On March, 29, Nature published a research article titled “The logic of single-cell projections from visual cortex”, demonstrating the logic of neural communication in visual cortex. Yunyun Han at Huzhong University of Science and Technology is the leading first author of the paper and the corresponding authors are Prof. Thomas Mrsic-Flogel at University of Basel in Switzerland and Prof. Anothy Zador at Cold Spring Harbor Laboratory in USA.
In the paper, the research team used two complementary high-throughput methods to map the projection patterns of individual neurons in the mouse primary visual cortex. They revealed that the patterns of information transfer were very diverse and highly organized, which was essential to maintain the high efficacy of information process in neuronal network.
In classical model of sensory processing, information flows from primary visual cortex to more specialized areas which is more focused on certain properties of vision, for example moving object or more detailed fine images. However, it is not unclear whether information transfer from primary visual cortex follows the rule of “one neuron – one target area”, or if individual neurons spread their signals across several downstream areas.
“Since the neuronal axon is the physical connection upon which each neuron sends out its information, the brain-wide fine-scale structure of single neurons will shed light on the logic of information transfer in the brain.”
In Han et al., researchers applied two complementary high-throughput methods to map the projection patterns of individual neurons in mouse primary visual cortex (V1). At first, they used whole-brain fluorescence-based axonal tracing to collect the fine-scale anatomy of individual neurons. They found that the neurons were of a high degree of projectional diversity. Their result confirmed the existence of dedicated projections to certain cortical areas (the rule of “one neuron – one target area” ). However, these were the exception and the majority of layer-2/3 individual neurons in primary visual cortex distribute information to multiple target areas at the same time. Therefore such neurons were termed ‘broadcasting neurons’.
“Then it is very interesting to test whether the targets of broadcasting neurons were organized in a random fashion or with a higher-order structure. For example, do they preferentially target, or avoid, specific subsets of areas thereby indicating a higher-order structure.” explained by Yunyun Han.
The team then used high-throughput DNA sequencing of genetically barcoded neurons (MAPseq) to acquire projection patterns of hundreds of individual neurons. Firstly, the unique RNA sequences were generated randomly like barcodes. Once the neuron was labeled with the barcoded RNA, it transported the barcode to its target areas along its own axons. The presence of the barcode could be read out by high throughout sequencing of a dissected target area. This technique revealed that the majority of V1 neurons project to six higher visual areas in a non-random manner. Six highly-organized projection motifs were identified, suggesting a high-order functional specialization of subpopulations of projection cells in the brain.
The work makes neuroscientists update the classical model of “one neuron – one target area”. Individual neurons can not only send information to one certain area via their dedicated axons, but also distribute information to multiple target areas in a random or highly-organized manner. Such projection patterns might be the network foundation for efficient computation during sensory processing in the brain.
Dr. Yunyun Han joint the School of Basic Medicine at Huazhong University of Science and Technology in 2016, focusing on the structure and function of neural circuits. She is supported by the National Natural Science Fundation of China (No.31600847) and the Junior Project of “1000 Plan”.
You can read the full research article in Nature: ‘The logic of single-cell projections from visual cortex’(https://www.nature.com/articles/nature26159) By Yunyun Han, et al.