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I am a systems neurobiologist working to understand the mechanisms of cognition and attention using functional brain imaging, both in health and disease. I have a particular interest in understanding how the different arms of the ascending arousal system flexibly modulate the cross-scale organisation of the brain to facilitate adaptive behaviour. I am currently working as a Robinson fellow at The University of Sydney.
@guidomeijer thanks Guido - we definitely considered adding more direct links regarding causal interactions between the two systems, but honestly ran out of space to do the concept justice. Plenty of cool work out there though!

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RT @TomNakai
Jaffe et al., Nat Hum Behav (2023)

Modelling human behaviour in cognitive tasks with latent dynamical systems

https://www.nature.com/articles/s41562-022-01510-8

Modelling human behaviour in cognitive tasks with latent dynamical systems - Nature Human Behaviour

The authors introduce a deep learning framework to reproduce sequences of response times and use it to provide evidence for a stability–flexibility trade-off underlying task-switching costs.

Nature
@dlevenstein @lili it's an interesting hypothesis, that's for sure. in a way, it's kind of what brains have had to deal with since their inception. for this reason, i definitely think that the idea of a bunch of noise in the long-term "training" of biological brains is super important for figuring out some of these weirder aspects of how it works (see also: dreams; hallucinations; psychedelics; people who like reality tv; etc)
@dlevenstein it might be too gross of an oversimplification, but I like to think of all organisms/brains being forced to operate in a regimen that allows for dynamic reconfigurations as a function of need. If they weren't, the organism/animal wouldn't be able to deal with the world around them, which is highly dynamic + context dependent. So in other words, the flexibility is baked in from day dot. RNNs aren't currently designed with this constraint, so they become fragile/flimsy/etc.
@dsmith @DrYohanJohn @Ryder @strangetruther @NicoleCRust @ekmiller @PessoaBrain @kendmiller @bwyble @achristensen56 I like that - linking the terms to convergence is a nice idea.
@dsmith @DrYohanJohn @Ryder @strangetruther @NicoleCRust @ekmiller @PessoaBrain @kendmiller @bwyble @achristensen56 I thought of a nice example - a scientist makes an explicit prediction regarding a particular experiment, rather than an anticipation. Most likely why I use prediction to mean a more deliberate process than anticipation, which can include more intuitive/subconscious processes that prepare ahead (given the current action/context)
@dlevenstein My guess is that it has to do with the extra complexity inherent between the interactions of the arousal system and the unique topological circuits that are distributed around the brain. Makes a huuuuge difference whether neuromodulatory receptors are on pre vs post-synaptic neurons, excitatory vs inhibitory cells and whether the receptors cause ultimate increase or decrease in excitability.
@dsmith @DrYohanJohn @Ryder @strangetruther @NicoleCRust @ekmiller @PessoaBrain @kendmiller @bwyble @achristensen56 fascinating... I think of predicting something as requiring someone to furrow their brow and focus on the details, whereas to me anticipating just means to get out in front of something, whether deliberately or not. #wordsarehard

@strangetruther @DrYohanJohn @NicoleCRust @dsmith @ekmiller @PessoaBrain @kendmiller @bwyble @achristensen56 would love to hear any thoughts/notes. In case you're interested, it's kind of the first in a series I've been slowly working on. This is the 2nd one, which incorporates the superior colliculus: https://shine-lab.org/wp-content/uploads/2022/11/2022_nbr.pdf.

Another was just accepted on the role that the neuromodulatory system plays in shaping the balance between the diff subsystems, but no pdf yet. Can share later.