@NicoleCRust@neuromatch.social avatar

NicoleCRust

@NicoleCRust@neuromatch.social

Professor (UPenn). Brain researcher. Author (nonfiction). Advocate for community based progress & collective intelligence.

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dhananjaythakur, to random
@dhananjaythakur@mastodon.social avatar

Asking for a friend who's about to submit a manuscript. The PI has, against the wishes of the first authors, changed the author list to be in order of "seniority", instead of impact of work and total effort.
For e.g. a postdoc who helped annotate one supplemental figure has been given precedence over an undergrad who did months of skilled work to make that and almost all main figures possible. How to best deal with this?

MCDuncanLab,
@MCDuncanLab@mstdn.social avatar

@dhananjaythakur

First off, ask everyone to cool down and try to assume the best intentions of others.

I understand that for someone who feels that their authorship position is disregarding their contributions, this hurts.

However, the PI must have some reason for making this change.

Approaching any discussion of this should come from a position of calm and, for lack of a better word, curiosity.

1/

gregeganSF, to random
@gregeganSF@mathstodon.xyz avatar

My novel “Scale” — a political thriller set in a world where people belong to seven groups that differ vastly in size — is included in the 2023 Locus recommended reading list.

https://locusmag.com/2024/02/2023-recommended-reading-list/

https://www.gregegan.net/SCALE/SCALE.html

albertcardona, to random
@albertcardona@mathstodon.xyz avatar

Arcadia is innovating in publishing: witness this manuscript by @PracheeAC et al. 2023

"Phenotypic differences between interfertile Chlamydomonas species" https://research.arcadiascience.com/pub/result-chlamydomonas-phenotypes/release/6

Includes a methods-first approach, aiming at easing how the data was acquired and to make it reproducible. With figures that contain animations without being videos, feeling very natural to the medium (a webpage).

And importantly: no "authors", but "contributors", listed AT THE BOTTOM, in a table sorted in alphabetical order by surname, alongside the role of each contributor. Laudable, and clear. No more first-author last-author nonsense.

And love starting with a section titled "Purpose" and ending with another titled "Next steps". Explicitly embedding the work into the broader stream of science.

NicoleCRust, (edited ) to random
@NicoleCRust@neuromatch.social avatar

Delightful mystery

People in Tampa can hear a low frequency sound across the Florida peninsula; even in their homes. The mystery: where is it coming from? One expert thinks it’s coming from under water: black drum fish mating season.

https://www.npr.org/2024/02/01/1228286349/south-tampa-mystery-where-is-the-sound-coming-from-neighbors-investigate

https://ocr.org/sounds/black-drum/

axoaxonic,
@axoaxonic@synapse.cafe avatar

@NicoleCRust there's a similar phenomenon in West Seattle https://www.knkx.org/other-news/2012-09-06/mysterious-hum-keeping-west-seattle-up-at-night

People think it's probably from a fish called the Midshipman fish

kristine_willis, to random
@kristine_willis@mstdn.science avatar

just a quick little graph, she thought. It’ll take ten minutes, she thought.

thetransmitter, to random
@thetransmitter@mastodon.social avatar

Sheena Josselyn and memories lost, found and created

By Alla Katsnelson

https://www.thetransmitter.org/memory/sheena-josselyn-and-memories-lost-found-and-created/?utm_source=mastodon&utm_medium=org-social&utm_campaign=2024130-sheena-josselyn

NicoleCRust, to random
@NicoleCRust@neuromatch.social avatar

Thoughts on these provocative ideas (about how research in psychology should proceed)?

The last author tipped me off to this one. Curious to hear impressions.

Beyond Playing 20 Questions with Nature: Integrative Experiment Design in the Social and Behavioral Sciences

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4284943

(also here, behind the BBS paywall: https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/article/abs/beyond-playing-20-questions-with-nature-integrative-experiment-design-in-the-social-and-behavioral-sciences/7E0D34D5AE2EFB9C0902414C23E0C292)

The dominant paradigm of experiments in the social and behavioral sciences views an experiment as a test of a theory, where the theory is assumed to generalize beyond the experiment’s specific conditions. According to this view, which Alan Newell once characterized as “playing twenty questions with nature,” theory is advanced one experiment at a time, and the integration of disparate findings is assumed to happen via the scientific publishing process. In this article, we argue that the process of integration is at best inefficient, and at worst it does not, in fact, occur. We further show that the challenge of integration cannot be adequately addressed by recently proposed reforms that focus on the reliability and replicability of individual findings, nor simply by conducting more or larger experiments. Rather, the problem arises from the imprecise nature of social and behavioral theories and, consequently, a lack of commensurability across experiments conducted under different conditions. Therefore, researchers must fundamentally rethink how they design experiments and how the experiments relate to theory. We specifically describe an alternative framework, integrative experiment design, which intrinsically promotes commensurability and continuous integration of knowledge. In this paradigm, researchers explicitly map the design space of possible experiments associated with a given research question, embracing many potentially relevant theories rather than focusing on just one. The researchers then iteratively generate theories and test them with experiments explicitly sampled from the design space, allowing results to be integrated across experiments. Given recent methodological and technological developments, we conclude that this approach is feasible and would generate more-reliable, more-cumulative empirical and theoretical knowledge than the current paradigm—and with far greater efficiency.

18+ jonny,
@jonny@neuromatch.social avatar

@beneuroscience @axoaxonic @NicoleCRust @MolemanPeter @UlrikeHahn I actually came to neuroscience through a fascination with nonlinear dynamics, was mostly dismayed at how neuroscience at large mostly ignores (IMO) the most important feature of the brain as a system, and was then sad I had already mostly drifted away from it bc i had no-one doing that work around me once dynamical manifolds finally caught some foothold among cortex ppl (which is who i was among in grad school).

i have found that questions of equilibrium, stability, and scale in nonlinear dynamics have a deceptively tricky time mapping to the way those concepts are used in greater neuroscience. I also am finding the combination of ideas in this thread between methodology/epistemology and properties of dynamical systems that @NicoleCRust and @UlrikeHahn introduced to be really interesting because that's often how I think of things but haven't heard other people express it this way too. I wanna come back around to that after returning to the paper in the OP bc i think it's a good backdrop for this convo.

It's sort of sad to me that the paper in the OP makes the same that almost all papers of its kind do and treats the background of "the rest of research infrastructure" as being fixed while proposing some radical change to a circumscribed part of it. That mirrors the kind of questions of fixity and locality y'all bring up downthread. I think when you are proposing something that is well trod ground by hundreds of prior authors, and that something starts with making some structural mapping between your work and the existing work, but you don't really engage with that work and coin a new field 'research cartography', then something has gone really wrong somewhere. They describe some examples of their proposed model, but not other people proposing similar models, which sort of neatly illustrates the problem with the idea: why didn't they do integrative research

The biggest problem here is that they treat what are ultimately social dynamics of publishing and communication as a physical system, and with it assume several demonstrably untrue things - perfect information, no misincentives, good and shared intentions, unambiguous interpretation of experimental results, etc. Their diagnosis of the problem effectively reduces to "people aren't formulating their experiments in terms of standardized ontologies/theories, so we can't do systematic reviews on them." They continue describing the reasons why this is the case as "people don't think cumulative knowledge is important/think things are good enough" and "nobody has proposed a workable alternative," but of which are, again, demonstrably false. Nobody actually thinks scientific results work their way into cumulative understanding, so that point is effectively a strawman, and oh boy do i have a folder of hundreds of proposals just like this (and also decades of work spent trying to realize them) to show them.

But at the bottom of it I of course share the idea that we need to make our work more mutually intelligible to one another, to put it in conversation with prior work, and to have many layers of consensusbuilding across many different modalities. What does that "metric space of conceivable experiments" actually look like? If in your paper for radically transforming science, it still looks like Journal PDFs and Review Papers (but with more closely aligned measurements this time), then you have left everything interesting on the table. I think one of the things that is a cognitive stumbling block here is how difficult it is to imagine different dynamical regimes, and so most scientists revert to a kind of single-pointed teleology - not out of any sort of strong philosophical commitment, but because it's easy to imagine science working like "sample all the points in an ontological space, find the maximal point, that's the truth!" I'll leave aside my own beliefs about what is possible here tho.

This has an interesting resonance with the problems in neuroscience re: appreciating the dynamical reality of the brain. One reason the NHST-style one-off papers connected to very little theory work so well is that they are acceptable units of work for the machine of academia - recording a bunch of neurons, averaging them together, a t-test or two, that's a paper baby! There is/was effectively no room for the kind of exploratory experiments that are just about characterizing a system without a story, and so we still get mostly those kinds of papers. the proposed idea in this paper is like a grid search to construct a vector map in an ontological space, that assumes the space is neutral/true and so i don't find it all that compelling. The observation that very simple functions like the logistic map make incredibly complex spaces doesn't necessarily imply that the goal of research should always be to derive those functions. The same kind of irreversibility with uncertainty in complex systems that gives a cone of predictability beyond which you can't see past might make it so that, for one reason or another, those functions are simply unobservable to us (the brain is not a computer capable of representing all possible information equally either). There are other ways of characterizing systems other than identifying their generating functions (ironically, the authors of OP paper should read Vapnik, who is in some ways the godfather of the gradient ascent underpinning of their strategy, who writes all about the relationship between identifying vs. imitating the generator, core to ML). Even some chaotic systems on attractors will have some kind of bounding space to them, and for larger/less closed systems the state can even be itinerant between multiple regimes, so it is possible to have satisfying characterizations of systems that are still "it depends," but the "it depends" part can be meaningful! It is imo the most important part of any information, who it comes from, what perspectives are brought to bear on it, how it is describing the problem, and so on. Rather than the derivation of a solution, a fluid, evolving flow that still nonetheless has some structuring principles to that flow.

The hollow core is always that we don't have a means of constructing these kinds of contextual maps, and it is vitally critically important to realize that that's on purpose and not because we don't care or haven't thought of anything better. until we stop treating this as a strictly academic exercise that we can think our way out of, we'll get nowhere! the point that these ideas always reach is "but the incentives," and that should indicate to us that maybe the billion dollar industries that might profit from a perpetual churn of disconnected papers has some structuring influence on our ability to make some kind of cumulative, fluid consensus. It's like trying to go to the moon but constantly ignoring how gravity is holding you to earth.

idk that's some loose and altogether too long thoughts on the interrelatedness of experimental methodology, epistemology, dynamics as understood in neuroscience, and this paper. it would be nice to live in a world where we can pull and knit these threads together in a way that others can follow, and that's all i rly care about in science anymore lol.

UlrikeHahn,
@UlrikeHahn@fediscience.org avatar

@NicoleCRust @jonny my personal take is that this paper has an important point but not a solution, because the full scale of the problem is (to my mind) still not fully grasped. To explain: imagine you are trying to understand a little agent-based model you have. It’s a complex dynamical system, so you can’t just pick out a few random parameter combinations and form local theories and hope to come up with deep understanding. You need to systematically explore the parameter space 1/2

18+ UlrikeHahn,
@UlrikeHahn@fediscience.org avatar

@jonny @beneuroscience @axoaxonic @NicoleCRust @MolemanPeter

Dear All, I've tried to make a drawing to help explicate what I was trying to get at and how it's different from Nicole's logis. eq.

Imagine trying to understand levels of group performance as A. Aalmatouq does in his great experiments. We're concerned with two variables -group size and amount of communication. These produce an outcome space - as shown in this figure.

1/2

thetransmitter, to random
@thetransmitter@mastodon.social avatar

Welcome to the second single-cell revolution: New high-throughput technologies are transforming how we define neurons

By Joshua Sanes

https://www.thetransmitter.org/defining-cell-types/welcome-to-the-second-single-cell-revolution-new-high-throughput-technologies-are-transforming-how-we-define-neurons/?utm_source=mastodon&utm_medium=org-social&utm_campaign=2024129-welcome-to

NicoleCRust, to random
@NicoleCRust@neuromatch.social avatar

Wow! I just learned the story of an amazing colleage:

https://chasingmycure.com/

I'm a patient with a deadly illness that has nearly killed me five times, and I'm also a physician-scientist racing to discover a cure before my time runs out.

Thanks to a drug that I discovered to treat my disease and began testing on myself, I'm currently in my longest remission ever and was able to have a beautiful daughter (2018) and son (2021) with the love of my life.

I dedicate my life to advancing cures for Castleman disease and many more diseases through Every Cure, spreading our innovative approach to other diseases.

Rhyothemis,
@Rhyothemis@zeroes.ca avatar

@NicoleCRust

Fajgenbaum's story is really fascinating, and I think, instructive.

He pointed out to his oncologist the pupura that would appear right before a disease flare; his dr's response was it was nothing to worry about. But Fajgenbaum was not 'worried' about them, he was pointing them out since they might indicate something about the disease process. The appearance of the pupura were what lead him to anti VEGF therapy as a means of suppressing flares.

The above is from memory, and I don't have time to review, so my apologies if incorrect.

I think it was this interview that I saw, but YT says I have not watched it -
https://youtu.be/EEZpppBFj5Q?si=N0CpznI3aWoMQC-q

mark_histed, to random

NIH spends in one year ten times what CZI says they'll spend in a decade.

(Philanthropy is good, but government funding is the bedrock of scientific and medical progress.)

PessoaBrain, to Neuroscience
@PessoaBrain@neuromatch.social avatar

𝗖𝗮𝘂𝘀𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝗻𝗲𝘂𝗿𝗼𝘀𝗰𝗶𝗲𝗻𝗰𝗲!

Join us at Neuroscience & Philosophy Salon to hear and discuss the recent paper by Lauren Ross and Dani Bassett.

Can we make progress on this front? Don't miss it!

Feb 2 at noon (eastern USA)
Register:
https://umd.zoom.us/meeting/register/tJckcuyvpj4pGdDaBKrrH41WJV3yVOrJzkP7

PessoaBrain, to Neuroscience
@PessoaBrain@neuromatch.social avatar

Systems neuroscience in trouble??

Some harsh words about just-so stories in systems neuroscience in general and network neuroscience in particular.

I'm not sure about the proposed solutions, but certainly something to think about.

https://doi.org/10.7554/eLife.79559


@cogneurophys

PessoaBrain,
@PessoaBrain@neuromatch.social avatar

@NicoleCRust @tdverstynen @albertcardona @cogneurophys

I don't know what to make of the paper. It is definitely worth it for a graduate student journal club. Not denigrating it but I found it naive in terms of asking for "benchmark models" that include "all that is known".

Perhaps our field of systems neuroscience is too immature, sure we can admit that. But it feels like the goal of science in the paper is something like the standard model of physics. But even in physics that's just a tiny domain. Sure it impacts everything but that's not even physics of complex matter.

joyce, to random
@joyce@hcommons.social avatar

Tonight I decided I needed to read something comforting. So I'm rereading The Last Unicorn. OMG it's good.

albertcardona, (edited ) to Neuroscience
@albertcardona@mathstodon.xyz avatar

"The brain: what for?" – my seminar for "everyone else" at the . Featuring brainless maggots and more.

https://www.youtube.com/watch?v=mcZwH5MYkFU

computingnature, to Neuroscience
@computingnature@neuromatch.social avatar

Simultaneous, cortex-wide and cellular-resolution neuronal population dynamics reveal an unbounded scaling of dimensionality with neuron number
https://www.biorxiv.org/content/10.1101/2024.01.15.575721v1

thetransmitter, to random
@thetransmitter@mastodon.social avatar

Are you interested in getting your science journalism career started? The Transmitter is seeking a summer intern to cover the fast-moving field of neuroscience. Find out more and apply for the role here: https://simonsfoundation.wd1.myworkdayjobs.com/en-US/simonsfoundationcareers/job/Summer-Writing-Intern--The-Transmitter_R0001491

DrYohanJohn, to Neuroscience
@DrYohanJohn@fediscience.org avatar

What do you think are the best critiques of the predictive processing framework in neuroscience?

I like the way that it has made top-down processing more popular in the minds of experimentalists. But I am skeptical that only errors are propagated up the hierarchies.

UlrikeHahn,
@UlrikeHahn@fediscience.org avatar

@knutson_brain @DrYohanJohn @skarthik @NicoleCRust

the biggest problem for predictive processing might well be the "dark room problem"

https://www.cell.com/trends/cognitive-sciences/pdf/S1364-6613(20)30058-9.pdf

the 'solution' proposed by van de Cruys, Friston & Clark's invokes 'optimism bias'

https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(20)30136-4

so draws on a putative 'bias' that is, arguably, simply a statistical artifact of poorly designed measurement scales (as revealed, ironically, by a Bayesian analysis)

https://www.ucl.ac.uk/lagnado-lab/publications/harris/PsychRevInPress.pdf

PessoaBrain, to Neuroscience
@PessoaBrain@neuromatch.social avatar

Can we control an entire distributed circuit in the brain? If not now, when?

Neurotechniques can do amazing things. One can target a population in region A to track specific projections to region B, and then study the impact on B.

How far beyond that can we already go? What is the most extreme example that you know of open- or closed-loop manipulation?


@cogneurophys

annaleen, to books
@annaleen@wandering.shop avatar

It's award nomination season! For your consideration, the best two things I published this year: The Terraformers, a novel, and "Unhearable Music," a short story which appeared in Rolling Stone's "future of music" issue. Thanks to all the kind people who supported me by publishing these strange stories about future ecologies, and mega-gratitude to my readers, who made The Terraformers a success.

You can read "Unhearable Music" here: https://www.rollingstone.com/music/music-features/unhearable-music-science-fiction-1234770203/

MatteoCarandini, to random
@MatteoCarandini@mastodon.social avatar

A nice news article about "representational drift" in The Transmitter:
https://www.thetransmitter.org/learning/what-drifting-representations-reveal-about-the-brain/

I wish they had interviewed Claudia Clopath too. She has very convincing evidence against representational drift in visual cortex (which she published in eLife).

PessoaBrain, to random
@PessoaBrain@neuromatch.social avatar

Non-determinism in classical (and quantum) physics

Very interesting talk by Nicolas Gisin suggesting that mathematical real numbers are really "random" (given they require infinite bits to be represented).

Thought @NicoleCRust and other folks might like it.

h/t @WiringtheBrain

Better link:
https://www.youtube.com/watch?v=Lx4u_96cAfc

PessoaBrain, to Neuroscience
@PessoaBrain@neuromatch.social avatar

What explains the rich exchange of information here on Masto? It's really a great community.

It's a deafening silence over at Bluesky... And the other place is not for many people for obvious reasons.

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