Decoding the morphology and physical connections of all the neurons populating a brain is necessary for predicting and studying the relationships between its form and function, as well as for documenting structural abnormalities in neuropathies. Digitizing a complete and high-fidelity map of the mammalian brain at the micro-scale will allow neuroscientists to understand disease, consciousness, and ultimately what it is that makes us humans. The critical obstacle for reaching this goal is the lack of robust and accurate tools able to deal with 3D datasets representing dense-packed cells in their native arrangement within the brain. This obliges neuroscientist to manually identify the neurons populating an acquired digital image stack, a notably time-consuming procedure prone to human bias. Here we review the automatic and semi-automatic algorithms and software for neuron segmentation available in the literature, as well as the metrics purposely designed for their validation, highlighting their strengths and limitations. In this direction, we also briefly introduce the recent advances in tissue clarification that enable significant improvements in both optical access of neural tissue and image stack quality, and which could enable more efficient segmentation approaches. Finally, we discuss new methods and tools for processing tissues and acquiring images at sub-cellular scales, which will require new robust algorithms for identifying neurons and their sub-structures (e.g., spines, thin neurites). This will lead to a more detailed structural map of the brain, taking twenty-first century cellular neuroscience to the next level, i.e., the Structural Connectome.

Tissue clarification has been recently proposed to allow deep tissue imaging without light scattering. The clarification parameters are somewhat arbitrary and dependent on tissue type, source and dimension: every laboratory has its own protocol, but a quantitative approach to determine the optimum clearing time is still lacking. Since the use of transgenic mouse lines that express fluorescent proteins to visualize specific cell populations is widespread, a quantitative approach to determine the optimum clearing time for genetically labeled neurons from thick murine brain slices using CLARITY2 is described. In particular, as the main objective of the delipidation treatment is to clarify tissues, while limiting loss of fluorescent signal, the "goodness" of clarification was evaluated by considering the bulk tissue clarification index (BTCi) and the fraction of the fluorescent marker retained in the slice as easily quantifiable macroscale parameters. Here we describe the approach, illustrating an example of how it can be used to determine the optimum clearing time for 1 mm-thick cerebellar slice from transgenic L7GFP mice, in which Purkinje neurons express the GFP (green fluorescent protein) tag. To validate the method, we evaluated confocal stacks of our samples using standard image processing indices (i.e., the mean pixel intensity of neurons and the contrast-to -noise ratio) as figures of merit for image quality. The results show that detergent-based delipidation for more than 5 days does not increase tissue clarity but the fraction of GFP in the tissue continues to diminish. The optimum clearing time for 1 mm-thick slices was thus identified as 5 days, which is the best compromise between the increase in light penetration depth due to removal of lipids and a decrease in fluorescent signal as a consequence of protein loss: further clearing does not improve tissue transparency, but only leads to more protein removal or degradation. The rigorous quantitative approach described can be generalized to any clarification method to identify the moment when the clearing process should be terminated to avoid useless protein loss.

Previous studies suggest that autism spectrum disorders are characterized by alterations in the microbiota–gut–brain axis. Probiotics may modify the composition and the functionality of the gut microbiota of autism spectrum disorder individuals, with possible cascading effects on brain function. In this study, we analyzed possible brain modifications induced by the administration of probiotics in 46 children with autism spectrum disorder using electroencephalography. A randomized 6-month controlled trial was performed. In subjects treated with probiotics, we observed a decrease of power in frontopolar regions in beta and gamma bands, and increased coherence in the same bands together with a shift in frontal asymmetry, which suggests a modification toward a typical brain activity. Electroencephalography measures were significantly correlated with clinical and biochemical measures. These findings support the importance of further investigations on probiotics’ benefits in autism spectrum disorder to better elucidate mechanistic links between probiotics supplementation and changes in brain activity. Lay abstract This study investigates the effects of a probiotic on preschoolers’ brain electrical activity with autism spectrum disorder. Autism is a disorder with an increasing prevalence characterized by an enormous individual, family, and social cost. Although the etiology of autism spectrum disorder is unknown, an interaction between genetic and environmental factors is implicated, converging in altered brain synaptogenesis and, therefore, connectivity. Besides deepening the knowledge on the resting brain electrical activity that characterizes this disorder, this study allows analyzing the positive central effects of a 6-month therapy with a probiotic through a randomized, double-blind placebo-controlled study and the correlations between electroencephalography activity and biochemical and clinical parameters. In subjects treated with probiotics, we observed a decrease of power in frontopolar regions in beta and gamma bands, and increased coherence in the same bands together with a shift in frontal asymmetry, which suggests a modification toward a typical brain activity. Electroencephalography measures were significantly correlated with clinical and biochemical measures. These findings support the importance of further investigations on probiotics’ benefits in autism spectrum disorder to better elucidate mechanistic links between probiotics supplementation and changes in brain activity.