NicoleCRust

NicoleCRust, 3 months ago to random

Fascinating first person account by a psychologist who faked data

The scientist: Diederik Stapel. A Dutch social psychologist. He wrote a book explaining the context and how one thing led to another until he was caught. Nick Brown translated it into English. Freely available here:

http://nick.brown.free.fr/stapel

Page 101:

I also became increasingly skilled in the use of techniques that could put a healthy-
looking shine on otherwise mediocre results. If I didn’t get the effect I wanted across all the
different measures I’d used or the questions I’d asked, I would use the ones that did show
that effect. If an effect was present in an experiment, but not strongly enough to be tapped
by all of the types of measurements I’d used, I would make it stronger by combining the measures where the effect seemed to be only partly working. ...

Page 102:

After years of balancing on the outer limits, the gray became darker and darker until
it was black, and I fell off the edge into the abyss. I’d been having trouble with my
experiments for some time. Even with my various “gray” methods for “improving” the data,
I wasn’t able to get the results the way I wanted them. I couldn’t resist the temptation to go wanted it so badly. I wanted to belong, to be part of the action, to score. I really, really wanted to be really, really good. I wanted to be published in the best journals
and speak in the largest room at conferences. I wanted people to hang on my every word
as I headed for coffee or lunch after delivering a lecture. I felt very alone.

p103

I was alone in my tastefully furnished office at the University of Groningen. I’d taken
extra care when closing the door, and made my desk extra tidy. Everything had to be neat
and orderly. No mess. I opened the computer file with the data that I had entered and
changed an unexpected 2 into a 4; then, a little further along, I changed a 3 into a 5. It
didn’t feel right. I looked around me, nervously. The data danced in front of my eyes.
When the results are just not quite what you’d so badly hoped for; when you know that that
hope is based on a thorough analysis of the literature; when this is your third experiment
on this topic and the first two worked great; when you know that there are other people
doing similar research elsewhere who are getting good results; then, surely, you’re entitled
to adjust the results just a little?

NicoleCRust, 3 months ago to random

If you were to recalibrate, what would you do?

I always suspected I would do something like study those amazing desert ants that navigate via the earth’s magnetic field. But when thinking through the question “How do you want to spend the next 10 years?” more seriously (pretending there are few constraints), that’s not where I actually point myself.

Acknowledging that it’s a tremendously priveleged (and emotional) thought experiment, What would you do with your next 10 years, assuming that thing needs to be useful enough that it’s reasonably supported (and you would continue to get a paycheck)?

NicoleCRust, 3 months ago to random

Ugh.

https://www.vulture.com/article/hugo-awards-china-censorship-controversy.html

the volunteer body that administered the 2023 Hugo Awards appeared to have directly engaged in self-censoring the nominees over political concerns about the host country, China. The emails allege members of the Hugo administration team succeeded in keeping certain books off-ballot because they wanted to operate under Chinese laws related to content and censorship

NicoleCRust, 3 months ago to random

Podcast rec

Continuing the compromise that I’ll run but only if I get to learn wonderful things, episode 1 of the Santa Fe Institute’s Complexity podcast is wonderful. The curiosity of my colleague Vijay Balasubrimanian is infectious. Borges, brains, the energy efficiency of abstractions - all there.

https://santafe.edu/culture/podcasts

NicoleCRust, 3 months ago to random

Do psychologists "measure"?

Weird question, right?

"Measurements of attributes such as emotions, well-being, or intelligence are widely used for various purposes in society, but it remains a matter of discussion whether psychological measurement is analogous to measurement in the natural sciences, and to what extent it qualifies as measurement at all.'
https://doi.org/10.1080/09515089.2023.2300693
Edit: author is here! @mieronen

My initial take: what?! This seems silly. But I'm starting to warm up to it. It's about causality. Consider: "insomnia causes fatigue"; no one disputes it. But there's not a physical thing in the world called insomnia that causes a physical thing in the world, fatigue billiard-ball-style. Rather, the physical causal chain happens by way of a lack of sleep causing the brain state that leads to the mind state of fatigue (in other words, that word "cause" is doing some heavy lifting in that phrase). The question is: can you meaningfully talk about causality when you have abstracted away from physical interactions?

On one hand, of course - you can develop causal models formulated entirely at the psychological level (rewards, punishments, surprises, mood) that make falsifiable predictions and you can both perturb and measure these things to test those models.

On the other hand, we probably do need to take some care that we aren't confusing ourselves as we throw around that word "cause" interchangeably for things that physically interact and abstractions of those things.

Thoughts? I'm particularly curious about cases in which this type of abstraction has led researchers astray.

NicoleCRust, 4 months ago (edited 4 months ago) to random

A bit surprised to see this on a JHU Med facts page.

"Depression is ... a chemical imbalance in your brain that needs to be treated."
"Depression is caused by an imbalance of brain chemicals."

https://www.hopkinsmedicine.org/health/conditions-and-diseases/major-depression

While the evidence suggests that antidepressants are effective in some cases, it's much less clear that "rebalancing chemicals" is how they operate. From Principles in Neural Science:

"Although antidepressant drugs bind to and inhibit MAO, NET, or SERT with their first dose, several weeks of treatment are typically required to observe a lifting of depressive symptoms. Several hypotheses have been put forward to explain this delay. One is that a slow buildup of newly synthesized proteins alters the responsiveness of neurons in a manner that treats the depression. Another is that increases in the levels of synaptic transmission of serotonin or norepinephrine rapidly increase plasticity in different emotion-processing circuits and that the latency to therapeutic benefit reflects the time it takes for new experiences to alter synaptic weights. A third hypothesis is that antidepressant efficacy is mediated in part by enhancement of hippocampal neurogenesis. Narrowing down the possible therapeutic mechanisms is challenging because of the lack of good animal models of depression. Without an animal model, it is not possible to know which of the many observable molecular, cellular, and synaptic changes cause depression or underlie the therapeutic actions of effective antidepressants."

https://en.wikipedia.org/wiki/Principles_of_Neural_Science

NicoleCRust, 4 months ago to random

Is an "algorithm" - like a line attractor in a (recurrent) neural network - a mechanism?

Many great papers about the brain describe the "algorithms" by which it computes. Among them are those that model it as complex dynamical system that operates by settling into different states called attractors; one example is Mante et al 2013 who used this approach to understand how prefrontal cortex contributes to decision making.
https://www.nature.com/articles/nature12742

Is that explanation mechanistic? To me: obviously. But I've just learned that some argue it's not. What's the logic? It begins by explaining that "mechanism" implies "causality" and it proceeds to question whether these types of explanations are causal.

With regard to that study:
https://www.journals.uchicago.edu/doi/abs/10.1093/bjps/axw034?journalCode=bjps

"One strike against the mechanistic interpretation is that the explanation offered by the dynamical model of the PFC is not a constitutive one. That is to say, it is not an explanation of how a global phenomenon— computation—comes about because of the activities of some network components, whether spatially localized or not. Instead, the dynamical properties of the network, which do the job of explaining the computational phenomena, are themselves global- or population-level properties of the network.28
...
Another important point is that the model gives us no information about how we might make changes to the network in order to affect changes to its information-processing properties. It does not tell us which connections would have to be rearranged in order to make the computation no longer context-dependent, for example.
...
This brings me to say more about the second option, which I endorse: that the model offers some kind of non-causal explanation. We can think of the dynamical model as offering an illuminating perspective on the network."

I have problems with this interpretation. In my own mind, algorithmic explanations are mechanistic. Curious to hear your thoughts!

BTW: My dive into this discussion was prompted by this paper:
https://www.nature.com/articles/s41583-023-00778-7.epdf?sharing_token=LlREMtfLsEuMP2cIGP8-CNRgN0jAjWel9jnR3ZoTv0OJW18pxUOzYI6WS9QWYKLbrMfHUnYQTzLgDtF-GegxI1N6TrMJPNhyio4bQPoB5cqsg7EyaZJfZng31XWQB5hPeXriZftbC-ae313h2IZqMg9bAlGExqGCnik85rG07zQ%3D

where the authors don't take a stance on algorithm per se but advocate for the field to arrive at some clarity around what "mechanism" means.

NicoleCRust, 4 months ago to random

Vivid description of emergence!

Mathematical biologist Jack Cowan loves to describe the difference between biophysicists and theoretical biologists …. “take an organism and homogenize it in a Waring blender. The biophysicist is interested in those properties that are invariant under that transformation.” One couldn’t get a more graphic image of the difference between aggregativity and emergence.

From Wimsatt:
https://www.hup.harvard.edu/books/9780674015456

NicoleCRust, 4 months ago to random

Inspired by @bwaber, I’ll try to post what I’m listening to on my long runs; I need more fresh content for those so please post what you’re listening to too!

Last week, I serendipitously met the author Jeffrey Keyes and listened to his book Killer Chef (co authored w/ James Patterson; an NYT best seller). Lighthearted and fun!

http://www.jeffreyjameskeyes.com/jeffrey-james-keyes

This week, I listened to a brain inspired podcast with Eric Shea Brown. Eric did a tremendous job of breaking down this important moment in neuroscience as we shift toward thinking about the brain as a dynamical system. Exceedingly approachable.

https://braininspired.co/podcast/178/

NicoleCRust, 4 months ago (edited 4 months ago) to random

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/

NicoleCRust, 4 months ago to random

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.

NicoleCRust, 4 months ago to random

Big welcome (back) to @bevil!

While he won't throw it in your face, know that Bevil is a super-star brain researcher AND an artist AND he doesn't just wear those two hats - he works at the intersection. For instance, here's a picture of Bevil and Alan Alda celebrating color:
https://bevilconway.com/?page_id=1293
On the first, he has opinions! ... Especially about how to make science a better an more equitable place. No doubt he'll find a home here; I highly recommended this follow.

https://bevilconway.com/

NicoleCRust, 4 months ago to random

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.

NicoleCRust, 4 months ago to random

Worst word (pronunciation)?

My vote: Colonel = “ker-nal”. How does one justify the ghost R to anyone?

https://www.smithsonianmag.com/smithsonian-institution/why-colonel-pronounced-r-and-more-questions-our-readers-180953036/

NicoleCRust, 4 months ago to random

Simple RNN models that capture neural network criticality / edge of chaos?

I'd like to play around with simple (tutorial-like) recurrent neural network models that capture the phenomenon of criticality. Something like the smallest possible number of recurrently connected model neurons that can recapitulate phenomenon (like information processing peaks for intermediate coupling weights).

Any leads?

NicoleCRust, 4 months ago to random

Virtually all the protein molecules in our body are replaced during the course of a year.

A fun fact with philosophical implications (ala: Where is the "you")?

https://www.cambridge.org/core/books/biological-thermodynamics/8FC8CAB10BFF5A4391B14FB171D7D351

NicoleCRust, 4 months ago to random

Done writing the book.

(Deep inhale).

~90K words. A few years of work. A transformative journey that did not end at all as I thought when I started. I'm grateful to have done it - what a privilege. A much bigger conceptual project than anything I've done up to this point.

I got to think intensely for a better part of a few years (in parallel to running a lab and teaching as a professor). Somehow there was not time for that before. I'm not exactly sure where I found it; I just did.

There will be many revisions going forward. And it won't hit the shelves anytime soon. But I'm going to pause and celebrate this moment, where every one of the bits are finally in place. I learned so much along the way. Even today, on the last day, I was fascinated, and I'm grateful. (That said, I'm also a bit tired).

What's the book about? A slice of the spirit behind it is captured here: https://www.thetransmitter.org/systems-neuroscience/is-the-brain-uncontrollable-like-the-weather/

NicoleCRust, 5 months ago to random

A brilliant reflection on what first brings curious minded folks to the table and how we evolve and change.

https://helendecruz.substack.com/p/how-i-almost-became-an-evolutionary?r=tfpzm

NicoleCRust, 5 months ago to random

To all my friends on the furry elephant: Happy New Year!

Looking back on 2023, I learned so much from this community. I was writing and mulling things over; you were supportive and insightful. I am grateful (and I hope I can ultimately give back what I have received).

My very best wishes to all of you for 2024!

NicoleCRust, 5 months ago to random

Should neuroscientists stay on X or go? Let’s ask a bunch of people who have decided to stay. Voices are missing here.

https://onlinelibrary.wiley.com/doi/full/10.1111/ejn.16236

NicoleCRust, 5 months ago to Neuroscience

My new piece for @thetransmitter. Why is treating brain dysfunction so ENORMOUSLY challenging?

Because it amounts to controlling a complex system.

Drawing from the history of weather research, I pose the question: Can it even be done? And 14 experts in complex systems chime in. Would love to hear your thoughts as well!

https://www.thetransmitter.org/systems-neuroscience/is-the-brain-uncontrollable-like-the-weather/

#neuroscience #complexity

NicoleCRust, 5 months ago to random

I love this quote about complexity

https://www.jstor.org/stable/2459579

Robert May and George Oster, circa 1976 at the time of the introduction of one of the niftiest equations, the logistic map.

(It has a single parameter (R), and tweaking it moves the system from collapse to a set point attractor to an oscillator to chaos)
https://en.wikipedia.org/wiki/Logistic_map

NicoleCRust, 5 months ago to random

Exciting development for brain stimulation therapies.

Building on work that teases apart causes in a complex system, predicts which stimulating electrodes will be effective based on resting activity alone.

Amin Nejatbakhsh, Francesco Fumarola, Saleh Esteki, Taro Toyoizumi, Roozbeh Kiani, and Luca Mazzucato

https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.5.043211

The work builds on 2012 insights from George Sugihara:

https://www.science.org/doi/10.1126/science.1227079

In a complex system, variables are nonlinearly related; consequently, you can play some nifty tricks. This one is called convergent cross-mapping (CCM). More of us should know about it!

NicoleCRust, 5 months ago to random

Yeah - @thetransmitter is here! Follow them for high quality news in the brain research space.

NicoleCRust, 5 months ago to random

Crowd sourcing big data collection efforts in the brain research space

Looking for both details as well as a conceptual parsing of the space. Here's a partial list (and a conceptual parsing,n loosely organized around -omics): https://en.wikipedia.org/wiki/Omics

Genomics > Human Genome Project is relevant. Modern version: PsychENCODE
https://psychencode.synapse.org/

Transcriptomics >
Mouse whole-brain transcriptomic cell type atlas https://knowledge.brain-map.org/data/LVDBJAW8BI5YSS1QUBG/collections

Connectomics > worms; fly larvae; mouse (eg MiCroNShttps://www.iarpa.gov/research-programs/microns)

Multi-omics: https://chanzuckerberg.com/science/programs-resources/single-cell-biology/

Cell type atlases > https://www.humancellatlas.org/
https://portal.brain-map.org/atlases-and-data/bkp/abc-atlas

Brain activity efforts (including human fMRI):
http://openfmri.org/
https://openneuro.org/
https://www.internationalbrainlab.com/

Thanks in advance!