In:
eLife, eLife Sciences Publications, Ltd, Vol. 7 ( 2018-09-26)
Kurzfassung:
The outer sheet of brain tissue, the neocortex, is composed of circuits formed from trillions of connections among billions of neurons, of which there are about one hundred different neuron types. The scale and complexity of cortical circuitry pose experimental challenges, leading to an incomplete understanding of how cortical cell types are connected and the computations that take place at the connections. About half of the cell types in the brain are excitatory, which means they can activate other cells. The cortex consists of several distinct layers of cells, within which excitatory cells cooperate to process the signals they receive from other cortical layers and brain areas. Using recordings of electrical activity arising from the connections between pairs of excitatory neurons, Seeman, Campagnola et al. measured the likelihood and strength of connectivity among related groups of excitatory cell types in slices of cortex taken from human and mouse brains. The initial results confirm previous findings that individual layers of human cortex can have more and stronger excitatory connections than the same layers of mouse cortex. In most layers of mouse cortex, repeatedly activating the excitatory cells leads to progressively weaker responses. However, in the upper layers of mouse cortex, the opposite effect is sometimes seen: more excitatory activity causes the connections to generate stronger responses. By feeding these data into a computer model, Seeman, Campagnola et al. described and compared the activity of the groups of related excitatory cell types. These results are the first of a new, large-scale project where findings can be integrated across experiments to gain a more detailed picture of cortical circuitry and computation. Neuroscientists will be able to use the results to build advanced computer models of cortical circuits. Such models will, for example, generate predictions for how the attributes of excitatory connectivity revealed by Seeman, Campagnola et al. influence how information is processed in the cortex. In so doing, the models will add to our understanding of how the human brain works both in health and in disease.
Materialart:
Online-Ressource
ISSN:
2050-084X
DOI:
10.7554/eLife.37349.001
DOI:
10.7554/eLife.37349.002
DOI:
10.7554/eLife.37349.003
DOI:
10.7554/eLife.37349.004
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10.7554/eLife.37349.006
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10.7554/eLife.37349.005
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10.7554/eLife.37349.007
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10.7554/eLife.37349.008
DOI:
10.7554/eLife.37349.009
DOI:
10.7554/eLife.37349.010
DOI:
10.7554/eLife.37349.011
DOI:
10.7554/eLife.37349.012
DOI:
10.7554/eLife.37349.013
DOI:
10.7554/eLife.37349.017
DOI:
10.7554/eLife.37349.014
DOI:
10.7554/eLife.37349.018
DOI:
10.7554/eLife.37349.015
DOI:
10.7554/eLife.37349.019
DOI:
10.7554/eLife.37349.016
DOI:
10.7554/eLife.37349.020
DOI:
10.7554/eLife.37349.021
DOI:
10.7554/eLife.37349.023
DOI:
10.7554/eLife.37349.022
DOI:
10.7554/eLife.37349.024
DOI:
10.7554/eLife.37349.025
DOI:
10.7554/eLife.37349.026
DOI:
10.7554/eLife.37349.027
DOI:
10.7554/eLife.37349.028
DOI:
10.7554/eLife.37349.029
DOI:
10.7554/eLife.37349.031
DOI:
10.7554/eLife.37349.032
Sprache:
Englisch
Verlag:
eLife Sciences Publications, Ltd
Publikationsdatum:
2018
ZDB Id:
2687154-3