human brain

Despite several studies investigating the relationship between blood-oxygen-level-dependent functional MRI (BOLD-fMRI) and neuroelectric activity, our understanding is rather incomplete. For instance, the canonical hemodynamic response function (HRF) is commonly used, regardless of brain region, frequency of electric activity and functional networks. We studied this relationship between BOLD-fMRI and electroencephalography (EEG) signal of the human brain in detail using simultaneous fMRI and EEG in healthy awake human subjects at rest. Signals from EEG sensors were filtered into different frequency bands and reconstructed it in the three-dimensional source space. The correlation of the time courses of the two modalities were quantified on a voxel-by-voxel basis on full-brain level as well as separately for each resting state network, with different temporal shifts and EEG frequency bands. We found highly significant correlations between the BOLD-fMRI signal and simultaneously measured EEG, yet with varying time-lags for different frequency bands and different resting state networks. Additionally, we found significant negative correlations with a much longer delay in the fMRI BOLD signal. The positive correlations were mostly around 6-8 seconds delayed in the BOLD time course while the negative correlations were noticed with a BOLD delay of around 20 to 26 seconds. These positive and negative correlation patterns included the commonly reported alpha and gamma bands but also extend in other frequency bands giving characteristic profiles for different resting state networks. Our results confirm recent works that suggest that the relationship between the two modalities is rather brain region / network-specific than a global function and suggest that applying a global canonical HRF for electrophysiological data is probably insufficient to account for the different spatial and temporal dynamics of different brain networks. Moreover, our results suggest that the HRF also varies in different frequency bands giving way to further studies investigating cross-frequency coupling and its interplay with resting state networks.

neuroscience↗