Imagine yourself sitting in a
noisy café trying to read. To focus on the book at hand, you need to ignore the
surrounding chatter and clattering of cups, with your brain filtering out the
irrelevant stimuli coming through your ears and ‘gating’ in the relevant ones
in your vision—words on a page. New York University researchers offer a new
theory, based on a computational model, on how the brain separates relevant
from irrelevant information in these and other circumstances. The analysis
focuses on inhibitory neurons—the brain’s traffic cops that help ensure proper
neurological responses to incoming stimuli by suppressing other neurons and
working to balance excitatory neurons, which aim to stimulate neuronal
activity. In their analysis, the researchers devised a model that maps out a
more complicated role for inhibitory neurons than had previously been
suggested.
Of particular interest to the
team was a specific subtype of inhibitory neurons that targets the excitatory
neurons’ dendrites—components of a neuron where inputs from other neurons are
located. These dendrite-targeting inhibitory neurons are labeled by a
biological marker called somatostatin and can be studied selectively by
experimentalists. The researchers proposed that they not only control the
overall inputs to a neuron, but also the inputs from individual pathways—for
example, the visual or auditory pathways converging onto a neuron. The study’s
authors used computational models to show that even with the seemingly random
connections, these dendrite-targeting neurons can gate individual pathways by
aligning with excitatory inputs through different pathways. They showed that
this alignment can be realized through synaptic plasticity—a brain mechanism
for learning through experience.
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