Left-brain bias in connectivity between social and auditory neural networks of bats

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Bat neuroscience research has proven to be highly informative yet somewhat overly cautious. Studies employing classic electrophysiological and behavioral techniques in bats have formed the foundations of many discoveries related to auditory processing, especially echolocation. However, since bats are wild-caught and do not readily breed in captivity, their use in neuroscience research is more limited than rodents. As a result, their use in modern neuroimaging techniques, such as functional MRI, has been limited too. This study represents (to our knowledge) the first *complete* fMRI study of a bat species. It reports a default mode-like network (DMLN, similar to the default mode network humans and other mammals) in bats, shows DMLN's strong connectivity with auditory cortex, and shows that those connections are preferentially left hemispheric. It must also be noted that the loudest components of MRI gradient noise fall below the hearing range of pale spear-nosed bats (Phyllostomus discolor). This study's results have wide implications for bat research and neuroimaging in general. Specifically, this study: 1. Reveals a focal basal-ganglia resting-state network in a species that has a clear caudate and putamen separated by an internal capsule, a feature that is more characteristic of humans and other primates than rodents and other animals. 2. Reports a network that includes one of the largest amygdalae (i.e., a nuclear complex responsible for processing fear and other emotions) relative to brain size amongst mammals, with the potential for seed-based analyses, and even future neural/behavioral stimulation experiments. 3. Bolsters already existing evidence for hemispheric asymmetry in the auditory cortex of a non-primate mammalian species (namely pale spear-nosed and mustached bats), which may have implications for aphasia, specific language impairment, and other communication disorders affecting humans. 4. Provides a means of acquiring fMRI data with little interference from gradient noise, which has important implications for auditory fMRI research. Each of these four bullet points represents a different “holy grail” long sought after by auditory neuroscientists and/or neuroimaging researchers.

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