The study updates one of the largest neuronal-type databases


Inhibitory neuron (white) recorded and labeled in vivo, along with other types of inhibitory cells (blue and yellow). Credit: Elena Cid. Cajal Institute (CSIC)

A study led by researchers at the Cajal Institute of the Spanish Research Council (CSIC) in Madrid, in collaboration with the Department of Bioengineering of the George Mason University of Virginia, has updated one of the largest databases of the world on neuronal types,

The study, which is published in the journal PLOS Biology, represents the most complete mapping performed to date between recoded in vivo and identified . This breakthrough may allow for biologically significant computer modeling of the complete neural circuit of the hippocampus, a region of the brain involved in memory function.

Mammalian cerebral cortex circuits are made up of two types of neurons: excitatory neurons, which release a neurotransmitter called glutamate, and inhibitory neurons, which release GABA (gamma-aminobutanoic acid), the major inhibitor of the central nervous system. . “A balanced dialogue between” excitatory “and” inhibitory “activities is essential . Identifying the contribution of the various types of excitatory and inhibitory cells is essential to better understand the functioning of the brain “, explains Liset Menéndez de la Prida, the director of the Laboratory of Neural Circuits of the Cajal Institute who directs the study at the CSIC.

In the case of the hippocampus, a brain region involved in memory function, 39 types of excitatory main cells and 85 types of inhibitory neurons are known. The activity patterns of these various cell types are very specific. All of this information is now collected at, a database created five years ago by the George Mason University Center for Neural Computing. This database integrates all current knowledge on morphology, biophysics, genetic identity, connectivity, and firing patterns of more than 120 types of neurons identified in the hippocampus of rodents.

This update, which has been possible thanks to a careful memory, identification and classification of at the Cajal Institute, will allow the annotation and classification of high-density brain recordings, fundamental to brain-machine interfaces. “Much of our knowledge about nerve cells so far comes from laboratory preparations that separate sections of tissue of interest from the rest of the brain,” says Giorgio Ascoli, a professor at George Mason University who runs the Center. of Neural Computing. “This new link to recorded animal activity shifts the game toward full-scale computer models of brain and memory functions,” Ascoli adds.

New computational models and machine learning applications

The new information provided by may have an impact on the development of more realistic predictive models that consider neuronal diversity as a source of information. The results of the work will help with decoding signals associated with complex cognitive processes for which single-cell activity information is essential.

This is the case of the hippocampus, which constructs a neural representation of sequential experiences that is subsequently reactivated in a very specific way to encode, store, and retrieve memories. To better understand this code, we need to decompose mixed neural representations. The additional data included on can now provide the tags needed to begin deconstructing the code using modern artificial intelligence tools.

How neural circuits strike a balance between arousal and inhibition

More information:
Alberto Sanchez-Aguilera et al, Update of through the integration of monocellular phenotypes with in vivo circuit function, PLOS Biology (2021). DOI: 10.1371 / journal.pbio.3001213

Provided by the National Research Council (CSIC)

Citation: Study Updates One of Largest Neural Type Databases (2021, May 27) Retrieved May 27, 2021 at

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