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Role of the gut microbiota in the development of alcohol use disorder
The gut microbiota is composed of a very large number of bacteria, viruses, fungi and yeasts that play an important role in the body, through the production of a series of metabolites (including neurotransmitters), and through an essential role in the barrier function of the gut and the regulation of immunity and stress response. In this lecture I will present, based mainly on human studies but also on preclinical studies, the evidence for a role of the gut microbiota in the development of alcohol use disorder. I will show the first results of trials to test the effects of nutritional approaches to address these deficits.
Gut Feelings: The Microbiota-Gut-Brain Axis Across the Lifespan
The microbiota-gut-brain axis is emerging as a research area of increasing interest for those investigating the biological and physiological basis of brain development and behaviour during early life, adolescence & ageing. The routes of communication between the gut and brain include the vagus nerve, the immune system, tryptophan metabolism, via the enteric nervous system or by way of microbial metabolites such as short chain fatty acids. Studies in animal models have shown that the development of an appropriate stress response is dependent on the microbiota. Developmentally, a variety of factors can impact the microbiota in early life including mode of birth delivery, antibiotic exposure, mode of nutritional provision, infection, stress as well as host genetics. Recently, the gut microbiota has been implicated in regulating the stress response, and social behaviour. Moreover, fundamental brain processes from adult hippocampal neurogenesis to myelination to microglia activation have been shown to be regulated by the microbiome. Further studies will focus on understanding the mechanisms underlying such brain effects and how they can be exploited by microbiota-targeted interventions including ‘psychobiotics’ and diet
Recurrent network models of adaptive and maladaptive learning
During periods of persistent and inescapable stress, animals can switch from active to passive coping strategies to manage effort-expenditure. Such normally adaptive behavioural state transitions can become maladaptive in disorders such as depression. We developed a new class of multi-region recurrent neural network (RNN) models to infer brain-wide interactions driving such maladaptive behaviour. The models were trained to match experimental data across two levels simultaneously: brain-wide neural dynamics from 10-40,000 neurons and the realtime behaviour of the fish. Analysis of the trained RNN models revealed a specific change in inter-area connectivity between the habenula (Hb) and raphe nucleus during the transition into passivity. We then characterized the multi-region neural dynamics underlying this transition. Using the interaction weights derived from the RNN models, we calculated the input currents from different brain regions to each Hb neuron. We then computed neural manifolds spanning these input currents across all Hb neurons to define subspaces within the Hb activity that captured communication with each other brain region independently. At the onset of stress, there was an immediate response within the Hb/raphe subspace alone. However, RNN models identified no early or fast-timescale change in the strengths of interactions between these regions. As the animal lapsed into passivity, the responses within the Hb/raphe subspace decreased, accompanied by a concomitant change in the interactions between the raphe and Hb inferred from the RNN weights. This innovative combination of network modeling and neural dynamics analysis points to dual mechanisms with distinct timescales driving the behavioural state transition: early response to stress is mediated by reshaping the neural dynamics within a preserved network architecture, while long-term state changes correspond to altered connectivity between neural ensembles in distinct brain regions.