I'm excited to share that my new postdoctoral position is going so well that I submitted a new paper at the end of my first week! www.biorxiv.org/content/10.1... A thread below
Why do we brush our teeth without having to think about it? Our brain can learn habits through repetition. Habits become automatized in that, once they’re formed slowly over many repetitions, we can execute them automatically without having to “think” about them.
A primary way this manifests in behavior is through action chunking, where predictable action sequences become compressed into cohesive, reusable units. Think of typing a familiar password, phone number, or playing a well-practiced song on an instrument.
What's another function the DLS is involved in? Time encoding! According to a review paper by Edvard and May-Britt Moser (2014 Nobel prize winners), the brain tracks time through "stable neural trajectories" where cell populations fire predictably along a trajectory.
If these functions are co-located, one might believe there's a common mechanism for them. Our work suggests that this mechanism is sensory compression!
The DLS is known to be a "bottleneck" in sensorimotor processing. Millions of cortical neurons project onto orders of magnitude fewer striatal cells, producing highly favorable conditions for compression.
To test our hypothesis on the effect of sensory compression on action chunking and time coding, we developed an RNN model with sensory bottlenecks and trained it on RL tasks that involve chunking.
We show that a model with a sensory bottleneck accounts for many behavioral effects that @gershbrain.bsky.social
and @lucylai.bsky.social
characterize in their work on human action chunking, whereas a non-bottleneck baseline does not.
We then show that this model accounts for seemingly paradoxical findings in time representations in the DLS. First, we show our model explains results that encoding of time in rat DLS is invariant to task relevancy and stimulus properties.
This is because sensory compression produces intrinsic, task-independent time encoding trajectories and these dynamics act as a scaffold to implement timing of task-specific behaviors where sensory stimuli guide the *progression* along these trajectories.
What are the implications? First, sensory compression is not just in DLS. It's also in other areas such as Hippocampus and Cerebellum. So we predict that wherever there is sensory compression happening, there is also time encoding and support of time-sensitive behaviors.
Second, it's known that we build compressed abstractions of our environments that allow us to generalize. What's maybe not known is that this process is intrinsically tied to forming habits and complex action plans!