Brandon Munn

Ever wondered what different layer-5 PC types do for learning?

Our work suggests that one (IT PCs) does representational learning whereas the other (ET PCs) encodes representational value!

A great exp-theory collaboration with the Larkum and Takahashi's labs!

schematic of neural recordings from mouse V1, whole-brain, and hippocampus; neural activity traces from the population, showing more correlated activity in V1 and whole-brain recordings versus more decorrelated activity in hippocampus

What if… spontaneous neural activity 🧠 reflects the baseline rumblings of a brainwide dynamical system initialized for learning? We find that the rumblings have macroscopic properties like those emerging from linear symmetric, critical systems 🧵 #neuroscience #neuroAI www.biorxiv.org/content/10.1...

I can try! The brain is made of MANY cells creating everything that is us. When we look at a cell it seems to work very smart but independent yet when we look at all the cells they seem to work together + very safely. It seems cells interconnect in a complex ordered way that achieves both benefits!

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Thank you Linden!!

Three must read papers for PhD students. #scisky #PhD #science #research #academicsky

1. The importance of stupidity in scientific research

Open Access
journals.biologists.com/jcs/article/...

Thank you for the interest!

shine-lab.org/wp-content/u...

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If you're collecting cool data and think this approach could be helpful to you or interested in the work, please reach out!

The code is all on GitHub. github.com/Bmunn/ICG

And, importantly, thank you to all the labs doing open science, permitting some Aussie scientists to test our crazy theories!

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Summary:

We found a conserved multiscale organisation trades-off efficient and resilient information processing regimes (spanning 1 billion years of phylogenetic diversity) and behaviourally functional neuronal reconfigurations, that are linked to the underlying structure.

Finally, we showed how iterative coarse-graining (ICG) can identify informative neuronal reconfigurations related to task dynamics in the zebrafish.

I bet this approach will be helpful for future behavioural studies!

These task induced zebrafish reconfigurations are most flexible and informative at the mesoscale (thousands of cells).

Interestingly, mice showed two distinct peaks of reconfiguration at the micro- and mesoscales, supporting the theory of multiple scale-dependent information processing streams.

Not done there, we explored beyond rest into behaviour and found conserved static scaling but evidence of a privileged temporal scale in zebrafish aligned with the stimuli.

That is, a multiscale organisation permits flexibility to adapt to behaviourally relevant timescales.

The few multiscale networks that recapitulated the diverging info theory regimes/nonGaussianity also revealed more beneficial features such as maximising dynamic range and communicability.

Contrasting MANY network null models, we found that only hierarchical modular networks could controllably change the slope and reproduce the empirical static and dynamic scaling

Though geometric networks worked well up to a scale dependence. See some related recent Aussie work by Pang et al 2023

We wanted to understand the origin of this scaling.

The C. elegans recordings contained tagged cells and a known anatomical connectivity, which let us show cross-scale functional pairings were far more likely if the cells had a physical connection.

That is multiscale structure and function!

This multiscale organisation also provides a functional dial to operate across varying timescales!

Again, with a conserved slope (despite the noisier measure), from sparse and fast activity at the cellular scale to more continuous fluctuations at the macroscale.

How could this pluralistic information capacity emerge?

We found evidence for a precise self-similar coordination consistent across species (invertebrates, fish, mammals) and balanced between two extremes (identical/independent).

This was unique against various nulls!

We discovered a divergence in redundant information capacity at coarser scales.

This shows that the cellular scale is optimised for efficiency, while coarser ensembles support resiliency. This mirrored a shift from heavy-tailed to Gaussian correlation distributions.

We opted for a Kadanoff iterative coarse-graining approach among the growing multiscale techniques. This was dyadic (maximal log spread), comparable to standard analyses (correlations), and fast. Letting me track activity across scales

Crazily, I applied this to as many species as possible!

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Mac, being the fantastic boss he is, let me pursue an initially very 'physicsy' project and listened to my unhinged arguments about how straight lines on logarithmic axes, particularly their subtle changes can have significant functional implications for this question.

Inspired by multiscale analyses, I wanted to understand how both a macroscale/systems framework arguing for a resilient “population code” and a cellular/microscale perspective favouring a minimal redundant/efficient neuronal code can both simultaneously be consistent in neural data.

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When I began working with Mac, we had “strong discussions” about how the brain coordinates activity to process information. Our different perspectives and starting points of macroscale vs. microscale, led to assumptions and predictions that didn’t always align.

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This combines all the science I love physics, info theory, modelling, and multiple species to understand what makes the brain so special!

It’s been cooking for the past four years, and only possible with the dream team

@macshine.bsky.social
@drbreaky.bsky.social and co!

Hi BlueSky fam, for my first post and to celebrate our recent paper being physically published I thought I’d do a summary thread!

This has been my most favourite (and toughest) work to date.

Please help share around!!

www.cell.com/cell/abstrac...
(Reach out if you can’t access)

Psilocybin slows and reduces complexity of neural dynamics in medial prefrontal cortex.

New paper with Ross Purple, Rahul Gupta, Matt Jones & Co.

The ascending arousal system shapes neural dynamics to mediate awareness of cognitive states - Nature Communications Models of brain organisation can overlook the role of the autonomic nervous system in cognitive processes. Here the authors show a link between the ascending arousal system and both low dimensional ne...

We were able to detect the slow-down of neural dynamics by adapting a measure that @macshine.bsky.social Brandon Munn and team developed for assessing energy landscapes in fMRI data (itself building on work by Bill Bialek) to use with our Neuropixels data. www.nature.com/articles/s41...

Glad you enjoyed and thank you for the share!! I completely agree

Multiscale organization of neuronal activity unifies scale-dependent theories of brain function Analysis of cellular recordings from five phylogenetically diverse species uncovers a conserved, multiscale organization of neuronal activity that resolves disparate theories of brain function. This hierarchical structure allows the brain to operate across multiple timescales, enhances information flow, flexibly reconfigures activity during behavior, and balances functional resiliency with efficiency across scales.

Conserved multiscale brain organization across five phylogenetically diverse species
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Unifies scale-dependent theories of brain function, balancing efficiency and resiliency

Enables flexible cross-scale reconfigurations of neural activity during behavior

www.cell.com/cell/fulltex...
#neuroscience