Jeff Johnston
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wjj.bsky.social
Jeff Johnston
@wjj.bsky.social
Postdoc in the Center for Theoretical Neuroscience at Columbia, previously at the University of Chicago
he/they
wj2.github.io
Thanks for reading! Here’s another link to the paper: arxiv.org/abs/2309.07766
This is also the second panel in a triptych of new work on how the brain does (or doesn’t) make sense of multiple stimuli. First part is here: twitter.com/wjeffjohnsto...

The last part is coming soon! (11/n)
Semi-orthogonal subspaces for value mediate a tradeoff between...
When choosing between options, we must associate their values with the action needed to select them. We hypothesize that the brain solves this binding problem through neural population subspaces....
arxiv.org
September 26, 2023 at 3:38 PM
Further, we show that these geometric measures are associated with trial-to-trial and average choice behavior. In particular, some suboptimal choices look like spatial (mixing up which value was on the left or right) misbinding errors! (10/n)
September 26, 2023 at 3:38 PM
Finally, we show that a similar process unfolds over time: The current offer is represented in a distinct subspace from the remembered past offer – this time, the subspaces are actually orthogonal! (9/n)
September 26, 2023 at 3:37 PM
Then, we show that the representational geometry in all but one of the regions we recorded from supports reliable binding; at the same time, the geometry can also support reliable generalization in every region. (8/n)
September 26, 2023 at 3:37 PM
We develop a mathematical theory that captures the tradeoff between the reliability of binding and generalization as a function of the representational geometry – which we then relate back to subspace correlation. (7/n)
September 26, 2023 at 3:36 PM
That they are not fully orthogonal means that the representation of value may be abstract: A decoder trained to decode the value of left offers could generalize to decode the value of right offers. This is important for learning and generalization to novel situations. (6/n)
September 26, 2023 at 3:36 PM
That they are not the same means that this representation *binds* offer value to position, and a decoder can figure out which value corresponds to which offer. This wouldn’t be the case if both values were encoded in the same subspace! (5/n)
September 26, 2023 at 3:36 PM
The two subspaces are not perfectly orthogonal – nor are they the same. They are semi-orthogonal – and this is important! (4/n)
September 26, 2023 at 3:35 PM
How does the monkey keep the different offer values straight? We show that the value of offers presented on the left is encoded in one subspace of population activity, while the value of offers presented on the right is in a distinct subspace. (3/n)
September 26, 2023 at 3:35 PM
In this setup, monkeys chose between two sequentially presented offers based on their expected reward value. While they did this, neural activity was recorded from neurons in five different value-sensitive regions. (2/n)
September 26, 2023 at 3:35 PM