Excited to share a paper we've been stewing for a while looking into ambiguity in defining phase for brain rhythms and how one can use metrics of uncertainty to identify moments when phase is less ambiguous.
https://doi.org/10.1101/2023.01.05.522914
#neuroscience #brain #tootprint #preprint
The big message we wanted to convey is that depending on what is intended for the phase to track (do you want it to act like a clock or do you want it to tell you when the peak/trough is reached?) you might want to consider alternative methods and use uncertainty metrics.
I focused in this #tootprint on one situation when the phase can become quite ambiguous - amplitude modulation, but in the paper we consider other cases as well including non-sinusoidal oscillations which lead to other considerations - do check it out! - https://doi.org/10.1101/2023.01.05.522914
We show how we can use confidence limits on the phase coming from a Hilbert transform and credible intervals from the state space model to define moments of time ("high confidence") when the phase will be correlated across these different methods. Here's an example for AR(2) sim data.
We consider two alternatives: a state space model of rhythms and using zero-crossings to define phase. Each of these suggests a different phase estimate during times when the rhythm power decreases or if the waveform of the rhythm is non-sinusoidal.
But in moments when there's less rhythm power the filter-Hilbert approach has to create a cycle since the instantaneous frequency is bounded by the filter. But this may not be what is desired for the phase estimate. Alternatives will suggest different estimates for the phase.
Classically, I've seen the filter-Hilbert transform-analytic signal approach used to define phase. This will work fine in many high rhythm power scenarios because the phase that comes out using this approach will strongly correlate with that from other approaches.
All this despite the fact that phase is only explicitly defined for a pure sinusoid, or a narrowband oscillation. If the data is anything else, we are constructing one potential phase estimate of many.
Phase is *the* exciting characteristic of brain rhythms, amplitude frequently seems to act like a barometer of rhythm presence while phase does all the grunt work in expectations about the function of rhythms.
Excited to share a paper we've been stewing for a while looking into ambiguity in defining phase for brain rhythms and how one can use metrics of uncertainty to identify moments when phase is less ambiguous.
https://doi.org/10.1101/2023.01.05.522914
#neuroscience #brain #tootprint #preprint
While ChatGPT is all the rage these days, as you may know it doesn't optimize for accuracy, but rather something like plausability.
I would thus like to highlight an alternative that only answers based on scientific papers, and does so while referencing all the sources:
To me, this is pretty awesome! Let's encourage this type of projects that promote accuracy and transparency of its sources!
The #LearningSalon, edition 2023 by @criticalneuro et al. is happening this Friday : strongly recommend! You can either just come to watch, contribute to the chat, or even ask a question live - it has something to give to everyone 😃
More info and link to the meeting: https://masto.ai/@criticalneuro/109634366781366289
@NicoleCRust @Neurograce @wandell @anilkseth
It's indeed a frustrating topic to work on, especially given that people who have their own theories of consciousness are too fixated on them.
My point has been: instead of trying to study these old theories, we should follow new findings in neurobiology and try come up with novel ideas.
My own crappy way to use advances in neuroscience to develop a new view of consciousness was written up in this tics paper https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(20)30175-3
Special issue of Journal of Cognitive Neuroscience dedicated to the pioneering work of Mark Stokes.
Get Stoke(s)d! Introduction to the Special Focus
https://direct.mit.edu/jocn/article/35/1/1/113585/Get-Stoke-s-d-Introduction-to-the-Special-Focus
Counting down, Day 4 (of 10): Modern & fascinating ideas about the brain for us all to discuss. How likely is each idea to be true? And if true, what are the implications?
Brain idea 7: Stimulation of the brain is effective at treating some patients with some disorders (such as Parkinson's disease and Depression), but in many cases, it does not work. This may be because current approaches target single brain regions but many functions in the brain are distributed across many areas. It is also the case that the brain is full of complex, feedback loops that pull it into "attractor states" that may be hard to pull away from. New work in physics focuses on controlling complex systems like these by stimulating multiple nodes. Someday, we might be able to use these approaches to 'dance' the brain from dysfunction to function.
The friendly version, as summarized by @PessoaBrain (Figure 4):
https://doi.org/10.1162/jocn_a_01908
A deeper dive:
https://arxiv.org/abs/1701.01531
Half way through the CountDown, Day 5 (of 10): Modern & fascinating ideas about the brain for us all to discuss. How likely is each idea to be true? And if true, what are the implications?
There once was a lot of optimism in brain research around the idea that if we could figure out the genetic mutations that lead to brain disorders, we could develop drugs to treat them. However, this hasn't always worked out so well, even when brain disorders are linked to single gene mutations. For example, the mutations associated with Fragile X and Huntington's Disease were determined over 30 years ago and we still do not have good treatments for them. Why not? It's complicated (e.g. those genes regulate other genes). One promising approach is gene therapy, which may be able to restore the mutated proteins even in the absence of understanding what the genes do. Gene therapy is currently used to treat two other nervous system disorders: spinal muscular atrophy and a form of retinal degeneration.
The friendly versions:
https://fragilexnewstoday.com/news/gene-therapy-shows-promise-in-fragile-x-rat-model/
https://www.uniqure.com/programs-pipeline/huntingtons-disease
The deeper dive: An excellent talk describing why finding a treatment for Fragile X has been so difficult:
https://www.simonsfoundation.org/event/cyclic-amp-regulation-and-pde4d-inhibitor-bpn14770-in-fragile-x-syndrome-a-life-journey/
@WiringtheBrain @NicoleCRust @juangallego Indeed and agreed! Biological details have a many-to-few mapping onto actually behaviourally-relevant dynamics, which can be quite low-dimensional and have a lot of preservation across individuals. Our paper that Kevin mentioned: https://www.biorxiv.org/content/10.1101/2022.09.26.509498.abstract
Lots of others starting to explore this space of questions with us too!
Continuing the holiday celebration on Day 2 (of 10). Topic: Modern and fascinating ideas about the brain for us all to discuss. How likely is each idea to be true? And if true, what are the implications?
Brain idea 9: Across different individuals, the same brain functions are implemented by biological details that vary a lot. This is true even for simple circuits like the ones that control the stomach of a crab, where the numbers of ion channels can vary 2-6x across different crabs but the circuit always does the same thing.
The friendly version:
https://www.quantamagazine.org/eve-marder-on-the-crucial-resilience-of-neurons-20210517/
The deeper dive:
https://www.sciencedirect.com/science/article/pii/S0959438822001040
#neuroscience
(And because I'm trying to work out the hashtag habit here ...)
#BrainIdeasCountdown
Turns out the hippocampus discretizes time by footsteps. 🦶
Dynamic Synchronization between Hippocampal Spatial Representations and the Stepping Rhythm
https://www.biorxiv.org/content/10.1101/2022.02.23.481357v1
We're looking for 16 (!) new colleagues!
We have job openings at the University of Groningen for assistant professors in the Departments of Psychology, Pedagogical & Educational Sciences, and Sociology.
https://www.rug.nl/about-ug/work-with-us/job-opportunities/?details=00347-02S0009T4P&dept=gmw
PostDoc At Boston University. Sleep | Rhythms | Networks | Photography | K'taka ಪ್ರೇಮಿ www.anirudhwodeyar.com