Autonomic Neuroscience is devoted to key findings about the development, function and dysfunction of the autonomic nervous system. We encourage submissions on basic and clinical aspects of autonomic regulation and its development. This includes research focused on specific regional aspects of body function, such as neuronal control of cardiovascular, digestive, genitourinary and respiratory function, and issues that impact more broadly on the body’s activities, such as neuronal regulation of metabolism, feeding and temperature. Autonomic Neuroscience has recently merged with Enteric Neuroscience, so now includes a major focus on neural control of gastrointestinal functions. This includes studies on the enteric nervous system (the “little brain” within the gastrointestinal tract), neural coordination between different intestinal regions, and the “brain-gut axis”. Our aim is to foster research that integrates all levels of autonomic function, including the development, dysfunction and aging of autonomic neurons and their circuits; communication with glial cells, interstitial cells and non-neuronal sensory cells; molecular mechanisms mediating synaptic, neuromuscular and neuroeffector transmission; identities of neurotransmitters; structural and dynamic properties of circuits and their interactions with the sensory and effector mechanisms that generate complex functions; relevant aspects of brainstem, hypothalamic and limbic function; emotional and motivational aspects of autonomic regulation. Submissions that address communication between the autonomic system and other regulatory systems are also strongly encouraged, including interactions with visceral sensation and pain, the immune system, inflammation, and neuroendocrine regulation. We welcome molecular, cellular and genetic analyses, investigations of tissue, organ and system function using anatomical, physiological and pharmacological methods, and studies of complex behaviors and clinical problems resulting from autonomic dysfunction. We also encourage studies using computational and mathematical models, especially those where the model’s predictions are tested experimentally.