The human brain is made up of billions of neurons (nerve cells) connected by trillions of synapses. While life experiences customize neural circuits in each individual, evolutionary processes inform brain networks so that the scaffolding is largely identical across individuals.
The idea that there are neuron types that share properties among their members has existed for over a century, but the ability to establish and agree on rigorous and quantitative definition has eluded scientists, not least because neurons have diverse, complex properties and their axons can span the entire brain, connecting multiple regions. The incredible resolution and processing power provided by single-cell genomics technologies now enables researchers to classify these neuron types and determine how they are organized and work together.
The BRAIN Initiative Cell Census Network (BICCN) leverages these technologies to generate an open-access reference brain cell atlas that integrates molecular, spatial, morphological, connectional, and functional data for describing cell types in mice, humans, and non-human primates. A key concept is the brain cell census, a classification and taxonomy that defines neuronal and non-neuronal cell types and their proportions, spatial distributions, and defining characteristics. The brain cell atlas registers and displays the precise location and distribution of all cell types and their features. As a spatial framework, the atlas facilitates integration, interpretation, and navigation of various types of information for understanding brain network organization and function.
In a paper published in Nature in October 2021, scientists including Ronna Hertzano, M.D., Ph.D., and Seth Ament, Ph.D., both at the University of Maryland and both members of Hearing Health Foundation’s Hearing Restoration Project (HRP), present the cell census and atlas of cell types in the primary motor cortex of the mouse, marmoset, and human. The primary motor cortex is important in the control of complex movement and is well conserved across species, with a rich history of anatomical, physiological, and functional studies to aid interpretation of this cell-type information. The paper describes a synthesis of 11 companion studies through a coordinated multi-laboratory effort, and the results advance the collective knowledge and understanding of brain cell-type organization.
This vast resource was shared with the research community using the NeMO Analytics portal. Users can click on figure legends of objects that describe gene expression/epigenetic modifications in the brain, and interactively search the data for their genes of interest. Importantly, NeMO Analytics is fully powered by the gEAR platform (the gene Expression Analysis Resource) which was invented by Hertzano and developed by her team, with the support of the HRP and the National Institute on Deafness and Other Communication Disorders (NIDCD). The curation of the BRAIN data in NeMO Analytics was led by Ament’s team.
Their research reveals a unified molecular genetic landscape of cortical cell types. Cross-species analysis has generated a taxonomy of transcriptomic types and their hierarchical organization across mouse, marmoset, and human, meaning the types are equivalent in developmental origins across these three species. A cross-modal analysis demonstrates that transcriptomic, genetic, and epigenetic mechanisms affect the physiological and anatomical properties of the neuron types consistently across these species as well, meaning neuron types are indeed a valid biological concept and regulated by the genome, as hypothesized over a century ago. —HHF staff
A 2009–10 Emerging Research Grants scientist, Ronna Hertzano, M.D., Ph.D., is an associate professor in the department of otolaryngology–head & neck surgery at the University of Maryland School of Medicine, where Seth Ament, Ph.D., is an assistant professor in department of psychiatry.
Both are members of HHF’s Hearing Restoration Project, which provided initial funding for the gEAR data analysis and visualization platform.
These findings support the idea that comprehension challenges can stem from cognitive limitations besides language structure. For educators and clinicians, this suggests that sentence comprehension measures can provide insights into children’s cognitive strengths and areas that need support.