I wonder if coupling with amygdala or (anterior vs posterior hippocampus) during rumination messes up the relationship between DMN and mind wandering. Why would the brain have redundant circuits for conceptually similar processes?

So, practically, direct attention externally switching to CTR/DAN etc circuits, to break out of repetitive thought cycles? Shouldn't DMN be negatively correlated with success?

Thank you for speaking out. Hoping for flat funding at FY 24 levels. When is the vote? Reps probably deserve a call on this one.

During inevitable conflict, is Exponential backoff key to deescalation? Are dysfunctional relationships characterized by deviations in these network patterns?

AIMD = Additive Increase, Multiplicative Decrease

By state I mean capturing the internal dynamics of your brain while you are integrating a new fact about a complex idea such as the reputation of a person. But put simply, it could mean are you relaxed or vigilant.

Thanks for reading, here's a link to the preprint, feel free to reach out with any questions! 15/end.
www.biorxiv.org/content/10.1...

What does this mean? Compressed representations may facilitate strategic exploration on a complex task like the clock task. There is evidence that entropy and value maxima are represented in vPFC. These representations may drive biological solutions to E/E problems. 14/15

Finally, we look at the effects of this connectivity analysis on exploration behavior. We find that following rewarded trials, higher entropy modulation of posterior hippocampal-DMN connectivity predicted subsequent exploration. Maybe these signals are related to choice. 13/15

We next examine interactions between vPFC and hippocampus using the deconvolved MLM framework. We do this by using HC as a regressor and vPFC as an outcome. A key result from this analysis is that hippocampal-DMN connectivity is higher when entropy is higher. 12/15

We find robust encoding of the value maximum in vPFC, strongest in region 14m25/32 of the DMN and in the LIM network. This is consistent with the neuroeconomic literature that suggests ventromedial PFC encodes scalar values. 11/15

We find that DMN responds when entropy is lower, when there is likely one prominent global value maximum that is easier to exploit. We use deconvolved BOLD aligned to trial onset in a MLM. This allows examination of the time course of signals w.r.t. an event (like a PETH). 10/15

Entropy is an emergent property that captures the complexity of the value function on a given trial: higher entropy indicates many local value maxima (complex value landscape) and lower entropy typically indicates one prominent global value maximum (simple value landscape). 9/15

An RL model is fit to subjects’ behavior, and the value maximum and entropy of the value distribution are calculated on each trial. We can then examine neural correlates with predictions from the model. 8/15

Subjects explore and exploit on a clock task where a dot rotates 360 deg, and responding at different locations gives probabilistic rewards. Hidden underlying value distributions are learned through exploration. Subjects play this task during an fMRI scan. 7/15

Here we extend these findings to ventral prefrontal cortex (vPFC), and interactions between hippocampus and vPFC. We examine 3 resting state networks, the control (CTR), default mode (DMN) and limbic (LIM). Importantly, we replicate key findings out-of-sample. 6/15