How brains find signal in the noise: insights from the thalamic reticular nucleus

December 27, 2014

Sensory signals enter the brain at a rapid rate, and they differ greatly in their relevance for the organism at a given moment: the voice of another speaker might contain far more signal than background noise from a barking dog, a television or a ringing phone. A large body of work has tried to understand how the brain achieves this. A new paper in Nature Neuroscience provides some new insights about the role of the thalamic reticular nucleus (TRN).

The TRN has been thought of as a “gatekeeper” of sensory information to the thalamus because it receives inputs from both cortex and thalamus, but only projects to thalamus. Interestingly, TRN neurons express high levels of ErbB4, a receptor tyrosine kinase implicated in mental disorders like schizophrenia. Understanding the role of ErbB4 neurons has become possible recently because, fortuitously, ErbB4-expressing TRN neurons are mostly SOM+ neurons, a well-studied class of inhibitory neurons which can be specifically controlled using cre driver lines.

Sandra Ahrens, Bo Li and colleagues did just that: they bred mice that were deficient in ErbB4-SOM neurons and tested their behavior. They found that the deficient mice had altered performance on behavioral tasks requiring them to filter out unnecessary information. On one task, animals had to ignore and auditory distractor and attend to a visual cue (Figure, right). The ErbB4 deficient animals were unable to suppress the incoming auditory signal, in keeping with the idea that the TRN plays a role in filtering out irrelevant information. But here’s the really interesting part: on another task, ErbB4 knockout animals actually did better! On this task, animals had to ignore auditory distractors and listen for an auditory target (a warble; Figure, left). The ErbB4 deficient animals were better at ignoring the irrelevant distractors, and could identify the target sound better than their spared litter mates.

nn.3897-F2The two tasks differ in a number of ways, so understanding why one got better and the other got worse is not straightforward. For instance, the impaired task was what the authors describe as “incongruent”: the auditory signal the mice were told to ignore had previously instructed them to do something else. This was unlike the other task in which the irrelevant information was more like background noise.

But even if task differences make it reasonable that the behaviors might differ, we are still left wondering what it was that happened to help the animals get better on the auditory only distractor task. The improvement in deficient animals suggests that in intact animals, an active process limits their ability to suppress distractors. A competing explanation is that in intact animals, maladaptive behavioral strategies limit performance- like paying attention to reward history, for instance. Reward history has no relevance for the current trial, but typically has an effect on decisions anyway. In the paper here, though, it is not clear why a maladaptive strategy would affect one behavior more than the other.

In any case, the differing effects on the two tasks are a mystery. The ability to target specific populations of neurons might bring about more such instances in which performance improves. Finding out the reason might require taking into account a number of factors which, together, shape the animal’s behavior.



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Fairhall lab

Computational neuroscience at the University of Washington

Pillow Lab Blog

Neural Coding and Computation Lab @ Princeton University

Churchland lab

Perceptual decision-making at Cold Spring Harbor

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