Neurons have diverse molecular, morphological, connectional and functional properties. We believe that the only realistic way to manage this complexity - and thereby pave the way for understanding the structure, function and development of brain circuits - is to group neurons into types, which can then be analysed systematically and reproducibly. However, neuronal classification has been challenging both technically and conceptually. New high-throughput methods have created opportunities to address the technical challenges associated with neuronal classification by collecting comprehensive information about individual cells. Nonetheless, conceptual difficulties persist. Borrowing from the field of species taxonomy, we propose principles to be followed in the cell-type classification effort, including the incorporation of multiple, quantitative features as criteria, the use of discontinuous variation to define types and the creation of a hierarchical system to represent relationships between cells. We review the progress of classifying cell types in the retina and cerebral cortex and propose a staged approach for moving forward with a systematic cell-type classification in the nervous system.

Neuronal cell-type classification: challenges, opportunities and the path forward

In vivo calcium imaging through microendoscopic lenses enables imaging of previously inaccessible neuronal populations deep within the brains of freely moving animals. However, it is computationally challenging to extract single-neuronal activity from microendoscopic data, because of the very large background fluctuations and high spatial overlaps intrinsic to this recording modality. Here, we describe a new constrained matrix factorization approach to accurately separate the background and then demix and denoise the neuronal signals of interest. We compared the proposed method against previous independent components analysis and constrained nonnegative matrix factorization approaches. On both simulated and experimental data recorded from mice, our method substantially improved the quality of extracted cellular signals and detected more well-isolated neural signals, especially in noisy data regimes. These advances can in turn significantly enhance the statistical power of downstream analyses, and ultimately improve scientific conclusions derived from microendoscopic data.

Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data

Anxiety Cells in a Hippocampal-Hypothalamic Circuit.

Adult neurogenesis in the dentate gyrus of the hippocampus is highly regulated by environmental influences, and functionally implicated in behavioural responses to stress and antidepressants1-4. However, how adult-born neurons regulate dentate gyrus information processing to protect from stress-induced anxiety-like behaviour is unknown. Here we show in mice that neurogenesis confers resilience to chronic stress by inhibiting the activity of mature granule cells in the ventral dentate gyrus (vDG), a subregion that is implicated in mood regulation. We found that chemogenetic inhibition of adult-born neurons in the vDG promotes susceptibility to social defeat stress, whereas increasing neurogenesis confers resilience to chronic stress. By using in vivo calcium imaging to record neuronal activity from large cell populations in the vDG, we show that increased neurogenesis results in a decrease in the activity of stress-responsive cells that are active preferentially during attacks or while mice explore anxiogenic environments. These effects on dentate gyrus activity are necessary and sufficient for stress resilience, as direct silencing of the vDG confers resilience whereas excitation promotes susceptibility. Our results suggest that the activity of the vDG may be a key factor in determining individual levels of vulnerability to stress and related psychiatric disorders.

Hippocampal neurogenesis confers stress resilience by inhibiting the ventral dentate gyrus.

Developments in miniaturized microscopes have enabled visualization of brain activities and structural dynamics in animals engaging in self-determined behaviors However, it remains a challenge to resolve activity at single dendritic spines in freely behaving animals Here, we report the design and application of a fast high-resolution, miniaturized two-photon microscope (FHIRM-TPM) that accomplishes this goal With a headpiece weighing 215 g and a hollow-core photonic crystal fiber delivering 920-nm femtosecond laser pulses, the FHIRM-TPM is capable of imaging commonly used biosensors (GFP and GCaMP6) at high spatiotemporal resolution (064 μm laterally and 335 μm axially, 40 Hz at 256 × 256 pixels for raster scanning and 10,000 Hz for free-line scanning) We demonstrate the microscope's robustness with hour-long recordings of neuronal activities at the level of spines in mice experiencing vigorous body movements

Fast high-resolution miniature two-photon microscopy for brain imaging in freely behaving mice

Genetically encoded calcium indicators for visualizing dynamic cellular activity have greatly expanded our understanding of the brain. However, owing to the light-scattering properties of the brain, as well as the size and rigidity of traditional imaging technology, in vivo calcium imaging has been limited to superficial brain structures during head-fixed behavioral tasks. These limitations can now be circumvented by using miniature, integrated microscopes in conjunction with an implantable microendoscopic lens to guide light into and out of the brain, thus permitting optical access to deep brain (or superficial) neural ensembles during naturalistic behaviors. Here we describe steps to conduct such imaging studies using mice. However, we anticipate that the protocol can be easily adapted for use in other small vertebrates. Successful completion of this protocol will permit cellular imaging of neuronal activity and the generation of data sets with sufficient statistical power to correlate neural activity with stimulus presentation, physiological state and other aspects of complex behavioral tasks. This protocol takes 6-11 weeks to complete.

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Visualization of cortical, subcortical and deep brain neural circuit dynamics during naturalistic mammalian behavior with head-mounted microscopes and chronically implanted lenses

Zhe Charles Zhou

Papers

Visualization of cortical, subcortical and deep brain neural circuit dynamics during naturalistic mammalian behavior with head-mounted microscopes and chronically implanted lenses