Maternal immune activation during pregnancy impacts on brain structure and function in the adult offspring.

Gestational infection constitutes a risk factor for the occurrence of psychiatric disorders in the offspring. Activation of the maternal immune system (MIA) with subsequent impact on the development of the fetal brain is considered to form the neurobiological basis for aberrant neural wiring and the psychiatric manifestations later in offspring life. The examination of validated animal models constitutes a premier resource for the investigation of the neural underpinnings. Here we used a mouse model of MIA based upon systemic treatment of pregnant mice with Poly(I:C) (polyriboinosinic-polyribocytidilic acid), for the unbiased and comprehensive analysis of the impact of MIA on adult offspring brain activity, morphometry, connectivity and function by a magnetic resonance imaging (MRI) approach. Overall lower neural activity, smaller brain regions and less effective fiber structure were observed for Poly(I:C) offspring compared to the control group. The corpus callosum was significantly smaller and presented with a disruption in myelin/ fiber structure in the MIA progeny. Subsequent resting-state functional MRI experiments demonstrated a paralleling dysfunctional interhemispheric connectivity. Additionally, while the overall flow of information was intact, cortico-limbic connectivity was hampered and limbic circuits revealed hyperconnectivity in Poly(I:C) offspring. Our study sheds new light on the impact of maternal infection during pregnancy on the offspring brain and identifies aberrant resting-state functional connectivity patterns as possible correlates of the behavioral phenotype with relevance for psychiatric disorders.

Snack food as a modulator of human resting-state functional connectivity.

OBJECTIVE: To elucidate the mechanisms of how snack foods may induce non-homeostatic food intake, we used resting state functional magnetic resonance imaging (fMRI), as resting state networks can individually adapt to experience after short time exposures. In addition, we used graph theoretical analysis together with machine learning techniques (support vector machine) to identifying biomarkers that can categorize between high-caloric (potato chips) vs. low-caloric (zucchini) food stimulation. METHODS: Seventeen healthy human subjects with body mass index (BMI) 19 to 27 underwent 2 different fMRI sessions where an initial resting state scan was acquired, followed by visual presentation of different images of potato chips and zucchini. There was then a 5-minute pause to ingest food (day 1=potato chips, day 3=zucchini), followed by a second resting state scan. fMRI data were further analyzed using graph theory analysis and support vector machine techniques. RESULTS: Potato chips vs. zucchini stimulation led to significant connectivity changes. The support vector machine was able to accurately categorize the 2 types of food stimuli with 100% accuracy. Visual, auditory, and somatosensory structures, as well as thalamus, insula, and basal ganglia were found to be important for food classification. After potato chips consumption, the BMI was associated with the path length and degree in nucleus accumbens, middle temporal gyrus, and thalamus. CONCLUSION: The results suggest that high vs. low caloric food stimulation in healthy individuals can induce significant changes in resting state networks. These changes can be detected using graph theory measures in conjunction with support vector machine. Additionally, we found that the BMI affects the response of the nucleus accumbens when high caloric food is consumed.