Effective brain connectivity at rest is associated with choice-induced preference formation

The double-edged sword of the hippocampus-ventromedial prefrontal cortex resting-state connectivity in stress susceptibility and resilience: A prospective study

The hippocampus has long been considered a pivotal region implicated in both stress susceptibility and resilience. A wealth of evidence from animal and human studies underscores the significance of hippocampal functional connectivity with the ventromedial prefrontal cortex (vmPFC) in these stress-related processes. However, there remains a scarcity of research that explores and contrasts the roles of hippocampus-vmPFC connectivity in stress susceptibility and resilience when facing a real-life traumatic event from a prospective standpoint. In the present study, we investigated the contributions of undirected and directed connectivity between the hippocampus and vmPFC to stress susceptibility and resilience within the context of the COVID-19 pandemic. Our findings revealed that the left hippocampus-left vmPFC connectivity prior to the pandemic exhibited a negative correlation with both stress susceptibility and resilience. Specifically, individuals with stronger left hippocampus-left vmPFC connectivity reported experiencing fewer stress-related feelings during the outbreak period of the epidemic but displayed lower levels of stress resilience five months later. Our application of spectral dynamic causal modeling unveiled an additional inhibitory connectivity pathway from the left hippocampus to the left vmPFC in the context of stress susceptibility, which was notably absent in stress resilience. Furthermore, we observed a noteworthy positive association between self-inhibition of the vmPFC and stress susceptibility, with this effect proving substantial enough to predict an individual's susceptibility to stress; conversely, these patterns did not manifest in the realm of stress resilience. These findings enrich our comprehension of stress susceptibility and stress resilience and might have implications for innovative approaches to managing stress-related disorders.

Hypothalamic effective connectivity at rest is associated with body weight and energy homeostasis

Hunger and satiety drive eating behaviours via changes in brain function. The hypothalamus is a central component of the brain networks that regulate food intake. Animal research parsed the roles of the lateral hypothalamus (LH) and medial hypothalamus (MH) in hunger and satiety, respectively. Here, we examined how hunger and satiety change information flow between human LH and MH brain networks, and how these interactions are influenced by body mass index (BMI). Forty participants (16 overweight/obese) underwent two resting-state functional MRI scans while being fasted and sated. The excitatory/inhibitory influence of information flow between the MH and LH was modelled using spectral dynamic causal modelling. Our results revealed two core networks interacting across homeostatic state and weight: subcortical bidirectional connections between the LH, MH and the substantia nigra pars compacta (prSN), and cortical top-down inhibition from fronto-parietal and temporal areas. During fasting, we found higher inhibition between the LH and prSN, whereas the prSN received greater top-down inhibition from across the cortex. Individuals with higher BMI showed that these network dynamics occur irrespective of homeostatic state. Our findings reveal fasting affects brain dynamics over a distributed hypothalamic-midbrain-cortical network. This network is less sensitive to state-related fluctuations among people with obesity.

Coexistence of sensory qualities and value representations in human orbitofrontal cortex

Despite the multiple regions and neural networks associated with value-based decision-making, the orbitofrontal cortex (OFC) is possible a particularly important one. Although the role of the OFC in reinforcer devaluation tasks, which assess the ability to represent identity, sensory qualities, and subjective values of the expected outcomes, has been established, the specific aspect represented in this area remains unclear. In this study, using functional magnetic resonance imaging, wherein participants rated the palatability of 128 food items using photographs, we investigated whether the human OFC represents object identity, sensory qualities, or value. Employing many items helped us dissociate object identity from sensory qualities and values; the inferred sensory qualities of identical items were manipulated by a change in metabolic state. Moreover, value differences between items were analytically controlled by employing a technique similar to age adjustment. The palatability ratings for food items significantly decreased after a meal. Using representational similarity analysis, we confirmed that the OFC represents value. Moreover, identical items were represented similarly in the lateral OFC in a given metabolic state; however, these representations were altered post-feeding. Importantly, this change was not explained by subjective value, suggesting that the OFC represents sensory quality and value, but not object identity.

Neural network modelling reveals changes in directional connectivity between cortical and hypothalamic regions with increased BMI

BACKGROUND/OBJECTIVES

Obesity has been ascribed to corticostriatal regions taking control over homeostatic areas. To test this assumption, we applied an effective connectivity approach to reveal the direction of information flow between brain regions and the valence of connections (excitatory versus inhibitory) as a function of increased BMI and homeostatic state.

SUBJECTS/METHODS

Forty-one participants (21 overweight/obese) underwent two resting-state fMRI scans: after overnight fasting (hunger) and following a standardised meal (satiety). We used spectral dynamic causal modelling to unravel hunger and increased BMI-related changes in directed connectivity between cortical, insular, striatal and hypothalamic regions.

RESULTS

During hunger, as compared to satiety, we found increased excitation of the ventromedial prefrontal cortex over the ventral striatum and hypothalamus, suggesting enhanced top-down modulation compensating energy depletion. Increased BMI was associated with increased excitation of the anterior insula over the hypothalamus across the hunger and satiety conditions. The interaction of hunger and increased BMI yielded decreased intra-cortical excitation from the dorso-lateral to the ventromedial prefrontal cortex.

CONCLUSIONS

Our findings suggest that excess weight and obesity is associated with persistent top-down excitation of the hypothalamus, regardless of homeostatic state, and hunger-related reductions of dorso-lateral to ventromedial prefrontal inputs. These findings are compatible with eating without hunger and reduced self-regulation views of obesity.

Dynamic Causal Modeling on the Identification of Interacting Networks in the Brain: A Systematic Review

Dynamic causal modeling (DCM) has long been used to characterize effective connectivity within networks of distributed neuronal responses. Previous reviews have highlighted the understanding of the conceptual basis behind DCM and its variants from different aspects. However, no detailed summary or classification research on the task-related effective connectivity of various brain regions has been made formally available so far, and there is also a lack of application analysis of DCM for hemodynamic and electrophysiological measurements. This review aims to analyze the effective connectivity of different brain regions using DCM for different measurement data. We found that, in general, most studies focused on the networks between different cortical regions, and the research on the networks between other deep subcortical nuclei or between them and the cerebral cortex are receiving increasing attention, but far from the same scale. Our analysis also reveals a clear bias towards some task types. Based on these results, we identify and discuss several promising research directions that may help the community to attain a clear understanding of the brain network interactions under different tasks.

Effective brain connectivity at rest is associated with choice-induced preference formation

Preferences can change as a consequence of making hard decisions whereby the value of chosen options increases and the value of rejected options decreases. Such choice-induced preference changes have been associated with brain areas detecting choice conflict (anterior cingulate cortex, ACC), updating stimulus value (dorsolateral prefrontal cortex, dlPFC) and supporting memory of stimulus value (hippocampus and ventromedial prefrontal cortex, vmPFC). Here we investigated whether resting-state neuronal activity within these regions is associated with the magnitude of individuals' preference updates. We fitted a dynamic causal model (DCM) to resting-state neuronal activity in the spectral domain (spDCM) and estimated the causal connectivity among core regions involved in preference formation following hard choices. The extent of individuals' choice-induced preference changes were found to be associated with a diminished resting-state excitation between the left dlPFC and the vmPFC, whereas preference consistency was related to a higher resting-state excitation from the ACC to the left hippocampus and vmPFC. Our results point to a model of preference formation during which the dynamic network configurations between left dlPFC, ACC, vmPFC and left hippocampus at rest are linked to preference change or stability.