Silence for thought: Special interneuron networks in the human brain

Helmstaedter and his team have discovered that human cortical networks have evolved a novel neuronal network type that is essentially absent in mice. This neuronal network relies on abundant connections between inhibitory interneurons.
“This suggests to us an almost ten-fold expansion of an interneuron-to-interneuron network”, says Sahil Loomba, one of the studies’ lead authors.

“Interneurons make about a fourth to a third of cortical nerve cells that behave in a very peculiar way: they are highly active, however, not to activate other neurons, rather to silence them. Just like kindergarten caretakers, or guards in the museum: their very laborious and highly energy consuming activity is to keep others peaceful, quiet”, explains Helmstaedter.

Theoretical work has suggested that such networks of silencers can prolong the time over which recent events can be kept in the neuronal network: expand the working memory.

“In fact, it is highly plausible that longer working memory will help you deal with more complex tasks, expand your ability for reasoning.

And last but not least: none of today’s main AI methods uses such interneuron-to-interneuron networks.”, says Helmstaedter.


Closer source article (but still no paper):


Twitter thread by Helmstaedter

(Behind paywall)

There is a function that seems to be fundamental to cognition: computing difference or gradient between the inputs. Fine-grained discrimination is the essence of intelligence. Excitatory neurons can’t do this on their own, and even conventional neuron-interneuron interactions don’t seem to do that well. Maybe this is done by those interneuron-interneuron interactions?

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This could be revolutionary, yet they contain it behind a paywall. Go figure.


This is the (non paywalled) paper which did the original measurements (Bakken et al., Nature 2021) mentioned in the twitter posts